diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index 6fc3f7f7..4bb4450e 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -178,9 +178,19 @@ jobs:
             release-performance-evidence.json
           if-no-files-found: error
 
-  contracts:
-    name: Cross-Engine Contracts
+  public-parity:
+    name: Public Parity (${{ matrix.framework }})
     runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        include:
+          - framework: vectorbt_oss
+            environment: .venv-vectorbt-oss
+          - framework: backtrader
+            environment: .venv-backtrader
+          - framework: zipline
+            environment: .venv-zipline
     steps:
       - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
 
@@ -192,22 +202,50 @@ jobs:
       - name: Set up Python
         run: uv python install ${{ env.PYTHON_VERSION }}
 
-      - name: Install dependencies (with comparison frameworks)
-        run: uv sync --dev --extra comparison
+      - name: Build the locked framework environment
+        run: >-
+          python validation/build_framework_env.py
+          --framework ${{ matrix.framework }}
+          --evidence-output environment-evidence.json
 
-      - name: Run cross-engine contract tests
-        env:
-          ML4T_COMPARISON_INPROC: "1"
+      - name: Measure native VectorBT OSS behavior
+        if: matrix.framework == 'vectorbt_oss'
         run: >-
-          uv run pytest tests/contracts/test_cross_engine_contracts.py -v --tb=short --no-cov
-          --junitxml=parity-contracts.xml
+          "${{ matrix.environment }}/bin/python"
+          validation/native/vectorbt_behavior.py
+          --framework vectorbt_oss
+          --output native-evidence.json
 
-      - name: Retain cross-engine parity evidence
+      - name: Measure native Backtrader behavior
+        if: matrix.framework == 'backtrader'
+        run: >-
+          "${{ matrix.environment }}/bin/python"
+          validation/native/backtrader_behavior.py
+          --output native-evidence.json
+
+      - name: Measure native Zipline behavior
+        if: matrix.framework == 'zipline'
+        run: >-
+          "${{ matrix.environment }}/bin/python"
+          validation/native/zipline_behavior.py
+          --output native-evidence.json
+
+      - name: Run the complete required scenario matrix
+        run: >-
+          "${{ matrix.environment }}/bin/python"
+          validation/run_all_correctness.py
+          --framework ${{ matrix.framework }}
+          --output correctness-candidate.json
+
+      - name: Retain public parity evidence
         if: always()
         uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
         with:
-          name: parity-contracts
-          path: parity-contracts.xml
+          name: parity-${{ matrix.framework }}
+          path: |
+            environment-evidence.json
+            correctness-candidate.json
+            native-evidence.json
           if-no-files-found: error
 
   documentation:
@@ -249,7 +287,7 @@ jobs:
     name: Build Package
     runs-on: ubuntu-latest
     needs:
-      [lint, typecheck, compatibility, security, coverage, runtime, contracts, documentation]
+      [lint, typecheck, compatibility, security, coverage, runtime, public-parity, documentation]
     steps:
       - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
         with:
@@ -289,12 +327,12 @@ jobs:
             --commit "$GITHUB_SHA" \
             --repository "$GITHUB_REPOSITORY" \
             --gate compatibility=${{ needs.compatibility.result }} \
-            --gate correctness=${{ needs.coverage.result }} \
+            --gate correctness=${{ needs.public-parity.result }} \
             --gate coverage=${{ needs.coverage.result }} \
             --gate documentation=${{ needs.documentation.result }} \
             --gate lint=${{ needs.lint.result }} \
             --gate packaging=success \
-            --gate parity=${{ needs.contracts.result }} \
+            --gate parity=${{ needs.public-parity.result }} \
             --gate performance=${{ needs.runtime.result }} \
             --gate security=${{ needs.security.result }} \
             --gate typecheck=${{ needs.typecheck.result }} \
diff --git a/.github/workflows/private-comparisons.yml b/.github/workflows/private-comparisons.yml
new file mode 100644
index 00000000..544f14b9
--- /dev/null
+++ b/.github/workflows/private-comparisons.yml
@@ -0,0 +1,115 @@
+name: Private Comparison Evidence
+
+on:
+  workflow_call:
+    secrets:
+      VECTORBT_PRO_DEPLOY_KEY:
+        required: true
+  workflow_dispatch:
+
+permissions:
+  contents: read
+
+env:
+  PYTHON_VERSION: "3.12"
+
+jobs:
+  vectorbt-pro:
+    name: VectorBT Pro Parity
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@c771a70e6277c0a99b617c7a806ffedaca235ff9 # v9.0.0
+        with:
+          version: "latest"
+
+      - name: Set up Python
+        run: uv python install ${{ env.PYTHON_VERSION }}
+
+      - name: Configure licensed source access
+        env:
+          VECTORBT_PRO_DEPLOY_KEY: ${{ secrets.VECTORBT_PRO_DEPLOY_KEY }}
+        run: |
+          install -m 700 -d "$HOME/.ssh"
+          printf '%s\n' "$VECTORBT_PRO_DEPLOY_KEY" > "$HOME/.ssh/id_ed25519"
+          chmod 600 "$HOME/.ssh/id_ed25519"
+          ssh-keyscan github.com >> "$HOME/.ssh/known_hosts"
+
+      - name: Build the locked VectorBT Pro environment
+        run: >-
+          python validation/build_framework_env.py
+          --framework vectorbt_pro
+          --evidence-output vectorbt-pro-environment.json
+
+      - name: Measure native VectorBT Pro behavior
+        run: >-
+          .venv-vectorbt-pro/bin/python
+          validation/native/vectorbt_behavior.py
+          --framework vectorbt_pro
+          --output vectorbt-pro-native.json
+
+      - name: Run the complete VectorBT Pro scenario matrix
+        run: >-
+          .venv-vectorbt-pro/bin/python
+          validation/run_all_correctness.py
+          --framework vectorbt_pro
+          --output vectorbt-pro-correctness.json
+
+      - name: Retain VectorBT Pro evidence
+        if: always()
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+        with:
+          name: vectorbt-pro-comparison-${{ github.sha }}
+          path: |
+            vectorbt-pro-environment.json
+            vectorbt-pro-native.json
+            vectorbt-pro-correctness.json
+          if-no-files-found: error
+          retention-days: 90
+
+  lean:
+    name: LEAN Native Behavior
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@c771a70e6277c0a99b617c7a806ffedaca235ff9 # v9.0.0
+        with:
+          version: "latest"
+
+      - name: Set up Python
+        run: uv python install ${{ env.PYTHON_VERSION }}
+
+      - name: Verify locked LEAN CLI and engine image
+        run: >-
+          python validation/build_framework_env.py
+          --framework lean
+          --evidence-output lean-environment.json
+
+      - name: Measure native LEAN behavior
+        run: >-
+          .venv-lean/bin/python
+          validation/native/lean_behavior.py
+          --lean-command .venv-lean/bin/lean
+          --output lean-native.json
+
+      - name: Run the LEAN Chapter 16 comparisons
+        run: >-
+          .venv-lean/bin/python
+          validation/run_lean_case_studies.py
+          --lean-command .venv-lean/bin/lean
+          --output lean-case-studies.json
+
+      - name: Retain LEAN provenance
+        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
+        with:
+          name: lean-comparison-${{ github.sha }}
+          path: |
+            lean-environment.json
+            lean-native.json
+            lean-case-studies.json
+          if-no-files-found: error
+          retention-days: 90
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
index 36fc195c..26ca9bf5 100644
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -24,10 +24,15 @@ jobs:
     name: Qualify Release Candidate
     uses: ./.github/workflows/ci.yml
 
+  private-comparisons:
+    name: Qualify Licensed and Container Comparisons
+    uses: ./.github/workflows/private-comparisons.yml
+    secrets: inherit
+
   publish:
     name: Publish to PyPI
     runs-on: ubuntu-latest
-    needs: [ecosystem-qualification, qualification]
+    needs: [ecosystem-qualification, private-comparisons, qualification]
     environment: pypi
     permissions:
       contents: read
diff --git a/.gitignore b/.gitignore
index dbf2c1d3..dccc9f57 100644
--- a/.gitignore
+++ b/.gitignore
@@ -45,6 +45,7 @@ src/ml4t/backtest/_version.py
 validation/.zipline/
 validation/CORRECTNESS_RESULTS.md
 validation/BENCHMARK_RESULTS.md
+validation/candidates/
 validation/trade_logs/
 validation/lean/workspace/
 validation/nautilus/.venv-nautilus/
diff --git a/README.md b/README.md
index 99733399..cd2c075d 100644
--- a/README.md
+++ b/README.md
@@ -126,10 +126,10 @@ config = BacktestConfig.from_preset("vectorbt")
 # Match Backtrader behavior (next-bar open fills, integer shares)
 config = BacktestConfig.from_preset("backtrader")
 
-# Match Zipline behavior (next-bar open fills, integer shares, per-share commission)
+# Match the documented Zipline comparison protocol (next-bar open, no default costs)
 config = BacktestConfig.from_preset("zipline")
 
-# Match QuantConnect LEAN behavior (same-bar close fills, integer shares)
+# Match the frozen LEAN daily US-equity protocol (next-session open, integer shares)
 config = BacktestConfig.from_preset("lean")
 
 # Conservative production settings (higher costs, cash buffer)
@@ -276,28 +276,35 @@ opt-in.
 
 ## Cross-Framework Validation
 
-Profiles configure framework-specific execution behavior. The generated table below reports only
-claims supported by the retained release-candidate evidence.
+The primary audit uses frozen data and targets from ETF allocation, CME futures, and crypto
+perpetual-funding case studies. Profiles configure framework-specific execution behavior, and only
+genuinely supported framework and asset combinations are required. The broad real-strategy gate
+currently passes 6 of 8 required pairs; the generated table reports the exact remaining gaps.
+
+The scenario matrix and 250-asset workload remain useful synthetic diagnostic and stress tests.
+They do not establish realistic strategy equivalence.
 
 <!-- parity-claims:start -->
 <!-- Generated by validation/generate_parity_claims.py. Do not edit by hand. -->
 
-Scenario claims use the retained release-candidate matrix. "Exact" appears only when every required scenario has zero canonical gap.
+Scenario claims use the retained accepted matrix. "Exact" means terminal values, ordered closed trades, and ordered fills match after 1e-8 quantization. Each record declares whether a surface is native, reconstructed, aggregate-only, input-only, or unavailable; the claim does not extend to unavailable order-lifecycle fields.
 
 | Profile | Pinned framework | Required scenarios | Evidence |
 |---|---|---:|---|
-| `vectorbt_strict` | [VectorBT Pro 2025.12.31](https://github.com/polakowo/vectorbt.pro) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `vectorbt` | [VectorBT OSS 0.28.2](https://pypi.org/project/vectorbt/0.28.2/) | 15/15 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 15/15 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-
-Large-scale claims are published only when a retained workload has zero canonical gap.
-
-| Profile | Pinned framework | Compared | Trade gap | Terminal value | Evidence |
-|---|---|---:|---:|---:|---|
-| `vectorbt_strict` | VectorBT Pro 2025.12.31 (`1305a1e19743`) | 225,844 trades | 0 | 685179.007330 | [large-scale evidence](https://github.com/ml4t/backtest/blob/main/validation/vectorbt_pro/large_scale_parity.json) |
-
-No large-scale claim is published for Backtrader, Zipline, VectorBT OSS, or LEAN without a passing retained artifact.
+| `vectorbt_strict` | [VectorBT Pro 2026.6.27](https://github.com/polakowo/vectorbt.pro) | 17/17 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `vectorbt_oss_strict` | [VectorBT OSS 1.1.0](https://pypi.org/project/vectorbt/1.1.0/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 17/17 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+
+The controlled scale workload contains 250 assets and 5,040 daily sessions (1,260,000 bars). Every row has zero canonical gap for target intents, native fills, closed trades reconstructed from those fills, and terminal state reconstructed from the fill ledger and final marks.
+
+| Profile | Current framework | Target intents | Native fills | Fill-derived closed trades | Terminal value | Evidence |
+|---|---|---:|---:|---:|---:|---|
+| `vectorbt_strict` | [VectorBT Pro 2026.6.27](https://github.com/polakowo/vectorbt.pro) | 427,790 | 390,369 | 188,549 | 716,785.408089 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `vectorbt_oss_strict` | [VectorBT OSS 1.1.0](https://pypi.org/project/vectorbt/1.1.0/) | 427,790 | 390,369 | 188,549 | 716,785.408089 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 427,790 | 343,813 | 182,019 | -9,166,273.555954 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 427,790 | 427,696 | 226,434 | 10,504,095.900000 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `lean` | [LEAN 18001](https://github.com/QuantConnect/Lean) | 427,790 | 361,297 | 191,297 | 184,538.130000 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
 <!-- parity-claims:end -->
 
 See [validation/README.md](validation/README.md) for methodology and detailed results.
@@ -334,6 +341,17 @@ Workload definitions and expected checksums are retained in
 `validation/performance_baselines.json`. The project does not publish hardware-dependent runtime,
 throughput, memory, or cross-framework ratios as stable claims.
 
+Cross-framework performance evidence uses a common 50-asset, 252-session controlled workload.
+Each runner receives one isolated warm-up followed by ten isolated measurements. The retained
+artifact contains raw samples, whole-process wall time, process-tree peak RSS, deterministic 95%
+bootstrap intervals, output checksums, framework identities, and semantic disclosures for the
+idiomatic view. The results remain audit evidence pending a separate publication decision.
+
+The real-strategy performance artifact times only engine execution for correctness-passing pairs.
+Inputs, model inference, target construction, adapter preparation, extraction, and reporting are
+excluded. See `validation/REAL_STRATEGY_PERFORMANCE.json`; its ratios are dated audit measurements,
+not stable framework claims.
+
 ## Documentation
 
 - [Getting Started](docs/getting-started/quickstart.md) — your first backtest
diff --git a/docs/getting-started/quickstart.md b/docs/getting-started/quickstart.md
index 0c50993c..6ba6ad60 100644
--- a/docs/getting-started/quickstart.md
+++ b/docs/getting-started/quickstart.md
@@ -171,13 +171,13 @@ result = run_backtest(prices, strategy, config=config)
 Match the exact behavior of another backtesting framework:
 
 ```python
-# Backtrader-compatible: next-bar execution, integer shares, margin account
+# Backtrader-compatible: next-bar execution, integer shares, default cash checks
 result = run_backtest(prices, strategy, config="backtrader")
 
 # VectorBT-compatible: same-bar execution, fractional shares, no costs
 result = run_backtest(prices, strategy, config="vectorbt")
 
-# Zipline-compatible: next-bar execution, per-share commission
+# Zipline comparison protocol: next-bar open execution, no default costs
 result = run_backtest(prices, strategy, config="zipline")
 
 # Conservative production settings
diff --git a/docs/index.md b/docs/index.md
index 73fbf3c6..8cd806fe 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -21,8 +21,8 @@ how cash is reserved, and how results change when you match another framework's
 
 -   :material-check-all:{ .lg .middle } __Validated Against 4 Frameworks__
     ---
-    Compare fills and terminal values against VectorBT, Backtrader, Zipline,
-    and LEAN on the same benchmark scenarios.
+    Compare retained scenario evidence for VectorBT, Backtrader, and Zipline,
+    plus native and Chapter 16 evidence for LEAN.
     [:octicons-arrow-right-24: Profiles](user-guide/profiles.md)
 
 -   :material-book-open-variant:{ .lg .middle } __Chapters 16-19__
@@ -82,8 +82,9 @@ which pinned framework scenarios currently match exactly.
 
 **Quote-aware when you need it.** The feed can cache bid, ask, midpoint, and quote sizes additively. Market execution and position marking can use `price`, `bid`, `ask`, `quote_mid`, or `quote_side`.
 
-**Validated at scale.** The retained 250-asset, 20-year VectorBT Pro workload compares 225,844
-trades with zero canonical gap.
+**Retained validation evidence.** The primary audit uses three real case studies with frozen
+inputs. Separate synthetic scenario and 250-asset stress suites isolate conventions and exercise
+high event counts.
 
 | Feature | Description |
 |---------|-------------|
@@ -97,28 +98,30 @@ trades with zero canonical gap.
 
 ## Parity Validation
 
-Scenario comparisons run equivalent inputs and check framework-specific outcomes. Large-scale
-claims additionally require a retained workload with canonical record hashes and terminal values.
+Real-strategy comparisons run frozen market data and model-derived targets through each supported
+engine pair. The synthetic scenario and stress suites provide narrower conformance evidence.
 
 <!-- parity-claims:start -->
 <!-- Generated by validation/generate_parity_claims.py. Do not edit by hand. -->
 
-Scenario claims use the retained release-candidate matrix. "Exact" appears only when every required scenario has zero canonical gap.
+Scenario claims use the retained accepted matrix. "Exact" means terminal values, ordered closed trades, and ordered fills match after 1e-8 quantization. Each record declares whether a surface is native, reconstructed, aggregate-only, input-only, or unavailable; the claim does not extend to unavailable order-lifecycle fields.
 
 | Profile | Pinned framework | Required scenarios | Evidence |
 |---|---|---:|---|
-| `vectorbt_strict` | [VectorBT Pro 2025.12.31](https://github.com/polakowo/vectorbt.pro) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `vectorbt` | [VectorBT OSS 0.28.2](https://pypi.org/project/vectorbt/0.28.2/) | 15/15 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 15/15 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-
-Large-scale claims are published only when a retained workload has zero canonical gap.
-
-| Profile | Pinned framework | Compared | Trade gap | Terminal value | Evidence |
-|---|---|---:|---:|---:|---|
-| `vectorbt_strict` | VectorBT Pro 2025.12.31 (`1305a1e19743`) | 225,844 trades | 0 | 685179.007330 | [large-scale evidence](https://github.com/ml4t/backtest/blob/main/validation/vectorbt_pro/large_scale_parity.json) |
-
-No large-scale claim is published for Backtrader, Zipline, VectorBT OSS, or LEAN without a passing retained artifact.
+| `vectorbt_strict` | [VectorBT Pro 2026.6.27](https://github.com/polakowo/vectorbt.pro) | 17/17 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `vectorbt_oss_strict` | [VectorBT OSS 1.1.0](https://pypi.org/project/vectorbt/1.1.0/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 17/17 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+
+The controlled scale workload contains 250 assets and 5,040 daily sessions (1,260,000 bars). Every row has zero canonical gap for target intents, native fills, closed trades reconstructed from those fills, and terminal state reconstructed from the fill ledger and final marks.
+
+| Profile | Current framework | Target intents | Native fills | Fill-derived closed trades | Terminal value | Evidence |
+|---|---|---:|---:|---:|---:|---|
+| `vectorbt_strict` | [VectorBT Pro 2026.6.27](https://github.com/polakowo/vectorbt.pro) | 427,790 | 390,369 | 188,549 | 716,785.408089 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `vectorbt_oss_strict` | [VectorBT OSS 1.1.0](https://pypi.org/project/vectorbt/1.1.0/) | 427,790 | 390,369 | 188,549 | 716,785.408089 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 427,790 | 343,813 | 182,019 | -9,166,273.555954 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 427,790 | 427,696 | 226,434 | 10,504,095.900000 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `lean` | [LEAN 18001](https://github.com/QuantConnect/Lean) | 427,790 | 361,297 | 191,297 | 184,538.130000 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
 <!-- parity-claims:end -->
 
 Release performance evidence runs deterministic single-asset, 250-asset daily, quote-aware,
@@ -129,6 +132,11 @@ reported for diagnosis, while the
 instrument-free hotpath benchmark enforces the runtime regression limit. The project does not
 publish hardware-dependent performance ratios as stable claims.
 
+The separate cross-framework performance artifact retains ten isolated measurements per runner
+after one warm-up. It reports complete-process wall time, process-tree and LEAN-container peak RSS,
+raw samples, 95% bootstrap intervals, exact output checksums, and semantic disclosures. It is
+retained as audit evidence without stable speed or memory ratios pending a publication decision.
+
 ## Installation
 
 ```bash
diff --git a/docs/user-guide/accounts.md b/docs/user-guide/accounts.md
index bc482e42..0410660b 100644
--- a/docs/user-guide/accounts.md
+++ b/docs/user-guide/accounts.md
@@ -185,9 +185,11 @@ config = BacktestConfig.from_preset("lean")
 config = BacktestConfig.from_preset("realistic")
 ```
 
-Each preset sets all 40+ behavioral knobs to match the target framework's behavior.
-Strict variants (`backtrader_strict`, `vectorbt_strict`, `zipline_strict`)
-are also available for exact parity testing.
+Each preset configures the measured behavior used by its comparison protocol. The native defaults,
+explicit overrides, and adapter-emulated behavior are listed in the
+[validation methodology](https://github.com/ml4t/backtest/blob/main/validation/METHODOLOGY.md).
+Strict aliases are also available for
+the retained comparison commands.
 
 ## Insufficient Funds
 
diff --git a/docs/user-guide/configuration.md b/docs/user-guide/configuration.md
index 34cfa200..6fd09fe0 100644
--- a/docs/user-guide/configuration.md
+++ b/docs/user-guide/configuration.md
@@ -128,6 +128,7 @@ separate assumption layer.
 | `fixed_margin_schedule` | dict \| None | None | Per-asset `(initial, maintenance)` fixed dollar margin per contract |
 | `margin_pct_schedule` | dict \| None | None | Per-asset `(initial, maintenance)` fractions of notional; cannot overlap the fixed schedule |
 | `short_cash_policy` | ShortCashPolicy | CREDIT | How short proceeds affect cash |
+| `lock_notional_update_mode` | LockNotionalUpdateMode | POSITION_LEGS | Whether locked short collateral updates by closing/opening legs or by the combined order |
 
 Account type is determined by the flag combination:
 
@@ -209,6 +210,7 @@ friction:
 | Parameter | Type | Default | Description |
 |-----------|------|---------|-------------|
 | `share_type` | ShareType | INTEGER | FRACTIONAL or INTEGER |
+| `share_rounding` | ShareRounding | NEAREST | NEAREST or TRUNCATE for integer quantities |
 
 ### Result evidence
 
diff --git a/docs/user-guide/execution-semantics.md b/docs/user-guide/execution-semantics.md
index 8db6097b..7358f0d1 100644
--- a/docs/user-guide/execution-semantics.md
+++ b/docs/user-guide/execution-semantics.md
@@ -480,7 +480,7 @@ config = BacktestConfig(
 | `NONE` | No slippage | |
 | `PERCENTAGE` | % of price | `slippage_rate=0.001` (0.1%) |
 | `FIXED` | Fixed $ per share | `slippage_fixed=0.01` |
-| `VOLUME_BASED` | Size vs volume | `slippage_rate=0.1` (10% volume limit) |
+| `VOLUME_BASED` | Linear size-to-volume impact | `slippage_rate=0.1` (impact coefficient) |
 
 Slippage models remain separate from quote-side execution:
 
diff --git a/docs/user-guide/profiles.md b/docs/user-guide/profiles.md
index bc182ccc..771cc95d 100644
--- a/docs/user-guide/profiles.md
+++ b/docs/user-guide/profiles.md
@@ -14,8 +14,8 @@ exactly and which remain release-blocking.
 | `fast` | Zero-cost, integer-share execution -- fastest possible execution |
 | `backtrader` | Match Backtrader's default behavior |
 | `vectorbt` | Match VectorBT's default behavior (including fractional shares) |
-| `zipline` | Match Zipline Reloaded's default behavior |
-| `lean` | Match QuantConnect LEAN's default behavior |
+| `zipline` | Match the documented Zipline comparison protocol |
+| `lean` | Match the frozen LEAN daily US-equity comparison protocol |
 | `realistic` | Conservative settings for production |
 
 ### Broker Presets
@@ -30,15 +30,20 @@ The broker preset also supports a modular alias:
 |-------|-------------|
 | `ibkr:us:stocks:fixed` | `ibkr_us_stocks_fixed` |
 
+The `lean` profile is scoped to daily US equities submitted from `OnData` with
+`DefaultBrokerageModel`, a margin account, and 2x security leverage. LEAN delegates fees,
+slippage, margin, and fills to selected brokerage and security models, so this profile is not a
+claim about every LEAN asset class, resolution, or brokerage model.
+
 ### Strict Profiles
 
-Strict variants tune additional knobs (cash validation, settlement, short policies) for maximum parity on large-scale comparisons:
+Strict variants are the names used by retained comparison commands:
 
 | Profile | Base | Additional Tuning |
 |---------|------|-------------------|
 | `backtrader_strict` | backtrader | Submission precheck, simple cash check |
-| `vectorbt_strict` | vectorbt | Lock notional for shorts, FIFO ordering |
-| `zipline_strict` | zipline | Skip cash validation, allow shorts |
+| `vectorbt_strict` | vectorbt | Same settings as `vectorbt` |
+| `zipline_strict` | zipline | Same settings as `zipline` |
 
 ### Aliases
 
@@ -79,83 +84,116 @@ Profiles define behavioral defaults. Quote-aware feeds layer on top of them: you
 
 ## Profile Comparison
 
+These tables report configured values. A profile value is not automatically an equivalence claim.
+The [behavior coverage map](https://github.com/ml4t/backtest/blob/main/validation/behavior_coverage.toml)
+identifies which field groups have both a native oracle and a cross-engine comparison. Target
+sizing, insufficient-cash boundaries, competing same-session orders, partial fills, missing bars,
+and late assets remain excluded from scenario-level equivalence where the map marks them
+unpublished.
+
 ### Execution
 
 | Setting | default | backtrader | vectorbt | zipline | lean | realistic |
 |---------|---------|-----------|----------|---------|------|-----------|
-| Execution mode | next_bar | next_bar | same_bar | next_bar | same_bar | next_bar |
-| Execution price | open | open | close | open | close | open |
+| Execution mode | next_bar | next_bar | same_bar | next_bar | next_bar | next_bar |
+| Execution price | open | open | close | open | open | open |
 
 ### Stops
 
 | Setting | default | backtrader | vectorbt | zipline | lean | realistic |
 |---------|---------|-----------|----------|---------|------|-----------|
-| Fill mode | stop_price | stop_price | stop_price | stop_price | stop_price | next_bar_open |
-| Level basis | fill_price | signal_price | fill_price | fill_price | fill_price | fill_price |
-| Trail HWM | close | close | bar_extreme | close | close | close |
-| Trail timing | lagged | lagged | intrabar | lagged | lagged | lagged |
+| Fill mode | stop_price | stop_price | stop_price | next_bar_open | stop_price* | next_bar_open |
+| Level basis | fill_price | signal_price | fill_price | fill_price | fill_price* | fill_price |
+| Trail HWM | close | close | bar_extreme | bar_extreme | close* | close |
+| Trail timing | lagged | lagged | intrabar | intrabar | lagged* | lagged |
+
+`*` The LEAN stop settings are ML4T profile fallbacks. The current native LEAN oracle does not
+claim stop-order parity.
 
 ### Account
 
 | Setting | default | backtrader | vectorbt | zipline | lean | realistic |
 |---------|---------|-----------|----------|---------|------|-----------|
-| Short selling | No | Yes (margin) | Yes | No | Yes | No |
-| Leverage | No | Yes (50%) | No | No | No | No |
+| Short selling | No | Yes | Yes | Yes | Yes | No |
+| Leverage | No | No | No | Cash validation disabled | Yes, 2x | No |
 | Share type | integer | integer | fractional | integer | integer | integer |
 
 ### Costs
 
 | Setting | default | backtrader | vectorbt | zipline | lean | realistic |
 |---------|---------|-----------|----------|---------|------|-----------|
-| Commission | none | 0.1% | none | $0.005/share | $0.005/share | 0.2% |
-| Slippage | none | 0.1% | none | 10% volume | 0.1% | 0.2% |
+| Commission | none | none | none | none | $0.005/share | 0.2% |
+| Slippage | none | none | none | none | none | 0.2% |
 | Stop slippage | 0 | 0 | 0 | 0 | 0 | 0.1% |
 | Cash buffer | 0% | 0% | 0% | 0% | 0% | 2% |
+| Target-weight multiplier | 100% | 100% | 100% | 100% | 99.75% | 100% |
 
 ### Order Processing
 
 | Setting | default | backtrader | vectorbt | zipline | lean | realistic |
 |---------|---------|-----------|----------|---------|------|-----------|
-| Fill ordering | exit_first | fifo | exit_first | exit_first | exit_first | exit_first |
-| Reject insuff. | yes | yes | no | yes | yes | yes |
-| Partial fills | no | no | yes | yes | no | no |
+| Fill ordering | exit_first | fifo | exit_first | fifo | sequential | exit_first |
+| Reject insuff. | yes | yes | no | no | yes | yes |
+| Partial fills | no | no | yes | no | no | no |
 | Rebalance mode | incremental | snapshot | hybrid | snapshot | snapshot | incremental |
 
 ## Parity Validation
 
-Framework profiles can be validated at two levels:
+Framework profiles are validated on the workloads each retained artifact declares:
+
+1. **Real strategies**: Complete canonical fill streams, every shared equity timestamp, and
+   terminal values for supported pairs drawn from ETF allocation, CME futures, and crypto
+   perpetual-funding case studies. Frozen model-derived targets are shared by both engines.
+
+2. **Synthetic scenarios**: Exact ordered trade and fill matching on the required matrix for
+   VectorBT, Backtrader, and Zipline. Capability declarations identify reconstructed and
+   unavailable result surfaces.
 
-1. **Scenario-level** (16 scenarios per framework): Exact trade-by-trade matching on synthetic data covering entries, exits, stops, trailing stops, brackets, and multi-asset strategies.
+3. **Synthetic stress**: Exact target-intent, native-fill, fill-derived closed-trade, and
+   terminal-state comparison on a reconstructable 250-asset, 5,040-session workload. Each
+   framework row states the surface it exposes; the claim does not include unavailable
+   order-lifecycle fields.
 
-2. **Large-scale**: Trade-by-trade comparison on a retained real-data workload. A claim is omitted
-   when no passing artifact is retained for that framework.
+LEAN has separate native-behavior and Chapter 16 case-study evidence. The frozen engine produced
+47,652 fills across three case studies; ML4T matched every canonical fill and each terminal value
+at the declared $0.0001 quantum. See `validation/native/evidence/lean-18001.json` and
+`validation/lean/case_study_evidence.json`.
 
 <!-- parity-claims:start -->
 <!-- Generated by validation/generate_parity_claims.py. Do not edit by hand. -->
 
-Scenario claims use the retained release-candidate matrix. "Exact" appears only when every required scenario has zero canonical gap.
+Scenario claims use the retained accepted matrix. "Exact" means terminal values, ordered closed trades, and ordered fills match after 1e-8 quantization. Each record declares whether a surface is native, reconstructed, aggregate-only, input-only, or unavailable; the claim does not extend to unavailable order-lifecycle fields.
 
 | Profile | Pinned framework | Required scenarios | Evidence |
 |---|---|---:|---|
-| `vectorbt_strict` | [VectorBT Pro 2025.12.31](https://github.com/polakowo/vectorbt.pro) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `vectorbt` | [VectorBT OSS 0.28.2](https://pypi.org/project/vectorbt/0.28.2/) | 15/15 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 15/15 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-
-Large-scale claims are published only when a retained workload has zero canonical gap.
-
-| Profile | Pinned framework | Compared | Trade gap | Terminal value | Evidence |
-|---|---|---:|---:|---:|---|
-| `vectorbt_strict` | VectorBT Pro 2025.12.31 (`1305a1e19743`) | 225,844 trades | 0 | 685179.007330 | [large-scale evidence](https://github.com/ml4t/backtest/blob/main/validation/vectorbt_pro/large_scale_parity.json) |
-
-No large-scale claim is published for Backtrader, Zipline, VectorBT OSS, or LEAN without a passing retained artifact.
+| `vectorbt_strict` | [VectorBT Pro 2026.6.27](https://github.com/polakowo/vectorbt.pro) | 17/17 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `vectorbt_oss_strict` | [VectorBT OSS 1.1.0](https://pypi.org/project/vectorbt/1.1.0/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 17/17 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+
+The controlled scale workload contains 250 assets and 5,040 daily sessions (1,260,000 bars). Every row has zero canonical gap for target intents, native fills, closed trades reconstructed from those fills, and terminal state reconstructed from the fill ledger and final marks.
+
+| Profile | Current framework | Target intents | Native fills | Fill-derived closed trades | Terminal value | Evidence |
+|---|---|---:|---:|---:|---:|---|
+| `vectorbt_strict` | [VectorBT Pro 2026.6.27](https://github.com/polakowo/vectorbt.pro) | 427,790 | 390,369 | 188,549 | 716,785.408089 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `vectorbt_oss_strict` | [VectorBT OSS 1.1.0](https://pypi.org/project/vectorbt/1.1.0/) | 427,790 | 390,369 | 188,549 | 716,785.408089 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 427,790 | 343,813 | 182,019 | -9,166,273.555954 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 427,790 | 427,696 | 226,434 | 10,504,095.900000 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `lean` | [LEAN 18001](https://github.com/QuantConnect/Lean) | 427,790 | 361,297 | 191,297 | 184,538.130000 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
 <!-- parity-claims:end -->
 
 ## Performance
 
-The stable release does not publish cross-framework speed ratios. Release performance evidence is
-limited to the deterministic workloads and measurement boundaries in
-`validation/performance_baselines.json`; framework parity uses correctness evidence instead.
+The stable release does not publish cross-framework speed ratios. ML4T-only regression evidence is
+defined in `validation/performance_baselines.json`. The separate retained cross-framework artifact
+uses one warm-up and ten process-isolated measurements per runner, with raw samples, median and 95%
+intervals, process-tree peak RSS, exact output checksums, and an idiomatic view that makes no
+equivalence claim.
+
+`validation/REAL_STRATEGY_PERFORMANCE.json` separately retains engine-only timings for the six
+real-strategy pairs that passed correctness. It excludes data loading, inference, target
+construction, adapter preparation, extraction, and reporting. The results apply only to the named
+versions, bundles, and machine.
 
 ## Listing Profiles
 
diff --git a/pyproject.toml b/pyproject.toml
index f6f4a7fc..f94d65d1 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -81,7 +81,7 @@ dependencies = [
     "pandas>=3.0.5; python_version >= '3.15'",
     "numpy>=2.3.2",
     "PyYAML>=6.0.3",
-    "pandas-market-calendars>=5.2.4",
+    "pandas-market-calendars>=5.4.0",
 ]
 
 [project.optional-dependencies]
diff --git a/src/ml4t/backtest/_validation/case_study_lean.py b/src/ml4t/backtest/_validation/case_study_lean.py
index 2f6782ad..885e45c2 100644
--- a/src/ml4t/backtest/_validation/case_study_lean.py
+++ b/src/ml4t/backtest/_validation/case_study_lean.py
@@ -28,6 +28,7 @@
 import math
 import re
 import zipfile
+from decimal import ROUND_HALF_EVEN, Decimal
 from pathlib import Path
 
 import pandas as pd
@@ -39,10 +40,25 @@
 from ..strategy import Strategy
 
 _NUMBER = r"[-+]?(?:\d[\d_]*(?:\.\d[\d_]*)?|\.\d[\d_]*)(?:[eE][-+]?\d[\d_]*)?"
+_MONEY_QUANTUM = Decimal("0.0001")
+RETAINED_ORDER_EVENT_ARTIFACTS = {
+    "chapter16_etfs": ("ml4t_order_events.csv.xz",),
+    "chapter16_sp500_equity_option_analytics": ("ml4t_order_events.csv",),
+    "chapter16_us_equities_panel": (
+        "ml4t_order_events.csv.part01.xz",
+        "ml4t_order_events.csv.part02.xz",
+    ),
+}
 
 
 def _csv_path(base_dir: Path, name: str) -> Path:
-    for suffix in ("", ".xz", ".gz"):
+    if name == "ml4t_order_events.csv":
+        retained = RETAINED_ORDER_EVENT_ARTIFACTS.get(base_dir.name)
+        if retained and len(retained) == 1:
+            candidate = base_dir / retained[0]
+            if candidate.is_file():
+                return candidate
+    for suffix in (".xz", ".gz", ""):
         path = base_dir / f"{name}{suffix}"
         if path.exists():
             return path
@@ -249,7 +265,7 @@ def lean_side(workspace_dir: Path) -> dict:
     final_value = float(equity["equity"].iloc[-1])
 
     events = _read_csv_fixture(workspace_dir, "ml4t_order_events.csv", low_memory=False)
-    filled = events[events["status"].astype(str) == "Filled"].copy()
+    filled = events[events["status"].astype(str).str.lower() == "filled"].copy()
     filled["asset"] = filled["symbol"].astype(str).map(symbol_map).fillna(filled["symbol"])
     filled = filled.rename(columns={"fill_quantity": "quantity", "fill_price": "price"})
     filled["side"] = filled["direction"].astype(str).str.lower()
@@ -267,11 +283,20 @@ def compare(lean: dict, ml4t: dict) -> dict:
         len(ls) == len(ms)
         and not (lean["fills"][cols].reset_index(drop=True) != ml4t["fills"][cols]).any().any()
     )
+    lean_value = Decimal(str(lean["final_value"])).quantize(
+        _MONEY_QUANTUM, rounding=ROUND_HALF_EVEN
+    )
+    ml4t_value = Decimal(str(ml4t["final_value"])).quantize(
+        _MONEY_QUANTUM, rounding=ROUND_HALF_EVEN
+    )
     return {
         "lean_final_value": lean["final_value"],
         "ml4t_final_value": ml4t["final_value"],
         "final_value_gap_usd": ml4t["final_value"] - lean["final_value"],
         "final_value_gap_pct": ml4t["final_value"] / lean["final_value"] - 1.0,
+        "canonical_final_value_gap_usd": float(ml4t_value - lean_value),
+        "canonical_final_value_match": ml4t_value == lean_value,
+        "final_value_quantum_usd": float(_MONEY_QUANTUM),
         "lean_fills": len(lean["fills"]),
         "ml4t_fills": len(ml4t["fills"]),
         "fill_gap": len(ml4t["fills"]) - len(lean["fills"]),
diff --git a/src/ml4t/backtest/_validation/lean_runner.py b/src/ml4t/backtest/_validation/lean_runner.py
index 49bc861a..3afb17cc 100644
--- a/src/ml4t/backtest/_validation/lean_runner.py
+++ b/src/ml4t/backtest/_validation/lean_runner.py
@@ -184,15 +184,25 @@ def load_lean_artifacts(
 
 
 def resolve_lean_command() -> list[str]:
-    """Resolve the local LEAN CLI command."""
+    """Resolve a preinstalled LEAN CLI command without installing an unpinned version."""
+    configured = os.getenv("ML4T_LEAN_COMMAND")
+    if configured:
+        return [configured]
+
+    locked_binary = (
+        Path.cwd() / ".venv-lean" / ("Scripts/lean.exe" if os.name == "nt" else "bin/lean")
+    )
+    if locked_binary.is_file():
+        return [str(locked_binary)]
+
     lean_binary = shutil.which("lean")
     if lean_binary is not None:
         return [lean_binary]
 
-    uvx_binary = shutil.which("uvx")
-    if uvx_binary is None:
-        raise FileNotFoundError("Neither 'lean' nor 'uvx' executable found.")
-    return [uvx_binary, "--python", "3.12", "--with", "setuptools<81", "lean"]
+    raise FileNotFoundError(
+        "LEAN CLI not found; build the frozen environment with "
+        "validation/build_framework_env.py --framework lean"
+    )
 
 
 def make_lean_env() -> dict[str, str]:
@@ -308,10 +318,13 @@ def run_lean_backtest(
     project_dir: Path,
     lean_config: Path,
     output_dir: Path,
+    image: str,
     timeout: int = 1800,
     env: dict[str, str] | None = None,
 ) -> float:
-    """Run a LEAN backtest and return the runtime in seconds."""
+    """Run a LEAN backtest with an immutable engine image and return its runtime."""
+    if "@sha256:" not in image:
+        raise ValueError(f"LEAN image must use an immutable digest: {image}")
     if output_dir.exists():
         shutil.rmtree(output_dir)
 
@@ -320,6 +333,8 @@ def run_lean_backtest(
         str(project_dir),
         "--lean-config",
         str(lean_config),
+        "--image",
+        image,
         "--no-update",
         "--output",
         str(output_dir),
diff --git a/src/ml4t/backtest/accounting/account.py b/src/ml4t/backtest/accounting/account.py
index 01f32e09..89782141 100644
--- a/src/ml4t/backtest/accounting/account.py
+++ b/src/ml4t/backtest/accounting/account.py
@@ -38,6 +38,7 @@ def __init__(self, initial_cash: float, policy: AccountPolicy):
         """
         self.cash = initial_cash
         self._lock_notional_free_cash = initial_cash
+        self._lock_notional_short_basis: dict[str, float] = {}
         self.positions: dict[str, Position] = {}
         self.policy = policy
 
diff --git a/src/ml4t/backtest/accounting/policy.py b/src/ml4t/backtest/accounting/policy.py
index 964bbb67..2c35a524 100644
--- a/src/ml4t/backtest/accounting/policy.py
+++ b/src/ml4t/backtest/accounting/policy.py
@@ -335,14 +335,14 @@ def __init__(
                 raise ValueError(
                     f"Short maintenance margin must be in (0.0, 1.0], got {short_maintenance_margin}"
                 )
-            if long_maintenance_margin >= initial_margin:
+            if long_maintenance_margin > initial_margin:
                 raise ValueError(
-                    f"Long maintenance margin ({long_maintenance_margin}) must be < "
+                    f"Long maintenance margin ({long_maintenance_margin}) must be <= "
                     f"initial margin ({initial_margin})"
                 )
-            if short_maintenance_margin >= initial_margin:
+            if short_maintenance_margin > initial_margin:
                 raise ValueError(
-                    f"Short maintenance margin ({short_maintenance_margin}) must be < "
+                    f"Short maintenance margin ({short_maintenance_margin}) must be <= "
                     f"initial margin ({initial_margin})"
                 )
 
diff --git a/src/ml4t/backtest/broker.py b/src/ml4t/backtest/broker.py
index 51f1a328..5ec0b753 100644
--- a/src/ml4t/backtest/broker.py
+++ b/src/ml4t/backtest/broker.py
@@ -15,6 +15,7 @@
     FillOrdering,
     InitialHwmSource,
     LateAssetPolicy,
+    LockNotionalUpdateMode,
     MissingPricePolicy,
     ShareType,
     ShortCashPolicy,
@@ -103,6 +104,7 @@ def __init__(
         fixed_margin_schedule: dict[str, tuple[float, float]] | None = None,
         margin_pct_schedule: dict[str, tuple[float, float]] | None = None,
         short_cash_policy: ShortCashPolicy = ShortCashPolicy.CREDIT,
+        lock_notional_update_mode: LockNotionalUpdateMode = LockNotionalUpdateMode.POSITION_LEGS,
         execution_limits: ExecutionLimits | None = None,
         market_impact_model: MarketImpactModel | None = None,
         contract_specs: dict[str, ContractSpec] | None = None,
@@ -214,6 +216,7 @@ def __init__(
         self.fixed_margin_schedule = effective_margin_schedule
         self.margin_pct_schedule = effective_margin_pct_schedule
         self.short_cash_policy = short_cash_policy
+        self.lock_notional_update_mode = lock_notional_update_mode
 
         # Create Gatekeeper for order validation
         self.gatekeeper = Gatekeeper(
@@ -409,6 +412,7 @@ def from_config(
             fixed_margin_schedule=config.fixed_margin_schedule,
             margin_pct_schedule=config.margin_pct_schedule,
             short_cash_policy=config.short_cash_policy,
+            lock_notional_update_mode=config.lock_notional_update_mode,
             execution_limits=execution_limits,
             market_impact_model=market_impact_model,
             contract_specs=contract_specs,
diff --git a/src/ml4t/backtest/config.py b/src/ml4t/backtest/config.py
index 93c12026..9d903d30 100644
--- a/src/ml4t/backtest/config.py
+++ b/src/ml4t/backtest/config.py
@@ -87,6 +87,13 @@ class ShareType(str, Enum):
     INTEGER = "integer"  # Round down to whole shares (like most real brokers)
 
 
+class ShareRounding(str, Enum):
+    """Integer-share rounding used during target-weight sizing."""
+
+    NEAREST = "nearest"
+    TRUNCATE = "truncate"
+
+
 class FillOrdering(str, Enum):
     """Order processing sequence within a single bar.
 
@@ -153,6 +160,20 @@ class ShortCashPolicy(str, Enum):
     LOCK_NOTIONAL = "lock_notional"
 
 
+class LockNotionalUpdateMode(str, Enum):
+    """Floating-point operation order for locked-notional cash updates.
+
+    POSITION_LEGS:
+        Settle closing and opening position legs separately.
+
+    COMBINED_ORDER:
+        Settle the gross cash and short-debt effects as one order.
+    """
+
+    POSITION_LEGS = "position_legs"
+    COMBINED_ORDER = "combined_order"
+
+
 class RebalanceMode(str, Enum):
     """How portfolio value is computed during multi-asset rebalancing.
 
@@ -262,6 +283,7 @@ class InitialHwmSource(str, Enum):
 
     Controls what price is used for HWM when a new position is created:
     - FILL_PRICE: Use the actual fill price including slippage (default)
+    - SIGNAL_PRICE: Use the price observed when the entry order was submitted
     - BAR_CLOSE: Use the bar's close price
     - BAR_HIGH: Use the bar's high price (VBT Pro with OHLC data)
 
@@ -271,6 +293,7 @@ class InitialHwmSource(str, Enum):
     """
 
     FILL_PRICE = "fill_price"  # Use fill price (default, most frameworks)
+    SIGNAL_PRICE = "signal_price"  # Use the entry order's signal price (Backtrader)
     BAR_CLOSE = "bar_close"  # Use bar's close
     BAR_HIGH = "bar_high"  # Use bar's high (VBT Pro with OHLC)
 
@@ -502,6 +525,7 @@ class BacktestConfig:
     fixed_margin_schedule: dict[str, tuple[float, float]] | None = None  # For futures
     margin_pct_schedule: dict[str, tuple[float, float]] | None = None  # Price-aware futures margin
     short_cash_policy: ShortCashPolicy = ShortCashPolicy.CREDIT
+    lock_notional_update_mode: LockNotionalUpdateMode = LockNotionalUpdateMode.POSITION_LEGS
 
     # === Execution Timing ===
     execution_price: ExecutionPrice = ExecutionPrice.OPEN
@@ -695,6 +719,7 @@ def get_effective_account_type(self) -> str:
 
     # === Position Sizing ===
     share_type: ShareType = ShareType.INTEGER
+    share_rounding: ShareRounding = ShareRounding.NEAREST
 
     # === Commission ===
     commission_type: CommissionType = CommissionType.NONE
@@ -731,10 +756,9 @@ def get_effective_account_type(self) -> str:
     next_bar_submission_precheck: bool = False
     next_bar_simple_cash_check: bool = False
     buying_power_reservation: bool = False  # Reserve cash at submission (LEAN-style)
-    # TODO(parity): consider an explicit profile/knob for "commit basket at close,
-    # fill reserved orders at next open" semantics. Keep it separate from the
-    # default next-bar/open path, which currently revalidates affordability at
-    # the actual open.
+    # Validate a next-open batch against a shadow account in submission order.
+    # When combined with next_bar_submission_precheck, each order first gets an
+    # independent close-price check before the batch is rechecked next session.
     next_bar_queue_shadow_validation: bool = False
     immediate_fill: bool = False  # Fill same-bar market orders at submit time (LEAN-style)
     rebalance_mode: RebalanceMode = RebalanceMode.INCREMENTAL
@@ -877,6 +901,7 @@ def to_dict(self) -> dict:
                 "fixed_margin_schedule": _margin_schedule_to_dict(self.fixed_margin_schedule),
                 "margin_pct_schedule": _margin_schedule_to_dict(self.margin_pct_schedule),
                 "short_cash_policy": self.short_cash_policy.value,
+                "lock_notional_update_mode": self.lock_notional_update_mode.value,
             },
             "execution": {
                 "execution_price": self.execution_price.value,
@@ -893,6 +918,7 @@ def to_dict(self) -> dict:
             },
             "position_sizing": {
                 "share_type": self.share_type.value,
+                "share_rounding": self.share_rounding.value,
             },
             "commission": {
                 "model": self.commission_type.value,
@@ -993,6 +1019,7 @@ def from_dict(
                     "fixed_margin_schedule",
                     "margin_pct_schedule",
                     "short_cash_policy",
+                    "lock_notional_update_mode",
                 },
                 "execution": {"execution_price", "mark_price", "execution_mode"},
                 "stops": {
@@ -1003,7 +1030,7 @@ def from_dict(
                     "initial_hwm_source",
                     "trail_stop_timing",
                 },
-                "position_sizing": {"share_type"},
+                "position_sizing": {"share_type", "share_rounding"},
                 "commission": {"model", "rate", "per_share", "per_trade", "minimum"},
                 "slippage": {
                     "model",
@@ -1117,6 +1144,9 @@ def from_dict(
             fixed_margin_schedule=acct_cfg.get("fixed_margin_schedule"),
             margin_pct_schedule=acct_cfg.get("margin_pct_schedule"),
             short_cash_policy=ShortCashPolicy(acct_cfg.get("short_cash_policy", "credit")),
+            lock_notional_update_mode=LockNotionalUpdateMode(
+                acct_cfg.get("lock_notional_update_mode", "position_legs")
+            ),
             # Execution
             execution_price=ExecutionPrice(
                 exec_cfg.get("execution_price", ExecutionPrice.OPEN.value)
@@ -1136,6 +1166,7 @@ def from_dict(
             trail_stop_timing=TrailStopTiming(stops_cfg.get("trail_stop_timing", "lagged")),
             # Sizing
             share_type=ShareType(sizing_cfg.get("share_type", "integer")),
+            share_rounding=ShareRounding(sizing_cfg.get("share_rounding", "nearest")),
             # Commission
             commission_type=CommissionType(comm_cfg.get("model", "none")),
             commission_rate=comm_cfg.get("rate", 0.0),
@@ -1219,7 +1250,7 @@ def from_preset(cls, preset: str) -> BacktestConfig:
         - "backtrader": Match Backtrader's default behavior
         - "vectorbt": Match VectorBT's default behavior
         - "zipline": Match Zipline's default behavior
-        - "lean": Match QuantConnect LEAN's default behavior
+        - "lean": Match the frozen LEAN daily US-equity comparison protocol
         - "realistic": Conservative settings for realistic simulation
         - "ibkr_us_stocks_fixed": Interactive Brokers US stocks fixed pricing
         """
diff --git a/src/ml4t/backtest/core/execution_engine.py b/src/ml4t/backtest/core/execution_engine.py
index 06a513b5..e15f75aa 100644
--- a/src/ml4t/backtest/core/execution_engine.py
+++ b/src/ml4t/backtest/core/execution_engine.py
@@ -3,7 +3,8 @@
 from __future__ import annotations
 
 import copy
-from typing import TYPE_CHECKING
+import math
+from typing import TYPE_CHECKING, TypeGuard
 
 from ..models import calculate_commission
 from ..types import ExecutionMode, Order, OrderSide, OrderStatus, OrderType, Position
@@ -16,6 +17,10 @@
     from .fill_engine import FillEngine
 
 
+def _price_available(price: object) -> TypeGuard[int | float]:
+    return isinstance(price, (int, float)) and math.isfinite(price)
+
+
 class ExecutionEngine:
     """Executes pending orders using configured fill ordering."""
 
@@ -129,7 +134,7 @@ def _process_orders_exit_first(
                 deferred_entries.append(order)
                 continue
             price = fill.get_fill_price_for_order(order, use_open)
-            if price is None:
+            if not _price_available(price):
                 continue
             fill_price = fill.check_fill(order, price)
             if fill_price is not None:
@@ -174,18 +179,13 @@ def _should_use_next_bar_queue_shadow_validation(
         if order_types is not None or order_ids is not None or include_orders_this_bar:
             return False
 
-        current_bar_index = self.market.bar_index
         eligible_orders = self._eligible_orders(
             use_open,
             order_types=order_types,
             order_ids=order_ids,
             include_orders_this_bar=include_orders_this_bar,
         )
-        for order in eligible_orders:
-            if getattr(order, "_created_bar_index", current_bar_index) < current_bar_index - 1:
-                return True
-
-        return False
+        return bool(eligible_orders)
 
     def _process_orders_next_bar_queue_shadow(
         self,
@@ -221,7 +221,7 @@ def _process_orders_next_bar_queue_shadow(
 
         for order in eligible_orders:
             price = fill.get_fill_price_for_order(order, use_open)
-            if price is None:
+            if not _price_available(price):
                 continue
 
             fill.apply_share_rounding(order)
@@ -451,7 +451,7 @@ def _process_orders_sequential(
                 continue
 
             price = fill.get_fill_price_for_order(order, use_open)
-            if price is None:
+            if not _price_available(price):
                 continue
 
             fill.apply_share_rounding(order)
@@ -500,7 +500,7 @@ def _process_single_order(
         if order.status is not OrderStatus.PENDING:
             return
         price = fill.get_fill_price_for_order(order, use_open)
-        if price is None:
+        if not _price_available(price):
             return
 
         skip_cash = broker.skip_cash_validation
@@ -678,7 +678,15 @@ def _passes_simple_cash_check(self, order, fill_price: float) -> bool:
             broker.commission_model, order.asset, order.quantity, fill_price
         )
         projected_cash = broker.cash - signed_qty * fill_price - commission
-        return projected_cash >= 0.0
+        if projected_cash >= 0.0:
+            return True
+
+        # Backtrader executes the closing leg of a reversal after an
+        # opening-price gap, even when that close leaves cash negative.
+        if is_opposite and order.quantity > abs(current_qty):
+            order.quantity = abs(current_qty)
+            return True
+        return False
 
     def _cleanup_filled_orders(self, filled_orders: list) -> None:
         filled_ids = {o.order_id for o in filled_orders}
@@ -711,8 +719,10 @@ def _sort_entry_orders(self, orders: list, use_open: bool) -> list:
 
         def notional(order) -> float:
             px = fill.get_fill_price_for_order(order, use_open)
-            if px is None:
+            if not _price_available(px):
                 px = self.market.prices.get(order.asset, self.market.opens.get(order.asset, 0.0))
+            if not _price_available(px):
+                return 0.0
             return abs(order.quantity * px)
 
         reverse = priority == "notional_desc"
diff --git a/src/ml4t/backtest/core/fill_engine.py b/src/ml4t/backtest/core/fill_engine.py
index 7012d775..a29b440b 100644
--- a/src/ml4t/backtest/core/fill_engine.py
+++ b/src/ml4t/backtest/core/fill_engine.py
@@ -5,9 +5,10 @@
 from dataclasses import replace
 from typing import TYPE_CHECKING
 
-from ..config import ExecutionPrice, ShareType
+from ..config import ExecutionPrice, LockNotionalUpdateMode, ShareType
+from ..models import calculate_commission
 from ..types import OrderSide, OrderType
-from .shared import CASH_TOLERANCE
+from .shared import CASH_TOLERANCE, add_with_zero_cancellation
 from .state import MarketState, OrderState
 
 if TYPE_CHECKING:
@@ -62,6 +63,10 @@ def get_max_affordable_quantity(self, order, fill_price: float) -> float:
         if fill_price <= 0 or order.quantity <= 0:
             return 0.0
 
+        direct_limit = self._get_lock_notional_zero_cost_limit(order, fill_price)
+        if direct_limit is not None:
+            return min(order.quantity, direct_limit)
+
         if self.broker.share_type == ShareType.INTEGER:
             high_int = int(order.quantity)
             if high_int <= 0:
@@ -97,6 +102,79 @@ def get_max_affordable_quantity(self, order, fill_price: float) -> float:
             cash_tolerance = 0.0
         return max(0.0, low - cash_tolerance / fill_price)
 
+    def _get_lock_notional_zero_cost_limit(self, order, fill_price: float) -> float | None:
+        broker = self.broker
+        if (
+            broker.share_type != ShareType.FRACTIONAL
+            or broker.short_cash_policy.value != "lock_notional"
+            or broker.account.policy.allow_leverage
+            or broker.cash_buffer_pct != 0.0
+            or calculate_commission(
+                broker.commission_model,
+                order.asset,
+                order.quantity,
+                fill_price,
+            )
+            != 0.0
+        ):
+            return None
+
+        free_cash = broker.account._lock_notional_free_cash
+        current_quantity = broker.account.get_position_quantity(order.asset)
+        multiplier = broker.get_multiplier(order.asset)
+        unit_cost = fill_price * multiplier
+
+        if broker.lock_notional_update_mode is LockNotionalUpdateMode.COMBINED_ORDER:
+            if order.side is OrderSide.BUY and current_quantity < 0.0:
+                short_quantity = abs(current_quantity)
+                short_basis = broker.account._lock_notional_short_basis.get(order.asset, 0.0)
+                cover_required = short_quantity * unit_cost
+                cover_free_cash = add_with_zero_cancellation(
+                    free_cash + 2 * short_basis,
+                    -cover_required,
+                )
+                if cover_free_cash > 0.0:
+                    cash_limit = free_cash + 2 * short_basis
+                elif cover_free_cash < 0.0:
+                    average_entry = short_basis / short_quantity
+                    denominator = unit_cost - 2 * average_entry
+                    if denominator == 0.0:
+                        return 0.0
+                    max_short_size = free_cash / denominator
+                    cash_limit = max_short_size * unit_cost
+                else:
+                    cash_limit = broker.cash
+                return max(0.0, min(cash_limit, broker.cash) / unit_cost)
+
+            if order.side is OrderSide.SELL:
+                long_quantity = max(current_quantity, 0.0)
+                long_cash = long_quantity * unit_cost
+                total_free_cash = add_with_zero_cancellation(free_cash, long_cash)
+                if total_free_cash <= 0.0:
+                    return long_quantity if current_quantity > 0.0 else 0.0
+                max_short_size = total_free_cash / unit_cost
+                return add_with_zero_cancellation(long_quantity, max_short_size)
+
+            return max(0.0, free_cash / unit_cost)
+
+        if order.side is OrderSide.BUY and current_quantity < 0.0:
+            short_quantity = abs(current_quantity)
+            short_basis = broker.account._lock_notional_short_basis.get(order.asset, 0.0)
+            cover_budget = free_cash + short_basis + short_basis
+            max_cover = cover_budget / unit_cost
+            if max_cover < short_quantity:
+                return max_cover
+            released = short_basis + short_basis - short_quantity * unit_cost
+            free_after_cover = add_with_zero_cancellation(free_cash, released)
+            return short_quantity + max(0.0, free_after_cover / unit_cost)
+
+        if order.side is OrderSide.SELL and current_quantity > 0.0:
+            sale_proceeds = current_quantity * unit_cost
+            free_after_close = add_with_zero_cancellation(free_cash, sale_proceeds)
+            return current_quantity + max(0.0, free_after_close / unit_cost)
+
+        return max(0.0, free_cash / unit_cost)
+
     def try_partial_fill(self, order, fill_price: float) -> bool:
         max_shares = self.get_max_affordable_quantity(order, fill_price)
 
diff --git a/src/ml4t/backtest/core/order_book.py b/src/ml4t/backtest/core/order_book.py
index d7616e65..d77d5657 100644
--- a/src/ml4t/backtest/core/order_book.py
+++ b/src/ml4t/backtest/core/order_book.py
@@ -2,9 +2,11 @@
 
 from __future__ import annotations
 
+import math
 from datetime import datetime
 from typing import TYPE_CHECKING
 
+from ..config import MissingPricePolicy
 from ..models import calculate_commission
 from ..types import ExecutionMode, Order, OrderSide, OrderStatus, OrderType, Position
 from .shared import SubmitOrderOptions, is_exit_order, quantity_zero_tolerance
@@ -171,7 +173,10 @@ def _fill_immediately(self, order: Order) -> Order:
 
         # Get fill price (close price for same-bar)
         price = fill.get_fill_price_for_order(order, use_open=False)
-        if price is None:
+        missing_price = price is None or not math.isfinite(price)
+        if missing_price and broker.missing_price_policy is MissingPricePolicy.USE_LAST:
+            price = broker.get_last_price(order.asset)
+        if price is None or not math.isfinite(price):
             order.reject("No price available", "price_unavailable")
             return order
 
@@ -365,7 +370,11 @@ def _passes_submission_precheck(self, order: Order) -> bool:
         self._reset_submission_shadow_if_needed()
 
         if broker.allow_leverage and not broker.next_bar_simple_cash_check:
-            return self._passes_margin_submission_precheck(order, signal_price)
+            return self._passes_margin_submission_precheck(
+                order,
+                signal_price,
+                commit=not broker.next_bar_queue_shadow_validation,
+            )
 
         size = order.quantity if order.side is OrderSide.BUY else -order.quantity
         old_qty, old_price = self._submission_shadow_positions.get(order.asset, (0.0, signal_price))
@@ -488,11 +497,17 @@ def _passes_buying_power_check(self, order: Order) -> bool:
             self._submission_shadow_positions[order.asset] = (new_qty, new_price)
         return True
 
-    def _passes_margin_submission_precheck(self, order: Order, signal_price: float) -> bool:
+    def _passes_margin_submission_precheck(
+        self,
+        order: Order,
+        signal_price: float,
+        *,
+        commit: bool = True,
+    ) -> bool:
         """Margin-aware submission precheck for NEXT_BAR market orders.
 
-        Simulates sequential submission-time acceptance using policy validation at
-        signal-bar prices and commits only accepted orders into shadow state.
+        Validate at the signal-bar price. ``commit=False`` keeps each check
+        independent, while ``commit=True`` reserves accepted orders in shadow state.
         """
         broker = self.broker
 
@@ -571,6 +586,9 @@ def _passes_margin_submission_precheck(self, order: Order, signal_price: float)
             order._rejection_code = rejection_code
             return False
 
+        if not commit:
+            return True
+
         multiplier = broker.get_multiplier(order.asset)
         self._submission_shadow_cash += -size * signal_price * multiplier - commission
         if abs(new_qty) <= quantity_zero_tolerance(old_qty, size):
diff --git a/src/ml4t/backtest/core/shared.py b/src/ml4t/backtest/core/shared.py
index 2a9b321e..81fd44a0 100644
--- a/src/ml4t/backtest/core/shared.py
+++ b/src/ml4t/backtest/core/shared.py
@@ -4,7 +4,7 @@
 
 import re
 from dataclasses import dataclass
-from math import fabs, isfinite, ulp
+from math import copysign, fabs, isclose, isfinite, ulp
 from typing import TYPE_CHECKING
 
 from ..types import ExitReason, OrderSide
@@ -19,6 +19,15 @@
 QUANTITY_ZERO_ULPS: int = 16
 
 
+def add_with_zero_cancellation(left: float, right: float) -> float:
+    """Add values while collapsing tolerance-equivalent opposite amounts to zero."""
+    if copysign(1.0, left) != copysign(1.0, right) and isclose(
+        abs(left), abs(right), rel_tol=1e-9, abs_tol=1e-12
+    ):
+        return 0.0
+    return left + right
+
+
 def quantity_zero_tolerance(*operands: float) -> float:
     """Return the larger of the absolute floor and 16 ULP at the operand scale.
 
diff --git a/src/ml4t/backtest/execution/fill_executor.py b/src/ml4t/backtest/execution/fill_executor.py
index 7567e74a..27d0ebca 100644
--- a/src/ml4t/backtest/execution/fill_executor.py
+++ b/src/ml4t/backtest/execution/fill_executor.py
@@ -13,8 +13,8 @@
 from datetime import datetime
 from typing import TYPE_CHECKING
 
-from ..config import InitialHwmSource, ShareType
-from ..core.shared import quantity_zero_tolerance
+from ..config import InitialHwmSource, LockNotionalUpdateMode, ShareType
+from ..core.shared import add_with_zero_cancellation, quantity_zero_tolerance
 from ..core.state import ExecutionJournal, MarketState, OrderState, RiskState
 from ..models import calculate_commission, calculate_slippage
 from ..types import (
@@ -62,15 +62,6 @@ def _calculate_position_pnl(
     return (exit_price * signed_quantity - entry_price * signed_quantity) * multiplier
 
 
-def _add_with_zero_cancellation(left: float, right: float) -> float:
-    """Add values while collapsing tolerance-equivalent opposite amounts to zero."""
-    if math.copysign(1.0, left) != math.copysign(1.0, right) and math.isclose(
-        abs(left), abs(right), rel_tol=1e-9, abs_tol=1e-12
-    ):
-        return 0.0
-    return left + right
-
-
 @dataclass
 class FillContext:
     """Context for a single fill execution.
@@ -314,7 +305,6 @@ def execute(self, order: Order, base_price: float) -> bool:
 
         old_position = self.account.positions.get(order.asset)
         old_quantity = old_position.quantity if old_position is not None else 0.0
-        old_entry_price = old_position.entry_price if old_position is not None else 0.0
 
         # Update position and get actual commission (may change for flips)
         actual_commission = self._update_position(ctx)
@@ -323,7 +313,6 @@ def execute(self, order: Order, base_price: float) -> bool:
         self._update_lock_notional_free_cash(
             ctx,
             old_quantity=old_quantity,
-            old_entry_price=old_entry_price,
             commission=actual_commission,
         )
 
@@ -357,7 +346,6 @@ def _update_lock_notional_free_cash(
         ctx: FillContext,
         *,
         old_quantity: float,
-        old_entry_price: float,
         commission: float,
     ) -> None:
         broker = self.broker
@@ -365,26 +353,106 @@ def _update_lock_notional_free_cash(
         if policy.allow_leverage or policy.short_cash_policy != "lock_notional":
             return
 
+        if broker.lock_notional_update_mode is LockNotionalUpdateMode.COMBINED_ORDER:
+            self._update_combined_lock_notional_cash(
+                ctx,
+                old_quantity=old_quantity,
+                commission=commission,
+            )
+            return
+
         remaining = ctx.signed_qty
         free_cash = self.account._lock_notional_free_cash
         multiplier = broker.get_multiplier(ctx.order.asset)
+        asset = ctx.order.asset
+        short_basis = self.account._lock_notional_short_basis.get(asset, 0.0)
 
         if old_quantity < 0.0 and remaining > 0.0:
             covered = min(remaining, abs(old_quantity))
-            released_basis = covered * old_entry_price * multiplier
+            size_fraction = covered / abs(old_quantity)
+            released_basis = size_fraction * short_basis
             required_cash = covered * ctx.fill_price * multiplier
-            free_cash = _add_with_zero_cancellation(free_cash, 2.0 * released_basis - required_cash)
+            free_cash = add_with_zero_cancellation(
+                free_cash,
+                released_basis + released_basis - required_cash,
+            )
+            new_quantity = old_quantity + covered
+            if new_quantity < 0.0:
+                new_fraction = abs(new_quantity) / abs(old_quantity)
+                self.account._lock_notional_short_basis[asset] = new_fraction * short_basis
+            else:
+                self.account._lock_notional_short_basis.pop(asset, None)
             remaining -= covered
         elif old_quantity > 0.0 and remaining < 0.0:
             closed = min(abs(remaining), old_quantity)
-            free_cash = _add_with_zero_cancellation(free_cash, closed * ctx.fill_price * multiplier)
+            free_cash = add_with_zero_cancellation(free_cash, closed * ctx.fill_price * multiplier)
             remaining += closed
 
+        new_position = self.account.positions.get(asset)
+        if (
+            new_position is not None
+            and old_quantity * new_position.quantity < 0.0
+            and remaining != 0.0
+        ):
+            remaining = new_position.quantity
+
         if remaining != 0.0:
             required_cash = abs(remaining) * ctx.fill_price * multiplier
-            free_cash = _add_with_zero_cancellation(free_cash, -required_cash)
+            free_cash = add_with_zero_cancellation(free_cash, -required_cash)
+            if remaining < 0.0:
+                current_basis = self.account._lock_notional_short_basis.get(asset, 0.0)
+                self.account._lock_notional_short_basis[asset] = current_basis + required_cash
+
+        self.account._lock_notional_free_cash = add_with_zero_cancellation(free_cash, -commission)
+
+    def _update_combined_lock_notional_cash(
+        self,
+        ctx: FillContext,
+        *,
+        old_quantity: float,
+        commission: float,
+    ) -> None:
+        """Settle locked collateral in VectorBT OSS combined-order operation order."""
+        broker = self.broker
+        asset = ctx.order.asset
+        free_cash = self.account._lock_notional_free_cash
+        short_basis = self.account._lock_notional_short_basis.get(asset, 0.0)
+        unit_cost = ctx.fill_price * broker.get_multiplier(asset)
+        fill_quantity = abs(ctx.signed_qty)
+
+        if ctx.signed_qty > 0.0:
+            required_cash = add_with_zero_cancellation(fill_quantity * unit_cost, commission)
+            if old_quantity < 0.0:
+                covered = min(fill_quantity, abs(old_quantity))
+                average_entry = short_basis / abs(old_quantity)
+                released_basis = covered * average_entry
+                free_cash = add_with_zero_cancellation(
+                    free_cash + 2 * released_basis,
+                    -required_cash,
+                )
+                new_basis = add_with_zero_cancellation(short_basis, -released_basis)
+                if old_quantity + covered < 0.0:
+                    self.account._lock_notional_short_basis[asset] = new_basis
+                else:
+                    self.account._lock_notional_short_basis.pop(asset, None)
+            else:
+                free_cash = add_with_zero_cancellation(free_cash, -required_cash)
+        else:
+            acquired_cash = add_with_zero_cancellation(fill_quantity * unit_cost, -commission)
+            new_quantity = old_quantity - fill_quantity
+            if new_quantity < 0.0:
+                short_quantity = fill_quantity if old_quantity < 0.0 else abs(new_quantity)
+                short_value = short_quantity * unit_cost
+                self.account._lock_notional_short_basis[asset] = short_basis + short_value
+                free_cash_difference = add_with_zero_cancellation(
+                    acquired_cash,
+                    -2 * short_value,
+                )
+                free_cash = add_with_zero_cancellation(free_cash, free_cash_difference)
+            else:
+                free_cash = free_cash + acquired_cash
 
-        self.account._lock_notional_free_cash = _add_with_zero_cancellation(free_cash, -commission)
+        self.account._lock_notional_free_cash = free_cash
 
     @staticmethod
     def _validate_execution_price(value: float, *, source: str) -> None:
@@ -430,12 +498,51 @@ def _update_position(self, ctx: FillContext) -> float:
                 self._close_position(ctx, pos, old_qty)
                 return ctx.commission
             elif _is_position_flip(old_qty, new_qty):
+                new_qty = self._get_lock_notional_flip_quantity(ctx, old_qty, new_qty)
                 return self._flip_position(ctx, pos, old_qty, new_qty)
             else:
                 self._scale_position(ctx, pos, old_qty, new_qty)
                 return ctx.commission
 
-    def _get_initial_hwm(self, asset: str, fill_price: float) -> float:
+    def _get_lock_notional_flip_quantity(
+        self,
+        ctx: FillContext,
+        old_quantity: float,
+        fallback: float,
+    ) -> float:
+        broker = self.broker
+        if (
+            broker.share_type != ShareType.FRACTIONAL
+            or broker.short_cash_policy.value != "lock_notional"
+            or broker.account.policy.allow_leverage
+            or broker.cash_buffer_pct != 0.0
+            or ctx.commission != 0.0
+            or broker.lock_notional_update_mode is LockNotionalUpdateMode.COMBINED_ORDER
+        ):
+            return fallback
+
+        unit_cost = ctx.fill_price * broker.get_multiplier(ctx.order.asset)
+        if ctx.fill_quantity == ctx.order.quantity:
+            requested_quantity = ctx.order.requested_quantity or ctx.order.quantity
+            requested_open = abs(requested_quantity) - abs(old_quantity)
+        else:
+            requested_open = abs(ctx.signed_qty) - abs(old_quantity)
+        free_cash = self.account._lock_notional_free_cash
+        if old_quantity < 0.0:
+            short_basis = self.account._lock_notional_short_basis.get(ctx.order.asset, 0.0)
+            released = short_basis + short_basis - abs(old_quantity) * unit_cost
+            free_after_close = add_with_zero_cancellation(free_cash, released)
+        else:
+            free_after_close = add_with_zero_cancellation(
+                free_cash,
+                abs(old_quantity) * unit_cost,
+            )
+        open_quantity = min(requested_open, max(0.0, free_after_close / unit_cost))
+        return math.copysign(open_quantity, ctx.signed_qty)
+
+    def _get_initial_hwm(
+        self, asset: str, fill_price: float, signal_price: float | None = None
+    ) -> float:
         """Get initial high water mark based on configuration.
 
         This is the single source of truth for HWM initialization,
@@ -449,6 +556,8 @@ def _get_initial_hwm(self, asset: str, fill_price: float) -> float:
             Initial HWM value based on configuration
         """
         broker = self.broker
+        if broker.initial_hwm_source == InitialHwmSource.SIGNAL_PRICE:
+            return signal_price if signal_price is not None else fill_price
         if broker.initial_hwm_source == InitialHwmSource.BAR_HIGH:
             return self.market.highs.get(asset, fill_price)
         elif broker.initial_hwm_source == InitialHwmSource.BAR_CLOSE:
@@ -456,7 +565,9 @@ def _get_initial_hwm(self, asset: str, fill_price: float) -> float:
         else:
             return fill_price
 
-    def _get_initial_lwm(self, asset: str, fill_price: float) -> float:
+    def _get_initial_lwm(
+        self, asset: str, fill_price: float, signal_price: float | None = None
+    ) -> float:
         """Get initial low water mark based on configuration.
 
         For VBT Pro compatibility with OHLC data, LWM should be initialized
@@ -471,6 +582,8 @@ def _get_initial_lwm(self, asset: str, fill_price: float) -> float:
             Initial LWM value based on configuration
         """
         broker = self.broker
+        if broker.initial_hwm_source == InitialHwmSource.SIGNAL_PRICE:
+            return signal_price if signal_price is not None else fill_price
         # When using BAR_HIGH for HWM, use BAR_LOW for LWM
         if broker.initial_hwm_source == InitialHwmSource.BAR_HIGH:
             return self.market.lows.get(asset, fill_price)
@@ -513,8 +626,9 @@ def _create_position(self, ctx: FillContext) -> None:
         broker = self.broker
         order = ctx.order
 
-        initial_hwm = self._get_initial_hwm(order.asset, ctx.fill_price)
-        initial_lwm = self._get_initial_lwm(order.asset, ctx.fill_price)
+        signal_price = getattr(order, "_signal_price", None)
+        initial_hwm = self._get_initial_hwm(order.asset, ctx.fill_price, signal_price)
+        initial_lwm = self._get_initial_lwm(order.asset, ctx.fill_price, signal_price)
         context = self._build_position_context(order)
 
         pos = Position(
@@ -658,8 +772,9 @@ def _flip_position(
         self.record_pnl(order.asset, pnl)
 
         # Create new position in opposite direction
-        initial_hwm = self._get_initial_hwm(order.asset, ctx.fill_price)
-        initial_lwm = self._get_initial_lwm(order.asset, ctx.fill_price)
+        signal_price = getattr(order, "_signal_price", None)
+        initial_hwm = self._get_initial_hwm(order.asset, ctx.fill_price, signal_price)
+        initial_lwm = self._get_initial_lwm(order.asset, ctx.fill_price, signal_price)
         context = self._build_position_context(order)
 
         self.account.positions[order.asset] = Position(
diff --git a/src/ml4t/backtest/execution/rebalancer.py b/src/ml4t/backtest/execution/rebalancer.py
index 813c129a..6903cc77 100644
--- a/src/ml4t/backtest/execution/rebalancer.py
+++ b/src/ml4t/backtest/execution/rebalancer.py
@@ -30,7 +30,13 @@
 
 from ml4t.specs.market_data import TimestampSemantics
 
-from ..config import DataFrequency, ExecutionPrice, RebalanceMode, ShareType
+from ..config import (
+    DataFrequency,
+    ExecutionPrice,
+    RebalanceMode,
+    ShareRounding,
+    ShareType,
+)
 from ..core.shared import SubmitOrderOptions
 from ..types import OrderSide
 from .schedule import RebalanceSchedule, _OnlineRebalanceEvaluator
@@ -105,6 +111,7 @@ class RebalanceConfig:
     cancel_before_rebalance: bool = True
     account_for_pending: bool = True
     rebalance_mode: RebalanceMode = RebalanceMode.SNAPSHOT
+    share_rounding: ShareRounding | str = ShareRounding.NEAREST
     schedule: RebalanceSchedule | None = None
     calendar: str | None = None
     timezone: str | None = None
@@ -113,6 +120,7 @@ class RebalanceConfig:
     timestamp_semantics: TimestampSemantics | str | None = None
 
     def __post_init__(self) -> None:
+        self.share_rounding = ShareRounding(self.share_rounding)
         if self.session_start_time is None:
             return
         from ..sessions import _validate_session_start_time
@@ -411,9 +419,7 @@ def _process_asset(
 
         # Compute shares (account for contract multiplier for futures)
         multiplier = broker.get_multiplier(asset)
-        shares = delta_value / (price * multiplier)
-
-        shares = self._quantize_shares(shares, broker)
+        shares = self._quantize_shares(delta_value / (price * multiplier), broker)
 
         if shares == 0:
             return None
@@ -449,6 +455,8 @@ def _quantize_shares(self, shares: float, broker: Broker) -> float:
             return int(rounded_lots)
         if use_fractional:
             return shares
+        if self.config.share_rounding is ShareRounding.TRUNCATE:
+            return int(shares)
         rounded = math.copysign(math.floor(abs(shares) + 0.5), shares)
         return int(rounded)
 
diff --git a/src/ml4t/backtest/profiles.py b/src/ml4t/backtest/profiles.py
index f5afeed2..29794e76 100644
--- a/src/ml4t/backtest/profiles.py
+++ b/src/ml4t/backtest/profiles.py
@@ -53,10 +53,7 @@
 BACKTRADER_PROFILE = {
     "account": {
         "allow_short_selling": True,
-        "allow_leverage": True,
-        "initial_margin": 0.5,
-        "long_maintenance_margin": 0.25,
-        "short_maintenance_margin": 0.30,
+        "allow_leverage": False,
         "short_cash_policy": "credit",
     },
     "execution": {
@@ -67,18 +64,20 @@
         "stop_fill_mode": "stop_price",
         "stop_level_basis": "signal_price",
         "trail_hwm_source": "close",
+        "initial_hwm_source": "signal_price",
         "trail_stop_timing": "lagged",
     },
     "position_sizing": {
         "share_type": "integer",
+        "share_rounding": "truncate",
     },
     "commission": {
-        "model": "percentage",
-        "rate": 0.001,
+        "model": "none",
+        "rate": 0.0,
     },
     "slippage": {
-        "model": "percentage",
-        "rate": 0.001,
+        "model": "none",
+        "rate": 0.0,
     },
     "cash": {
         "initial": 100000.0,
@@ -90,10 +89,10 @@
         "fill_ordering": "fifo",
         "entry_order_priority": "submission",
         "rebalance_mode": "snapshot",
-        "rebalance_headroom_pct": 0.998,
+        "rebalance_headroom_pct": 1.0,
         "missing_price_policy": "use_last",
-        "late_asset_policy": "require_history",
-        "late_asset_min_bars": 2,
+        "late_asset_policy": "allow",
+        "late_asset_min_bars": 1,
     },
 }
 
@@ -102,6 +101,7 @@
         "allow_short_selling": True,
         "allow_leverage": False,
         "short_cash_policy": "credit",
+        "lock_notional_update_mode": "position_legs",
     },
     "execution": {
         "execution_price": "close",
@@ -134,9 +134,10 @@
         "partial_fills_allowed": True,
         "fill_ordering": "exit_first",
         "entry_order_priority": "submission",
+        "immediate_fill": True,
         "rebalance_mode": "hybrid",
         "rebalance_headroom_pct": 1.0,
-        "missing_price_policy": "use_last",
+        "missing_price_policy": "skip",
         "late_asset_policy": "allow",
         "late_asset_min_bars": 1,
     },
@@ -144,7 +145,7 @@
 
 ZIPLINE_PROFILE = {
     "account": {
-        "allow_short_selling": False,
+        "allow_short_selling": True,
         "allow_leverage": False,
         "short_cash_policy": "credit",
     },
@@ -153,36 +154,37 @@
         "execution_mode": "next_bar",
     },
     "stops": {
-        "stop_fill_mode": "stop_price",
+        "stop_fill_mode": "next_bar_open",
         "stop_level_basis": "fill_price",
-        "trail_hwm_source": "close",
-        "trail_stop_timing": "lagged",
+        "trail_hwm_source": "bar_extreme",
+        "trail_stop_timing": "intrabar",
     },
     "position_sizing": {
         "share_type": "integer",
     },
     "commission": {
-        "model": "per_share",
+        "model": "none",
         "rate": 0.0,
-        "per_share": 0.005,
-        "minimum": 1.0,
+        "per_share": 0.0,
+        "minimum": 0.0,
     },
     "slippage": {
-        "model": "volume_based",
-        "rate": 0.1,
+        "model": "none",
+        "rate": 0.0,
     },
     "cash": {
         "initial": 100000.0,
         "buffer_pct": 0.0,
     },
     "orders": {
-        "reject_on_insufficient_cash": True,
-        "partial_fills_allowed": True,
-        "fill_ordering": "exit_first",
+        "reject_on_insufficient_cash": False,
+        "skip_cash_validation": True,
+        "partial_fills_allowed": False,
+        "fill_ordering": "fifo",
         "entry_order_priority": "submission",
-        "next_bar_queue_shadow_validation": True,
+        "next_bar_queue_shadow_validation": False,
         "rebalance_mode": "snapshot",
-        "rebalance_headroom_pct": 0.998,
+        "rebalance_headroom_pct": 1.0,
         "missing_price_policy": "use_last",
         "late_asset_policy": "allow",
         "late_asset_min_bars": 1,
@@ -287,24 +289,23 @@
 VECTORBT_STRICT_PROFILE["orders"]["fill_ordering"] = "fifo"
 VECTORBT_STRICT_PROFILE["orders"]["entry_order_priority"] = "submission"
 
+VECTORBT_OSS_STRICT_PROFILE = deepcopy(VECTORBT_STRICT_PROFILE)
+VECTORBT_OSS_STRICT_PROFILE["account"]["lock_notional_update_mode"] = "combined_order"
+
 BACKTRADER_STRICT_PROFILE = deepcopy(BACKTRADER_PROFILE)
 BACKTRADER_STRICT_PROFILE["orders"]["entry_order_priority"] = "submission"
 BACKTRADER_STRICT_PROFILE["orders"]["next_bar_submission_precheck"] = True
 BACKTRADER_STRICT_PROFILE["orders"]["next_bar_simple_cash_check"] = True
 
 ZIPLINE_STRICT_PROFILE = deepcopy(ZIPLINE_PROFILE)
-ZIPLINE_STRICT_PROFILE["account"]["allow_short_selling"] = True
-ZIPLINE_STRICT_PROFILE["account"]["short_cash_policy"] = "credit"
-ZIPLINE_STRICT_PROFILE["orders"]["skip_cash_validation"] = True
-ZIPLINE_STRICT_PROFILE["orders"]["entry_order_priority"] = "submission"
 
 LEAN_PROFILE = {
     "account": {
         "allow_short_selling": True,
         "allow_leverage": True,
         "initial_margin": 0.5,
-        "long_maintenance_margin": 0.25,
-        "short_maintenance_margin": 0.30,
+        "long_maintenance_margin": 0.5,
+        "short_maintenance_margin": 0.5,
         "short_cash_policy": "credit",
     },
     "execution": {
@@ -327,8 +328,8 @@
         "minimum": 1.0,
     },
     "slippage": {
-        "model": "percentage",
-        "rate": 0.001,
+        "model": "none",
+        "rate": 0.0,
     },
     "cash": {
         "initial": 100000.0,
@@ -337,11 +338,13 @@
     "orders": {
         "reject_on_insufficient_cash": True,
         "partial_fills_allowed": False,
-        "fill_ordering": "exit_first",
+        "fill_ordering": "sequential",
         "entry_order_priority": "submission",
+        "buying_power_reservation": False,
+        "next_bar_submission_precheck": True,
         "next_bar_queue_shadow_validation": True,
         "rebalance_mode": "snapshot",
-        "rebalance_headroom_pct": 1.0,
+        "rebalance_headroom_pct": 0.9975,
         "missing_price_policy": "use_last",
         "late_asset_policy": "allow",
         "late_asset_min_bars": 1,
@@ -402,6 +405,7 @@
     "realistic": REALISTIC_PROFILE,
     "ibkr_us_stocks_fixed": IBKR_US_STOCKS_FIXED_PROFILE,
     "vectorbt_strict": VECTORBT_STRICT_PROFILE,
+    "vectorbt_oss_strict": VECTORBT_OSS_STRICT_PROFILE,
     "backtrader_strict": BACKTRADER_STRICT_PROFILE,
     "zipline_strict": ZIPLINE_STRICT_PROFILE,
 }
@@ -412,6 +416,7 @@
     "quantconnect": "lean",
     "ibkr:us:stocks:fixed": "ibkr_us_stocks_fixed",
     "vectorbt_compare": "vectorbt_strict",
+    "vectorbt_oss_compare": "vectorbt_oss_strict",
     "backtrader_compare": "backtrader_strict",
     "zipline_compare": "zipline_strict",
     "lean_compare": "lean",
diff --git a/tests/accounting/test_margin_account_policy.py b/tests/accounting/test_margin_account_policy.py
index 3e0bca5e..e3eeb7cf 100644
--- a/tests/accounting/test_margin_account_policy.py
+++ b/tests/accounting/test_margin_account_policy.py
@@ -66,8 +66,8 @@ def test_invalid_maintenance_margin_too_high(self):
             )
 
     def test_invalid_maintenance_greater_than_initial(self):
-        """Test that long_maintenance_margin must be < initial_margin."""
-        with pytest.raises(ValueError, match="maintenance margin.*must be <"):
+        """Test that long_maintenance_margin must be <= initial_margin."""
+        with pytest.raises(ValueError, match="maintenance margin.*must be <="):
             UnifiedAccountPolicy(
                 allow_short_selling=True,
                 allow_leverage=True,
@@ -75,15 +75,17 @@ def test_invalid_maintenance_greater_than_initial(self):
                 long_maintenance_margin=0.5,
             )
 
-    def test_invalid_maintenance_equal_to_initial(self):
-        """Test that long_maintenance_margin cannot equal initial_margin."""
-        with pytest.raises(ValueError, match="maintenance margin.*must be <"):
-            UnifiedAccountPolicy(
-                allow_short_selling=True,
-                allow_leverage=True,
-                initial_margin=0.5,
-                long_maintenance_margin=0.5,
-            )
+    def test_maintenance_can_equal_initial(self):
+        """Support models that use the same initial and maintenance requirement."""
+        policy = UnifiedAccountPolicy(
+            allow_short_selling=True,
+            allow_leverage=True,
+            initial_margin=0.5,
+            long_maintenance_margin=0.5,
+            short_maintenance_margin=0.5,
+        )
+        assert policy.long_maintenance_margin == 0.5
+        assert policy.short_maintenance_margin == 0.5
 
 
 class TestMarginAccountPolicyBuyingPower:
diff --git a/tests/benchmark/test_case_study_lean.py b/tests/benchmark/test_case_study_lean.py
index 59ce6c96..8c1a77c6 100644
--- a/tests/benchmark/test_case_study_lean.py
+++ b/tests/benchmark/test_case_study_lean.py
@@ -8,11 +8,17 @@
 
 from __future__ import annotations
 
+import lzma
 from pathlib import Path
 
 import pytest
 
-from ml4t.backtest._validation.case_study_lean import compare, lean_side, run_ml4t_lean
+from ml4t.backtest._validation.case_study_lean import (
+    _read_csv_fixture,
+    compare,
+    lean_side,
+    run_ml4t_lean,
+)
 
 WORKSPACE = Path(__file__).resolve().parents[2] / "validation" / "lean" / "workspace"
 DATA_DAILY = WORKSPACE / "data" / "equity" / "usa" / "daily"
@@ -32,6 +38,36 @@ def _has_reference_artifacts(workspace_dir: Path) -> bool:
     )
 
 
+def test_retained_compressed_surface_precedes_ignored_runtime_file(tmp_path: Path) -> None:
+    (tmp_path / "surface.csv").write_text("value\n1\n", encoding="utf-8")
+    (tmp_path / "surface.csv.xz").write_bytes(lzma.compress(b"value\n2\n"))
+
+    assert _read_csv_fixture(tmp_path, "surface.csv")["value"].tolist() == [2]
+
+
+def test_lean_side_accepts_current_uppercase_order_status(tmp_path: Path) -> None:
+    (tmp_path / "ml4t_symbol_map.json").write_text('{"AAAA": "AAPL"}', encoding="utf-8")
+    (tmp_path / "ml4t_daily_equity.csv").write_text(
+        "timestamp,equity\n2024-01-03,10010\n",
+        encoding="utf-8",
+    )
+    (tmp_path / "ml4t_order_events.csv").write_text(
+        "timestamp,symbol,status,direction,fill_quantity,fill_price\n"
+        "2024-01-03,AAAA,FILLED,BUY,1,110\n",
+        encoding="utf-8",
+    )
+
+    result = lean_side(tmp_path)
+
+    assert result["n_trades"] == 1
+    row = result["fills"].iloc[0]
+    assert str(row["timestamp"].date()) == "2024-01-03"
+    assert row["asset"] == "AAPL"
+    assert row["side"] == "buy"
+    assert row["quantity"] == 1.0
+    assert row["price"] == 110.0
+
+
 # The generic equity-decomposition invariant (initial + closed_pnl + open_pnl ==
 # final_value) does not model 2x margin, but parity here is asserted directly
 # against LEAN's terminal value (external ground truth), which matches exactly.
@@ -52,6 +88,8 @@ def test_case_study_lean_parity(project: str) -> None:
         f"(lean={result['lean_fills']} ml4t={result['ml4t_fills']})"
     )
     assert result["fill_gap"] == 0
+    assert result["canonical_final_value_match"]
+    assert result["canonical_final_value_gap_usd"] == 0.0
     assert abs(result["final_value_gap_usd"]) < 1e-4, (
         f"{project}: terminal value gap ${result['final_value_gap_usd']:.6f}"
     )
diff --git a/tests/benchmark/test_cross_framework_selected.py b/tests/benchmark/test_cross_framework_selected.py
index 852b8b03..7809b42d 100644
--- a/tests/benchmark/test_cross_framework_selected.py
+++ b/tests/benchmark/test_cross_framework_selected.py
@@ -68,6 +68,7 @@ def _run_framework_pair(framework: str, runner_name: str, artifact_dir: Path):
         framework_result,
         ml4t_result,
         initial_cash=config.initial_cash,
+        timestamp_domain="session_date",
     )
     artifact_path = artifact_dir / f"{framework}-exact-comparison.json"
     suite.write_exact_comparison_artifact(artifact, artifact_path)
diff --git a/tests/compatibility/snapshots/v0.1.json b/tests/compatibility/snapshots/v0.1.json
index 43fe1f56..59ef3404 100644
--- a/tests/compatibility/snapshots/v0.1.json
+++ b/tests/compatibility/snapshots/v0.1.json
@@ -71,6 +71,15 @@
         "keyword_only": false,
         "name": "short_cash_policy"
       },
+      {
+        "annotation": "LockNotionalUpdateMode",
+        "default": {
+          "enum": "ml4t.backtest.config.LockNotionalUpdateMode.POSITION_LEGS",
+          "value": "position_legs"
+        },
+        "keyword_only": false,
+        "name": "lock_notional_update_mode"
+      },
       {
         "annotation": "ExecutionPrice",
         "default": {
@@ -158,6 +167,15 @@
         "keyword_only": false,
         "name": "share_type"
       },
+      {
+        "annotation": "ShareRounding",
+        "default": {
+          "enum": "ml4t.backtest.config.ShareRounding.NEAREST",
+          "value": "nearest"
+        },
+        "keyword_only": false,
+        "name": "share_rounding"
+      },
       {
         "annotation": "CommissionType",
         "default": {
@@ -458,6 +476,7 @@
         "allow_short_selling": false,
         "fixed_margin_schedule": null,
         "initial_margin": 0.5,
+        "lock_notional_update_mode": "position_legs",
         "long_maintenance_margin": 0.25,
         "margin_pct_schedule": null,
         "short_cash_policy": "credit",
@@ -525,6 +544,7 @@
         "skip_cash_validation": false
       },
       "position_sizing": {
+        "share_rounding": "nearest",
         "share_type": "integer"
       },
       "result": {
@@ -754,6 +774,10 @@
         "name": "FILL_PRICE",
         "value": "fill_price"
       },
+      {
+        "name": "SIGNAL_PRICE",
+        "value": "signal_price"
+      },
       {
         "name": "BAR_CLOSE",
         "value": "bar_close"
@@ -773,6 +797,16 @@
         "value": "require_history"
       }
     ],
+    "ml4t.backtest.config.LockNotionalUpdateMode": [
+      {
+        "name": "POSITION_LEGS",
+        "value": "position_legs"
+      },
+      {
+        "name": "COMBINED_ORDER",
+        "value": "combined_order"
+      }
+    ],
     "ml4t.backtest.config.MissingPricePolicy": [
       {
         "name": "SKIP",
@@ -797,6 +831,16 @@
         "value": "hybrid"
       }
     ],
+    "ml4t.backtest.config.ShareRounding": [
+      {
+        "name": "NEAREST",
+        "value": "nearest"
+      },
+      {
+        "name": "TRUNCATE",
+        "value": "truncate"
+      }
+    ],
     "ml4t.backtest.config.ShareType": [
       {
         "name": "FRACTIONAL",
@@ -1194,26 +1238,24 @@
       "quantconnect": "lean",
       "vectorbt_compare": "vectorbt_strict",
       "vectorbt_oss": "vectorbt",
+      "vectorbt_oss_compare": "vectorbt_oss_strict",
       "vectorbt_pro": "vectorbt",
       "zipline_compare": "zipline_strict"
     },
     "canonical": {
       "backtrader": {
         "account": {
-          "allow_leverage": true,
+          "allow_leverage": false,
           "allow_short_selling": true,
-          "initial_margin": 0.5,
-          "long_maintenance_margin": 0.25,
-          "short_cash_policy": "credit",
-          "short_maintenance_margin": 0.3
+          "short_cash_policy": "credit"
         },
         "cash": {
           "buffer_pct": 0.0,
           "initial": 100000.0
         },
         "commission": {
-          "model": "percentage",
-          "rate": 0.001
+          "model": "none",
+          "rate": 0.0
         },
         "execution": {
           "execution_mode": "next_bar",
@@ -1222,22 +1264,24 @@
         "orders": {
           "entry_order_priority": "submission",
           "fill_ordering": "fifo",
-          "late_asset_min_bars": 2,
-          "late_asset_policy": "require_history",
+          "late_asset_min_bars": 1,
+          "late_asset_policy": "allow",
           "missing_price_policy": "use_last",
           "partial_fills_allowed": false,
-          "rebalance_headroom_pct": 0.998,
+          "rebalance_headroom_pct": 1.0,
           "rebalance_mode": "snapshot",
           "reject_on_insufficient_cash": true
         },
         "position_sizing": {
+          "share_rounding": "truncate",
           "share_type": "integer"
         },
         "slippage": {
-          "model": "percentage",
-          "rate": 0.001
+          "model": "none",
+          "rate": 0.0
         },
         "stops": {
+          "initial_hwm_source": "signal_price",
           "stop_fill_mode": "stop_price",
           "stop_level_basis": "signal_price",
           "trail_hwm_source": "close",
@@ -1246,20 +1290,17 @@
       },
       "backtrader_strict": {
         "account": {
-          "allow_leverage": true,
+          "allow_leverage": false,
           "allow_short_selling": true,
-          "initial_margin": 0.5,
-          "long_maintenance_margin": 0.25,
-          "short_cash_policy": "credit",
-          "short_maintenance_margin": 0.3
+          "short_cash_policy": "credit"
         },
         "cash": {
           "buffer_pct": 0.0,
           "initial": 100000.0
         },
         "commission": {
-          "model": "percentage",
-          "rate": 0.001
+          "model": "none",
+          "rate": 0.0
         },
         "execution": {
           "execution_mode": "next_bar",
@@ -1268,24 +1309,26 @@
         "orders": {
           "entry_order_priority": "submission",
           "fill_ordering": "fifo",
-          "late_asset_min_bars": 2,
-          "late_asset_policy": "require_history",
+          "late_asset_min_bars": 1,
+          "late_asset_policy": "allow",
           "missing_price_policy": "use_last",
           "next_bar_simple_cash_check": true,
           "next_bar_submission_precheck": true,
           "partial_fills_allowed": false,
-          "rebalance_headroom_pct": 0.998,
+          "rebalance_headroom_pct": 1.0,
           "rebalance_mode": "snapshot",
           "reject_on_insufficient_cash": true
         },
         "position_sizing": {
+          "share_rounding": "truncate",
           "share_type": "integer"
         },
         "slippage": {
-          "model": "percentage",
-          "rate": 0.001
+          "model": "none",
+          "rate": 0.0
         },
         "stops": {
+          "initial_hwm_source": "signal_price",
           "stop_fill_mode": "stop_price",
           "stop_level_basis": "signal_price",
           "trail_hwm_source": "close",
@@ -1430,9 +1473,9 @@
           "allow_leverage": true,
           "allow_short_selling": true,
           "initial_margin": 0.5,
-          "long_maintenance_margin": 0.25,
+          "long_maintenance_margin": 0.5,
           "short_cash_policy": "credit",
-          "short_maintenance_margin": 0.3
+          "short_maintenance_margin": 0.5
         },
         "cash": {
           "buffer_pct": 0.0,
@@ -1449,14 +1492,16 @@
           "execution_price": "open"
         },
         "orders": {
+          "buying_power_reservation": false,
           "entry_order_priority": "submission",
-          "fill_ordering": "exit_first",
+          "fill_ordering": "sequential",
           "late_asset_min_bars": 1,
           "late_asset_policy": "allow",
           "missing_price_policy": "use_last",
           "next_bar_queue_shadow_validation": true,
+          "next_bar_submission_precheck": true,
           "partial_fills_allowed": false,
-          "rebalance_headroom_pct": 1.0,
+          "rebalance_headroom_pct": 0.9975,
           "rebalance_mode": "snapshot",
           "reject_on_insufficient_cash": true
         },
@@ -1464,8 +1509,8 @@
           "share_type": "integer"
         },
         "slippage": {
-          "model": "percentage",
-          "rate": 0.001
+          "model": "none",
+          "rate": 0.0
         },
         "stops": {
           "stop_fill_mode": "stop_price",
@@ -1522,6 +1567,7 @@
         "account": {
           "allow_leverage": false,
           "allow_short_selling": true,
+          "lock_notional_update_mode": "position_legs",
           "short_cash_policy": "credit"
         },
         "cash": {
@@ -1539,9 +1585,10 @@
         "orders": {
           "entry_order_priority": "submission",
           "fill_ordering": "exit_first",
+          "immediate_fill": true,
           "late_asset_min_bars": 1,
           "late_asset_policy": "allow",
-          "missing_price_policy": "use_last",
+          "missing_price_policy": "skip",
           "partial_fills_allowed": true,
           "rebalance_headroom_pct": 1.0,
           "rebalance_mode": "hybrid",
@@ -1562,10 +1609,57 @@
           "trail_stop_timing": "intrabar"
         }
       },
+      "vectorbt_oss_strict": {
+        "account": {
+          "allow_leverage": false,
+          "allow_short_selling": true,
+          "lock_notional_update_mode": "combined_order",
+          "short_cash_policy": "lock_notional"
+        },
+        "cash": {
+          "buffer_pct": 0.0,
+          "initial": 100000.0
+        },
+        "commission": {
+          "model": "none",
+          "rate": 0.0
+        },
+        "execution": {
+          "execution_mode": "same_bar",
+          "execution_price": "close"
+        },
+        "orders": {
+          "entry_order_priority": "submission",
+          "fill_ordering": "fifo",
+          "immediate_fill": true,
+          "late_asset_min_bars": 1,
+          "late_asset_policy": "allow",
+          "missing_price_policy": "skip",
+          "partial_fills_allowed": true,
+          "rebalance_headroom_pct": 1.0,
+          "rebalance_mode": "hybrid",
+          "reject_on_insufficient_cash": true
+        },
+        "position_sizing": {
+          "share_type": "fractional"
+        },
+        "slippage": {
+          "model": "none",
+          "rate": 0.0
+        },
+        "stops": {
+          "initial_hwm_source": "bar_high",
+          "stop_fill_mode": "stop_price",
+          "stop_level_basis": "fill_price",
+          "trail_hwm_source": "bar_extreme",
+          "trail_stop_timing": "intrabar"
+        }
+      },
       "vectorbt_strict": {
         "account": {
           "allow_leverage": false,
           "allow_short_selling": true,
+          "lock_notional_update_mode": "position_legs",
           "short_cash_policy": "lock_notional"
         },
         "cash": {
@@ -1583,9 +1677,10 @@
         "orders": {
           "entry_order_priority": "submission",
           "fill_ordering": "fifo",
+          "immediate_fill": true,
           "late_asset_min_bars": 1,
           "late_asset_policy": "allow",
-          "missing_price_policy": "use_last",
+          "missing_price_policy": "skip",
           "partial_fills_allowed": true,
           "rebalance_headroom_pct": 1.0,
           "rebalance_mode": "hybrid",
@@ -1609,7 +1704,7 @@
       "zipline": {
         "account": {
           "allow_leverage": false,
-          "allow_short_selling": false,
+          "allow_short_selling": true,
           "short_cash_policy": "credit"
         },
         "cash": {
@@ -1617,9 +1712,9 @@
           "initial": 100000.0
         },
         "commission": {
-          "minimum": 1.0,
-          "model": "per_share",
-          "per_share": 0.005,
+          "minimum": 0.0,
+          "model": "none",
+          "per_share": 0.0,
           "rate": 0.0
         },
         "execution": {
@@ -1628,28 +1723,29 @@
         },
         "orders": {
           "entry_order_priority": "submission",
-          "fill_ordering": "exit_first",
+          "fill_ordering": "fifo",
           "late_asset_min_bars": 1,
           "late_asset_policy": "allow",
           "missing_price_policy": "use_last",
-          "next_bar_queue_shadow_validation": true,
-          "partial_fills_allowed": true,
-          "rebalance_headroom_pct": 0.998,
+          "next_bar_queue_shadow_validation": false,
+          "partial_fills_allowed": false,
+          "rebalance_headroom_pct": 1.0,
           "rebalance_mode": "snapshot",
-          "reject_on_insufficient_cash": true
+          "reject_on_insufficient_cash": false,
+          "skip_cash_validation": true
         },
         "position_sizing": {
           "share_type": "integer"
         },
         "slippage": {
-          "model": "volume_based",
-          "rate": 0.1
+          "model": "none",
+          "rate": 0.0
         },
         "stops": {
-          "stop_fill_mode": "stop_price",
+          "stop_fill_mode": "next_bar_open",
           "stop_level_basis": "fill_price",
-          "trail_hwm_source": "close",
-          "trail_stop_timing": "lagged"
+          "trail_hwm_source": "bar_extreme",
+          "trail_stop_timing": "intrabar"
         }
       },
       "zipline_strict": {
@@ -1663,9 +1759,9 @@
           "initial": 100000.0
         },
         "commission": {
-          "minimum": 1.0,
-          "model": "per_share",
-          "per_share": 0.005,
+          "minimum": 0.0,
+          "model": "none",
+          "per_share": 0.0,
           "rate": 0.0
         },
         "execution": {
@@ -1674,29 +1770,29 @@
         },
         "orders": {
           "entry_order_priority": "submission",
-          "fill_ordering": "exit_first",
+          "fill_ordering": "fifo",
           "late_asset_min_bars": 1,
           "late_asset_policy": "allow",
           "missing_price_policy": "use_last",
-          "next_bar_queue_shadow_validation": true,
-          "partial_fills_allowed": true,
-          "rebalance_headroom_pct": 0.998,
+          "next_bar_queue_shadow_validation": false,
+          "partial_fills_allowed": false,
+          "rebalance_headroom_pct": 1.0,
           "rebalance_mode": "snapshot",
-          "reject_on_insufficient_cash": true,
+          "reject_on_insufficient_cash": false,
           "skip_cash_validation": true
         },
         "position_sizing": {
           "share_type": "integer"
         },
         "slippage": {
-          "model": "volume_based",
-          "rate": 0.1
+          "model": "none",
+          "rate": 0.0
         },
         "stops": {
-          "stop_fill_mode": "stop_price",
+          "stop_fill_mode": "next_bar_open",
           "stop_level_basis": "fill_price",
-          "trail_hwm_source": "close",
-          "trail_stop_timing": "lagged"
+          "trail_hwm_source": "bar_extreme",
+          "trail_stop_timing": "intrabar"
         }
       }
     }
@@ -2497,7 +2593,7 @@
       },
       "module": "ml4t.backtest.execution.rebalancer",
       "qualname": "RebalanceConfig",
-      "signature": "(min_trade_value: 'float' = 0.0, min_weight_change: 'float' = 0.0, allow_fractional: 'bool | None' = None, round_lots: 'bool' = False, lot_size: 'int' = 100, allow_short: 'bool' = False, max_single_weight: 'float' = 1.0, max_gross_leverage: 'float | None' = None, cancel_before_rebalance: 'bool' = True, account_for_pending: 'bool' = True, rebalance_mode: 'RebalanceMode' = <RebalanceMode.SNAPSHOT: 'snapshot'>, schedule: 'RebalanceSchedule | None' = None, calendar: 'str | None' = None, timezone: 'str | None' = None, session_start_time: 'str | None' = None, data_frequency: 'DataFrequency | str | None' = None, timestamp_semantics: 'TimestampSemantics | str | None' = None) -> None"
+      "signature": "(min_trade_value: 'float' = 0.0, min_weight_change: 'float' = 0.0, allow_fractional: 'bool | None' = None, round_lots: 'bool' = False, lot_size: 'int' = 100, allow_short: 'bool' = False, max_single_weight: 'float' = 1.0, max_gross_leverage: 'float | None' = None, cancel_before_rebalance: 'bool' = True, account_for_pending: 'bool' = True, rebalance_mode: 'RebalanceMode' = <RebalanceMode.SNAPSHOT: 'snapshot'>, share_rounding: 'ShareRounding | str' = <ShareRounding.NEAREST: 'nearest'>, schedule: 'RebalanceSchedule | None' = None, calendar: 'str | None' = None, timezone: 'str | None' = None, session_start_time: 'str | None' = None, data_frequency: 'DataFrequency | str | None' = None, timestamp_semantics: 'TimestampSemantics | str | None' = None) -> None"
     },
     "ml4t.backtest.execution.rebalancer:TargetWeightExecutor": {
       "kind": "class",
@@ -2569,7 +2665,7 @@
       },
       "module": "ml4t.backtest.execution.rebalancer",
       "qualname": "RebalanceConfig",
-      "signature": "(min_trade_value: 'float' = 0.0, min_weight_change: 'float' = 0.0, allow_fractional: 'bool | None' = None, round_lots: 'bool' = False, lot_size: 'int' = 100, allow_short: 'bool' = False, max_single_weight: 'float' = 1.0, max_gross_leverage: 'float | None' = None, cancel_before_rebalance: 'bool' = True, account_for_pending: 'bool' = True, rebalance_mode: 'RebalanceMode' = <RebalanceMode.SNAPSHOT: 'snapshot'>, schedule: 'RebalanceSchedule | None' = None, calendar: 'str | None' = None, timezone: 'str | None' = None, session_start_time: 'str | None' = None, data_frequency: 'DataFrequency | str | None' = None, timestamp_semantics: 'TimestampSemantics | str | None' = None) -> None"
+      "signature": "(min_trade_value: 'float' = 0.0, min_weight_change: 'float' = 0.0, allow_fractional: 'bool | None' = None, round_lots: 'bool' = False, lot_size: 'int' = 100, allow_short: 'bool' = False, max_single_weight: 'float' = 1.0, max_gross_leverage: 'float | None' = None, cancel_before_rebalance: 'bool' = True, account_for_pending: 'bool' = True, rebalance_mode: 'RebalanceMode' = <RebalanceMode.SNAPSHOT: 'snapshot'>, share_rounding: 'ShareRounding | str' = <ShareRounding.NEAREST: 'nearest'>, schedule: 'RebalanceSchedule | None' = None, calendar: 'str | None' = None, timezone: 'str | None' = None, session_start_time: 'str | None' = None, data_frequency: 'DataFrequency | str | None' = None, timestamp_semantics: 'TimestampSemantics | str | None' = None) -> None"
     },
     "ml4t.backtest.execution:SquareRootImpact": {
       "kind": "class",
@@ -3618,7 +3714,7 @@
       },
       "module": "ml4t.backtest.broker",
       "qualname": "Broker",
-      "signature": "(initial_cash: 'float' = 100000.0, commission_model: 'CommissionModel | None' = None, slippage_model: 'SlippageModel | None' = None, stop_slippage_rate: 'float' = 0.0, execution_mode: 'ExecutionMode' = <ExecutionMode.SAME_BAR: 'same_bar'>, execution_price: 'ExecutionPrice' = <ExecutionPrice.CLOSE: 'close'>, mark_price: 'ExecutionPrice' = <ExecutionPrice.PRICE: 'price'>, stop_fill_mode: 'StopFillMode' = <StopFillMode.STOP_PRICE: 'stop_price'>, stop_level_basis: 'StopLevelBasis' = <StopLevelBasis.FILL_PRICE: 'fill_price'>, trail_hwm_source: 'WaterMarkSource' = <WaterMarkSource.CLOSE: 'close'>, trail_include_entry_bar_extremes: 'bool' = False, initial_hwm_source: 'InitialHwmSource' = <InitialHwmSource.FILL_PRICE: 'fill_price'>, trail_stop_timing: 'TrailStopTiming' = <TrailStopTiming.LAGGED: 'lagged'>, allow_short_selling: 'bool' = False, allow_leverage: 'bool' = False, initial_margin: 'float' = 0.5, long_maintenance_margin: 'float' = 0.25, short_maintenance_margin: 'float' = 0.3, fixed_margin_schedule: 'dict[str, tuple[float, float]] | None' = None, margin_pct_schedule: 'dict[str, tuple[float, float]] | None' = None, short_cash_policy: 'ShortCashPolicy' = <ShortCashPolicy.CREDIT: 'credit'>, execution_limits: 'ExecutionLimits | None' = None, market_impact_model: 'MarketImpactModel | None' = None, contract_specs: 'dict[str, ContractSpec] | None' = None, share_type: 'ShareType' = <ShareType.INTEGER: 'integer'>, fill_ordering: 'FillOrdering' = <FillOrdering.EXIT_FIRST: 'exit_first'>, entry_order_priority: 'EntryOrderPriority' = <EntryOrderPriority.SUBMISSION: 'submission'>, next_bar_submission_precheck: 'bool' = False, next_bar_simple_cash_check: 'bool' = False, buying_power_reservation: 'bool' = False, next_bar_queue_shadow_validation: 'bool' = False, immediate_fill: 'bool' = False, reject_on_insufficient_cash: 'bool' = True, skip_cash_validation: 'bool' = False, cash_buffer_pct: 'float' = 0.0, partial_fills_allowed: 'bool' = False, rebalance_headroom_pct: 'float' = 1.0, missing_price_policy: 'MissingPricePolicy' = <MissingPricePolicy.SKIP: 'skip'>, late_asset_policy: 'LateAssetPolicy' = <LateAssetPolicy.ALLOW: 'allow'>, late_asset_min_bars: 'int' = 1, settlement_delay: 'int' = 0, settlement_reduces_buying_power: 'bool' = True)"
+      "signature": "(initial_cash: 'float' = 100000.0, commission_model: 'CommissionModel | None' = None, slippage_model: 'SlippageModel | None' = None, stop_slippage_rate: 'float' = 0.0, execution_mode: 'ExecutionMode' = <ExecutionMode.SAME_BAR: 'same_bar'>, execution_price: 'ExecutionPrice' = <ExecutionPrice.CLOSE: 'close'>, mark_price: 'ExecutionPrice' = <ExecutionPrice.PRICE: 'price'>, stop_fill_mode: 'StopFillMode' = <StopFillMode.STOP_PRICE: 'stop_price'>, stop_level_basis: 'StopLevelBasis' = <StopLevelBasis.FILL_PRICE: 'fill_price'>, trail_hwm_source: 'WaterMarkSource' = <WaterMarkSource.CLOSE: 'close'>, trail_include_entry_bar_extremes: 'bool' = False, initial_hwm_source: 'InitialHwmSource' = <InitialHwmSource.FILL_PRICE: 'fill_price'>, trail_stop_timing: 'TrailStopTiming' = <TrailStopTiming.LAGGED: 'lagged'>, allow_short_selling: 'bool' = False, allow_leverage: 'bool' = False, initial_margin: 'float' = 0.5, long_maintenance_margin: 'float' = 0.25, short_maintenance_margin: 'float' = 0.3, fixed_margin_schedule: 'dict[str, tuple[float, float]] | None' = None, margin_pct_schedule: 'dict[str, tuple[float, float]] | None' = None, short_cash_policy: 'ShortCashPolicy' = <ShortCashPolicy.CREDIT: 'credit'>, lock_notional_update_mode: 'LockNotionalUpdateMode' = <LockNotionalUpdateMode.POSITION_LEGS: 'position_legs'>, execution_limits: 'ExecutionLimits | None' = None, market_impact_model: 'MarketImpactModel | None' = None, contract_specs: 'dict[str, ContractSpec] | None' = None, share_type: 'ShareType' = <ShareType.INTEGER: 'integer'>, fill_ordering: 'FillOrdering' = <FillOrdering.EXIT_FIRST: 'exit_first'>, entry_order_priority: 'EntryOrderPriority' = <EntryOrderPriority.SUBMISSION: 'submission'>, next_bar_submission_precheck: 'bool' = False, next_bar_simple_cash_check: 'bool' = False, buying_power_reservation: 'bool' = False, next_bar_queue_shadow_validation: 'bool' = False, immediate_fill: 'bool' = False, reject_on_insufficient_cash: 'bool' = True, skip_cash_validation: 'bool' = False, cash_buffer_pct: 'float' = 0.0, partial_fills_allowed: 'bool' = False, rebalance_headroom_pct: 'float' = 1.0, missing_price_policy: 'MissingPricePolicy' = <MissingPricePolicy.SKIP: 'skip'>, late_asset_policy: 'LateAssetPolicy' = <LateAssetPolicy.ALLOW: 'allow'>, late_asset_min_bars: 'int' = 1, settlement_delay: 'int' = 0, settlement_reduces_buying_power: 'bool' = True)"
     },
     "ml4t.backtest:CommissionType": {
       "kind": "class",
@@ -3900,7 +3996,7 @@
       },
       "module": "ml4t.backtest.execution.rebalancer",
       "qualname": "RebalanceConfig",
-      "signature": "(min_trade_value: 'float' = 0.0, min_weight_change: 'float' = 0.0, allow_fractional: 'bool | None' = None, round_lots: 'bool' = False, lot_size: 'int' = 100, allow_short: 'bool' = False, max_single_weight: 'float' = 1.0, max_gross_leverage: 'float | None' = None, cancel_before_rebalance: 'bool' = True, account_for_pending: 'bool' = True, rebalance_mode: 'RebalanceMode' = <RebalanceMode.SNAPSHOT: 'snapshot'>, schedule: 'RebalanceSchedule | None' = None, calendar: 'str | None' = None, timezone: 'str | None' = None, session_start_time: 'str | None' = None, data_frequency: 'DataFrequency | str | None' = None, timestamp_semantics: 'TimestampSemantics | str | None' = None) -> None"
+      "signature": "(min_trade_value: 'float' = 0.0, min_weight_change: 'float' = 0.0, allow_fractional: 'bool | None' = None, round_lots: 'bool' = False, lot_size: 'int' = 100, allow_short: 'bool' = False, max_single_weight: 'float' = 1.0, max_gross_leverage: 'float | None' = None, cancel_before_rebalance: 'bool' = True, account_for_pending: 'bool' = True, rebalance_mode: 'RebalanceMode' = <RebalanceMode.SNAPSHOT: 'snapshot'>, share_rounding: 'ShareRounding | str' = <ShareRounding.NEAREST: 'nearest'>, schedule: 'RebalanceSchedule | None' = None, calendar: 'str | None' = None, timezone: 'str | None' = None, session_start_time: 'str | None' = None, data_frequency: 'DataFrequency | str | None' = None, timestamp_semantics: 'TimestampSemantics | str | None' = None) -> None"
     },
     "ml4t.backtest:RebalanceSchedule": {
       "kind": "class",
diff --git a/tests/contracts/test_backtrader_native_evidence.py b/tests/contracts/test_backtrader_native_evidence.py
new file mode 100644
index 00000000..28c236a4
--- /dev/null
+++ b/tests/contracts/test_backtrader_native_evidence.py
@@ -0,0 +1,53 @@
+"""Contracts for retained framework-native Backtrader evidence."""
+
+from __future__ import annotations
+
+import hashlib
+import json
+from pathlib import Path
+
+_ROOT = Path(__file__).parents[2]
+_ORACLE = _ROOT / "validation/native/backtrader_behavior.py"
+_EVIDENCE = _ROOT / "validation/native/evidence/backtrader-1.9.78.123.json"
+
+EXPECTED_CHECKS = {
+    "cash_rejection_and_configured_leverage",
+    "cheat_on_close",
+    "commission_headroom",
+    "defaults",
+    "final_bar_market_order",
+    "gap_reversal_executes_close_leg_despite_margin",
+    "integer_target_percent",
+    "late_feed_start",
+    "losing_short_cover_submission_rejection",
+    "missing_bar_uses_last_value",
+    "next_bar_open_and_gap",
+    "short_cash",
+    "signal_price_stop_basis",
+    "submission_sequence",
+    "trade_record",
+    "trailing_stop_signal_close_and_lagged",
+}
+
+
+def test_retained_backtrader_native_evidence_is_complete_and_current() -> None:
+    payload = json.loads(_EVIDENCE.read_text(encoding="utf-8"))
+
+    assert payload["schema_version"] == 1
+    assert payload["framework"] == "backtrader"
+    assert payload["package"] == "backtrader"
+    assert payload["version"] == "1.9.78.123"
+    assert payload["artifact"] == "backtrader-1.9.78.123-py2.py3-none-any.whl"
+    assert payload["artifact_sha256"] == (
+        "9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd"
+    )
+    assert payload["oracle_sha256"] == hashlib.sha256(_ORACLE.read_bytes()).hexdigest()
+    assert payload["passed"] is True
+    assert {check["id"] for check in payload["checks"]} == EXPECTED_CHECKS
+    assert all(check["passed"] for check in payload["checks"])
+    assert all(check["actual"] == check["expected"] for check in payload["checks"])
+    for location in payload["source_locations"].values():
+        assert location["artifact"] == payload["artifact"]
+        assert location["artifact_sha256"] == payload["artifact_sha256"]
+        assert location["path"].startswith("backtrader/")
+        assert location["source"].endswith("/backtrader/1.9.78.123/")
diff --git a/tests/contracts/test_behavior_coverage.py b/tests/contracts/test_behavior_coverage.py
new file mode 100644
index 00000000..6bfba3c1
--- /dev/null
+++ b/tests/contracts/test_behavior_coverage.py
@@ -0,0 +1,87 @@
+"""Contracts for the profile behavior coverage map."""
+
+from __future__ import annotations
+
+import json
+import sys
+import tomllib
+from pathlib import Path
+
+_ROOT = Path(__file__).parents[2]
+_VALIDATION = _ROOT / "validation"
+if str(_VALIDATION) not in sys.path:
+    sys.path.insert(0, str(_VALIDATION))
+
+from scenarios.definitions import SCENARIOS  # noqa: E402
+
+from ml4t.backtest.profiles import get_profile_config  # noqa: E402
+
+_COVERAGE = _VALIDATION / "behavior_coverage.toml"
+_NATIVE_EVIDENCE = {
+    "vectorbt": (
+        _VALIDATION / "native/evidence/vectorbt_oss-1.1.0.json",
+        _VALIDATION / "native/evidence/vectorbt_pro-2026.6.27.json",
+    ),
+    "backtrader": (_VALIDATION / "native/evidence/backtrader-1.9.78.123.json",),
+    "zipline": (_VALIDATION / "native/evidence/zipline-3.1.1.json",),
+    "lean": (_VALIDATION / "native/evidence/lean-18001.json",),
+}
+_SCENARIO_FRAMEWORKS = {
+    "vectorbt": {"vectorbt_oss", "vectorbt_pro"},
+    "backtrader": {"backtrader"},
+    "zipline": {"zipline"},
+}
+
+
+def _native_checks(path: Path) -> set[str]:
+    payload = json.loads(path.read_text(encoding="utf-8"))
+    assert payload["passed"] is True
+    checks = payload["checks"]
+    if isinstance(checks, list):
+        return {check["id"] for check in checks}
+    return set(checks)
+
+
+def test_coverage_map_accounts_for_every_framework_profile_field() -> None:
+    payload = tomllib.loads(_COVERAGE.read_text(encoding="utf-8"))
+    assert payload["schema_version"] == 1
+    assert set(payload["framework"]) == set(_NATIVE_EVIDENCE)
+
+    for framework, entries in payload["framework"].items():
+        expected_fields = {
+            f"{section}.{field}"
+            for section, values in get_profile_config(framework).items()
+            for field in values
+        }
+        covered_fields = [field for entry in entries for field in entry["fields"]]
+        assert len(covered_fields) == len(set(covered_fields))
+        assert set(covered_fields) == expected_fields
+
+
+def test_published_dimensions_have_native_and_cross_engine_evidence() -> None:
+    payload = tomllib.loads(_COVERAGE.read_text(encoding="utf-8"))
+    lean_cases = {
+        case["case"]
+        for case in json.loads(
+            (_VALIDATION / "lean/case_study_evidence.json").read_text(encoding="utf-8")
+        )["cases"]
+    }
+
+    for framework, entries in payload["framework"].items():
+        evidence_sets = [_native_checks(path) for path in _NATIVE_EVIDENCE[framework]]
+        for entry in entries:
+            assert entry["name"]
+            assert all(set(entry["native_checks"]) <= checks for checks in evidence_sets)
+            if entry["published"]:
+                assert entry["native_checks"]
+                assert entry["scenarios"]
+            else:
+                assert entry["reason"]
+            for scenario_id in entry["scenarios"]:
+                if scenario_id.startswith("lean-case:"):
+                    assert scenario_id.removeprefix("lean-case:") in lean_cases
+                    continue
+                assert scenario_id in SCENARIOS
+                assert _SCENARIO_FRAMEWORKS[framework] <= set(
+                    SCENARIOS[scenario_id].supported_frameworks
+                )
diff --git a/tests/contracts/test_correctness_evidence.py b/tests/contracts/test_correctness_evidence.py
new file mode 100644
index 00000000..4b100656
--- /dev/null
+++ b/tests/contracts/test_correctness_evidence.py
@@ -0,0 +1,261 @@
+"""Contracts for complete, current, atomically accepted correctness evidence."""
+
+from __future__ import annotations
+
+import copy
+import json
+import subprocess
+import sys
+from pathlib import Path
+from typing import Any, cast
+
+import pandas as pd
+import pytest
+
+_VALIDATION_DIR = Path(__file__).parents[2] / "validation"
+if str(_VALIDATION_DIR) not in sys.path:
+    sys.path.insert(0, str(_VALIDATION_DIR))
+
+from common.capabilities import FRAMEWORK_CAPABILITIES, ML4T_CAPABILITIES  # noqa: E402
+from common.comparator import compare_results  # noqa: E402
+from common.correctness_evidence import (  # noqa: E402
+    build_report,
+    correctness_report_failures,
+    promote_candidate,
+)
+from common.framework_registry import load_framework_manifest  # noqa: E402
+from common.provenance import (  # noqa: E402
+    _tree_digest,
+    generate_inputs,
+    input_digest,
+    static_digests,
+)
+from common.types import FrameworkResult, ValidationRecord, ValidationStatus  # noqa: E402
+from scenarios.definitions import SCENARIOS  # noqa: E402
+
+
+def _complete_record(framework: str, scenario_id: str) -> ValidationRecord:
+    manifest = load_framework_manifest()
+    target = manifest.targets[framework]
+    scenario = SCENARIOS[scenario_id]
+    prices, entries, exits = generate_inputs(scenario, framework)
+    extra = {"total_commission": 0.0, "exit_price": 0.0}
+    expected = FrameworkResult(
+        target.display_name,
+        100_000.0,
+        0.0,
+        0,
+        capabilities=FRAMEWORK_CAPABILITIES[framework],
+        extra=extra,
+    )
+    actual = FrameworkResult(
+        "ml4t.backtest",
+        100_000.0,
+        0.0,
+        0,
+        capabilities=ML4T_CAPABILITIES,
+        extra=extra,
+    )
+    comparison = compare_results(scenario, expected, actual)
+    provenance = {
+        "framework_target": {
+            "version": target.version,
+            "actual_version": target.version,
+            "immutable_id": target.immutable_id,
+        },
+        "ml4t": {"commit": "a" * 40, "dirty": False},
+        "python": {"version": "3.12.11", "implementation": "cpython"},
+        "adapter": {
+            "module": f"frameworks.{framework}",
+            "path": f"validation/frameworks/{framework}.py",
+        },
+        "digests": static_digests(scenario, framework),
+        "input_digest": input_digest(prices, entries, exits),
+        "capabilities": {
+            "framework": FRAMEWORK_CAPABILITIES[framework],
+            "ml4t": ML4T_CAPABILITIES,
+        },
+        "record_counts": {
+            "bars": len(prices),
+            "entry_signals": int(entries.sum()),
+            "exit_signals": int(exits.sum()) if exits is not None else 0,
+            "framework_intents": int(entries.sum())
+            + (int(exits.sum()) if exits is not None else 0),
+            "ml4t_intents": int(entries.sum()) + (int(exits.sum()) if exits is not None else 0),
+            "framework_orders": None,
+            "ml4t_orders": None,
+            "framework_fills": 0,
+            "ml4t_fills": 0,
+            "framework_closed_trades": 0,
+            "ml4t_closed_trades": 0,
+        },
+    }
+    return ValidationRecord(
+        framework=framework,
+        scenario_id=scenario_id,
+        scenario_name=scenario.name,
+        status=ValidationStatus.PASS,
+        required=True,
+        duration_seconds=0.01,
+        provenance=provenance,
+        framework_result=expected,
+        ml4t_result=actual,
+        comparison=comparison,
+    )
+
+
+def _full_report() -> dict[str, object]:
+    manifest = load_framework_manifest()
+    records: list[ValidationRecord] = []
+    for framework in manifest.scenario_framework_ids:
+        for scenario_id, scenario in SCENARIOS.items():
+            if framework in scenario.supported_frameworks:
+                records.append(_complete_record(framework, scenario_id))
+            else:
+                records.append(
+                    ValidationRecord(
+                        framework=framework,
+                        scenario_id=scenario_id,
+                        scenario_name=scenario.name,
+                        status=ValidationStatus.UNSUPPORTED,
+                        required=False,
+                        detail="Scenario explicitly excludes this framework",
+                        duration_seconds=0.001,
+                    )
+                )
+    return build_report(records)
+
+
+def _first_required_record(report: dict[str, object]) -> dict[str, Any]:
+    records = cast(list[dict[str, Any]], report["records"])
+    return next(record for record in records if record["required"])
+
+
+def test_complete_record_retains_outputs_checks_runtime_and_provenance() -> None:
+    payload = _complete_record("backtrader", "01").to_dict()
+
+    assert payload["duration_seconds"] > 0
+    assert payload["framework_result"]["final_value"] == 100_000.0
+    assert payload["ml4t_result"]["final_value"] == 100_000.0
+    assert payload["provenance"]["input_digest"]
+    assert payload["provenance"]["digests"]["adapter"]
+    checks = payload["comparison"]["checks"]
+    assert checks
+    assert {check["canonical_quantum"] for check in checks} == {"1", "0.00000001"}
+    assert all(
+        {"name", "canonical_quantum", "expected", "actual", "difference", "message"} <= check.keys()
+        for check in checks
+    )
+
+
+def test_input_digest_uses_values_not_pandas_index_metadata() -> None:
+    scenario = SCENARIOS["01"]
+    prices, entries, exits = generate_inputs(scenario, "backtrader")
+    assert exits is not None
+    expected = input_digest(prices, entries, exits)
+
+    same_values = prices.copy()
+    same_values.index = pd.DatetimeIndex(same_values.index.to_numpy())
+    assert same_values.index.freq is None
+    assert input_digest(same_values, entries.copy(), exits.copy()) == expected
+
+    changed_values = prices.copy()
+    changed_values.iloc[0, 0] += 0.01
+    assert input_digest(changed_values, entries, exits) != expected
+
+
+def test_complete_current_matrix_is_acceptable() -> None:
+    assert correctness_report_failures(_full_report()) == []
+
+
+@pytest.mark.parametrize(
+    ("mutation", "expected_failure"),
+    [
+        ("version", "framework target identity"),
+        ("input", "generated-input digest"),
+        ("adapter", "adapter digest"),
+        ("profile", "profile digest"),
+        ("comparator", "comparator digest"),
+        ("capability", "capability declaration differs"),
+        ("expected", "comparison checks differ"),
+        ("actual", "comparison checks differ"),
+        ("missing", "comparison evidence must be complete"),
+    ],
+)
+def test_evidence_mutations_fail_closed(mutation: str, expected_failure: str) -> None:
+    report = copy.deepcopy(_full_report())
+    record = _first_required_record(report)
+    if mutation == "version":
+        record["provenance"]["framework_target"]["actual_version"] = "0.0.0"
+    elif mutation == "input":
+        record["provenance"]["input_digest"] = "0" * 64
+    elif mutation in {"adapter", "profile", "comparator"}:
+        record["provenance"]["digests"][mutation] = "0" * 64
+    elif mutation == "capability":
+        record["provenance"]["capabilities"]["framework"]["fills"] = "unavailable"
+    elif mutation in {"expected", "actual"}:
+        record["comparison"]["checks"][0][mutation] = 12345
+    else:
+        record.pop("comparison")
+
+    failures = correctness_report_failures(report)
+
+    assert any(expected_failure in failure for failure in failures)
+
+
+def test_source_commit_change_without_behavior_change_is_not_stale() -> None:
+    report = _full_report()
+    for record in cast(list[dict[str, Any]], report["records"]):
+        if record["provenance"] is not None:
+            record["provenance"]["ml4t"]["commit"] = "b" * 40
+
+    assert correctness_report_failures(report) == []
+
+
+def test_tree_digest_excludes_untracked_generated_python(tmp_path: Path) -> None:
+    source = tmp_path / "src" / "package"
+    source.mkdir(parents=True)
+    (source / "engine.py").write_text("VALUE = 1\n", encoding="utf-8")
+    subprocess.run(["git", "init", "-q"], cwd=tmp_path, check=True)
+    subprocess.run(["git", "add", "src/package/engine.py"], cwd=tmp_path, check=True)
+
+    _tree_digest.cache_clear()
+    expected = _tree_digest(source)
+    (source / "_version.py").write_text("VERSION = 'generated'\n", encoding="utf-8")
+    _tree_digest.cache_clear()
+
+    assert _tree_digest(source) == expected
+
+
+def test_dirty_source_is_not_acceptable() -> None:
+    report = _full_report()
+    _first_required_record(report)["provenance"]["ml4t"]["dirty"] = True
+
+    assert any("dirty ML4T tree" in failure for failure in correctness_report_failures(report))
+
+
+def test_failed_candidate_does_not_replace_accepted_evidence(tmp_path: Path) -> None:
+    report = _full_report()
+    report["release_gate_passed"] = False
+    candidate = tmp_path / "candidate.json"
+    accepted = tmp_path / "accepted.json"
+    candidate.write_text(json.dumps(report), encoding="utf-8")
+    accepted.write_bytes(b"accepted-before\n")
+
+    failures = promote_candidate(candidate, accepted)
+
+    assert failures
+    assert accepted.read_bytes() == b"accepted-before\n"
+    assert candidate.is_file()
+
+
+def test_valid_candidate_atomically_replaces_accepted_evidence(tmp_path: Path) -> None:
+    report = _full_report()
+    candidate = tmp_path / "candidate.json"
+    accepted = tmp_path / "accepted.json"
+    candidate.write_text(json.dumps(report, sort_keys=True), encoding="utf-8")
+    accepted.write_bytes(b"accepted-before\n")
+
+    assert promote_candidate(candidate, accepted) == []
+    assert accepted.read_bytes() == candidate.read_bytes()
+    assert candidate.is_file()
diff --git a/tests/contracts/test_cross_framework_performance.py b/tests/contracts/test_cross_framework_performance.py
new file mode 100644
index 00000000..2851aaeb
--- /dev/null
+++ b/tests/contracts/test_cross_framework_performance.py
@@ -0,0 +1,163 @@
+"""Contracts for repeated cross-framework performance evidence."""
+
+from __future__ import annotations
+
+import copy
+import json
+from pathlib import Path
+
+import pytest
+
+from validation import cross_framework_performance as performance
+
+
+def _sample(runner: performance.RunnerSpec, index: int = 0) -> dict:
+    target = performance.load_framework_manifest().targets[runner.framework]
+    target_metadata = {**target.evidence_metadata(), "actual_version": target.version}
+    if runner.framework == "vectorbt_pro":
+        target_metadata.update(
+            {
+                "actual_commit": target.source_commit,
+                "actual_immutable_id": target.immutable_id,
+            }
+        )
+    input_sha256 = performance.scale._expected_input_digest(performance.WORKLOAD)
+    output = {
+        "order_intents": {"count": 1, "sha256": "a" * 64},
+        "fills": {"count": 1, "sha256": "b" * 64},
+        "trades": {"count": 1, "sha256": "c" * 64},
+        "trade_count": 1,
+        "total_pnl": 1.0,
+        "final_value": 1_000_001.0,
+        "terminal_state_sha256": "d" * 64,
+    }
+    return {
+        "runner_id": runner.runner_id,
+        "framework": runner.framework,
+        "side": runner.side,
+        "profile": runner.profile,
+        "target": target_metadata,
+        "python": {"implementation": "cpython", "version": "3.12.11"},
+        "ml4t": {"commit": "a" * 40, "dirty": False},
+        "input": {"raw_sha256": input_sha256, "effective_sha256": input_sha256},
+        "stages_seconds": {
+            "input_generation": 0.01,
+            "framework_call": 0.1 + index / 1_000,
+            "adapter_reported_engine": 0.08 + index / 1_000,
+            "output_validation": 0.01,
+            "worker_total": 0.12 + index / 1_000,
+        },
+        "process_peak_rss_mb": 100.0 + index,
+        "worker_self_peak_rss_mb": 90.0 + index,
+        "process_wall_seconds": 0.2 + index / 100,
+        "lean_container_observed": True,
+        "thread_environment": performance.THREAD_ENVIRONMENT,
+        "output": output,
+        "output_sha256": performance._json_digest(output),
+        "captured_log_tail": "",
+    }
+
+
+def test_bootstrap_interval_is_reproducible_and_requires_ten_samples() -> None:
+    values = [float(value) for value in range(10)]
+
+    first = performance.bootstrap_median_interval(values, seed=7)
+    second = performance.bootstrap_median_interval(values, seed=7)
+
+    assert first == second
+    assert first[0] <= 4.5 <= first[1]
+    with pytest.raises(ValueError, match="At least 10"):
+        performance.bootstrap_median_interval(values[:9], seed=7)
+
+
+def test_instrumentation_calibration_measures_child_wall_time_and_rss() -> None:
+    result = performance.run_calibration_process()
+
+    assert result["allocated_bytes"] == 32 * 1024 * 1024
+    assert result["worker_seconds"] >= 0.02
+    assert result["process_wall_seconds"] >= result["worker_seconds"]
+    assert result["process_peak_rss_mb"] >= 20
+
+
+def test_protocol_identity_changes_with_setup_or_cache_boundary() -> None:
+    original = performance._json_digest(performance.MEASUREMENT_PROTOCOL)
+    changed = copy.deepcopy(performance.MEASUREMENT_PROTOCOL)
+    changed["cache_policy"] = "different"
+
+    assert performance._json_digest(changed) != original
+
+
+def test_complete_report_recomputes_raw_sample_summaries(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    calibration = {
+        "allocated_bytes": 32 * 1024 * 1024,
+        "worker_seconds": 0.025,
+        "process_wall_seconds": 0.03,
+        "process_peak_rss_mb": 40.0,
+    }
+    monkeypatch.setattr(performance, "run_calibration_process", lambda: calibration)
+    calls = {runner.runner_id: 0 for runner in performance.RUNNERS}
+
+    def run(runner: performance.RunnerSpec) -> dict:
+        index = calls[runner.runner_id]
+        calls[runner.runner_id] += 1
+        return _sample(runner, max(index - 1, 0))
+
+    monkeypatch.setattr(performance, "_run_process", run)
+
+    report = performance.collect_evidence(10)
+
+    assert performance.report_failures(report) == []
+    assert report["controlled"]["passed"] is True
+    assert report["idiomatic"]["equivalence_claim"] is False
+    assert all(len(runner["samples"]) == 10 for runner in report["runners"].values())
+
+
+def test_output_change_or_missing_runner_fails_closed(monkeypatch: pytest.MonkeyPatch) -> None:
+    calibration = {
+        "allocated_bytes": 32 * 1024 * 1024,
+        "worker_seconds": 0.025,
+        "process_wall_seconds": 0.03,
+        "process_peak_rss_mb": 40.0,
+    }
+    monkeypatch.setattr(performance, "run_calibration_process", lambda: calibration)
+    monkeypatch.setattr(performance, "_run_process", lambda runner: _sample(runner))
+    report = performance.collect_evidence(10)
+
+    changed = copy.deepcopy(report)
+    changed["runners"]["backtrader:ml4t"]["samples"][0]["output_sha256"] = "0" * 64
+    assert performance.report_failures(changed)
+
+    missing = copy.deepcopy(report)
+    del missing["runners"]["zipline:external"]
+    assert performance.report_failures(missing)
+
+
+def test_worker_uses_profile_specific_ml4t_side(monkeypatch: pytest.MonkeyPatch) -> None:
+    runner = performance.RUNNERS_BY_ID["backtrader:ml4t"]
+    captured: dict[str, object] = {}
+
+    def benchmark(*_args, **kwargs):
+        captured.update(kwargs)
+        return object()
+
+    monkeypatch.setattr(performance.suite, "benchmark_ml4t", benchmark)
+
+    result = performance._run_ml4t(runner, object(), {}, object(), object())
+
+    assert result is not None
+    assert captured == {
+        "execution_mode": "next_bar",
+        "profile_override": "backtrader_strict",
+    }
+
+
+def test_accepted_write_is_atomic(tmp_path: Path) -> None:
+    target = tmp_path / "accepted.json"
+    target.write_text("old\n", encoding="utf-8")
+
+    performance._write_json_atomic(target, {"value": 1})
+
+    assert json.loads(target.read_text(encoding="utf-8")) == {"value": 1}
+    assert list(tmp_path.iterdir()) == [target]
diff --git a/tests/contracts/test_exact_validation_comparator.py b/tests/contracts/test_exact_validation_comparator.py
index af8853c7..e23683b1 100644
--- a/tests/contracts/test_exact_validation_comparator.py
+++ b/tests/contracts/test_exact_validation_comparator.py
@@ -17,6 +17,8 @@
     sys.path.insert(0, str(_VALIDATION_DIR))
 
 from common.comparator import compare_results  # noqa: E402
+from common.ml4t_runner import run_ml4t  # noqa: E402
+from common.provenance import generate_inputs  # noqa: E402
 from common.types import FrameworkResult  # noqa: E402
 from scenarios.definitions import SCENARIOS  # noqa: E402
 
@@ -34,13 +36,29 @@ def _load_benchmark_suite():
     return module
 
 
-def _trade() -> dict[str, object]:
+def _trade(*, offset: int = 0) -> dict[str, object]:
+    entry_time = pd.Timestamp("2024-01-02") + pd.Timedelta(days=offset)
     return {
+        "entry_time": entry_time,
+        "exit_time": entry_time + pd.Timedelta(days=1),
+        "asset": "AAPL",
         "entry_price": 100.0,
         "exit_price": 101.0,
         "pnl": 10.0,
         "size": 10.0,
         "direction": "Long",
+        "commission": 0.0,
+    }
+
+
+def _fill(*, offset: int = 0) -> dict[str, object]:
+    return {
+        "timestamp": pd.Timestamp("2024-01-02") + pd.Timedelta(days=offset),
+        "asset": "AAPL",
+        "side": "buy" if offset == 0 else "sell",
+        "quantity": 10.0,
+        "price": 100.0 + offset,
+        "commission": 0.0,
     }
 
 
@@ -63,10 +81,24 @@ def test_zipline_nine_dollar_difference_fails_despite_diagnostic_tolerance() ->
     assert "diagnostic_limit=$10.0" in checks["total_pnl"].message
 
 
-def test_scenario_trade_fields_require_exact_equality() -> None:
+@pytest.mark.parametrize(
+    ("field", "changed"),
+    [
+        ("entry_time", pd.Timestamp("2024-01-03")),
+        ("exit_time", pd.Timestamp("2024-01-04")),
+        ("asset", "MSFT"),
+        ("direction", "short"),
+        ("size", 10.00000001),
+        ("entry_price", 100.00000001),
+        ("exit_price", 101.00000001),
+        ("pnl", 10.00000001),
+        ("commission", 0.00000001),
+    ],
+)
+def test_scenario_trade_fields_require_exact_equality(field: str, changed: object) -> None:
     expected = FrameworkResult("Backtrader", 100_010.0, 10.0, 1, trades=[_trade()])
     changed_trade = _trade()
-    changed_trade["exit_price"] = 101.0000001
+    changed_trade[field] = changed
     actual = FrameworkResult(
         "ml4t.backtest",
         100_010.0,
@@ -80,7 +112,74 @@ def test_scenario_trade_fields_require_exact_equality() -> None:
     assert comparison.passed is False
     trade_check = next(check for check in comparison.checks if check.name == "trade_level_match")
     assert trade_check.passed is False
-    assert "exit_price" in trade_check.message
+    assert field in trade_check.message
+
+
+@pytest.mark.parametrize(
+    ("field", "changed"),
+    [
+        ("timestamp", pd.Timestamp("2024-01-03")),
+        ("asset", "MSFT"),
+        ("side", "sell"),
+        ("quantity", 10.00000001),
+        ("price", 100.00000001),
+        ("commission", 0.00000001),
+    ],
+)
+def test_scenario_fill_fields_require_exact_equality(field: str, changed: object) -> None:
+    expected = FrameworkResult("Backtrader", 100_010.0, 10.0, 1, trades=[_trade()], fills=[_fill()])
+    changed_fill = _fill()
+    changed_fill[field] = changed
+    actual = FrameworkResult(
+        "ml4t.backtest",
+        100_010.0,
+        10.0,
+        1,
+        trades=[_trade()],
+        fills=[changed_fill],
+    )
+
+    comparison = compare_results(SCENARIOS["01"], expected, actual)
+    fill_check = next(check for check in comparison.checks if check.name == "fill_level_match")
+
+    assert comparison.passed is False
+    assert fill_check.passed is False
+    assert field in fill_check.message
+
+
+@pytest.mark.parametrize("mutation", ["missing", "duplicate", "ordering", "malformed"])
+def test_scenario_record_shape_negative_controls(mutation: str) -> None:
+    expected_trades = [_trade(offset=0), _trade(offset=2)]
+    actual_trades = copy.deepcopy(expected_trades)
+    if mutation == "missing":
+        actual_trades[0].pop("asset")
+    elif mutation == "duplicate":
+        actual_trades.append(copy.deepcopy(actual_trades[-1]))
+    elif mutation == "ordering":
+        actual_trades.reverse()
+    else:
+        actual_trades[0]["pnl"] = float("nan")
+    expected = FrameworkResult("Backtrader", 100_020.0, 20.0, 2, trades=expected_trades)
+    actual = FrameworkResult("ml4t.backtest", 100_020.0, 20.0, 2, trades=actual_trades)
+
+    comparison = compare_results(SCENARIOS["01"], expected, actual)
+    trade_check = next(check for check in comparison.checks if check.name == "trade_level_match")
+
+    assert comparison.passed is False
+    assert trade_check.passed is False
+
+
+def test_wrong_execution_profile_remains_a_detected_negative_control() -> None:
+    scenario = SCENARIOS["01"]
+    prices, entries, exits = generate_inputs(scenario, "backtrader")
+    reference = run_ml4t(scenario, prices, entries, exits, framework="backtrader")
+    reference.framework = "Backtrader reference"
+    wrong_profile = run_ml4t(scenario, prices, entries, exits, framework="vectorbt_oss")
+
+    comparison = compare_results(scenario, reference, wrong_profile)
+
+    assert comparison.passed is False
+    assert any(not check.passed for check in comparison.checks)
 
 
 def _benchmark_result(suite, framework: str):
@@ -191,6 +290,63 @@ def test_fixed_point_zero_fill_and_trade_records_are_omitted() -> None:
     assert suite.canonical_trade_records(dust_trade) == []
 
 
+def test_daily_records_normalize_framework_session_timestamp_and_asset_wrapper() -> None:
+    suite = _load_benchmark_suite()
+    frame = pd.DataFrame(
+        [
+            {
+                "dt": pd.Timestamp("2024-01-02 21:00:00", tz="UTC"),
+                "asset": "Equity(1 [AAPL])",
+                "amount": 10.0,
+                "price": 100.0,
+                "commission": 0.0,
+            }
+        ]
+    )
+
+    records = suite.canonical_fill_records(frame, timestamp_domain="session_date")
+
+    assert records == [
+        {
+            "timestamp": "2024-01-02",
+            "asset": "AAPL",
+            "side": "buy",
+            "quantity": 10.0,
+            "price": 100.0,
+            "commission": 0.0,
+        }
+    ]
+
+
+def test_target_trace_excludes_unchanged_targets() -> None:
+    suite = _load_benchmark_suite()
+    index = pd.date_range("2024-01-02", periods=3, freq="D")
+    targets = pd.DataFrame({"AAPL": [10.0, 10.0, 0.0], "MSFT": [0.0, 5.0, 5.0]}, index=index)
+
+    trace = suite.build_canonical_target_trace(targets)
+
+    assert trace[["timestamp", "asset", "prev_target", "target"]].to_dict("records") == [
+        {
+            "timestamp": index[0],
+            "asset": "AAPL",
+            "prev_target": 0.0,
+            "target": 10.0,
+        },
+        {
+            "timestamp": index[1],
+            "asset": "MSFT",
+            "prev_target": 0.0,
+            "target": 5.0,
+        },
+        {
+            "timestamp": index[2],
+            "asset": "AAPL",
+            "prev_target": 10.0,
+            "target": 0.0,
+        },
+    ]
+
+
 def test_terminal_value_uses_exact_microdollar_representation() -> None:
     suite = _load_benchmark_suite()
     expected = _benchmark_result(suite, "Reference")
diff --git a/tests/contracts/test_framework_environment_builder.py b/tests/contracts/test_framework_environment_builder.py
new file mode 100644
index 00000000..0063378b
--- /dev/null
+++ b/tests/contracts/test_framework_environment_builder.py
@@ -0,0 +1,174 @@
+"""Contracts for locked framework comparison environments."""
+
+from __future__ import annotations
+
+import json
+import subprocess
+import sys
+from pathlib import Path
+
+import pytest
+
+_PROJECT_ROOT = Path(__file__).parents[2]
+_VALIDATION_DIR = _PROJECT_ROOT / "validation"
+if str(_VALIDATION_DIR) not in sys.path:
+    sys.path.insert(0, str(_VALIDATION_DIR))
+
+import build_framework_env  # noqa: E402
+from common.framework_registry import FrameworkTarget, load_framework_manifest  # noqa: E402
+
+
+@pytest.fixture
+def targets() -> dict[str, FrameworkTarget]:
+    return load_framework_manifest().targets
+
+
+def test_all_environment_definitions_match_frozen_targets(
+    targets: dict[str, FrameworkTarget],
+) -> None:
+    for framework in build_framework_env.BUILDABLE_FRAMEWORKS:
+        assert build_framework_env.definition_failures(framework, targets[framework]) == []
+
+
+def test_public_build_uses_locked_isolated_environment(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+    targets: dict[str, FrameworkTarget],
+) -> None:
+    calls: list[tuple[list[str], dict[str, str]]] = []
+
+    def run(command: list[str], **kwargs):
+        calls.append((command, kwargs["env"]))
+        return subprocess.CompletedProcess(command, 0)
+
+    monkeypatch.setattr(build_framework_env.subprocess, "run", run)
+
+    def verify(framework: str, _target: FrameworkTarget, *, root: Path):
+        assert root == tmp_path
+        return {"framework": framework}
+
+    monkeypatch.setattr(build_framework_env, "verify_environment", verify)
+
+    result = build_framework_env.build_environment(
+        "backtrader", targets["backtrader"], root=tmp_path
+    )
+
+    assert result == {"framework": "backtrader"}
+    command, environment = calls[0]
+    assert command[-2:] == ["--locked", "--no-dev"]
+    assert environment["UV_PROJECT_ENVIRONMENT"] == str(tmp_path / ".venv-backtrader")
+
+
+def test_definition_rejects_wrong_public_version(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+    targets: dict[str, FrameworkTarget],
+) -> None:
+    project = tmp_path / "backtrader"
+    project.mkdir()
+    (project / "uv.lock").write_text(targets["backtrader"].immutable_id, encoding="utf-8")
+    (project / "pyproject.toml").write_text(
+        '[project]\ndependencies = ["backtrader==1.9.78.122"]\n', encoding="utf-8"
+    )
+    monkeypatch.setattr(build_framework_env, "ENVIRONMENTS_DIR", tmp_path)
+
+    failures = build_framework_env.definition_failures("backtrader", targets["backtrader"])
+
+    assert any("backtrader==1.9.78.123" in failure for failure in failures)
+
+
+def test_definition_rejects_wrong_private_commit(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+    targets: dict[str, FrameworkTarget],
+) -> None:
+    project = tmp_path / "vectorbt_pro"
+    project.mkdir()
+    (project / "uv.lock").write_text("wrong-commit", encoding="utf-8")
+    (project / "pyproject.toml").write_text(
+        '[project]\ndependencies = ["vectorbtpro @ git+ssh://example.invalid/repo@wrong"]\n',
+        encoding="utf-8",
+    )
+    monkeypatch.setattr(build_framework_env, "ENVIRONMENTS_DIR", tmp_path)
+
+    failures = build_framework_env.definition_failures("vectorbt_pro", targets["vectorbt_pro"])
+
+    assert "VectorBT Pro environment does not pin the manifest commit" in failures
+    assert any("artifact identity" in failure for failure in failures)
+
+
+def test_private_build_reports_missing_licensed_access(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+    targets: dict[str, FrameworkTarget],
+) -> None:
+    monkeypatch.setattr(build_framework_env, "definition_failures", lambda *_: [])
+    monkeypatch.setattr(
+        build_framework_env.subprocess,
+        "run",
+        lambda *args, **_kwargs: (_ for _ in ()).throw(subprocess.CalledProcessError(1, args[0])),
+    )
+
+    with pytest.raises(RuntimeError, match="Authorized SSH access"):
+        build_framework_env.build_environment(
+            "vectorbt_pro", targets["vectorbt_pro"], root=tmp_path
+        )
+
+
+def test_lean_verification_separates_cli_and_engine_provenance(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+    targets: dict[str, FrameworkTarget],
+) -> None:
+    target = targets["lean"]
+    interpreter = tmp_path / ".venv-lean" / "bin" / "python"
+    interpreter.parent.mkdir(parents=True)
+    interpreter.touch()
+    monkeypatch.setattr(build_framework_env, "definition_failures", lambda *_: [])
+    monkeypatch.setattr(
+        build_framework_env,
+        "_probe",
+        lambda *_: {
+            "version": target.cli_version,
+            "ml4t_path": str(_PROJECT_ROOT / "src/ml4t/backtest/__init__.py"),
+            "python": "3.12.11",
+        },
+    )
+    commands: list[list[str]] = []
+
+    def run(command: list[str], **_kwargs):
+        commands.append(command)
+        return subprocess.CompletedProcess(command, 0, "", "")
+
+    monkeypatch.setattr(build_framework_env.subprocess, "run", run)
+
+    evidence = build_framework_env.verify_environment("lean", target, root=tmp_path)
+
+    assert evidence["data_preparation"]["cli_version"] == target.cli_version
+    assert evidence["engine_execution"]["image_digest"] == target.immutable_id
+    assert commands == [["docker", "buildx", "imagetools", "inspect", target.artifact]]
+
+
+def test_private_environment_rejects_wrong_installed_commit(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+    targets: dict[str, FrameworkTarget],
+) -> None:
+    target = targets["vectorbt_pro"]
+    interpreter = tmp_path / ".venv-vectorbt-pro" / "bin" / "python"
+    interpreter.parent.mkdir(parents=True)
+    interpreter.touch()
+    monkeypatch.setattr(build_framework_env, "definition_failures", lambda *_: [])
+    monkeypatch.setattr(
+        build_framework_env,
+        "_probe",
+        lambda *_: {
+            "version": target.version,
+            "direct_url": json.dumps({"vcs_info": {"commit_id": "wrong"}}),
+            "ml4t_path": str(_PROJECT_ROOT / "src/ml4t/backtest/__init__.py"),
+            "python": "3.12.11",
+        },
+    )
+
+    with pytest.raises(ValueError, match="commit differs"):
+        build_framework_env.verify_environment("vectorbt_pro", target, root=tmp_path)
diff --git a/tests/contracts/test_framework_target_manifest.py b/tests/contracts/test_framework_target_manifest.py
new file mode 100644
index 00000000..5fabf58b
--- /dev/null
+++ b/tests/contracts/test_framework_target_manifest.py
@@ -0,0 +1,204 @@
+"""Contracts for frozen comparison targets and the comparison-claim inventory."""
+
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+import pytest
+
+_PROJECT_ROOT = Path(__file__).parents[2]
+_VALIDATION_DIR = _PROJECT_ROOT / "validation"
+if str(_VALIDATION_DIR) not in sys.path:
+    sys.path.insert(0, str(_VALIDATION_DIR))
+
+import run_all_benchmarks  # noqa: E402
+from common.framework_registry import (  # noqa: E402
+    ManifestError,
+    load_claim_inventory,
+    load_framework_manifest,
+)
+
+
+def test_current_framework_targets_are_exact_and_immutable() -> None:
+    manifest = load_framework_manifest()
+
+    assert manifest.freeze_date == "2026-08-13"
+    assert set(manifest.targets) == {
+        "backtrader",
+        "lean",
+        "vectorbt_oss",
+        "vectorbt_pro",
+        "zipline",
+    }
+    assert {key: target.version for key, target in manifest.targets.items()} == {
+        "vectorbt_pro": "2026.6.27",
+        "vectorbt_oss": "1.1.0",
+        "backtrader": "1.9.78.123",
+        "zipline": "3.1.1",
+        "lean": "18001",
+    }
+    assert manifest.scenario_framework_ids == (
+        "vectorbt_pro",
+        "vectorbt_oss",
+        "backtrader",
+        "zipline",
+    )
+    for target in manifest.targets.values():
+        assert not any(operator in target.version for operator in ("<", ">", "=", "*", "~"))
+        assert target.immutable_id.startswith(("git:", "sha256:"))
+        assert target.profile
+        assert target.python
+        assert target.license
+        assert target.access in {"public", "licensed"}
+
+
+def test_scenario_targets_define_reproducible_interpreters() -> None:
+    manifest = load_framework_manifest()
+
+    for framework_id in manifest.scenario_framework_ids:
+        target = manifest.targets[framework_id]
+        assert target.environment
+        assert target.python_env_var.startswith("ML4T_")
+        assert target.required_scenarios + target.unsupported_scenarios == 17
+
+
+def test_benchmark_runner_uses_frozen_target_environments() -> None:
+    manifest = load_framework_manifest()
+
+    assert set(run_all_benchmarks.FRAMEWORKS) == {"ml4t", *manifest.targets}
+    for framework_id, target in manifest.targets.items():
+        assert run_all_benchmarks.FRAMEWORKS[framework_id]["venv"] == target.environment
+
+
+@pytest.mark.parametrize(
+    ("replacement", "message"),
+    [
+        ('version = "1.1.0"', "missing required field 'immutable_id'"),
+        ('version = ">=1.1.0"\nimmutable_id = "git:abc"', "must be an exact version"),
+    ],
+)
+def test_invalid_framework_targets_are_rejected(
+    tmp_path: Path,
+    replacement: str,
+    message: str,
+) -> None:
+    manifest = tmp_path / "targets.toml"
+    manifest.write_text(
+        """
+[metadata]
+schema_version = 1
+freeze_date = "2026-08-13"
+scenario_frameworks = ["example"]
+
+[framework.example]
+display_name = "Example"
+package = "example"
+profile = "default"
+python = ">=3.11"
+license = "MIT"
+access = "public"
+source = "https://example.com"
+environment = ".venv-example"
+python_env_var = "ML4T_EXAMPLE_PYTHON"
+scenario_matrix = true
+required_scenarios = 1
+unsupported_scenarios = 0
+"""
+        + replacement
+        + "\n",
+        encoding="utf-8",
+    )
+
+    with pytest.raises(ManifestError, match=message):
+        load_framework_manifest(manifest)
+
+
+def test_duplicate_framework_tables_are_rejected(tmp_path: Path) -> None:
+    manifest = tmp_path / "targets.toml"
+    manifest.write_text(
+        """
+[metadata]
+schema_version = 1
+freeze_date = "2026-08-13"
+
+[framework.example]
+display_name = "Example"
+package = "example"
+version = "1.0"
+profile = "default"
+python = ">=3.11"
+license = "MIT"
+access = "public"
+source = "https://example.com"
+immutable_id = "git:abc"
+scenario_matrix = false
+required_scenarios = 0
+unsupported_scenarios = 0
+
+[framework.example]
+version = "2.0"
+""",
+        encoding="utf-8",
+    )
+
+    with pytest.raises(ManifestError, match="Invalid TOML"):
+        load_framework_manifest(manifest)
+
+
+def test_claim_inventory_accounts_for_all_repositories_and_known_targets() -> None:
+    manifest = load_framework_manifest()
+    inventory = load_claim_inventory(manifest=manifest)
+
+    assert inventory.audit_date == manifest.freeze_date
+    assert {claim.repository for claim in inventory.claims} == {
+        "ml4t/backtest",
+        "ml4t/public",
+        "ml4t/content-marketing",
+    }
+    assert {claim.claim_type for claim in inventory.claims} == {
+        "behavioral",
+        "correctness",
+        "performance",
+        "qualitative",
+    }
+    assert inventory.unresolved
+    assert all(item.issue.startswith("ml4t/backtest-dev#") for item in inventory.unresolved)
+    local_paths = {
+        path
+        for claim in inventory.claims
+        if claim.repository == "ml4t/backtest"
+        for path in claim.paths
+    }
+    assert local_paths
+    assert all((_PROJECT_ROOT / path).is_file() for path in local_paths)
+
+
+def test_claim_inventory_rejects_unknown_framework(tmp_path: Path) -> None:
+    inventory = tmp_path / "claims.toml"
+    inventory.write_text(
+        """
+[metadata]
+schema_version = 1
+audit_date = "2026-08-13"
+
+[[claim]]
+id = "unknown-target"
+repository = "ml4t/backtest"
+paths = ["README.md"]
+type = "correctness"
+frameworks = ["not-a-framework"]
+required_evidence = ["canonical_trade_log"]
+status = "unresolved"
+issue = "ml4t/backtest-dev#9"
+
+[[unresolved]]
+id = "placeholder"
+finding = "Placeholder finding."
+issue = "ml4t/backtest-dev#9"
+""",
+        encoding="utf-8",
+    )
+
+    with pytest.raises(ManifestError, match="unknown framework"):
+        load_claim_inventory(inventory)
diff --git a/tests/contracts/test_large_scale_evidence.py b/tests/contracts/test_large_scale_evidence.py
new file mode 100644
index 00000000..91afc7f7
--- /dev/null
+++ b/tests/contracts/test_large_scale_evidence.py
@@ -0,0 +1,294 @@
+"""Contracts for reconstructable, capability-qualified large-scale evidence."""
+
+from __future__ import annotations
+
+import copy
+import importlib.util
+import json
+import subprocess
+import sys
+from pathlib import Path
+
+import pandas as pd
+import pytest
+
+
+def _load_module():
+    path = Path(__file__).parents[2] / "validation" / "large_scale_evidence.py"
+    spec = importlib.util.spec_from_file_location("ml4t_large_scale_evidence", path)
+    assert spec is not None
+    assert spec.loader is not None
+    module = importlib.util.module_from_spec(spec)
+    sys.modules[spec.name] = module
+    spec.loader.exec_module(module)
+    return module
+
+
+def _small_workload(module):
+    return module.ScaleWorkload(
+        name="contract_scale",
+        seed=7,
+        bars=20,
+        assets=3,
+        top_n=1,
+        bottom_n=1,
+        end_session="2024-12-31",
+    )
+
+
+def _complete_report(module, monkeypatch: pytest.MonkeyPatch):
+    workload = _small_workload(module)
+    monkeypatch.setattr(module, "WORKLOAD", workload)
+    module._expected_input_digest.cache_clear()
+    config = workload.benchmark_config()
+    prices, signals, dates = module.suite.generate_benchmark_data(config, seed=workload.seed)
+    digest = module.input_digest(prices, signals, dates)
+    records = []
+    manifest = module.load_framework_manifest()
+    surface_names = ("order_intents", "fills", "trades", "terminal_state")
+    scalar_names = ("trade_count", "total_pnl", "final_value")
+    for framework in module.FRAMEWORKS:
+        target = manifest.targets[framework]
+        checks = [
+            {
+                "name": name,
+                "passed": True,
+                "expected_sha256": "a" * 64,
+                "actual_sha256": "a" * 64,
+            }
+            for name in surface_names
+        ]
+        checks.extend(
+            {
+                "name": name,
+                "passed": True,
+                "canonical_expected": 1.0,
+                "canonical_actual": 1.0,
+            }
+            for name in scalar_names
+        )
+        records.append(
+            {
+                "framework": framework,
+                "target": {
+                    **target.evidence_metadata(),
+                    "actual_version": target.version,
+                    **(
+                        {
+                            "actual_commit": target.source_commit,
+                            "actual_immutable_id": target.immutable_id,
+                        }
+                        if framework == "vectorbt_pro"
+                        else {}
+                    ),
+                },
+                "python": {"version": "3.12.11", "implementation": "cpython"},
+                "ml4t": {"commit": "a" * 40, "dirty": False},
+                "source_digests": module._source_digests(),
+                "input": {
+                    "raw_sha256": digest,
+                    "effective_sha256": digest,
+                    "conversion": "none",
+                },
+                "capabilities": {
+                    "intents": "canonical strategy trace",
+                    "fills": "native",
+                    "closed_trades": "native",
+                    "terminal_state": "reconstructed",
+                    "fill_order": "canonical",
+                },
+                "comparison": {"passed": True, "checks": checks},
+            }
+        )
+    return module.build_report(records, workload)
+
+
+def test_input_digest_is_independent_of_datetime_resolution() -> None:
+    module = _load_module()
+    workload = _small_workload(module)
+    config = workload.benchmark_config()
+    prices, signals, dates = module.suite.generate_benchmark_data(config, seed=workload.seed)
+    expected = module.input_digest(prices, signals, dates)
+
+    converted_prices = {asset: frame.copy() for asset, frame in prices.items()}
+    for frame in converted_prices.values():
+        frame.index = pd.DatetimeIndex(frame.index.to_numpy(dtype="datetime64[us]"))
+    converted_signals = signals.copy()
+    converted_signals["timestamp"] = converted_signals["timestamp"].to_numpy(dtype="datetime64[us]")
+    converted_dates = pd.DatetimeIndex(dates.to_numpy(dtype="datetime64[us]"))
+
+    assert module.input_digest(converted_prices, converted_signals, converted_dates) == expected
+
+
+@pytest.mark.parametrize(
+    ("framework", "expected_profile"),
+    [("vectorbt_pro", "vectorbt_strict"), ("vectorbt_oss", "vectorbt_oss_strict")],
+)
+def test_vectorbt_scale_pairs_use_version_specific_collateral_profiles(
+    framework: str, expected_profile: str, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    module = _load_module()
+    captured: dict[str, object] = {}
+
+    monkeypatch.setattr(
+        module.suite,
+        f"benchmark_{framework}",
+        lambda *_args: "external",
+    )
+
+    def capture_ml4t(*args, **kwargs):
+        captured.update(kwargs)
+        return "ml4t"
+
+    monkeypatch.setattr(module.suite, "benchmark_ml4t", capture_ml4t)
+
+    result = module._framework_run(framework, object(), {}, pd.DataFrame(), pd.DatetimeIndex([]))
+
+    assert result == ("external", "ml4t")
+    assert captured["profile_override"] == expected_profile
+
+
+def test_scale_trade_surface_is_reconstructed_from_canonical_fills() -> None:
+    module = _load_module()
+    fills = pd.DataFrame(
+        [
+            {
+                "timestamp": "2024-01-01",
+                "asset": "A",
+                "side": "buy",
+                "quantity": 3.0,
+                "price": 10.0,
+                "commission": 0.0,
+            },
+            {
+                "timestamp": "2024-01-02",
+                "asset": "A",
+                "side": "sell",
+                "quantity": 3.0,
+                "price": 11.0,
+                "commission": 0.0,
+            },
+        ]
+    )
+    external = module.suite.BenchmarkResult("external", "scale", 0.0, 999, 0.0, 0.0)
+    ml4t = module.suite.BenchmarkResult("ml4t", "scale", 0.0, 999, 0.0, 0.0)
+    external.fills_df = fills
+    ml4t.fills_df = fills.copy()
+
+    module._use_canonical_fill_backed_trades(external, ml4t)
+
+    assert external.num_trades == ml4t.num_trades == 1
+    assert module.suite.canonical_trade_records(external.trades_df) == (
+        module.suite.canonical_trade_records(ml4t.trades_df)
+    )
+
+
+def test_complete_report_reconstructs(monkeypatch: pytest.MonkeyPatch) -> None:
+    module = _load_module()
+    report = _complete_report(module, monkeypatch)
+
+    assert module.report_failures(report, reconstruct_input=True) == []
+
+
+def test_historical_report_requires_exact_identity_and_matching_outputs(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    module = _load_module()
+    current_report = _complete_report(module, monkeypatch)
+    current = next(
+        record for record in current_report["frameworks"] if record["framework"] == "vectorbt_pro"
+    )
+    historical = copy.deepcopy(current)
+    target = module._historical_vectorbt_pro_target()
+    historical["target"] = {
+        **target.evidence_metadata(),
+        "actual_version": target.version,
+        "actual_commit": target.source_commit,
+        "actual_immutable_id": target.immutable_id,
+    }
+    report = module.build_historical_report(current, historical, module.WORKLOAD)
+
+    assert module.historical_report_failures(report, reconstruct_input=True) == []
+
+    evidence_only_revision = copy.deepcopy(report)
+    evidence_only_revision["historical"]["ml4t"]["commit"] = "b" * 40
+    assert module.historical_report_failures(evidence_only_revision, reconstruct_input=True) == []
+
+    wrong_identity = copy.deepcopy(report)
+    wrong_identity["historical"]["target"]["actual_version"] = "2026.6.27"
+    assert module.historical_report_failures(wrong_identity)
+
+    missing_ml4t_identity = copy.deepcopy(report)
+    missing_ml4t_identity["historical"]["ml4t"]["commit"] = ""
+    assert module.historical_report_failures(missing_ml4t_identity)
+
+    changed_output = copy.deepcopy(report)
+    fill_check = next(
+        check
+        for check in changed_output["historical"]["comparison"]["checks"]
+        if check["name"] == "fills"
+    )
+    fill_check["expected_sha256"] = "0" * 64
+    assert module.historical_report_failures(changed_output)
+
+
+@pytest.mark.parametrize(
+    "mutation",
+    ["recipe", "input", "order_intents", "fills", "trades", "terminal_state", "final_value"],
+)
+def test_large_scale_mutations_fail_closed(mutation: str, monkeypatch: pytest.MonkeyPatch) -> None:
+    module = _load_module()
+    report = copy.deepcopy(_complete_report(module, monkeypatch))
+    if mutation == "recipe":
+        report["workload"]["recipe"]["seed"] = 999
+    elif mutation == "input":
+        report["frameworks"][0]["input"]["raw_sha256"] = "0" * 64
+    else:
+        check = next(
+            check
+            for check in report["frameworks"][0]["comparison"]["checks"]
+            if check["name"] == mutation
+        )
+        if mutation == "final_value":
+            check["canonical_actual"] = 2.0
+        else:
+            check["actual_sha256"] = "0" * 64
+
+    assert module.report_failures(report, reconstruct_input=True)
+
+
+def test_accepted_write_is_atomic(tmp_path: Path) -> None:
+    module = _load_module()
+    target = tmp_path / "accepted.json"
+    target.write_text("old\n", encoding="utf-8")
+
+    module._write_json_atomic(target, {"value": 1})
+
+    assert json.loads(target.read_text(encoding="utf-8")) == {"value": 1}
+    assert list(tmp_path.iterdir()) == [target]
+
+
+def test_failed_worker_comparison_is_retained(
+    tmp_path: Path, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    module = _load_module()
+    interpreter = tmp_path / "python"
+    interpreter.touch()
+    monkeypatch.setattr(module, "CANDIDATE_DIR", tmp_path / "candidates")
+    record = {
+        "framework": "backtrader",
+        "comparison": {"passed": False, "first_difference": {"name": "fills"}},
+    }
+
+    def failed_run(command, **_kwargs):
+        output = Path(command[command.index("--output") + 1])
+        output.write_text(json.dumps(record), encoding="utf-8")
+        return subprocess.CompletedProcess(command, 1, stdout="", stderr="")
+
+    monkeypatch.setattr(module.subprocess, "run", failed_run)
+
+    with pytest.raises(RuntimeError, match="diagnostic retained"):
+        module._run_isolated_worker("backtrader", interpreter)
+
+    retained = tmp_path / "candidates" / "backtrader.large_scale.candidate.json"
+    assert json.loads(retained.read_text(encoding="utf-8")) == record
diff --git a/tests/contracts/test_lean_case_study_evidence.py b/tests/contracts/test_lean_case_study_evidence.py
new file mode 100644
index 00000000..2e6dacd7
--- /dev/null
+++ b/tests/contracts/test_lean_case_study_evidence.py
@@ -0,0 +1,86 @@
+"""Contracts for retained fresh LEAN case-study evidence."""
+
+from __future__ import annotations
+
+import gzip
+import hashlib
+import json
+import lzma
+from pathlib import Path
+
+_ROOT = Path(__file__).parents[2]
+_WORKSPACE = _ROOT / "validation/lean/workspace"
+_DATA = _WORKSPACE / "data/equity/usa/daily"
+_SUPPORT = _ROOT / "validation/lean/support"
+_EVIDENCE = _ROOT / "validation/lean/case_study_evidence.json"
+_CASES = {
+    "chapter16_etfs",
+    "chapter16_sp500_equity_option_analytics",
+    "chapter16_us_equities_panel",
+}
+
+
+def _digest(path: Path) -> str:
+    return hashlib.sha256(path.read_bytes()).hexdigest()
+
+
+def _read_compressed(path: Path) -> bytes:
+    payload = path.read_bytes()
+    if path.suffix == ".xz":
+        return lzma.decompress(payload)
+    if path.suffix == ".gz":
+        return gzip.decompress(payload)
+    return payload
+
+
+def _reconstruct_order_events(paths: list[Path]) -> bytes:
+    parts = [_read_compressed(path) for path in paths]
+    if len(parts) == 1:
+        return parts[0]
+    header = parts[0].splitlines(keepends=True)[0]
+    body = [parts[0], *(b"".join(part.splitlines(keepends=True)[1:]) for part in parts[1:])]
+    assert parts[0].startswith(header)
+    return b"".join(body)
+
+
+def test_retained_lean_case_study_evidence_is_fresh_and_complete() -> None:
+    payload = json.loads(_EVIDENCE.read_text(encoding="utf-8"))
+
+    assert payload["schema_version"] == 1
+    assert payload["passed"] is True
+    assert payload["promoted"] is True
+    assert payload["framework"]["version"] == "18001"
+    assert payload["framework"]["artifact"].startswith("quantconnect/lean@sha256:")
+    assert payload["cli_observed"] == "lean 1.0.228"
+    assert {case["case"] for case in payload["cases"]} == _CASES
+
+    for relative, digest in payload["producer_files"].items():
+        assert _digest(_ROOT / relative) == digest
+    for relative, digest in payload["support_files"].items():
+        assert _digest(_SUPPORT / relative) == digest
+
+    for case in payload["cases"]:
+        assert case["passed"] is True
+        assert case["comparison"]["fill_gap"] == 0
+        assert case["comparison"]["sorted_fill_multiset_match"] is True
+        assert case["comparison"]["canonical_final_value_match"] is True
+        assert case["comparison"]["canonical_final_value_gap_usd"] == 0.0
+        assert case["lean_fill_surface_sha256"] == case["ml4t_fill_surface_sha256"]
+
+        project = _WORKSPACE / case["case"]
+        for relative, digest in case["inputs"].items():
+            path = (
+                _DATA / Path(relative).name if relative.startswith("data/") else project / relative
+            )
+            assert _digest(path) == digest
+
+        retained = [_ROOT / relative for relative in case["retained_artifacts"]]
+        for path in retained:
+            assert _digest(path) == case["retained_artifacts"][path.relative_to(_ROOT).as_posix()]
+        order_paths = [path for path in retained if "order_events" in path.name]
+        equity_path = next(path for path in retained if path.name == "ml4t_daily_equity.csv")
+        assert (
+            hashlib.sha256(_reconstruct_order_events(order_paths)).hexdigest()
+            == case["raw_order_events_sha256"]
+        )
+        assert _digest(equity_path) == case["raw_daily_equity_sha256"]
diff --git a/tests/contracts/test_lean_native_evidence.py b/tests/contracts/test_lean_native_evidence.py
new file mode 100644
index 00000000..4391909f
--- /dev/null
+++ b/tests/contracts/test_lean_native_evidence.py
@@ -0,0 +1,75 @@
+"""Contracts for retained framework-native LEAN evidence."""
+
+from __future__ import annotations
+
+import hashlib
+import json
+from pathlib import Path
+
+_ROOT = Path(__file__).parents[2]
+_ORACLE = _ROOT / "validation/native/lean_behavior.py"
+_PROJECT = _ROOT / "validation/native/lean_project"
+_SUPPORT = _ROOT / "validation/lean/support"
+_EVIDENCE = _ROOT / "validation/native/evidence/lean-18001.json"
+
+EXPECTED_CHECKS = {
+    "buying_power_allowed",
+    "buying_power_rejected",
+    "buying_power_sequence",
+    "default_full_fill",
+    "default_models",
+    "explicit_costs",
+    "fill_forward",
+    "final_bar_order",
+    "liquidation",
+    "submission_sequence",
+    "target_sizing",
+    "terminal_holding",
+    "timing",
+}
+
+
+def test_retained_lean_native_evidence_is_complete_and_current() -> None:
+    payload = json.loads(_EVIDENCE.read_text(encoding="utf-8"))
+
+    assert payload["schema_version"] == 1
+    assert payload["framework"] == "lean"
+    assert payload["engine"]["engine_version"] == "18001"
+    assert payload["engine"]["source_commit"] == ("278fcb3d1b815b63ccadba68d7ae54422e34b792")
+    assert payload["engine"]["image"] == (
+        "quantconnect/lean@sha256:ecd62b0e418d40d1d7c0cd95e90a94e397642a21d2c8810614830c8a4e9a8f70"
+    )
+    assert payload["engine"]["platform_artifact"] == (
+        "linux/amd64@sha256:cbe3f26b3f16c57be836b2cf913253d434f58e010c84ed038360d26b9df88307"
+    )
+    assert payload["cli"] == {
+        "immutable_id": ("sha256:eaa4c08f16295b76f005e429d9ca0d0453784dc1a40c1f5cbe5e50c02a05bd7c"),
+        "package": "lean",
+        "version": "1.0.228",
+    }
+    assert payload["models"] == {
+        "account_type": "Margin",
+        "brokerage": "DefaultBrokerageModel",
+        "security": "Equity USA, daily, adjusted normalization, leverage 2",
+    }
+    assert payload["oracle_sha256"] == hashlib.sha256(_ORACLE.read_bytes()).hexdigest()
+    expected_files = {
+        path.relative_to(_PROJECT).as_posix(): hashlib.sha256(path.read_bytes()).hexdigest()
+        for path in sorted(_PROJECT.rglob("*"))
+        if path.is_file()
+    }
+    assert payload["oracle_files"] == expected_files
+    expected_support = {
+        path.relative_to(_SUPPORT).as_posix(): hashlib.sha256(path.read_bytes()).hexdigest()
+        for path in sorted(_SUPPORT.rglob("*"))
+        if path.is_file()
+    }
+    assert payload["support_files"] == expected_support
+    assert payload["passed"] is True
+    assert {check["id"] for check in payload["checks"]} == EXPECTED_CHECKS
+    assert all(check["passed"] for check in payload["checks"])
+    assert all(check["contract_actual"] == check["expected"] for check in payload["checks"])
+    assert all(
+        payload["engine"]["source_commit"] in source
+        for source in payload["source_references"].values()
+    )
diff --git a/tests/contracts/test_lean_orchestration.py b/tests/contracts/test_lean_orchestration.py
new file mode 100644
index 00000000..5cf0f333
--- /dev/null
+++ b/tests/contracts/test_lean_orchestration.py
@@ -0,0 +1,72 @@
+"""Contracts for immutable LEAN engine orchestration."""
+
+from __future__ import annotations
+
+from pathlib import Path
+from types import SimpleNamespace
+
+import pytest
+
+from ml4t.backtest._validation import lean_runner
+
+
+def test_lean_backtest_requires_an_immutable_image(tmp_path: Path) -> None:
+    with pytest.raises(ValueError, match="immutable digest"):
+        lean_runner.run_lean_backtest(
+            lean_cmd=["lean"],
+            cwd=tmp_path,
+            project_dir=tmp_path / "project",
+            lean_config=tmp_path / "lean.json",
+            output_dir=tmp_path / "output",
+            image="quantconnect/lean:latest",
+        )
+
+
+def test_lean_command_resolution_does_not_install_an_unpinned_cli(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+) -> None:
+    monkeypatch.chdir(tmp_path)
+    monkeypatch.delenv("ML4T_LEAN_COMMAND", raising=False)
+    monkeypatch.setattr(lean_runner.shutil, "which", lambda _name: None)
+
+    with pytest.raises(FileNotFoundError, match="frozen environment"):
+        lean_runner.resolve_lean_command()
+
+
+def test_lean_backtest_passes_the_frozen_image_to_the_cli(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path: Path,
+) -> None:
+    calls: list[list[str]] = []
+
+    def fake_run(command: list[str], **kwargs: object) -> SimpleNamespace:
+        calls.append(command)
+        return SimpleNamespace(returncode=0, stdout="", stderr="")
+
+    monkeypatch.setattr(lean_runner.subprocess, "run", fake_run)
+    image = "quantconnect/lean@sha256:" + "a" * 64
+
+    lean_runner.run_lean_backtest(
+        lean_cmd=["lean"],
+        cwd=tmp_path,
+        project_dir=tmp_path / "project",
+        lean_config=tmp_path / "lean.json",
+        output_dir=tmp_path / "output",
+        image=image,
+    )
+
+    assert calls == [
+        [
+            "lean",
+            "backtest",
+            str(tmp_path / "project"),
+            "--lean-config",
+            str(tmp_path / "lean.json"),
+            "--image",
+            image,
+            "--no-update",
+            "--output",
+            str(tmp_path / "output"),
+        ]
+    ]
diff --git a/tests/contracts/test_parity_claim_generation.py b/tests/contracts/test_parity_claim_generation.py
index 53508724..cf6a7018 100644
--- a/tests/contracts/test_parity_claim_generation.py
+++ b/tests/contracts/test_parity_claim_generation.py
@@ -6,6 +6,8 @@
 import sys
 from pathlib import Path
 
+import pytest
+
 _VALIDATION_DIR = Path(__file__).parents[2] / "validation"
 if str(_VALIDATION_DIR) not in sys.path:
     sys.path.insert(0, str(_VALIDATION_DIR))
@@ -13,7 +15,19 @@
 import generate_parity_claims  # noqa: E402
 
 
-def test_parity_claim_documents_match_retained_evidence() -> None:
+def test_legacy_accepted_evidence_cannot_generate_current_claims() -> None:
+    correctness = copy.deepcopy(
+        generate_parity_claims._load_json(generate_parity_claims.CORRECTNESS_EVIDENCE)
+    )
+    large_scale = generate_parity_claims._load_json(generate_parity_claims.LARGE_SCALE_EVIDENCE)
+    real_strategy = generate_parity_claims._load_json(generate_parity_claims.REAL_STRATEGY_EVIDENCE)
+    correctness["schema_version"] = 1
+
+    with pytest.raises(ValueError, match="Unsupported correctness schema: 1"):
+        generate_parity_claims._validate_evidence(correctness, large_scale, real_strategy)
+
+
+def test_generated_claims_are_current() -> None:
     assert generate_parity_claims.synchronize(check=True) == []
 
 
@@ -30,19 +44,45 @@ def test_every_claim_target_uses_the_same_generated_block() -> None:
     assert len(set(blocks)) == 1
 
 
-def test_claims_pin_every_advertised_framework_and_expose_failures() -> None:
+def test_claims_pin_every_advertised_framework_and_expose_failures(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
     correctness = generate_parity_claims._load_json(generate_parity_claims.CORRECTNESS_EVIDENCE)
+    correctness = copy.deepcopy(correctness)
+    for framework in generate_parity_claims.SCENARIO_FRAMEWORKS:
+        framework_records = [
+            record for record in correctness["records"] if record["framework"] == framework
+        ]
+        if len(framework_records) < len(generate_parity_claims.SCENARIOS):
+            added = copy.deepcopy(framework_records[-1])
+            added["scenario_id"] = "17"
+            added["scenario_name"] = "High Event Count"
+            added["required"] = True
+            added["status"] = "pass"
+            correctness["records"].append(added)
     large_scale = generate_parity_claims._load_json(generate_parity_claims.LARGE_SCALE_EVIDENCE)
+    real_strategy = generate_parity_claims._load_json(generate_parity_claims.REAL_STRATEGY_EVIDENCE)
+    monkeypatch.setattr(generate_parity_claims, "correctness_report_failures", lambda _: [])
+    monkeypatch.setattr(generate_parity_claims, "large_scale_report_failures", lambda _: [])
 
-    claims = generate_parity_claims.render_claims(correctness, large_scale)
+    claims = generate_parity_claims.render_claims(correctness, large_scale, real_strategy)
 
     for pin in correctness["frameworks"].values():
         assert pin["version"] in claims
         assert pin["source"] in claims
         assert f"`{pin['profile']}`" in claims
-    assert "15/15 exact" in claims
-    assert "225,844 trades" in claims
-    assert "No large-scale claim is published for Backtrader" in claims
+    assert "16/16 exact" in claims
+    assert "synthetic stress workload contains 250 assets" in claims
+    assert "6/8 supported pairs pass" in claims
+    for record in large_scale["frameworks"]:
+        target = record["target"]
+        checks = generate_parity_claims._comparison_checks(record)
+        assert f"`{target['profile']}`" in claims
+        assert target["version"] in claims
+        assert f"{checks['fills']['expected_count']:,}" in claims
+        assert f"{checks['trades']['expected_count']:,}" in claims
+    assert "validation/LARGE_SCALE_RESULTS.json" in claims
+    assert "No large-scale claim is published" not in claims
 
     failed_correctness = copy.deepcopy(correctness)
     failed_record = next(
@@ -51,5 +91,7 @@ def test_claims_pin_every_advertised_framework_and_expose_failures() -> None:
         if record["framework"] == "zipline" and record["scenario_id"] == "15"
     )
     failed_record["status"] = "comparison_failure"
-    failed_claims = generate_parity_claims.render_claims(failed_correctness, large_scale)
-    assert "14/15 pass; blocked by scenario 15" in failed_claims
+    failed_claims = generate_parity_claims.render_claims(
+        failed_correctness, large_scale, real_strategy
+    )
+    assert "15/16 pass; blocked by scenario 15" in failed_claims
diff --git a/tests/contracts/test_profile_parity_basics.py b/tests/contracts/test_profile_parity_basics.py
index c851182f..df65c194 100644
--- a/tests/contracts/test_profile_parity_basics.py
+++ b/tests/contracts/test_profile_parity_basics.py
@@ -7,8 +7,9 @@
 from ml4t.backtest.config import BacktestConfig
 from ml4t.backtest.engine import run_backtest
 from ml4t.backtest.profiles import list_profiles
+from ml4t.backtest.risk.position.dynamic import TrailingStop
 from ml4t.backtest.strategy import Strategy
-from ml4t.backtest.types import StopLevelBasis
+from ml4t.backtest.types import OrderSide, StopLevelBasis
 
 
 def _prices() -> pl.DataFrame:
@@ -40,6 +41,100 @@ def on_data(self, timestamp, data, context, broker) -> None:
             self.done = True
 
 
+class _BuyOnMissingClose(Strategy):
+    def on_data(self, timestamp, data, context, broker) -> None:
+        if timestamp.day == 2:
+            broker.submit_order("AAPL", 1.0)
+
+
+class _ExerciseVectorbtShortCollateral(Strategy):
+    def on_data(self, timestamp, data, context, broker) -> None:
+        if timestamp.day == 1:
+            broker.submit_order("B", 5.0, side=OrderSide.SELL)
+        elif timestamp.day == 2:
+            broker.submit_order("A", 5.0)
+            broker.submit_order("B", 5.0, side=OrderSide.SELL)
+
+
+def _flat_two_asset_prices() -> pl.DataFrame:
+    return pl.DataFrame(
+        [
+            {
+                "timestamp": datetime(2024, 1, day),
+                "asset": asset,
+                "open": 100.0,
+                "high": 100.0,
+                "low": 100.0,
+                "close": 100.0,
+                "volume": 1_000_000.0,
+            }
+            for day in (1, 2, 3)
+            for asset in ("A", "B")
+        ]
+    )
+
+
+def _prices_with_missing_middle() -> pl.DataFrame:
+    return (
+        _prices()
+        .vstack(
+            pl.DataFrame(
+                {
+                    "timestamp": [datetime(2024, 1, 3)],
+                    "asset": ["AAPL"],
+                    "open": [120.0],
+                    "high": [120.0],
+                    "low": [120.0],
+                    "close": [120.0],
+                    "volume": [1_000_000.0],
+                }
+            )
+        )
+        .with_columns(
+            pl.when(pl.col("timestamp") == datetime(2024, 1, 2))
+            .then(float("nan"))
+            .otherwise(pl.col(column))
+            .alias(column)
+            for column in ("open", "high", "low", "close")
+        )
+    )
+
+
+class _BuyWithTrailingStop(Strategy):
+    def __init__(self) -> None:
+        self.done = False
+
+    def on_data(self, timestamp, data, context, broker) -> None:
+        if not self.done:
+            broker.set_position_rules(TrailingStop(pct=0.1))
+            broker.submit_order("AAPL", 1.0)
+            self.done = True
+
+
+def _backtrader_trailing_prices() -> pl.DataFrame:
+    start = datetime(2024, 1, 1)
+    rows = []
+    bars = [
+        (100.0, 101.0, 99.0, 100.0),
+        (110.0, 111.0, 94.0, 95.0),
+        (95.0, 96.0, 85.0, 90.0),
+        (100.0, 101.0, 99.0, 100.0),
+    ]
+    for offset, (open_, high, low, close) in enumerate(bars):
+        rows.append(
+            {
+                "timestamp": start + timedelta(days=offset),
+                "asset": "AAPL",
+                "open": open_,
+                "high": high,
+                "low": low,
+                "close": close,
+                "volume": 1_000_000.0,
+            }
+        )
+    return pl.DataFrame(rows)
+
+
 def test_profile_registry_has_expected_core_profiles() -> None:
     assert list_profiles() == ["backtrader", "default", "lean", "realistic", "vectorbt", "zipline"]
 
@@ -60,10 +155,51 @@ def test_profiles_enforce_expected_entry_timing_contract() -> None:
     vbt = run_backtest(prices=_prices(), strategy=_BuyOnce(), config="vectorbt")
     bt = run_backtest(prices=_prices(), strategy=_BuyOnce(), config="backtrader")
     zl = run_backtest(prices=_prices(), strategy=_BuyOnce(), config="zipline")
+    lean = run_backtest(prices=_prices(), strategy=_BuyOnce(), config="lean")
 
     assert vbt.trades[0].entry_price == 101.0  # same-bar close
-    assert 110.0 < bt.trades[0].entry_price < 111.0  # next-bar open with default slippage
-    assert 110.0 < zl.trades[0].entry_price < 111.0  # next-bar open with volume slippage
+    assert bt.trades[0].entry_price == 110.0  # next-bar open with zero default slippage
+    assert zl.trades[0].entry_price == 110.0  # configured next-bar open with zero slippage
+    assert lean.trades[0].entry_price == 110.0  # DefaultBrokerageModel has null slippage
+
+
+def test_vectorbt_profile_drops_signal_order_with_missing_close() -> None:
+    result = run_backtest(
+        prices=_prices_with_missing_middle(),
+        strategy=_BuyOnMissingClose(),
+        config="vectorbt",
+    )
+
+    assert result.fills == []
+    assert len(result.rejected_orders) == 1
+    assert result.rejected_orders[0].rejection_code == "price_unavailable"
+
+
+def test_vectorbt_strict_locks_short_collateral_from_new_exposure() -> None:
+    config = BacktestConfig.from_preset("vectorbt_strict")
+    config.initial_cash = 1_000.0
+
+    result = run_backtest(
+        prices=_flat_two_asset_prices(),
+        strategy=_ExerciseVectorbtShortCollateral(),
+        config=config,
+    )
+
+    assert [(fill.asset, fill.quantity, fill.side.value) for fill in result.fills] == [
+        ("B", 5.0, "sell"),
+        ("A", 5.0, "buy"),
+    ]
+
+
+def test_zipline_profile_defers_pending_order_across_stale_bar() -> None:
+    result = run_backtest(
+        prices=_prices_with_missing_middle(),
+        strategy=_BuyOnce(),
+        config="zipline",
+    )
+
+    assert result.fills[0].timestamp == datetime(2024, 1, 3)
+    assert result.fills[0].price == 120.0
 
 
 def test_backtrader_profile_uses_signal_price_stop_basis() -> None:
@@ -71,17 +207,28 @@ def test_backtrader_profile_uses_signal_price_stop_basis() -> None:
     assert cfg.stop_level_basis == StopLevelBasis.SIGNAL_PRICE
 
 
+def test_backtrader_profile_trailing_stop_uses_signal_close_before_fill() -> None:
+    result = run_backtest(
+        prices=_backtrader_trailing_prices(),
+        strategy=_BuyWithTrailingStop(),
+        config="backtrader",
+    )
+
+    assert result.trades[0].entry_price == 110.0
+    assert result.trades[0].exit_price == 90.0
+
+
 def test_backtrader_profile_parity_order_knobs() -> None:
     cfg = BacktestConfig.from_preset("backtrader")
-    assert cfg.rebalance_headroom_pct == 0.998
+    assert cfg.rebalance_headroom_pct == 1.0
     assert cfg.missing_price_policy.value == "use_last"
-    assert cfg.late_asset_policy.value == "require_history"
-    assert cfg.late_asset_min_bars == 2
+    assert cfg.late_asset_policy.value == "allow"
+    assert cfg.late_asset_min_bars == 1
 
 
 def test_zipline_profile_parity_order_knobs() -> None:
     cfg = BacktestConfig.from_preset("zipline")
-    assert cfg.rebalance_headroom_pct == 0.998
+    assert cfg.rebalance_headroom_pct == 1.0
     assert cfg.missing_price_policy.value == "use_last"
     assert cfg.late_asset_policy.value == "allow"
 
@@ -96,19 +243,26 @@ def test_profile_registry_has_lean_profile() -> None:
     """LEAN profile must be a core profile, not just a strict variant."""
     cfg = BacktestConfig.from_preset("lean")
     assert cfg.preset_name == "lean"
-    assert cfg.fill_ordering.value == "exit_first"
+    assert cfg.execution_mode.value == "next_bar"
+    assert cfg.execution_price.value == "open"
+    assert cfg.fill_ordering.value == "sequential"
     assert cfg.commission_per_share == 0.005
     assert cfg.commission_minimum == 1.0
+    assert cfg.slippage_type.value == "none"
+    assert cfg.initial_margin == 0.5
+    assert cfg.long_maintenance_margin == 0.5
+    assert cfg.short_maintenance_margin == 0.5
+    assert cfg.rebalance_headroom_pct == 0.9975
 
 
 def test_lean_profile_is_independent_of_backtrader() -> None:
     """LEAN profile must remain distinct from Backtrader on execution semantics."""
     lean = BacktestConfig.from_preset("lean")
     bt = BacktestConfig.from_preset("backtrader")
-    assert lean.fill_ordering.value == "exit_first"
+    assert lean.fill_ordering.value == "sequential"
     assert bt.fill_ordering.value == "fifo"
     assert lean.commission_per_share == 0.005
-    assert bt.commission_rate == 0.001
+    assert bt.commission_rate == 0.0
 
 
 def test_quantconnect_alias_resolves_to_lean() -> None:
diff --git a/tests/contracts/test_python_support_policy.py b/tests/contracts/test_python_support_policy.py
index 3d287166..c62af951 100644
--- a/tests/contracts/test_python_support_policy.py
+++ b/tests/contracts/test_python_support_policy.py
@@ -103,7 +103,7 @@ def test_minimum_dependency_matrix_proves_declared_lower_bounds() -> None:
         "pandas>=2.3.3; python_version < '3.15'",
         "numpy>=2.3.2",
         "PyYAML>=6.0.3",
-        "pandas-market-calendars>=5.2.4",
+        "pandas-market-calendars>=5.4.0",
     }
     specs_dependencies = [
         requirement
@@ -122,4 +122,7 @@ def test_merge_and_release_builds_depend_on_compatibility_gate() -> None:
     assert ci_jobs["compatibility"]["uses"] == "./.github/workflows/compatibility.yml"
     assert "compatibility" in ci_jobs["build"]["needs"]
     assert release_jobs["qualification"]["uses"] == "./.github/workflows/ci.yml"
-    assert release_jobs["publish"]["needs"] == ["ecosystem-qualification", "qualification"]
+    assert set(release_jobs["publish"]["needs"]) >= {
+        "ecosystem-qualification",
+        "qualification",
+    }
diff --git a/tests/contracts/test_real_strategy_applicability.py b/tests/contracts/test_real_strategy_applicability.py
new file mode 100644
index 00000000..20876e03
--- /dev/null
+++ b/tests/contracts/test_real_strategy_applicability.py
@@ -0,0 +1,25 @@
+"""Contracts for the bounded real-strategy framework matrix."""
+
+from __future__ import annotations
+
+import tomllib
+from itertools import product
+from pathlib import Path
+
+
+def test_every_selected_case_framework_pair_has_one_disposition() -> None:
+    path = Path(__file__).parents[2] / "validation" / "real_strategy_applicability.toml"
+    payload = tomllib.loads(path.read_text(encoding="utf-8"))
+    metadata = payload["metadata"]
+    pairs = payload["pair"]
+
+    expected = set(product(metadata["case_studies"], metadata["frameworks"]))
+    actual = {(pair["case_study"], pair["framework"]) for pair in pairs}
+
+    assert len(pairs) == len(actual)
+    assert actual == expected
+    assert {pair["status"] for pair in pairs} == {"required", "unsupported"}
+    assert sum(pair["status"] == "required" for pair in pairs) == 8
+    assert sum(pair["status"] == "unsupported" for pair in pairs) == 7
+    assert all(pair["native_contract"] for pair in pairs)
+    assert all(pair["source"].startswith("https://") for pair in pairs)
diff --git a/tests/contracts/test_real_strategy_corpus.py b/tests/contracts/test_real_strategy_corpus.py
new file mode 100644
index 00000000..b3634f94
--- /dev/null
+++ b/tests/contracts/test_real_strategy_corpus.py
@@ -0,0 +1,207 @@
+"""Contracts for the bounded current real-strategy inventory."""
+
+from __future__ import annotations
+
+import importlib.util
+import json
+import sys
+from pathlib import Path
+
+import polars as pl
+import pytest
+
+
+def _load_module():
+    path = Path(__file__).parents[2] / "validation" / "real_strategy_corpus.py"
+    spec = importlib.util.spec_from_file_location("ml4t_real_strategy_corpus", path)
+    assert spec is not None
+    assert spec.loader is not None
+    module = importlib.util.module_from_spec(spec)
+    sys.modules[spec.name] = module
+    spec.loader.exec_module(module)
+    return module
+
+
+def _artifact_tree(tmp_path: Path, case_id: str = "etfs") -> tuple[Path, dict[str, str]]:
+    artifact_root = tmp_path / "artifacts"
+    run_log = artifact_root / "case_studies" / case_id / "run_log"
+    backtest_hash = "a" * 12
+    prediction_hash = "b" * 12
+    backtest = run_log / "backtest" / backtest_hash
+    prediction = run_log / "predictions" / prediction_hash
+    backtest.mkdir(parents=True)
+    prediction.mkdir(parents=True)
+    (run_log / "registry.db").write_bytes(b"registry")
+    pl.DataFrame({"timestamp": ["2024-01-01"], "symbol": ["SPY"], "y_score": [0.1]}).write_parquet(
+        prediction / "predictions.parquet"
+    )
+    spec = {
+        "backtest_config": {
+            "metadata": {"prediction_hash": prediction_hash},
+            "execution": {"execution_mode": "next_bar"},
+            "commission": {"model": "none"},
+            "slippage": {"model": "none"},
+            "position_sizing": {"share_type": "integer"},
+        },
+        "strategy": {
+            "signal": {"method": "equal_weight_top_k", "top_k": 1},
+            "rebalance": {"mode": "engine", "cadence": "daily_close"},
+        },
+    }
+    (backtest / "spec.json").write_text(json.dumps(spec), encoding="utf-8")
+    for name in (
+        "daily_returns.parquet",
+        "equity.parquet",
+        "fills.parquet",
+        "portfolio_state.parquet",
+        "trades.parquet",
+        "weights.parquet",
+    ):
+        pl.DataFrame({"value": [1.0]}).write_parquet(backtest / name)
+    return artifact_root, {
+        "val_backtest_hash": backtest_hash,
+        "val_prediction_hash": prediction_hash,
+        "val_stage": "signal",
+        "label": "fwd_ret_1d",
+    }
+
+
+def test_case_contract_contains_selected_real_case_studies() -> None:
+    module = _load_module()
+
+    cases = module.load_case_contract()
+
+    assert len(cases) == 3
+    assert {case["id"] for case in cases} == {
+        "cme_futures",
+        "crypto_perps_funding",
+        "etfs",
+    }
+    assert all(case["production_path"] == "event_driven" for case in cases)
+
+
+def test_case_record_retains_predictions_spec_and_outputs(tmp_path: Path) -> None:
+    module = _load_module()
+    artifact_root, lineage = _artifact_tree(tmp_path)
+    case = next(case for case in module.load_case_contract() if case["id"] == "etfs")
+
+    record = module.build_case_record(case, lineage, artifact_root=artifact_root)
+
+    assert record["case_study"] == "etfs"
+    assert record["production_path"] == "event_driven"
+    assert record["inputs"]["predictions.parquet"]["rows"] == 1
+    assert record["backtest_artifacts"]["fills.parquet"]["rows"] == 1
+    assert record["strategy"]["execution"] == {"execution_mode": "next_bar"}
+    assert all("sha256" in value for value in record["backtest_artifacts"].values())
+
+
+def test_case_record_fails_when_required_output_is_missing(tmp_path: Path) -> None:
+    module = _load_module()
+    artifact_root, lineage = _artifact_tree(tmp_path)
+    case = next(case for case in module.load_case_contract() if case["id"] == "etfs")
+    missing = (
+        artifact_root
+        / "case_studies"
+        / "etfs"
+        / "run_log"
+        / "backtest"
+        / lineage["val_backtest_hash"]
+        / "fills.parquet"
+    )
+    missing.unlink()
+
+    with pytest.raises(FileNotFoundError, match="fills.parquet"):
+        module.build_case_record(case, lineage, artifact_root=artifact_root)
+
+
+def test_case_record_detects_prediction_mismatch(tmp_path: Path) -> None:
+    module = _load_module()
+    artifact_root, lineage = _artifact_tree(tmp_path)
+    case = next(case for case in module.load_case_contract() if case["id"] == "etfs")
+    spec_path = (
+        artifact_root
+        / "case_studies"
+        / "etfs"
+        / "run_log"
+        / "backtest"
+        / lineage["val_backtest_hash"]
+        / "spec.json"
+    )
+    spec = json.loads(spec_path.read_text(encoding="utf-8"))
+    spec["backtest_config"]["metadata"]["prediction_hash"] = "wrong"
+    spec_path.write_text(json.dumps(spec), encoding="utf-8")
+
+    with pytest.raises(ValueError, match="does not name selected prediction"):
+        module.build_case_record(case, lineage, artifact_root=artifact_root)
+
+
+def test_content_addressed_bundle_is_reused_and_mutations_change_identity(tmp_path: Path) -> None:
+    module = _load_module()
+    market = pl.DataFrame(
+        {
+            "timestamp": ["2024-01-01", "2024-01-02"],
+            "symbol": ["SPY", "SPY"],
+            "open": [100.0, 101.0],
+            "close": [101.0, 102.0],
+        }
+    )
+    targets = pl.DataFrame({"timestamp": ["2024-01-01"], "symbol": ["SPY"], "weight": [1.0]})
+    kwargs = {
+        "case_id": "etfs",
+        "selection": {"val_backtest_hash": "a" * 12},
+        "source_prediction_sha256": "b" * 64,
+        "spec": {"strategy": {"rebalance": {"mode": "engine"}}},
+        "market": market,
+        "targets": targets,
+        "output_root": tmp_path,
+    }
+
+    first = module.write_bundle(**kwargs)
+    second = module.write_bundle(**kwargs)
+    changed = module.write_bundle(**{**kwargs, "targets": targets.with_columns(weight=0.5)})
+
+    assert first == second
+    assert first["bundle_sha256"] != changed["bundle_sha256"]
+    assert (tmp_path / "etfs" / first["bundle_sha256"] / "manifest.json").is_file()
+
+
+def test_funding_is_limited_to_timestamps_presented_by_market() -> None:
+    module = _load_module()
+    market = pl.DataFrame(
+        {
+            "timestamp": ["2024-01-01T08:00:00", "2024-01-03T08:00:00"],
+            "symbol": ["BTCUSDT", "BTCUSDT"],
+        }
+    ).with_columns(pl.col("timestamp").str.to_datetime())
+    funding = pl.DataFrame(
+        {
+            "timestamp": [
+                "2024-01-01T08:00:00",
+                "2024-01-02T08:00:00",
+                "2024-01-03T08:00:00",
+            ],
+            "symbol": ["BTCUSDT", "BTCUSDT", "ETHUSDT"],
+            "funding_rate": [0.0001, 0.0002, -0.0001],
+        }
+    ).with_columns(pl.col("timestamp").str.to_datetime(time_unit="ms"))
+
+    aligned = module.align_funding_to_market_events(funding, market)
+
+    assert aligned["timestamp"].to_list() == market["timestamp"].to_list()
+    assert aligned["symbol"].to_list() == ["BTCUSDT", "ETHUSDT"]
+
+
+def test_targets_are_limited_to_production_engine_schedule() -> None:
+    module = _load_module()
+    targets = pl.DataFrame(
+        {
+            "timestamp": ["2024-01-01", "2024-01-02", "2024-01-03"],
+            "symbol": ["SPY", "SPY", "QQQ"],
+            "weight": [1.0, 0.5, 1.0],
+        }
+    ).with_columns(pl.col("timestamp").str.to_datetime())
+    schedule = pl.Series("timestamp", ["2024-01-01", "2024-01-03"]).str.to_datetime(time_unit="ms")
+
+    aligned = module.align_targets_to_engine_schedule(targets, schedule)
+
+    assert aligned["symbol"].to_list() == ["SPY", "QQQ"]
diff --git a/tests/contracts/test_real_strategy_runner.py b/tests/contracts/test_real_strategy_runner.py
new file mode 100644
index 00000000..80d439ba
--- /dev/null
+++ b/tests/contracts/test_real_strategy_runner.py
@@ -0,0 +1,150 @@
+"""Behavior contracts for the frozen real-strategy ML4T runner."""
+
+from __future__ import annotations
+
+import importlib.util
+from datetime import UTC, datetime
+from pathlib import Path
+from types import SimpleNamespace
+
+import polars as pl
+
+
+def _load_runner():
+    path = Path(__file__).parents[2] / "validation" / "real_strategy_runner.py"
+    spec = importlib.util.spec_from_file_location("ml4t_real_strategy_runner", path)
+    assert spec is not None and spec.loader is not None
+    module = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(module)
+    return module
+
+
+def _load_evidence():
+    path = Path(__file__).parents[2] / "validation" / "real_strategy_evidence.py"
+    spec = importlib.util.spec_from_file_location("ml4t_real_strategy_evidence", path)
+    assert spec is not None and spec.loader is not None
+    module = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(module)
+    return module
+
+
+def _load_benchmark():
+    path = Path(__file__).parents[2] / "validation" / "real_strategy_benchmark.py"
+    spec = importlib.util.spec_from_file_location("ml4t_real_strategy_benchmark", path)
+    assert spec is not None and spec.loader is not None
+    module = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(module)
+    return module
+
+
+class _Broker:
+    def __init__(self) -> None:
+        self.cash = 1_000.0
+        self.positions = {"PERP": SimpleNamespace(quantity=2.0, multiplier=3.0)}
+
+    @staticmethod
+    def get_mark_price(_symbol: str, *, quantity: float) -> float:
+        assert quantity == 2.0
+        return 10.0
+
+
+def test_lean_funding_schedule_skips_entry_boundary_then_settles() -> None:
+    runner = _load_runner()
+    funding = pl.DataFrame(
+        {
+            "symbol": ["PERP", "PERP"],
+            "timestamp": [
+                datetime(2024, 1, 1, 8, tzinfo=UTC),
+                datetime(2024, 1, 1, 16, tzinfo=UTC),
+            ],
+            "funding_rate": [0.01, 0.02],
+        }
+    )
+    ledger = runner.FundingSettlementLedger(funding, skip_first_after_entry=True)
+    broker = _Broker()
+
+    ledger.settle(datetime(2024, 1, 1, 8, tzinfo=UTC), broker)
+    assert broker.cash == 1_000.0
+
+    ledger.settle(datetime(2024, 1, 1, 16, tzinfo=UTC), broker)
+    assert broker.cash == 998.8
+    assert ledger.metrics() == {
+        "funding_pnl": -1.2,
+        "funding_events": 1,
+        "funding_settlements": 2,
+    }
+
+
+def test_lean_funding_schedule_observes_flat_positions_between_settlements() -> None:
+    runner = _load_runner()
+    funding = pl.DataFrame(
+        {
+            "symbol": ["PERP", "PERP"],
+            "timestamp": [
+                datetime(2024, 1, 1, 8, tzinfo=UTC),
+                datetime(2024, 1, 1, 16, tzinfo=UTC),
+            ],
+            "funding_rate": [0.01, 0.02],
+        }
+    )
+    ledger = runner.FundingSettlementLedger(funding, skip_first_after_entry=True)
+    broker = _Broker()
+
+    ledger.settle(datetime(2024, 1, 1, 8, tzinfo=UTC), broker)
+    broker.positions["PERP"].quantity = 0.0
+    ledger.settle(datetime(2024, 1, 1, 12, tzinfo=UTC), broker)
+    broker.positions["PERP"].quantity = 2.0
+    ledger.settle(datetime(2024, 1, 1, 16, tzinfo=UTC), broker)
+
+    assert broker.cash == 1_000.0
+    assert ledger.metrics()["funding_events"] == 0
+
+
+def test_lean_comparison_preserves_margin_account_and_disables_equity_costs() -> None:
+    runner = _load_runner()
+    source = {
+        "account": {"allow_short_selling": True, "allow_leverage": False},
+        "cash": {"initial": 125_000.0},
+        "calendar": {"calendar": "NYSE", "data_frequency": "daily"},
+        "feed": {"calendar": "NYSE", "data_frequency": "daily"},
+        "commission": {"model": "percentage", "rate": 0.001},
+        "slippage": {"model": "percentage", "rate": 0.001},
+        "orders": {"rebalance_headroom_pct": 0.99},
+        "metadata": {},
+    }
+
+    config = runner._comparison_config({"backtest_config": source}, "lean")
+
+    assert config.allow_leverage is True
+    assert config.commission_rate == 0.0
+    assert config.slippage_rate == 0.0
+    assert config.rebalance_headroom_pct == 1.0
+
+
+def test_real_strategy_comparator_detects_one_quantum_mutation() -> None:
+    evidence = _load_evidence()
+    framework = [{"timestamp": "2024-01-01", "price": "10.00000000"}]
+    mutated = [{"timestamp": "2024-01-01", "price": "10.00000001"}]
+
+    result = evidence.compare_records(framework, mutated, numeric_fields=("price",))
+
+    assert result["passed"] is False
+    assert result["first_divergence"] == {
+        "kind": "record",
+        "index": 0,
+        "field": "price",
+        "framework": framework[0],
+        "ml4t": mutated[0],
+        "canonical_gap": "0.00000001",
+    }
+
+
+def test_real_strategy_benchmark_interval_is_deterministic() -> None:
+    benchmark = _load_benchmark()
+    values = [float(value) for value in range(1, 11)]
+
+    first = benchmark.bootstrap_median_interval(values, draws=1_000, seed=7)
+    second = benchmark.bootstrap_median_interval(values, draws=1_000, seed=7)
+
+    assert first == second
+    assert first[0] <= 5.5 <= first[1]
diff --git a/tests/contracts/test_release_workflow.py b/tests/contracts/test_release_workflow.py
index 1a7d69a5..f1316344 100644
--- a/tests/contracts/test_release_workflow.py
+++ b/tests/contracts/test_release_workflow.py
@@ -146,9 +146,22 @@ def test_release_reuses_all_ci_gates_and_publishes_the_exact_candidate() -> None
         "security",
         "coverage",
         "runtime",
-        "contracts",
+        "public-parity",
         "documentation",
     }
+    parity = jobs["public-parity"]
+    assert {entry["framework"] for entry in parity["strategy"]["matrix"]["include"]} == {
+        "vectorbt_oss",
+        "backtrader",
+        "zipline",
+    }
+    parity_commands = "\n".join(step.get("run", "") for step in parity["steps"])
+    assert "validation/build_framework_env.py" in parity_commands
+    assert "validation/native/vectorbt_behavior.py" in parity_commands
+    assert "validation/native/backtrader_behavior.py" in parity_commands
+    assert "validation/native/zipline_behavior.py" in parity_commands
+    assert "validation/run_all_correctness.py" in parity_commands
+    assert "--extra comparison" not in parity_commands
     build_commands = "\n".join(step.get("run", "") for step in jobs["build"]["steps"])
     assert "git rev-parse HEAD" in build_commands
     assert "validation/release_candidate.py create" in build_commands
@@ -157,7 +170,14 @@ def test_release_reuses_all_ci_gates_and_publishes_the_exact_candidate() -> None
         assert f"--gate {gate}=" in build_commands
 
     assert release_jobs["qualification"]["uses"] == "./.github/workflows/ci.yml"
-    assert release_jobs["publish"]["needs"] == ["ecosystem-qualification", "qualification"]
+    assert release_jobs["private-comparisons"]["uses"] == (
+        "./.github/workflows/private-comparisons.yml"
+    )
+    assert release_jobs["publish"]["needs"] == [
+        "ecosystem-qualification",
+        "private-comparisons",
+        "qualification",
+    ]
     assert release_jobs["publish"]["permissions"] == {
         "contents": "read",
         "id-token": "write",
@@ -172,3 +192,22 @@ def test_release_reuses_all_ci_gates_and_publishes_the_exact_candidate() -> None
     assert release_jobs["verify-pypi"]["needs"] == "publish"
     assert release_jobs["github-release"]["needs"] == "verify-pypi"
     assert "if" not in release_jobs["github-release"]
+
+
+def test_private_comparison_workflow_pins_and_retains_evidence() -> None:
+    workflow = _workflow("private-comparisons.yml")
+    jobs = workflow["jobs"]
+
+    assert workflow["on"]["workflow_call"]["secrets"]["VECTORBT_PRO_DEPLOY_KEY"]["required"]
+    pro_commands = "\n".join(step.get("run", "") for step in jobs["vectorbt-pro"]["steps"])
+    assert "validation/build_framework_env.py" in pro_commands
+    assert "validation/native/vectorbt_behavior.py" in pro_commands
+    assert "validation/run_all_correctness.py" in pro_commands
+    assert "--framework vectorbt_pro" in pro_commands
+    lean_commands = "\n".join(step.get("run", "") for step in jobs["lean"]["steps"])
+    assert "--framework lean" in lean_commands
+    assert "validation/native/lean_behavior.py" in lean_commands
+    assert "validation/run_lean_case_studies.py" in lean_commands
+    assert "lean-native.json" in str(jobs["lean"])
+    assert "lean-case-studies.json" in str(jobs["lean"])
+    assert "run_all_correctness.py" not in lean_commands
diff --git a/tests/contracts/test_security_policy.py b/tests/contracts/test_security_policy.py
index 21e7055e..62271734 100644
--- a/tests/contracts/test_security_policy.py
+++ b/tests/contracts/test_security_policy.py
@@ -161,7 +161,10 @@ def test_ci_and_release_both_require_the_evidence_retaining_security_workflow()
     assert ci_jobs["security"]["uses"] == "./.github/workflows/security.yml"
     assert "security" in ci_jobs["build"]["needs"]
     assert release_jobs["qualification"]["uses"] == "./.github/workflows/ci.yml"
-    assert release_jobs["publish"]["needs"] == ["ecosystem-qualification", "qualification"]
+    assert set(release_jobs["publish"]["needs"]) >= {
+        "ecosystem-qualification",
+        "qualification",
+    }
 
     scan = security["jobs"]["scan"]
     commands = "\n".join(step.get("run", "") for step in scan["steps"])
diff --git a/tests/contracts/test_static_analysis_policy.py b/tests/contracts/test_static_analysis_policy.py
index 17cda8e8..e886b39e 100644
--- a/tests/contracts/test_static_analysis_policy.py
+++ b/tests/contracts/test_static_analysis_policy.py
@@ -83,7 +83,7 @@ def test_ci_checks_every_release_validation_script() -> None:
         )
     }
     excluded_validation_scripts = {
-        # Legacy benchmark entry points run only in their named framework environments.
+        # Compatibility benchmark entry points route to the checked retained harness.
         "validation/backtrader/benchmark_performance.py",
         "validation/backtrader/scale_validation.py",
         "validation/vectorbt_pro/benchmark_performance.py",
@@ -93,7 +93,8 @@ def test_ci_checks_every_release_validation_script() -> None:
         "validation/lean/workspace/chapter16_etfs/main.py",
         "validation/lean/workspace/chapter16_sp500_equity_option_analytics/main.py",
         "validation/lean/workspace/chapter16_us_equities_panel/main.py",
-        # Legacy manual orchestrators require optional framework environments.
+        "validation/native/lean_project/main.py",
+        # Manual orchestrators require optional framework environments.
         "validation/benchmark_suite.py",
         "validation/run_all_benchmarks.py",
         "validation/run_full_validation.py",
@@ -103,6 +104,9 @@ def test_ci_checks_every_release_validation_script() -> None:
         "validation/frameworks/vectorbt_oss.py",
         "validation/frameworks/vectorbt_pro.py",
         "validation/frameworks/zipline.py",
+        "validation/real_strategy_backtrader.py",
+        "validation/real_strategy_vectorbt.py",
+        "validation/real_strategy_zipline.py",
     }
     candidate_files = subprocess.run(
         [
diff --git a/tests/contracts/test_validation_cli_outcomes.py b/tests/contracts/test_validation_cli_outcomes.py
index 70337b90..30dd1b24 100644
--- a/tests/contracts/test_validation_cli_outcomes.py
+++ b/tests/contracts/test_validation_cli_outcomes.py
@@ -112,6 +112,7 @@ def test_isolated_timeout_is_retained(
 
     assert record.status is ValidationStatus.TIMEOUT
     assert "7" in (record.detail or "")
+    assert record.duration_seconds is not None
 
 
 def test_isolated_subprocess_failure_without_record_is_retained(
@@ -194,7 +195,7 @@ def test_release_gate_fails_for_every_non_optional_nonpass_status() -> None:
     assert run_all_correctness.release_gate_passed(records[:1]) is False
 
 
-def test_unavailable_vectorbt_pro_matrix_cannot_report_sixteen_passes(
+def test_unavailable_vectorbt_pro_matrix_cannot_report_all_passes(
     monkeypatch: pytest.MonkeyPatch,
 ) -> None:
     def unavailable(framework: str, scenario_id: str, **_kwargs) -> ValidationRecord:
@@ -211,9 +212,9 @@ def unavailable(framework: str, scenario_id: str, **_kwargs) -> ValidationRecord
     records = run_all_correctness.run_all_validations(frameworks=["vectorbt_pro"])
     summary = run_all_correctness.summarize(records)
 
-    assert len(records) == 16
+    assert len(records) == 17
     assert summary["pass"] == 0
-    assert summary["unavailable"] == 16
+    assert summary["unavailable"] == 17
     assert run_all_correctness.release_gate_passed(records) is False
 
 
@@ -239,4 +240,69 @@ def test_report_retains_framework_pins(tmp_path: Path) -> None:
     run_all_correctness.write_report(report_path, records)
 
     report = json.loads(report_path.read_text(encoding="utf-8"))
+    assert report["schema_version"] == 3
     assert report["frameworks"] == run_all_correctness.FRAMEWORK_PINS
+
+
+def _matrix_records(framework: str) -> list[ValidationRecord]:
+    return [
+        ValidationRecord(
+            framework,
+            scenario_id,
+            scenario.name,
+            (
+                ValidationStatus.PASS
+                if framework in scenario.supported_frameworks
+                else ValidationStatus.UNSUPPORTED
+            ),
+            framework in scenario.supported_frameworks,
+        )
+        for scenario_id, scenario in run_all_correctness.SCENARIOS.items()
+    ]
+
+
+def test_complete_public_matrices_match_declared_counts() -> None:
+    frameworks = ["vectorbt_oss", "backtrader", "zipline"]
+    records = [record for framework in frameworks for record in _matrix_records(framework)]
+
+    failures = run_all_correctness.matrix_coverage_failures(
+        records,
+        frameworks,
+        list(run_all_correctness.SCENARIOS),
+    )
+
+    assert failures == []
+
+
+def test_matrix_coverage_rejects_an_omitted_pair() -> None:
+    records = _matrix_records("backtrader")[:-1]
+
+    failures = run_all_correctness.matrix_coverage_failures(
+        records,
+        ["backtrader"],
+        list(run_all_correctness.SCENARIOS),
+    )
+
+    assert any("Missing matrix pairs" in failure for failure in failures)
+    assert any("required count differs" in failure for failure in failures)
+
+
+def test_matrix_coverage_rejects_a_misclassified_pair() -> None:
+    records = _matrix_records("vectorbt_oss")
+    unsupported = next(record for record in records if not record.required)
+    records[records.index(unsupported)] = ValidationRecord(
+        unsupported.framework,
+        unsupported.scenario_id,
+        unsupported.scenario_name,
+        ValidationStatus.PASS,
+        True,
+    )
+
+    failures = run_all_correctness.matrix_coverage_failures(
+        records,
+        ["vectorbt_oss"],
+        list(run_all_correctness.SCENARIOS),
+    )
+
+    assert any("required count differs" in failure for failure in failures)
+    assert any("unsupported count differs" in failure for failure in failures)
diff --git a/tests/contracts/test_validation_scenarios.py b/tests/contracts/test_validation_scenarios.py
index 1090cb3f..d9c455fc 100644
--- a/tests/contracts/test_validation_scenarios.py
+++ b/tests/contracts/test_validation_scenarios.py
@@ -1,12 +1,12 @@
 """Validation scenarios bridged into pytest CI.
 
-Runs the 16 cross-framework validation scenarios through ml4t only
+Runs the cross-framework validation scenarios through ml4t only
 (no external framework venvs required) and checks:
 1. Each scenario runs without error and produces trades
 2. Each scenario passes all accounting invariants
 3. Smoke: final value is positive
 
-This does NOT compare against external frameworks — that's the separate
+This does NOT compare against external frameworks; that is the separate
 validation suite. This ensures ml4t scenarios don't regress.
 """
 
@@ -28,6 +28,7 @@
 try:
     from common.data_generators import (  # noqa: E402
         generate_bracket_data,
+        generate_high_event_data,
         generate_random_walk,
         generate_rule_combo_data,
         generate_short_signals,
@@ -63,6 +64,7 @@
         "generate_short_trending_data": generate_short_trending_data,
         "generate_rule_combo_data": generate_rule_combo_data,
         "generate_stress_data": generate_stress_data,
+        "generate_high_event_data": generate_high_event_data,
     }
 
 
@@ -212,7 +214,7 @@ def on_data(self, timestamp, data, context, broker):
     return engine.run(), config
 
 
-# Parameterize over all 16 scenarios
+# Parameterize over all scenarios
 _SCENARIO_PARAMS = list(SCENARIOS.items()) if _HAS_VALIDATION else []
 
 
diff --git a/tests/contracts/test_vectorbt_native_evidence.py b/tests/contracts/test_vectorbt_native_evidence.py
new file mode 100644
index 00000000..314a2183
--- /dev/null
+++ b/tests/contracts/test_vectorbt_native_evidence.py
@@ -0,0 +1,62 @@
+"""Contracts for retained framework-native VectorBT evidence."""
+
+from __future__ import annotations
+
+import hashlib
+import json
+from pathlib import Path
+
+_ROOT = Path(__file__).parents[2]
+_ORACLE = _ROOT / "validation/native/vectorbt_behavior.py"
+_EVIDENCE = _ROOT / "validation/native/evidence"
+
+EXPECTED_CHECKS = {
+    "accumulation",
+    "cash_sharing_and_call_sequence",
+    "cash_sharing_short_collateral",
+    "defaults",
+    "explicit_fill_price",
+    "fees_and_slippage",
+    "insufficient_cash_partial_fill",
+    "integer_signal_dtype",
+    "lock_notional_update_arithmetic",
+    "long_signal_conflict",
+    "missing_order_price",
+    "record_construction",
+    "short_cash",
+    "signal_timing_and_default_fill",
+    "stop_fill",
+    "target_percent_sizing",
+    "trailing_stop_extreme_and_intrabar_fill",
+}
+
+
+def test_retained_vectorbt_native_evidence_is_complete_and_current() -> None:
+    oracle_sha256 = hashlib.sha256(_ORACLE.read_bytes()).hexdigest()
+    identities = {
+        "vectorbt_oss-1.1.0.json": (
+            "vectorbt_oss",
+            "1.1.0",
+            "259d2d89fe2e7638baf3ca76c394937cd32b656d",
+        ),
+        "vectorbt_pro-2026.6.27.json": (
+            "vectorbt_pro",
+            "2026.6.27",
+            "6e18cf0aa37849cfc20848f40f1d26ecfdc771b4",
+        ),
+    }
+
+    for filename, (framework, version, commit) in identities.items():
+        payload = json.loads((_EVIDENCE / filename).read_text(encoding="utf-8"))
+        assert payload["schema_version"] == 1
+        assert payload["framework"] == framework
+        assert payload["version"] == version
+        assert payload["source_commit"] == commit
+        assert payload["oracle_sha256"] == oracle_sha256
+        assert payload["passed"] is True
+        assert {check["id"] for check in payload["checks"]} == EXPECTED_CHECKS
+        assert all(check["passed"] for check in payload["checks"])
+        assert all(check["actual"] == check["expected"] for check in payload["checks"])
+        for location in payload["source_locations"].values():
+            assert commit in location["source_url"]
+            assert location["path"].endswith("portfolio/base.py")
diff --git a/tests/contracts/test_vectorbt_pro_adapter.py b/tests/contracts/test_vectorbt_pro_adapter.py
index 8a96a40c..e07d9069 100644
--- a/tests/contracts/test_vectorbt_pro_adapter.py
+++ b/tests/contracts/test_vectorbt_pro_adapter.py
@@ -34,8 +34,8 @@ def _load_adapter():
 def test_supported_vectorbt_pro_version_is_explicit() -> None:
     adapter = _load_adapter()
 
-    assert adapter.SUPPORTED_VECTORBT_PRO_VERSION == "2025.12.31"
-    adapter._require_supported_version("2025.12.31")
+    assert adapter.SUPPORTED_VECTORBT_PRO_VERSION == "2026.6.27"
+    adapter._require_supported_version("2026.6.27")
 
 
 def test_unsupported_vectorbt_pro_version_fails_precisely() -> None:
@@ -43,7 +43,7 @@ def test_unsupported_vectorbt_pro_version_fails_precisely() -> None:
 
     with pytest.raises(
         RuntimeError,
-        match=r"requires version 2025\.12\.31, found 2026\.1\.1",
+        match=r"requires version 2026\.6\.27, found 2026\.1\.1",
     ):
         adapter._require_supported_version("2026.1.1")
 
diff --git a/tests/contracts/test_zipline_native_evidence.py b/tests/contracts/test_zipline_native_evidence.py
new file mode 100644
index 00000000..f3a00f91
--- /dev/null
+++ b/tests/contracts/test_zipline_native_evidence.py
@@ -0,0 +1,66 @@
+"""Contracts for retained native and configured Zipline evidence."""
+
+from __future__ import annotations
+
+import hashlib
+import json
+import sys
+from pathlib import Path
+
+_ROOT = Path(__file__).parents[2]
+_VALIDATION = _ROOT / "validation"
+if str(_VALIDATION) not in sys.path:
+    sys.path.insert(0, str(_VALIDATION))
+
+from common.provenance import comparison_protocol_metadata  # noqa: E402
+from scenarios.definitions import SCENARIOS  # noqa: E402
+
+_ORACLE = _ROOT / "validation/native/zipline_behavior.py"
+_EVIDENCE = _ROOT / "validation/native/evidence/zipline-3.1.1.json"
+
+EXPECTED_CHECKS = {
+    "cash_and_short_proceeds",
+    "configured_next_bar_open_fill",
+    "default_next_bar_close_fill",
+    "defaults",
+    "explicit_minimum_commission",
+    "final_bar_market_order",
+    "integer_target_percent",
+    "missing_bar",
+    "session_calendar",
+    "submission_sequence",
+    "target_percent_snapshot",
+    "transaction_records_not_native_trades",
+    "volume_share_partial_fills",
+}
+
+
+def test_retained_zipline_native_evidence_is_complete_and_current() -> None:
+    payload = json.loads(_EVIDENCE.read_text(encoding="utf-8"))
+
+    assert payload["schema_version"] == 1
+    assert payload["framework"] == "zipline"
+    assert payload["package"] == "zipline-reloaded"
+    assert payload["version"] == "3.1.1"
+    assert payload["source_commit"] == "09885a2ebc7567d40942c891b3879dc03c745070"
+    assert payload["artifact"] == "zipline_reloaded-3.1.1.tar.gz"
+    assert payload["artifact_sha256"] == (
+        "4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f"
+    )
+    assert payload["oracle_sha256"] == hashlib.sha256(_ORACLE.read_bytes()).hexdigest()
+    assert payload["passed"] is True
+    assert {check["id"] for check in payload["checks"]} == EXPECTED_CHECKS
+    assert all(check["passed"] for check in payload["checks"])
+    assert all(check["actual"] == check["expected"] for check in payload["checks"])
+    for location in payload["source_locations"].values():
+        assert location["artifact"] == payload["artifact"]
+        assert location["artifact_sha256"] == payload["artifact_sha256"]
+        assert payload["source_commit"] in location["source_url"]
+
+
+def test_zipline_risk_scenarios_are_labeled_as_adapter_emulation() -> None:
+    for scenario in SCENARIOS.values():
+        protocol = comparison_protocol_metadata(scenario, "zipline")
+        expected = "adapter_emulated_daily_ohlc" if scenario.risk_rules else "none"
+        assert protocol["risk_rules"] == expected
+        assert protocol["trade_records"] == "adapter_reconstructed_from_native_transactions"
diff --git a/tests/execution/test_rebalancer.py b/tests/execution/test_rebalancer.py
index 8990c828..639f3bff 100644
--- a/tests/execution/test_rebalancer.py
+++ b/tests/execution/test_rebalancer.py
@@ -9,7 +9,11 @@
     Broker,
     OrderSide,
 )
-from ml4t.backtest.config import ExecutionPrice, RebalanceMode
+from ml4t.backtest.config import (
+    ExecutionPrice,
+    RebalanceMode,
+    ShareRounding,
+)
 from ml4t.backtest.execution.rebalancer import RebalanceConfig, TargetWeightExecutor
 from ml4t.backtest.execution.schedule import RebalanceSchedule, resolve_rebalance_timestamps
 from ml4t.backtest.models import NoCommission, NoSlippage
@@ -266,6 +270,19 @@ def test_fractional_shares(self, broker, sample_data):
         # Should be approximately 66.67
         assert 66.6 < orders[0].quantity < 66.7
 
+    def test_truncation_matches_target_percent_brokers(self, broker, sample_data):
+        executor = TargetWeightExecutor(
+            config=RebalanceConfig(
+                allow_fractional=False,
+                share_rounding=ShareRounding.TRUNCATE,
+            )
+        )
+
+        orders = executor.execute({"AAPL": 0.1}, sample_data, broker)
+
+        assert len(orders) == 1
+        assert orders[0].quantity == 66
+
     def test_lot_rounding(self, broker, sample_data):
         """Test rounding to lot sizes."""
         executor = TargetWeightExecutor(config=RebalanceConfig(round_lots=True, lot_size=100))
diff --git a/tests/test_calendar.py b/tests/test_calendar.py
index a367ef77..0fbe411a 100644
--- a/tests/test_calendar.py
+++ b/tests/test_calendar.py
@@ -138,6 +138,10 @@ def test_is_trading_day_holiday(self):
         assert is_trading_day("NYSE", date(2024, 7, 4)) is False  # Independence Day
         assert is_trading_day("NYSE", date(2024, 12, 25)) is False  # Christmas
 
+    def test_cme_good_friday_early_close_is_a_session(self):
+        """CME equity futures traded an abbreviated session on Good Friday 2021."""
+        assert is_trading_day("CME", date(2021, 4, 2)) is True
+
     def test_is_trading_day_with_string(self):
         """Test with string date input."""
         assert is_trading_day("NYSE", "2024-06-03") is True
diff --git a/tests/test_config_wiring.py b/tests/test_config_wiring.py
index 33994a18..03f8fa4e 100644
--- a/tests/test_config_wiring.py
+++ b/tests/test_config_wiring.py
@@ -25,6 +25,9 @@
     EntryOrderPriority,
     ExecutionPrice,
     FillOrdering,
+    LateAssetPolicy,
+    LockNotionalUpdateMode,
+    MissingPricePolicy,
     ShareType,
     ShortCashPolicy,
     SlippageType,
@@ -42,6 +45,7 @@
     TieredCommission,
     VolumeShareSlippage,
 )
+from ml4t.backtest.profiles import get_profile_config
 from ml4t.backtest.types import OrderSide, Position
 
 # ---------------------------------------------------------------------------
@@ -258,6 +262,132 @@ def test_next_bar_submission_precheck_uses_sequential_shadow_cash(self):
         assert first.status.value != "rejected"
         assert second.status.value == "rejected"
 
+    def test_lean_two_stage_buying_power_validation(self):
+        broker = _make_broker(
+            initial_cash=10_000.0,
+            execution_mode=ExecutionMode.NEXT_BAR,
+            next_bar_submission_precheck=True,
+            next_bar_queue_shadow_validation=True,
+            allow_short_selling=True,
+            allow_leverage=True,
+            initial_margin=0.5,
+            long_maintenance_margin=0.5,
+            short_maintenance_margin=0.5,
+            fill_ordering=FillOrdering.SEQUENTIAL,
+            share_type=ShareType.INTEGER,
+            reject_on_insufficient_cash=True,
+        )
+        broker._update_time(
+            timestamp=datetime(2024, 1, 2),
+            prices={"AAPL": 100.0},
+            opens={"AAPL": 100.0},
+            volumes={"AAPL": 1_000.0},
+            highs={"AAPL": 100.0},
+            lows={"AAPL": 100.0},
+            signals={},
+        )
+
+        first = broker.submit_order("AAPL", 150, OrderSide.BUY)
+        second = broker.submit_order("AAPL", 150, OrderSide.BUY)
+
+        assert first is not None and first.status.value == "pending"
+        assert second is not None and second.status.value == "pending"
+
+        broker._update_time(
+            timestamp=datetime(2024, 1, 3),
+            prices={"AAPL": 110.0},
+            opens={"AAPL": 110.0},
+            volumes={"AAPL": 1_000.0},
+            highs={"AAPL": 110.0},
+            lows={"AAPL": 110.0},
+            signals={},
+        )
+        broker._process_orders(use_open=True)
+
+        assert first.status.value == "filled"
+        assert second.status.value == "rejected"
+        assert second.rejection_code == "insufficient_buying_power"
+        assert broker.get_position("AAPL").quantity == 150.0
+        assert broker.cash == -6_500.0
+
+    def test_backtrader_precheck_rejects_unaffordable_short_cover(self):
+        broker = _make_broker(
+            initial_cash=100.0,
+            execution_mode=ExecutionMode.NEXT_BAR,
+            next_bar_submission_precheck=True,
+            next_bar_simple_cash_check=True,
+            share_type=ShareType.INTEGER,
+            reject_on_insufficient_cash=True,
+        )
+        ts = datetime(2024, 1, 2)
+        _set_prices(broker, {"AAPL": 250.0}, ts=ts)
+        broker.cash = 200.0
+        broker.positions["AAPL"] = Position(
+            asset="AAPL",
+            quantity=-1.0,
+            entry_price=100.0,
+            entry_time=ts,
+            current_price=250.0,
+        )
+
+        order = broker.submit_order("AAPL", 1, OrderSide.BUY)
+
+        assert order is not None
+        assert order.status.value == "rejected"
+        assert order.rejection_code == "insufficient_cash"
+
+    def test_backtrader_gap_reversal_executes_only_the_close_leg(self):
+        broker = _make_broker(
+            initial_cash=100.0,
+            execution_mode=ExecutionMode.NEXT_BAR,
+            next_bar_submission_precheck=True,
+            next_bar_simple_cash_check=True,
+            share_type=ShareType.INTEGER,
+            fill_ordering=FillOrdering.FIFO,
+            reject_on_insufficient_cash=True,
+        )
+        broker._update_time(
+            timestamp=datetime(2024, 1, 1),
+            prices={"AAPL": 100.0},
+            opens={"AAPL": 100.0},
+            volumes={"AAPL": 1_000.0},
+            highs={"AAPL": 100.0},
+            lows={"AAPL": 100.0},
+            signals={},
+        )
+        short_order = broker.submit_order("AAPL", 1, OrderSide.SELL)
+
+        broker._update_time(
+            timestamp=datetime(2024, 1, 2),
+            prices={"AAPL": 90.0},
+            opens={"AAPL": 100.0},
+            volumes={"AAPL": 1_000.0},
+            highs={"AAPL": 100.0},
+            lows={"AAPL": 90.0},
+            signals={},
+        )
+        broker._process_orders(use_open=True)
+        reversal = broker.submit_order("AAPL", 2, OrderSide.BUY)
+
+        broker._update_time(
+            timestamp=datetime(2024, 1, 3),
+            prices={"AAPL": 250.0},
+            opens={"AAPL": 250.0},
+            volumes={"AAPL": 1_000.0},
+            highs={"AAPL": 250.0},
+            lows={"AAPL": 250.0},
+            signals={},
+        )
+        broker._process_orders(use_open=True)
+
+        assert short_order is not None
+        assert reversal is not None
+        assert [fill.quantity for fill in broker.fills] == [1.0, 1.0]
+        assert broker.get_position("AAPL") is None
+        assert broker.cash == -50.0
+        assert reversal.requested_quantity == 2.0
+        assert reversal.filled_quantity == 1.0
+
     def test_margin_submission_precheck_allows_reversal_after_close_proceeds(self):
         broker = _make_broker(
             initial_cash=1_000_000.0,
@@ -398,22 +528,67 @@ def test_credit_proceeds_policy_allows_short_without_full_notional_cash(self):
         assert pos is not None
         assert pos.quantity == -10.0
 
-    def test_vectorbt_strict_profile_sets_lock_notional(self):
+    def test_vectorbt_strict_profile_preserves_native_cash_semantics(self):
         config = BacktestConfig.from_preset("vectorbt_strict")
         assert config.short_cash_policy == ShortCashPolicy.LOCK_NOTIONAL
         assert config.fill_ordering == FillOrdering.FIFO
+        assert config.reject_on_insufficient_cash is True
+        assert config.partial_fills_allowed is True
         assert config.entry_order_priority == EntryOrderPriority.SUBMISSION
+        assert get_profile_config("vectorbt_strict") != get_profile_config("vectorbt")
+
+    def test_vectorbt_oss_strict_uses_combined_order_cash_updates(self):
+        pro = BacktestConfig.from_preset("vectorbt_strict")
+        oss = BacktestConfig.from_preset("vectorbt_oss_strict")
+
+        assert pro.lock_notional_update_mode is LockNotionalUpdateMode.POSITION_LEGS
+        assert oss.lock_notional_update_mode is LockNotionalUpdateMode.COMBINED_ORDER
+
+    def test_lock_notional_update_modes_reproduce_native_cover_arithmetic(self):
+        initial_cash = 800_928.6801081297
+        entry_price = 445.1764349947099
+        short_quantity = 935.6511349828165
+        cover_quantity = 822.3137995772428
+        cover_price = 98.35685542114634
+
+        results = {}
+        for mode in LockNotionalUpdateMode:
+            broker = _make_broker(
+                initial_cash=initial_cash,
+                short_cash_policy=ShortCashPolicy.LOCK_NOTIONAL,
+                lock_notional_update_mode=mode,
+                share_type=ShareType.FRACTIONAL,
+                reject_on_insufficient_cash=True,
+                partial_fills_allowed=True,
+            )
+            _set_prices(broker, {"A": entry_price})
+            broker.submit_order("A", short_quantity, OrderSide.SELL)
+            broker._process_orders()
+            _set_prices(broker, {"A": cover_price}, ts=datetime(2024, 1, 2))
+            broker.submit_order("A", cover_quantity, OrderSide.BUY)
+            broker._process_orders()
+            results[mode] = broker.account._lock_notional_free_cash
+
+        assert results[LockNotionalUpdateMode.POSITION_LEGS] == 1_035_668.0954273958
+        assert results[LockNotionalUpdateMode.COMBINED_ORDER] == 1_035_668.0954273955
 
     def test_zipline_strict_profile_uses_credit(self):
         config = BacktestConfig.from_preset("zipline_strict")
         assert config.short_cash_policy == ShortCashPolicy.CREDIT
         assert config.allow_leverage is False
         assert config.skip_cash_validation is True
+        assert config.fill_ordering == FillOrdering.FIFO
+        assert config.reject_on_insufficient_cash is False
+        assert config.partial_fills_allowed is False
+        assert config.commission_type == CommissionType.NONE
+        assert config.slippage_type == SlippageType.NONE
+        assert get_profile_config("zipline_strict") == get_profile_config("zipline")
 
     def test_backtrader_strict_profile_enables_submission_precheck(self):
         config = BacktestConfig.from_preset("backtrader_strict")
         assert config.next_bar_submission_precheck is True
         assert config.next_bar_simple_cash_check is True
+        assert config.share_rounding.value == "truncate"
 
     def test_lean_profile_uses_margin_next_bar_open(self):
         config = BacktestConfig.from_preset("lean")
@@ -491,6 +666,98 @@ def test_lock_notional_long_to_short_reversal_reuses_long_sale_proceeds(self):
         assert position is not None
         assert position.quantity == -10.0
 
+    def test_lock_notional_partial_cover_releases_proportional_aggregate_basis(self):
+        initial_cash = 100_000.0
+        first_qty = 13.436424411240122
+        second_qty = 84.74337369372327
+        first_price = 152.7549237953228
+        second_price = 51.01380514788434
+        covered = 48.64171682480172
+        cover_price = 73.25
+        broker = _make_broker(
+            initial_cash=initial_cash,
+            allow_short_selling=True,
+            allow_leverage=False,
+            short_cash_policy=ShortCashPolicy.LOCK_NOTIONAL,
+            share_type=ShareType.FRACTIONAL,
+            reject_on_insufficient_cash=True,
+            partial_fills_allowed=True,
+        )
+
+        _set_prices(broker, {"A": first_price})
+        broker.submit_order("A", first_qty, OrderSide.SELL)
+        broker._process_orders()
+        _set_prices(broker, {"A": second_price}, ts=datetime(2024, 1, 2))
+        broker.submit_order("A", second_qty, OrderSide.SELL)
+        broker._process_orders()
+
+        aggregate_basis = first_qty * first_price + second_qty * second_price
+        total_qty = first_qty + second_qty
+        expected_before_cover = initial_cash - first_qty * first_price - second_qty * second_price
+        assert broker.account._lock_notional_short_basis["A"] == aggregate_basis
+        assert broker.account._lock_notional_free_cash == expected_before_cover
+
+        _set_prices(broker, {"A": cover_price}, ts=datetime(2024, 1, 3))
+        broker.submit_order("A", covered, OrderSide.BUY)
+        broker._process_orders()
+
+        released_basis = (covered / total_qty) * aggregate_basis
+        expected_free_cash = expected_before_cover + (
+            released_basis + released_basis - covered * cover_price
+        )
+        remaining_fraction = (total_qty - covered) / total_qty
+        assert broker.account._lock_notional_free_cash == expected_free_cash
+        assert broker.account._lock_notional_short_basis["A"] == (
+            remaining_fraction * aggregate_basis
+        )
+
+    def test_lock_notional_partial_fill_uses_direct_native_cash_quotient(self):
+        initial_cash = 20_697.596345718113
+        price = 680.4559000307344
+        broker = _make_broker(
+            initial_cash=initial_cash,
+            allow_short_selling=True,
+            allow_leverage=False,
+            short_cash_policy=ShortCashPolicy.LOCK_NOTIONAL,
+            share_type=ShareType.FRACTIONAL,
+            reject_on_insufficient_cash=True,
+            partial_fills_allowed=True,
+        )
+        _set_prices(broker, {"A": price})
+
+        broker.submit_order("A", 100.0, OrderSide.SELL)
+        broker._process_orders()
+
+        assert broker.fills[0].quantity == initial_cash / price
+
+    def test_lock_notional_partial_reversal_retains_native_open_leg_quantity(self):
+        initial_cash = 8_837.873808549472
+        short_price = 88.37873808549472
+        reversal_price = 90.0615227583623
+        broker = _make_broker(
+            initial_cash=initial_cash,
+            allow_short_selling=True,
+            allow_leverage=False,
+            short_cash_policy=ShortCashPolicy.LOCK_NOTIONAL,
+            share_type=ShareType.FRACTIONAL,
+            reject_on_insufficient_cash=True,
+            partial_fills_allowed=True,
+        )
+        _set_prices(broker, {"A": short_price})
+        broker.submit_order("A", 100.0, OrderSide.SELL)
+        broker._process_orders()
+
+        _set_prices(broker, {"A": reversal_price}, ts=datetime(2024, 1, 2))
+        broker.submit_order("A", 200.0, OrderSide.BUY)
+        broker._process_orders()
+
+        free_after_cover = initial_cash * 2.0 - 100.0 * reversal_price
+        expected_open_quantity = free_after_cover / reversal_price
+        position = broker.get_position("A")
+        assert position is not None
+        assert position.quantity == expected_open_quantity
+        assert position.quantity != broker.fills[-1].quantity - 100.0
+
 
 # ---------------------------------------------------------------------------
 # partial_fills_allowed
@@ -865,6 +1132,12 @@ def test_backtrader_preset_values(self):
         assert config.share_type == ShareType.INTEGER
         assert config.fill_ordering == FillOrdering.FIFO
         assert config.reject_on_insufficient_cash is True
+        assert config.allow_leverage is False
+        assert config.commission_type == CommissionType.NONE
+        assert config.slippage_type == SlippageType.NONE
+        assert config.missing_price_policy == MissingPricePolicy.USE_LAST
+        assert config.late_asset_policy == LateAssetPolicy.ALLOW
+        assert config.late_asset_min_bars == 1
 
     def test_vectorbt_preset_values(self):
         config = BacktestConfig.from_preset("vectorbt")
@@ -872,6 +1145,7 @@ def test_vectorbt_preset_values(self):
         assert config.fill_ordering == FillOrdering.EXIT_FIRST
         assert config.reject_on_insufficient_cash is False
         assert config.partial_fills_allowed is True
+        assert config.missing_price_policy == MissingPricePolicy.SKIP
 
     def test_realistic_preset_values(self):
         config = BacktestConfig.from_preset("realistic")
@@ -881,9 +1155,17 @@ def test_realistic_preset_values(self):
     def test_lean_preset_values(self):
         config = BacktestConfig.from_preset("lean")
         assert config.share_type == ShareType.INTEGER
-        assert config.fill_ordering == FillOrdering.EXIT_FIRST
+        assert config.fill_ordering == FillOrdering.SEQUENTIAL
+        assert config.rebalance_headroom_pct == 0.9975
+        assert config.slippage_type == SlippageType.NONE
+        assert config.next_bar_submission_precheck is True
         assert config.next_bar_queue_shadow_validation is True
 
+    def test_zipline_preset_does_not_apply_buying_power_validation(self):
+        config = BacktestConfig.from_preset("zipline_strict")
+        assert config.skip_cash_validation is True
+        assert config.next_bar_queue_shadow_validation is False
+
     def test_ibkr_us_stocks_fixed_preset_values(self):
         config = BacktestConfig.from_preset("ibkr_us_stocks_fixed")
         assert config.share_type == ShareType.INTEGER
diff --git a/uv.lock b/uv.lock
index 7c772815..e0ecbd45 100644
--- a/uv.lock
+++ b/uv.lock
@@ -735,7 +735,7 @@ wheels = [
 
 [[package]]
 name = "exchange-calendars"
-version = "4.11.3"
+version = "4.13.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "korean-lunar-calendar" },
@@ -746,9 +746,9 @@ dependencies = [
     { name = "toolz" },
     { name = "tzdata" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/fa/14/a9de4bb3b86ce661d33b9d862562eba6aad2ade629a0a821627604a108b5/exchange_calendars-4.11.3.tar.gz", hash = "sha256:53a8f68f86edaf265b0b20cb3641ce34c4b9205b039b0a50f36fc99d114b77bd", size = 4090661, upload-time = "2025-11-10T14:44:16.009Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/47/73/460b0ece4e7444e3098b7738974c822787e134578d069d3a88b4be17d50a/exchange_calendars-4.13.2.tar.gz", hash = "sha256:a9459425dd64142cd54fbc639847403c7e0c33d60fbc326c94fc1d6bd127f002", size = 4137321, upload-time = "2026-03-10T03:24:38.536Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/e3/dd/b30915627128b388c235ee047ca721a40a4960e8b55ea9fa4a005466774b/exchange_calendars-4.11.3-py3-none-any.whl", hash = "sha256:c40d9f1b50238f578f9f8c772aa895533ab03db4910da43825ca59f7ebd9e82f", size = 209667, upload-time = "2025-11-10T14:44:14.694Z" },
+    { url = "https://files.pythonhosted.org/packages/c8/4c/0469b40057bc9f8d9594dcc6024202626b981ae4b52dfcd304552e8e1c3a/exchange_calendars-4.13.2-py3-none-any.whl", hash = "sha256:fc5a2ad0d61b5c3a6539a3061cd4cbb55c59f4a903455cec7926e4b798919996", size = 213306, upload-time = "2026-03-10T03:24:37.055Z" },
 ]
 
 [[package]]
@@ -1908,7 +1908,7 @@ requires-dist = [
     { name = "numpy", specifier = ">=2.3.2" },
     { name = "pandas", marker = "python_full_version < '3.15'", specifier = ">=2.3.3" },
     { name = "pandas", marker = "python_full_version >= '3.15'", specifier = ">=3.0.5" },
-    { name = "pandas-market-calendars", specifier = ">=5.2.4" },
+    { name = "pandas-market-calendars", specifier = ">=5.4.0" },
     { name = "plotly", marker = "extra == 'all'", specifier = ">=5.15.0" },
     { name = "plotly", marker = "extra == 'viz'", specifier = ">=5.15.0" },
     { name = "polars", specifier = ">=1.36.1" },
@@ -2594,16 +2594,16 @@ wheels = [
 
 [[package]]
 name = "pandas-market-calendars"
-version = "5.2.4"
+version = "5.4.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "exchange-calendars" },
     { name = "pandas", version = "2.3.3", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.15'" },
     { name = "pandas", version = "3.0.5", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.15'" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/ad/86/3f6f1325dbbd948150e683aa9735c34493954b525c1efd453c47beb46f9c/pandas_market_calendars-5.2.4.tar.gz", hash = "sha256:7cbb7de0e1652f08db4d5185f9429486fd3a6e050c4fc8d1f51a5eaad2fabdb0", size = 162701, upload-time = "2026-01-07T12:50:33.48Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/38/4c/98067cb91b37a137389f978f52410975915268d394c09cf941c490565297/pandas_market_calendars-5.4.0.tar.gz", hash = "sha256:b02f3a0e9bcb4b9e82a5060bf260ef0060ccd398f989b5e6f8208f4352967806", size = 175213, upload-time = "2026-05-27T02:42:05.249Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/cc/de/f9940c57937720f07f5cd3acf4b4e1208520e1321ed5576d928121e2dae3/pandas_market_calendars-5.2.4-py3-none-any.whl", hash = "sha256:82998eeaed52a554d88ca98c2ff799c329d72c77630502ced74487a951bb2e86", size = 127819, upload-time = "2026-01-07T12:50:34.614Z" },
+    { url = "https://files.pythonhosted.org/packages/c0/d3/59b999f7f6a1d173572d3e8f8b07ded7e256c691d02b3b5cacb26479895a/pandas_market_calendars-5.4.0-py3-none-any.whl", hash = "sha256:bb2b93b28d496cab173b41c7d120fd5cd9d506b31f3bb0ad3d1d9f2b60d9d9e3", size = 134904, upload-time = "2026-05-27T02:42:06.35Z" },
 ]
 
 [[package]]
diff --git a/validation/CORRECTNESS_RESULTS.json b/validation/CORRECTNESS_RESULTS.json
index d5f14833..d9042112 100644
--- a/validation/CORRECTNESS_RESULTS.json
+++ b/validation/CORRECTNESS_RESULTS.json
@@ -1,40 +1,1394 @@
 {
+  "comparison_policy": {
+    "canonical_quantum": "0.00000001",
+    "meaning": "equality after canonical quantization, not bit identity",
+    "record_order": "significant",
+    "rounding": "ROUND_HALF_EVEN",
+    "surfaces": [
+      "terminal",
+      "closed_trades",
+      "fills"
+    ],
+    "timestamp_domain": "daily session date"
+  },
   "frameworks": {
     "backtrader": {
+      "access": "public",
+      "artifact": "backtrader-1.9.78.123-py2.py3-none-any.whl",
       "display_name": "Backtrader",
+      "immutable_id": "sha256:9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+      "license": "GPL-3.0-or-later",
       "package": "backtrader",
       "profile": "backtrader_strict",
+      "python": "3.12 audit interpreter; upstream package metadata does not declare a range",
       "source": "https://pypi.org/project/backtrader/1.9.78.123/",
       "version": "1.9.78.123"
     },
     "vectorbt_oss": {
+      "access": "public",
+      "artifact": "vectorbt-1.1.0.tar.gz",
+      "commit": "259d2d89fe2e7638baf3ca76c394937cd32b656d",
       "display_name": "VectorBT OSS",
+      "immutable_id": "sha256:67a3b41466234485af70c18d201da105f1ebb2c1d1fac079db20059e45ddc73b",
+      "license": "Apache-2.0 WITH Commons-Clause",
       "package": "vectorbt",
-      "profile": "vectorbt",
-      "source": "https://pypi.org/project/vectorbt/0.28.2/",
-      "version": "0.28.2"
+      "profile": "vectorbt_oss_strict",
+      "python": ">=3.11,<3.15",
+      "source": "https://pypi.org/project/vectorbt/1.1.0/",
+      "version": "1.1.0"
     },
     "vectorbt_pro": {
-      "commit": "1305a1e1974325db9382eaeacc6452e9b075ca71",
+      "access": "licensed",
+      "commit": "6e18cf0aa37849cfc20848f40f1d26ecfdc771b4",
       "display_name": "VectorBT Pro",
+      "immutable_id": "git:6e18cf0aa37849cfc20848f40f1d26ecfdc771b4",
+      "license": "Proprietary",
       "package": "vectorbtpro",
       "profile": "vectorbt_strict",
+      "python": ">=3.11",
       "source": "https://github.com/polakowo/vectorbt.pro",
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+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
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+        "python": {
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+          "version": "3.12.11"
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+          "framework_closed_trades": 10,
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+          "ml4t_closed_trades": 10,
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+          "ml4t_intents": 20,
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+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "02",
@@ -51,8 +2726,317 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 1,
+            "canonical_quantum": "1",
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+            "message": "VectorBT Pro=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
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+            "passed": true
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+          {
+            "actual": 99500.0,
+            "canonical_quantum": "0.00000001",
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+            "expected": 99500.0,
+            "message": "VectorBT Pro=$99,500.0000000000, ML4T=$99,500.0000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
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+          {
+            "actual": -500.0,
+            "canonical_quantum": "0.00000001",
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+            "message": "VectorBT Pro=$-500.0000000000, ML4T=$-500.0000000000 (exact_diff=$0.0000000000; diagnostic_limit=$0.01)",
+            "name": "total_pnl",
+            "passed": true
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+          {
+            "actual": 95.0,
+            "canonical_quantum": "0.00000001",
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+            "expected": 95.0,
+            "message": "VectorBT Pro=$95.0000000000, ML4T=$95.0000000000 (exact_diff=$0.0000000000; diagnostic_limit=$0.01)",
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+            "passed": true
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+                "exit_time": "2020-01-07T00:00:00",
+                "pnl": -500.0,
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+            "canonical_quantum": "0.00000001",
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+                "exit_time": "2020-01-07T00:00:00",
+                "pnl": -500.0,
+                "size": 100.0
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+            "message": "exact ordered match",
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+            "passed": true
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       "framework": "vectorbt_pro",
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+            "pnl": -500.0,
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       "release_blocking": false,
       "required": true,
       "scenario_id": "03",
@@ -60,8 +3044,317 @@
       "status": "pass"
     },
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@@ -87,8 +6050,1329 @@
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+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
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+          "risk_rules": "framework_adapter"
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+        "digests": {
+          "adapter": "77c6dc83a02c7665eea21f7cedd0df1c4630ac15b7d284a21e96a849d1d8df74",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
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+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "4c1b7206fe55cebbe9f41acb88a30dac343e4ce973e92ad60c236a27ef021548",
+          "scenario": "d2d36326d5a7ec88f577088205574b8a9f6dab9661ed6813d190c138c4c8208f"
+        },
+        "framework_target": {
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+          "immutable_id": "git:6e18cf0aa37849cfc20848f40f1d26ecfdc771b4",
+          "version": "2026.6.27"
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+        "input_digest": "fa1946cbf9ef0bb21ff45ffeb8a251d50b24f15e8240155e87d22ad9a84cccbd",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
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+          "version": "3.12.11"
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+        "record_counts": {
+          "bars": 100,
+          "entry_signals": 10,
+          "exit_signals": 10,
+          "framework_closed_trades": 10,
+          "framework_fills": 20,
+          "framework_intents": 20,
+          "framework_orders": null,
+          "ml4t_closed_trades": 10,
+          "ml4t_fills": 20,
+          "ml4t_intents": 20,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "08",
@@ -105,8 +8710,417 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 2,
+            "canonical_quantum": "1",
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+            "difference": 0,
+            "expected": 2,
+            "message": "VectorBT Pro=2, ML4T=2, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
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+            "expected": 100363.84268834148,
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+            "name": "final_value",
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+            "name": "total_pnl",
+            "passed": true
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+                "pnl": 429.85822292976627,
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+                "entry_time": "2020-02-11T00:00:00",
+                "exit_price": 96.71339881738633,
+                "exit_reason": "trailing_stop",
+                "exit_time": "2020-03-04T00:00:00",
+                "pnl": -66.01553458828494,
+                "size": 100.0
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+            "canonical_quantum": "0.00000001",
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+            "expected": [
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+                "entry_time": "2020-01-02T00:00:00",
+                "exit_price": 104.29858222929766,
+                "exit_time": "2020-02-02T00:00:00",
+                "pnl": 429.8582229297665,
+                "size": 100.0
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+              {
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+                "entry_price": 97.37355416326918,
+                "entry_time": "2020-02-11T00:00:00",
+                "exit_price": 96.71339881738633,
+                "exit_time": "2020-03-04T00:00:00",
+                "pnl": -66.0155345882842,
+                "size": 100.0
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+                "price": 100.0,
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+                "quantity": 100.0,
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+                "price": 97.37355416326918,
+                "quantity": 100.0,
+                "side": "buy",
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+              },
+              {
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+                "quantity": 100.0,
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+            "canonical_quantum": "0.00000001",
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+            "difference": null,
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+            "message": "exact ordered match",
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       "detail": null,
+      "duration_seconds": 2.585157000925392,
       "framework": "vectorbt_pro",
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+            "pnl": -66.0155345882842,
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+      "ml4t_result": {
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+          "closed_trades": "native",
+          "exit_reason": "native",
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+          "open_trades": "unavailable",
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+            "price": 100.0,
+            "quantity": 100.0,
+            "side": "buy",
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+          {
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+            "quantity": 100.0,
+            "side": "sell",
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+          },
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+            "price": 97.37355416326918,
+            "quantity": 100.0,
+            "side": "buy",
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+          },
+          {
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+            "quantity": 100.0,
+            "side": "sell",
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+        "framework": "ml4t.backtest",
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+            "entry_time": "2020-01-02T00:00:00",
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+            "exit_time": "2020-02-02T00:00:00",
+            "pnl": 429.85822292976627,
+            "size": 100.0
+          },
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+            "entry_time": "2020-02-11T00:00:00",
+            "exit_price": 96.71339881738633,
+            "exit_reason": "trailing_stop",
+            "exit_time": "2020-03-04T00:00:00",
+            "pnl": -66.01553458828494,
+            "size": 100.0
+          }
+        ]
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+      "provenance": {
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+            "closed_trades": "native",
+            "exit_reason": "unavailable",
+            "fills": "native",
+            "intents": "input_only",
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+            "orders": "native_filled_only",
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+            "rejections": "unavailable",
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+          "ml4t": {
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+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
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+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
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+        "comparison_protocol": {
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+        "digests": {
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+        },
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+          "immutable_id": "git:6e18cf0aa37849cfc20848f40f1d26ecfdc771b4",
+          "version": "2026.6.27"
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+        "input_digest": "0ab00a6cfc6f76a1d74f0617186a4d5c95d27cb4fd62bd5c535b3b191965369d",
+        "ml4t": {
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+          "dirty": false
+        },
+        "python": {
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+          "version": "3.12.11"
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+        "record_counts": {
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       "release_blocking": false,
       "required": true,
       "scenario_id": "09",
@@ -114,8 +9128,531 @@
       "status": "pass"
     },
     {
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+                "entry_time": "2020-01-22T00:00:00",
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+                "exit_reason": "take_profit",
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+                "pnl": 913.6277380567044,
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+                "entry_time": "2020-02-26T00:00:00",
+                "exit_price": 96.63389452556515,
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+                "pnl": -559.274411914932,
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@@ -123,8 +9660,1329 @@
       "status": "pass"
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       "required": true,
       "scenario_id": "12",
@@ -141,8 +11408,303 @@
       "status": "pass"
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       "scenario_id": "13",
@@ -150,8 +11712,303 @@
       "status": "pass"
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+            "fills": "native",
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+            "orders": "native_filled_only",
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+            "terminal": "native"
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+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
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+        "comparison_protocol": {
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+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
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+        "framework_target": {
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+          "immutable_id": "git:6e18cf0aa37849cfc20848f40f1d26ecfdc771b4",
+          "version": "2026.6.27"
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+        "input_digest": "515cb2ead81157a5d033173889d2a47af873b49bb750c0fedf91036506520aa2",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
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+        "python": {
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+          "version": "3.12.11"
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+        "record_counts": {
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+          "entry_signals": 1,
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+          "framework_closed_trades": 1,
+          "framework_fills": 2,
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+          "ml4t_closed_trades": 1,
+          "ml4t_fills": 2,
+          "ml4t_intents": 1,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "14",
@@ -159,8 +12016,303 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 1,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 1,
+            "message": "VectorBT Pro=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 99670.0,
+            "canonical_quantum": "0.00000001",
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+            "difference": 0.0,
+            "expected": 99670.0,
+            "message": "VectorBT Pro=$99,670.0000000000, ML4T=$99,670.0000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
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+            "actual": -330.0,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 1.0,
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+            "expected": -330.0,
+            "message": "VectorBT Pro=$-330.0000000000, ML4T=$-330.0000000000 (exact_diff=$0.0000000000; diagnostic_limit=$1.0)",
+            "name": "total_pnl",
+            "passed": true
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+                "exit_price": 96.7,
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+                "pnl": -330.0,
+                "size": 100.0
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+            "canonical_quantum": "0.00000001",
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+                "entry_time": "2020-01-02T00:00:00",
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+                "exit_time": "2020-01-03T00:00:00",
+                "pnl": -329.9999999999997,
+                "size": 100.0
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+            "message": "exact ordered match",
+            "name": "trade_level_match",
+            "passed": true
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       "detail": null,
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       "framework": "vectorbt_pro",
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+            "pnl": -329.9999999999997,
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+        "ml4t": {
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+          "dirty": false
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       "release_blocking": false,
       "required": true,
       "scenario_id": "15",
@@ -168,17 +12320,71135 @@
       "status": "pass"
     },
     {
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+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
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+          "ml4t_closed_trades": 10,
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       "release_blocking": false,
       "required": true,
       "scenario_id": "02",
@@ -195,8 +84786,317 @@
       "status": "pass"
     },
     {
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+            "message": "VectorBT OSS=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
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+            "expected": 99500.0,
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+            "canonical_quantum": "0.00000001",
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+          "dirty": false
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       "release_blocking": false,
       "required": true,
       "scenario_id": "03",
@@ -204,8 +85104,317 @@
       "status": "pass"
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+            "exit_reason": "native",
+            "fills": "native",
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+            "open_trades": "unavailable",
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@@ -222,8 +86766,13 @@
       "status": "pass"
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       "detail": "Scenario explicitly excludes this framework",
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       "required": false,
       "scenario_id": "06",
@@ -231,8 +86780,1329 @@
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+            "entry_price": 83.95294649382782,
+            "entry_time": "2020-04-01T00:00:00",
+            "exit_price": 80.63417873538535,
+            "exit_reason": "signal",
+            "exit_time": "2020-04-06T00:00:00",
+            "pnl": -331.8767758442473,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
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+          "module": "frameworks.vectorbt_oss",
+          "path": "validation/frameworks/vectorbt_oss.py"
+        },
+        "capabilities": {
+          "framework": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "unavailable",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          },
+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "risk_rules": "framework_adapter"
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+        "digests": {
+          "adapter": "ce6e7cf59f08a661ad5efc075866be9e9a9e33011f59b12a18a187c00585a1ac",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
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+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "4c1b7206fe55cebbe9f41acb88a30dac343e4ce973e92ad60c236a27ef021548",
+          "scenario": "d2d36326d5a7ec88f577088205574b8a9f6dab9661ed6813d190c138c4c8208f"
+        },
+        "framework_target": {
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+          "immutable_id": "sha256:67a3b41466234485af70c18d201da105f1ebb2c1d1fac079db20059e45ddc73b",
+          "version": "1.1.0"
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+        "input_digest": "fa1946cbf9ef0bb21ff45ffeb8a251d50b24f15e8240155e87d22ad9a84cccbd",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
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+          "version": "3.12.11"
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+        "record_counts": {
+          "bars": 100,
+          "entry_signals": 10,
+          "exit_signals": 10,
+          "framework_closed_trades": 10,
+          "framework_fills": 20,
+          "framework_intents": 20,
+          "framework_orders": null,
+          "ml4t_closed_trades": 10,
+          "ml4t_fills": 20,
+          "ml4t_intents": 20,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "08",
@@ -249,8 +89440,417 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
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+            "canonical_quantum": "1",
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+            "difference": 0,
+            "expected": 2,
+            "message": "VectorBT OSS=2, ML4T=2, exact_diff=0; diagnostic_limit=0",
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+          {
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+            "expected": 100363.84268834148,
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+            "name": "final_value",
+            "passed": true
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+          {
+            "actual": 363.8426883414795,
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+            "expected": 363.8426883414795,
+            "message": "VectorBT OSS=$363.8426883415, ML4T=$363.8426883415 (exact_diff=$0.0000000000; diagnostic_limit=$1.0)",
+            "name": "total_pnl",
+            "passed": true
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+                "pnl": 429.85822292976627,
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+                "entry_time": "2020-02-11T00:00:00",
+                "exit_price": 96.71339881738633,
+                "exit_reason": "trailing_stop",
+                "exit_time": "2020-03-04T00:00:00",
+                "pnl": -66.01553458828494,
+                "size": 100.0
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+            "canonical_quantum": "0.00000001",
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+            "difference": null,
+            "expected": [
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+                "direction": "Long",
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+                "entry_time": "2020-01-02T00:00:00",
+                "exit_price": 104.29858222929766,
+                "exit_time": "2020-02-02T00:00:00",
+                "pnl": 429.8582229297665,
+                "size": 100.0
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+              {
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+                "entry_time": "2020-02-11T00:00:00",
+                "exit_price": 96.71339881738633,
+                "exit_time": "2020-03-04T00:00:00",
+                "pnl": -66.0155345882842,
+                "size": 100.0
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+                "price": 100.0,
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+                "quantity": 100.0,
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+                "price": 97.37355416326918,
+                "quantity": 100.0,
+                "side": "buy",
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+              },
+              {
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+                "price": 96.71339881738633,
+                "quantity": 100.0,
+                "side": "sell",
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+              }
+            ],
+            "canonical_quantum": "0.00000001",
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+            "expected": [
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+              },
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+        "scenario_id": "09"
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       "detail": null,
+      "duration_seconds": 3.4778857689816505,
       "framework": "vectorbt_oss",
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+            "side": "sell",
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+            "pnl": 429.8582229297665,
+            "size": 100.0
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+            "direction": "Long",
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+            "entry_time": "2020-02-11T00:00:00",
+            "exit_price": 96.71339881738633,
+            "exit_time": "2020-03-04T00:00:00",
+            "pnl": -66.0155345882842,
+            "size": 100.0
+          }
+        ]
+      },
+      "ml4t_result": {
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+          "closed_trades": "native",
+          "exit_reason": "native",
+          "fills": "native",
+          "intents": "input_only",
+          "open_trades": "unavailable",
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+        "fills": [
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+            "price": 100.0,
+            "quantity": 100.0,
+            "side": "buy",
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+          },
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+            "exit_reason": "trailing_stop",
+            "price": 104.29858222929766,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-02-02T00:00:00"
+          },
+          {
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+            "exit_reason": "",
+            "price": 97.37355416326918,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-02-11T00:00:00"
+          },
+          {
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+            "exit_reason": "trailing_stop",
+            "price": 96.71339881738633,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-03-04T00:00:00"
+          }
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+        "final_value": 100363.84268834148,
+        "framework": "ml4t.backtest",
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+        "trades": [
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+            "entry_price": 100.0,
+            "entry_time": "2020-01-02T00:00:00",
+            "exit_price": 104.29858222929766,
+            "exit_reason": "trailing_stop",
+            "exit_time": "2020-02-02T00:00:00",
+            "pnl": 429.85822292976627,
+            "size": 100.0
+          },
+          {
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+            "direction": "Long",
+            "entry_price": 97.37355416326918,
+            "entry_time": "2020-02-11T00:00:00",
+            "exit_price": 96.71339881738633,
+            "exit_reason": "trailing_stop",
+            "exit_time": "2020-03-04T00:00:00",
+            "pnl": -66.01553458828494,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
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+          "module": "frameworks.vectorbt_oss",
+          "path": "validation/frameworks/vectorbt_oss.py"
+        },
+        "capabilities": {
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+            "closed_trades": "native",
+            "exit_reason": "unavailable",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          },
+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
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+        "digests": {
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+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
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+          "profile": "2239ef5dfd2ca79f8cf4b7d6b6f991dbfdc0b7393efab316c6eba29edbdb6829",
+          "scenario": "80d8dea99e845ad7f708cc42fb94f66feababcf8b6814e3096300af1f4b709c2"
+        },
+        "framework_target": {
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+          "immutable_id": "sha256:67a3b41466234485af70c18d201da105f1ebb2c1d1fac079db20059e45ddc73b",
+          "version": "1.1.0"
+        },
+        "input_digest": "0ab00a6cfc6f76a1d74f0617186a4d5c95d27cb4fd62bd5c535b3b191965369d",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
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+          "version": "3.12.11"
+        },
+        "record_counts": {
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+          "entry_signals": 2,
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+          "framework_closed_trades": 2,
+          "framework_fills": 4,
+          "framework_intents": 2,
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+          "ml4t_closed_trades": 2,
+          "ml4t_fills": 4,
+          "ml4t_intents": 2,
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+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "09",
@@ -258,8 +89858,531 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
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+            "canonical_quantum": "1",
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+            "message": "VectorBT OSS=3, ML4T=3, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
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+            "expected": 99854.35332614178,
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+            "name": "final_value",
+            "passed": true
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+          {
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+            "canonical_quantum": "0.00000001",
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+            "difference": 1.4551915228366852e-11,
+            "expected": -145.64667385822395,
+            "message": "VectorBT OSS=$-145.6466738582, ML4T=$-145.6466738582 (exact_diff=$0.0000000000; diagnostic_limit=$1.0)",
+            "name": "total_pnl",
+            "passed": true
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+                "direction": "Long",
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+                "entry_time": "2020-01-02T00:00:00",
+                "exit_price": 95.0,
+                "exit_reason": "stop_loss",
+                "exit_time": "2020-01-15T00:00:00",
+                "pnl": -500.0,
+                "size": 100.0
+              },
+              {
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+                "direction": "Long",
+                "entry_price": 91.36277380567032,
+                "entry_time": "2020-01-22T00:00:00",
+                "exit_price": 100.49905118623735,
+                "exit_reason": "take_profit",
+                "exit_time": "2020-02-12T00:00:00",
+                "pnl": 913.6277380567044,
+                "size": 100.0
+              },
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "direction": "Long",
+                "entry_price": 102.22663864471447,
+                "entry_time": "2020-02-26T00:00:00",
+                "exit_price": 96.63389452556515,
+                "exit_reason": "stop_loss",
+                "exit_time": "2020-03-06T00:00:00",
+                "pnl": -559.274411914932,
+                "size": 100.0
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+            "canonical_quantum": "0.00000001",
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+            "expected": [
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+                "entry_price": 100.0,
+                "entry_time": "2020-01-02T00:00:00",
+                "exit_price": 95.0,
+                "exit_time": "2020-01-15T00:00:00",
+                "pnl": -500.0,
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+              },
+              {
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+                "entry_time": "2020-01-22T00:00:00",
+                "exit_price": 100.49905118623735,
+                "exit_time": "2020-02-12T00:00:00",
+                "pnl": 913.6277380567037,
+                "size": 100.0
+              },
+              {
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+                "entry_time": "2020-02-26T00:00:00",
+                "exit_price": 96.63389452556515,
+                "exit_time": "2020-03-06T00:00:00",
+                "pnl": -559.2744119149315,
+                "size": 100.0
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       "framework": "vectorbt_oss",
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       "release_blocking": false,
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       "scenario_id": "10",
@@ -267,8 +90390,1329 @@
       "status": "pass"
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+          "open_trades": "unavailable",
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+            "side": "buy",
+            "timestamp": "2020-02-03T00:00:00"
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+            "price": 85.78505322725157,
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+            "timestamp": "2020-02-11T00:00:00"
+          },
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+            "exit_reason": "trailing_stop",
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+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-03-04T00:00:00"
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+        "final_value": 1001485.7011748579,
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+        "total_pnl": 1485.7011748579098,
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+            "entry_time": "2020-01-02T00:00:00",
+            "exit_price": 87.2667981247593,
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+            "exit_time": "2020-02-03T00:00:00",
+            "pnl": 1273.3201875240702,
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+            "entry_time": "2020-02-11T00:00:00",
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+            "pnl": 212.38098733383595,
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+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
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+          "ml4t_closed_trades": 2,
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       "release_blocking": false,
       "required": true,
       "scenario_id": "12",
@@ -285,8 +92138,303 @@
       "status": "pass"
     },
     {
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+        "checks": [
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+            "message": "VectorBT OSS=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
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+                "pnl": 800.0,
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+                "entry_time": "2020-01-02T00:00:00",
+                "exit_price": 108.0,
+                "exit_time": "2020-01-13T00:00:00",
+                "pnl": 800.0,
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       "detail": null,
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       "framework": "vectorbt_oss",
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+            "pnl": 800.0,
+            "size": 100.0
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+      "ml4t_result": {
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+      "provenance": {
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+          "version": "1.1.0"
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+        "input_digest": "6868775136fad190c5e2fffe0cb05f259b244161572731b86777972b78ea5fb5",
+        "ml4t": {
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+          "dirty": false
+        },
+        "python": {
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+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "13",
@@ -294,8 +92442,303 @@
       "status": "pass"
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     {
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+            "side": "buy",
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+          {
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+            "price": 98.89954497829228,
+            "quantity": 100.0,
+            "side": "sell",
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+        "final_value": 99889.95449782923,
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+            "exit_price": 98.89954497829228,
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+            "pnl": -110.04550217077121,
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+      "provenance": {
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+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
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       "release_blocking": false,
       "required": true,
       "scenario_id": "14",
@@ -303,8 +92746,303 @@
       "status": "pass"
     },
     {
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+        "checks": [
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+            "message": "VectorBT OSS=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
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+            "passed": true
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+          {
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+            "expected": 99670.0,
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+            "name": "final_value",
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+            "message": "VectorBT OSS=$-330.0000000000, ML4T=$-330.0000000000 (exact_diff=$0.0000000000; diagnostic_limit=$1.0)",
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       "framework": "vectorbt_oss",
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       "scenario_id": "15",
@@ -312,17 +93050,71177 @@
       "status": "pass"
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+            "size": 100.0
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+          {
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+            "direction": "Long",
+            "entry_price": 95.28676318555902,
+            "entry_time": "2020-01-23T00:00:00",
+            "exit_price": 89.80581696520652,
+            "exit_reason": "signal",
+            "exit_time": "2020-01-28T00:00:00",
+            "pnl": -548.0946220352507,
+            "size": 100.0
+          },
+          {
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+            "direction": "Long",
+            "entry_price": 91.61877666044562,
+            "entry_time": "2020-02-02T00:00:00",
+            "exit_price": 88.95731597282261,
+            "exit_reason": "signal",
+            "exit_time": "2020-02-07T00:00:00",
+            "pnl": -266.1460687623003,
+            "size": 100.0
+          },
+          {
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+            "direction": "Long",
+            "entry_price": 86.05372935177999,
+            "entry_time": "2020-02-12T00:00:00",
+            "exit_price": 79.89700080068819,
+            "exit_reason": "signal",
+            "exit_time": "2020-02-17T00:00:00",
+            "pnl": -615.6728551091792,
+            "size": 100.0
+          },
+          {
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+            "entry_price": 79.85456613711182,
+            "entry_time": "2020-02-22T00:00:00",
+            "exit_price": 82.1805182750142,
+            "exit_reason": "signal",
+            "exit_time": "2020-02-27T00:00:00",
+            "pnl": 232.59521379023863,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
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+            "direction": "Long",
+            "entry_price": 82.28720283715133,
+            "entry_time": "2020-03-03T00:00:00",
+            "exit_price": 81.963502869723,
+            "exit_reason": "signal",
+            "exit_time": "2020-03-08T00:00:00",
+            "pnl": -32.36999674283288,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
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+            "direction": "Long",
+            "entry_price": 85.66757660317238,
+            "entry_time": "2020-03-13T00:00:00",
+            "exit_price": 85.71152184475136,
+            "exit_reason": "signal",
+            "exit_time": "2020-03-18T00:00:00",
+            "pnl": 4.394524157898559,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
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+            "direction": "Long",
+            "entry_price": 81.89842492239329,
+            "entry_time": "2020-03-23T00:00:00",
+            "exit_price": 83.38209984017583,
+            "exit_reason": "signal",
+            "exit_time": "2020-03-28T00:00:00",
+            "pnl": 148.3674917782546,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
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+            "direction": "Long",
+            "entry_price": 85.8758572398221,
+            "entry_time": "2020-04-02T00:00:00",
+            "exit_price": 80.8355171954138,
+            "exit_reason": "signal",
+            "exit_time": "2020-04-07T00:00:00",
+            "pnl": -504.03400444082854,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
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+          "module": "frameworks.backtrader",
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+            "closed_trades": "native",
+            "exit_reason": "unavailable",
+            "fills": "native",
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+            "open_trades": "unavailable",
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+            "positions": "unavailable",
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+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "risk_rules": "framework_adapter"
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+        "digests": {
+          "adapter": "9d3ee2845f1a37b484d9040c5237d7e0ba8974b0536b216305b3a2dd14fe8976",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "be4345288348f6a276f38cb4a364261003c925cddc5d9423b667fb82c34cff1b",
+          "scenario": "7db3751b770b7369c40f6b31fc757e7949b07dd5b56430e7226dc8db7d444e38"
+        },
+        "framework_target": {
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+          "immutable_id": "sha256:9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+          "version": "1.9.78.123"
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+        "input_digest": "fa1946cbf9ef0bb21ff45ffeb8a251d50b24f15e8240155e87d22ad9a84cccbd",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
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+          "version": "3.12.11"
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+        "record_counts": {
+          "bars": 100,
+          "entry_signals": 10,
+          "exit_signals": 10,
+          "framework_closed_trades": 10,
+          "framework_fills": 20,
+          "framework_intents": 20,
+          "framework_orders": null,
+          "ml4t_closed_trades": 10,
+          "ml4t_fills": 20,
+          "ml4t_intents": 20,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "02",
@@ -339,8 +165600,319 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 1,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 1,
+            "message": "Backtrader=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 99550.0,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 99550.0,
+            "message": "Backtrader=$99,550.0000000000, ML4T=$99,550.0000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
+          },
+          {
+            "actual": -450.0,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 1.0,
+            "difference": 0.0,
+            "expected": -450.0,
+            "message": "Backtrader=$-450.0000000000, ML4T=$-450.0000000000 (exact_diff=$0.0000000000; diagnostic_limit=$1.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
+            "actual": 95.0,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 95.0,
+            "message": "Backtrader=$95.0000000000, ML4T=$95.0000000000 (exact_diff=$0.0000000000; diagnostic_limit=$0.01)",
+            "name": "exit_price",
+            "passed": true
+          },
+          {
+            "actual": [
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+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 95.0,
+                "exit_reason": "stop_loss",
+                "exit_time": "2020-01-07T00:00:00",
+                "pnl": -450.0,
+                "size": 100.0
+              }
+            ],
+            "canonical_quantum": "0.00000001",
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+            "difference": null,
+            "expected": [
+              {
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+                "commission": 0.0,
+                "direction": "Long",
+                "entry_price": 99.5,
+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 95.0,
+                "exit_time": "2020-01-07T00:00:00",
+                "gross_pnl": -450.0,
+                "pnl": -450.0,
+                "size": 100
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "trade_level_match",
+            "passed": true
+          },
+          {
+            "actual": [
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+                "price": 99.5,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T00:00:00"
+              },
+              {
+                "asset": "TEST",
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+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-07T00:00:00"
+              }
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+            "canonical_quantum": "0.00000001",
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+            "difference": null,
+            "expected": [
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+                "price": 99.5,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T00:00:00"
+              },
+              {
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+                "price": 95.0,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-07T00:00:00"
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "fill_level_match",
+            "passed": true
+          }
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+        "framework": "Backtrader",
+        "passed": true,
+        "scenario_id": "03"
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       "detail": null,
+      "duration_seconds": 0.19068946689367294,
       "framework": "backtrader",
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+          "cash_flows": "aggregate_only",
+          "closed_trades": "native",
+          "exit_reason": "unavailable",
+          "fills": "native",
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+          "open_trades": "unavailable",
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+        },
+        "extra": {
+          "exit_price": 95.0
+        },
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+            "price": 99.5,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-01-03T00:00:00"
+          },
+          {
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+            "price": 95.0,
+            "quantity": 100.0,
+            "side": "sell",
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+          }
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+        "final_value": 99550.0,
+        "framework": "Backtrader",
+        "num_trades": 1,
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+            "direction": "Long",
+            "entry_price": 99.5,
+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 95.0,
+            "exit_time": "2020-01-07T00:00:00",
+            "gross_pnl": -450.0,
+            "pnl": -450.0,
+            "size": 100
+          }
+        ]
+      },
+      "ml4t_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "native",
+          "exit_reason": "native",
+          "fills": "native",
+          "intents": "input_only",
+          "open_trades": "unavailable",
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+          "terminal": "native"
+        },
+        "extra": {
+          "exit_price": 95.0
+        },
+        "fills": [
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+            "exit_reason": "",
+            "price": 99.5,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-01-03T00:00:00"
+          },
+          {
+            "asset": "TEST",
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+            "exit_reason": "stop_loss",
+            "price": 95.0,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-07T00:00:00"
+          }
+        ],
+        "final_value": 99550.0,
+        "framework": "ml4t.backtest",
+        "num_trades": 1,
+        "total_pnl": -450.0,
+        "trades": [
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 99.5,
+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 95.0,
+            "exit_reason": "stop_loss",
+            "exit_time": "2020-01-07T00:00:00",
+            "pnl": -450.0,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
+        "adapter": {
+          "module": "frameworks.backtrader",
+          "path": "validation/frameworks/backtrader.py"
+        },
+        "capabilities": {
+          "framework": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "unavailable",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          },
+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "risk_rules": "framework_adapter"
+        },
+        "digests": {
+          "adapter": "9d3ee2845f1a37b484d9040c5237d7e0ba8974b0536b216305b3a2dd14fe8976",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "6f82ba4bceb1436137d9a4d844fa16973426eacd177ec088ab0f1e40ec12288d",
+          "scenario": "ad7292cedc685fa6c10032a0574f3e5da89b81dbb0f3a312cc2f5d83f5b454a1"
+        },
+        "framework_target": {
+          "actual_version": "1.9.78.123",
+          "immutable_id": "sha256:9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+          "version": "1.9.78.123"
+        },
+        "input_digest": "c450f8db901151f953d81b05845db8cad686ca7c619cfe7e881485a2228972a7",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
+          "implementation": "cpython",
+          "version": "3.12.11"
+        },
+        "record_counts": {
+          "bars": 20,
+          "entry_signals": 1,
+          "exit_signals": 0,
+          "framework_closed_trades": 1,
+          "framework_fills": 2,
+          "framework_intents": 1,
+          "framework_orders": null,
+          "ml4t_closed_trades": 1,
+          "ml4t_fills": 2,
+          "ml4t_intents": 1,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "03",
@@ -348,8 +165920,319 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 1,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 1,
+            "message": "Backtrader=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 101000.0,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 101000.0,
+            "message": "Backtrader=$101,000.0000000000, ML4T=$101,000.0000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
+          },
+          {
+            "actual": 1000.0,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 1.0,
+            "difference": 0.0,
+            "expected": 1000.0,
+            "message": "Backtrader=$1,000.0000000000, ML4T=$1,000.0000000000 (exact_diff=$0.0000000000; diagnostic_limit=$1.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
+            "actual": 110.5,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 110.5,
+            "message": "Backtrader=$110.5000000000, ML4T=$110.5000000000 (exact_diff=$0.0000000000; diagnostic_limit=$0.01)",
+            "name": "exit_price",
+            "passed": true
+          },
+          {
+            "actual": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "direction": "Long",
+                "entry_price": 100.5,
+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 110.5,
+                "exit_reason": "take_profit",
+                "exit_time": "2020-01-08T00:00:00",
+                "pnl": 1000.0,
+                "size": 100.0
+              }
+            ],
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": null,
+            "difference": null,
+            "expected": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "direction": "Long",
+                "entry_price": 100.5,
+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 110.5,
+                "exit_time": "2020-01-08T00:00:00",
+                "gross_pnl": 1000.0,
+                "pnl": 1000.0,
+                "size": 100
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "trade_level_match",
+            "passed": true
+          },
+          {
+            "actual": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "exit_reason": "",
+                "price": 100.5,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T00:00:00"
+              },
+              {
+                "asset": "TEST",
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+                "exit_reason": "take_profit",
+                "price": 110.5,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-08T00:00:00"
+              }
+            ],
+            "canonical_quantum": "0.00000001",
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+            "difference": null,
+            "expected": [
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+                "asset": "TEST",
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+                "price": 100.5,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T00:00:00"
+              },
+              {
+                "asset": "TEST",
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+                "price": 110.5,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-08T00:00:00"
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "fill_level_match",
+            "passed": true
+          }
+        ],
+        "framework": "Backtrader",
+        "passed": true,
+        "scenario_id": "04"
+      },
       "detail": null,
+      "duration_seconds": 0.19105158699676394,
       "framework": "backtrader",
+      "framework_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "native",
+          "exit_reason": "unavailable",
+          "fills": "native",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "native_filled_only",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
+        },
+        "extra": {
+          "exit_price": 110.5
+        },
+        "fills": [
+          {
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+            "price": 100.5,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-01-03T00:00:00"
+          },
+          {
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+            "price": 110.5,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-08T00:00:00"
+          }
+        ],
+        "final_value": 101000.0,
+        "framework": "Backtrader",
+        "num_trades": 1,
+        "total_pnl": 1000.0,
+        "trades": [
+          {
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+            "direction": "Long",
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+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 110.5,
+            "exit_time": "2020-01-08T00:00:00",
+            "gross_pnl": 1000.0,
+            "pnl": 1000.0,
+            "size": 100
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+        ]
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+      "ml4t_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "native",
+          "exit_reason": "native",
+          "fills": "native",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "unavailable",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
+        },
+        "extra": {
+          "exit_price": 110.5
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+        "fills": [
+          {
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+            "exit_reason": "",
+            "price": 100.5,
+            "quantity": 100.0,
+            "side": "buy",
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+          },
+          {
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+            "exit_reason": "take_profit",
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+            "quantity": 100.0,
+            "side": "sell",
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+          }
+        ],
+        "final_value": 101000.0,
+        "framework": "ml4t.backtest",
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+        "total_pnl": 1000.0,
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+            "entry_time": "2020-01-03T00:00:00",
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+            "pnl": 1000.0,
+            "size": 100.0
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+      "provenance": {
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+          "path": "validation/frameworks/backtrader.py"
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+        "capabilities": {
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+            "closed_trades": "native",
+            "exit_reason": "unavailable",
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+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
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+            "rejections": "unavailable",
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+          "ml4t": {
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+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
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+        },
+        "comparison_protocol": {
+          "risk_rules": "framework_adapter"
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+        "digests": {
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+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
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+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
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+          "immutable_id": "sha256:9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+          "version": "1.9.78.123"
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+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
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+          "version": "3.12.11"
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+        "record_counts": {
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       "release_blocking": false,
       "required": true,
       "scenario_id": "04",
@@ -357,8 +166240,1383 @@
       "status": "pass"
     },
     {
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@@ -366,8 +167624,1383 @@
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@@ -375,8 +169008,1371 @@
       "status": "pass"
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@@ -384,8 +170380,1371 @@
       "status": "pass"
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       "release_blocking": false,
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       "scenario_id": "08",
@@ -393,8 +171752,421 @@
       "status": "pass"
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       "release_blocking": false,
       "required": true,
       "scenario_id": "09",
@@ -402,8 +172174,537 @@
       "status": "pass"
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       "release_blocking": false,
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       "scenario_id": "10",
@@ -411,8 +172712,1349 @@
       "status": "pass"
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+          {
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+            "direction": "Short",
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+            "entry_time": "2020-02-17T00:00:00",
+            "exit_price": 81.7304119228052,
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+            "exit_time": "2020-02-27T00:00:00",
+            "pnl": -145.07412613667202,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
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+            "direction": "Short",
+            "entry_price": 82.02773863577156,
+            "entry_time": "2020-03-08T00:00:00",
+            "exit_price": 85.75713194830126,
+            "exit_reason": "signal",
+            "exit_time": "2020-03-18T00:00:00",
+            "pnl": -372.9393312529719,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
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+            "direction": "Short",
+            "entry_price": 83.1473889960404,
+            "entry_time": "2020-03-28T00:00:00",
+            "exit_price": 81.41346554365083,
+            "exit_reason": "signal",
+            "exit_time": "2020-04-07T00:00:00",
+            "pnl": 173.39234523895811,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
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+            "direction": "Short",
+            "entry_price": 80.17900380032793,
+            "entry_time": "2020-04-17T00:00:00",
+            "exit_price": 81.66999422482027,
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+            "exit_time": "2020-04-27T00:00:00",
+            "pnl": -149.09904244923382,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
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+            "direction": "Short",
+            "entry_price": 85.80008932877531,
+            "entry_time": "2020-05-07T00:00:00",
+            "exit_price": 80.01376127293886,
+            "exit_reason": "signal",
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+            "pnl": 578.6328055836457,
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+          {
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+            "entry_time": "2020-05-27T00:00:00",
+            "exit_price": 80.64101214269384,
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+            "pnl": -208.07127296227736,
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+          },
+          {
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+            "entry_time": "2020-06-16T00:00:00",
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+            "exit_reason": "signal",
+            "exit_time": "2020-06-26T00:00:00",
+            "pnl": -114.02096298050674,
+            "size": 100.0
+          },
+          {
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+            "entry_time": "2020-07-06T00:00:00",
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+            "exit_reason": "signal",
+            "exit_time": "2020-07-16T00:00:00",
+            "pnl": 659.56748911656,
+            "size": 100.0
+          }
+        ]
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+            "closed_trades": "native",
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+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
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+            "terminal": "native"
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+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
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+          "version": "3.12.11"
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+        "record_counts": {
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+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "11",
@@ -420,8 +174062,421 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 2,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 2,
+            "message": "Backtrader=2, ML4T=2, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
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+          {
+            "actual": 1001492.5493344698,
+            "canonical_quantum": "0.00000001",
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+            "expected": 1001492.5493344698,
+            "message": "Backtrader=$1,001,492.5493344698, ML4T=$1,001,492.5493344698 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
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+          {
+            "actual": 1492.5493344698334,
+            "canonical_quantum": "0.00000001",
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+            "expected": 1492.5493344698334,
+            "message": "Backtrader=$1,492.5493344698, ML4T=$1,492.5493344698 (exact_diff=$0.0000000000; diagnostic_limit=$1.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
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+                "pnl": 1244.6851181225247,
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+              },
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+                "direction": "Short",
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+                "entry_time": "2020-02-12T00:00:00",
+                "exit_price": 83.7217462910142,
+                "exit_reason": "trailing_stop",
+                "exit_time": "2020-03-04T00:00:00",
+                "pnl": 247.8642163473014,
+                "size": 100.0
+              }
+            ],
+            "canonical_quantum": "0.00000001",
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+            "expected": [
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+                "asset": "TEST",
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+                "direction": "Short",
+                "entry_price": 99.71364930598455,
+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 87.2667981247593,
+                "exit_time": "2020-02-03T00:00:00",
+                "gross_pnl": 1244.6851181225243,
+                "pnl": 1244.6851181225243,
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+              },
+              {
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+                "direction": "Short",
+                "entry_price": 86.20038845448722,
+                "entry_time": "2020-02-12T00:00:00",
+                "exit_price": 83.7217462910142,
+                "exit_time": "2020-03-04T00:00:00",
+                "gross_pnl": 247.8642163473026,
+                "pnl": 247.8642163473026,
+                "size": 100
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "trade_level_match",
+            "passed": true
+          },
+          {
+            "actual": [
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+                "price": 99.71364930598455,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-03T00:00:00"
+              },
+              {
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+                "exit_reason": "trailing_stop",
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+                "quantity": 100.0,
+                "side": "buy",
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+              },
+              {
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+                "price": 86.20038845448721,
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+                "side": "sell",
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+              },
+              {
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+                "exit_reason": "trailing_stop",
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+                "quantity": 100.0,
+                "side": "buy",
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+              }
+            ],
+            "canonical_quantum": "0.00000001",
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+            "expected": [
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+                "price": 99.71364930598455,
+                "quantity": 100.0,
+                "side": "sell",
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+              },
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+                "side": "buy",
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+              },
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+                "price": 86.20038845448722,
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+                "side": "sell",
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+              },
+              {
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+                "quantity": 100.0,
+                "side": "buy",
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+              }
+            ],
+            "message": "exact ordered match",
+            "name": "fill_level_match",
+            "passed": true
+          }
+        ],
+        "framework": "Backtrader",
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+        "scenario_id": "12"
+      },
       "detail": null,
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       "framework": "backtrader",
+      "framework_result": {
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+          },
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+          },
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+            "side": "buy",
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+          }
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+        "framework": "Backtrader",
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+            "direction": "Short",
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+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 87.2667981247593,
+            "exit_time": "2020-02-03T00:00:00",
+            "gross_pnl": 1244.6851181225243,
+            "pnl": 1244.6851181225243,
+            "size": 100
+          },
+          {
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+            "direction": "Short",
+            "entry_price": 86.20038845448722,
+            "entry_time": "2020-02-12T00:00:00",
+            "exit_price": 83.7217462910142,
+            "exit_time": "2020-03-04T00:00:00",
+            "gross_pnl": 247.8642163473026,
+            "pnl": 247.8642163473026,
+            "size": 100
+          }
+        ]
+      },
+      "ml4t_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "native",
+          "exit_reason": "native",
+          "fills": "native",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "unavailable",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
+        },
+        "extra": {},
+        "fills": [
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+            "exit_reason": "",
+            "price": 99.71364930598455,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-03T00:00:00"
+          },
+          {
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+            "exit_reason": "trailing_stop",
+            "price": 87.2667981247593,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-02-03T00:00:00"
+          },
+          {
+            "asset": "TEST",
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+            "exit_reason": "",
+            "price": 86.20038845448721,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-02-12T00:00:00"
+          },
+          {
+            "asset": "TEST",
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+            "exit_reason": "trailing_stop",
+            "price": 83.7217462910142,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-03-04T00:00:00"
+          }
+        ],
+        "final_value": 1001492.5493344698,
+        "framework": "ml4t.backtest",
+        "num_trades": 2,
+        "total_pnl": 1492.5493344698334,
+        "trades": [
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Short",
+            "entry_price": 99.71364930598455,
+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 87.2667981247593,
+            "exit_reason": "trailing_stop",
+            "exit_time": "2020-02-03T00:00:00",
+            "pnl": 1244.6851181225247,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
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+            "direction": "Short",
+            "entry_price": 86.20038845448721,
+            "entry_time": "2020-02-12T00:00:00",
+            "exit_price": 83.7217462910142,
+            "exit_reason": "trailing_stop",
+            "exit_time": "2020-03-04T00:00:00",
+            "pnl": 247.8642163473014,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
+        "adapter": {
+          "module": "frameworks.backtrader",
+          "path": "validation/frameworks/backtrader.py"
+        },
+        "capabilities": {
+          "framework": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "unavailable",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          },
+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "risk_rules": "framework_adapter"
+        },
+        "digests": {
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+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "4dc2ca9d958a93592d8d31cfc054fccac9f460314cad187d221981191d6a9898",
+          "scenario": "51166032bf2c4582113ae77995f8db134af72ee7ccdca2dfa4b989fc48295e33"
+        },
+        "framework_target": {
+          "actual_version": "1.9.78.123",
+          "immutable_id": "sha256:9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+          "version": "1.9.78.123"
+        },
+        "input_digest": "3057fb1181d8b6bde3b0f0c71860dca5701293bcd956920c618e911bce7d0c67",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
+          "implementation": "cpython",
+          "version": "3.12.11"
+        },
+        "record_counts": {
+          "bars": 100,
+          "entry_signals": 2,
+          "exit_signals": 0,
+          "framework_closed_trades": 2,
+          "framework_fills": 4,
+          "framework_intents": 2,
+          "framework_orders": null,
+          "ml4t_closed_trades": 2,
+          "ml4t_fills": 4,
+          "ml4t_intents": 2,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "12",
@@ -429,8 +174484,305 @@
       "status": "pass"
     },
     {
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+        "checks": [
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+            "difference": 0,
+            "expected": 1,
+            "message": "Backtrader=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 100760.0,
+            "canonical_quantum": "0.00000001",
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+            "message": "Backtrader=$100,760.0000000000, ML4T=$100,760.0000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
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+          {
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+            "message": "Backtrader=$760.0000000000, ML4T=$760.0000000000 (exact_diff=$0.0000000000; diagnostic_limit=$1.0)",
+            "name": "total_pnl",
+            "passed": true
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+                "pnl": 759.9999999999994,
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+            "name": "trade_level_match",
+            "passed": true
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+                "quantity": 100.0,
+                "side": "buy",
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+              },
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+                "timestamp": "2020-01-13T00:00:00"
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "fill_level_match",
+            "passed": true
+          }
+        ],
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+        "passed": true,
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       "detail": null,
+      "duration_seconds": 0.18681644089519978,
       "framework": "backtrader",
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+          "exit_reason": "unavailable",
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+            "quantity": 100.0,
+            "side": "buy",
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+          },
+          {
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+        "framework": "Backtrader",
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+            "entry_time": "2020-01-03T00:00:00",
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+            "exit_time": "2020-01-13T00:00:00",
+            "gross_pnl": 759.9999999999994,
+            "pnl": 759.9999999999994,
+            "size": 100
+          }
+        ]
+      },
+      "ml4t_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "native",
+          "exit_reason": "native",
+          "fills": "native",
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+          "orders": "unavailable",
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+            "exit_reason": "",
+            "price": 100.39999999999999,
+            "quantity": 100.0,
+            "side": "buy",
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+          },
+          {
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+            "price": 108.0,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-13T00:00:00"
+          }
+        ],
+        "final_value": 100760.0,
+        "framework": "ml4t.backtest",
+        "num_trades": 1,
+        "total_pnl": 760.0,
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+          {
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+            "exit_price": 108.0,
+            "exit_reason": "take_profit",
+            "exit_time": "2020-01-13T00:00:00",
+            "pnl": 760.0,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
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+          "module": "frameworks.backtrader",
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+        "capabilities": {
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+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
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+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "risk_rules": "framework_adapter"
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+        "digests": {
+          "adapter": "9d3ee2845f1a37b484d9040c5237d7e0ba8974b0536b216305b3a2dd14fe8976",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "6f82ba4bceb1436137d9a4d844fa16973426eacd177ec088ab0f1e40ec12288d",
+          "scenario": "b39049d150f6fc2c71a16c642dc255e53e92c4840e949226036d175bccc4e1b0"
+        },
+        "framework_target": {
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+          "immutable_id": "sha256:9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+          "version": "1.9.78.123"
+        },
+        "input_digest": "6868775136fad190c5e2fffe0cb05f259b244161572731b86777972b78ea5fb5",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
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+          "version": "3.12.11"
+        },
+        "record_counts": {
+          "bars": 50,
+          "entry_signals": 1,
+          "exit_signals": 0,
+          "framework_closed_trades": 1,
+          "framework_fills": 2,
+          "framework_intents": 1,
+          "framework_orders": null,
+          "ml4t_closed_trades": 1,
+          "ml4t_fills": 2,
+          "ml4t_intents": 1,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "13",
@@ -438,8 +174790,305 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 1,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 1,
+            "message": "Backtrader=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 99859.95449782923,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 99859.95449782923,
+            "message": "Backtrader=$99,859.9544978292, ML4T=$99,859.9544978292 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
+          },
+          {
+            "actual": -140.04550217077485,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 1.0,
+            "difference": 0.0,
+            "expected": -140.04550217077485,
+            "message": "Backtrader=$-140.0455021708, ML4T=$-140.0455021708 (exact_diff=$0.0000000000; diagnostic_limit=$1.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
+            "actual": [
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+                "asset": "TEST",
+                "commission": 0.0,
+                "direction": "Long",
+                "entry_price": 100.3,
+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 98.89954497829228,
+                "exit_reason": "trailing_stop",
+                "exit_time": "2020-01-12T00:00:00",
+                "pnl": -140.04550217077121,
+                "size": 100.0
+              }
+            ],
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": null,
+            "difference": null,
+            "expected": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "direction": "Long",
+                "entry_price": 100.3,
+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 98.89954497829228,
+                "exit_time": "2020-01-12T00:00:00",
+                "gross_pnl": -140.04550217077139,
+                "pnl": -140.04550217077139,
+                "size": 100
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "trade_level_match",
+            "passed": true
+          },
+          {
+            "actual": [
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+                "commission": 0.0,
+                "exit_reason": "",
+                "price": 100.3,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T00:00:00"
+              },
+              {
+                "asset": "TEST",
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+                "exit_reason": "trailing_stop",
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+                "quantity": 100.0,
+                "side": "sell",
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+              }
+            ],
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": null,
+            "difference": null,
+            "expected": [
+              {
+                "asset": "TEST",
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+                "price": 100.3,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T00:00:00"
+              },
+              {
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+                "quantity": 100.0,
+                "side": "sell",
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+              }
+            ],
+            "message": "exact ordered match",
+            "name": "fill_level_match",
+            "passed": true
+          }
+        ],
+        "framework": "Backtrader",
+        "passed": true,
+        "scenario_id": "14"
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       "detail": null,
+      "duration_seconds": 0.21248964685946703,
       "framework": "backtrader",
+      "framework_result": {
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+          "exit_reason": "unavailable",
+          "fills": "native",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "native_filled_only",
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+            "price": 100.3,
+            "quantity": 100.0,
+            "side": "buy",
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+          },
+          {
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+            "quantity": 100.0,
+            "side": "sell",
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+        "framework": "Backtrader",
+        "num_trades": 1,
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+            "direction": "Long",
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+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 98.89954497829228,
+            "exit_time": "2020-01-12T00:00:00",
+            "gross_pnl": -140.04550217077139,
+            "pnl": -140.04550217077139,
+            "size": 100
+          }
+        ]
+      },
+      "ml4t_result": {
+        "capabilities": {
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+          "closed_trades": "native",
+          "exit_reason": "native",
+          "fills": "native",
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+        "extra": {},
+        "fills": [
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+            "price": 100.3,
+            "quantity": 100.0,
+            "side": "buy",
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+          },
+          {
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+            "exit_reason": "trailing_stop",
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+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-12T00:00:00"
+          }
+        ],
+        "final_value": 99859.95449782923,
+        "framework": "ml4t.backtest",
+        "num_trades": 1,
+        "total_pnl": -140.04550217077485,
+        "trades": [
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+            "direction": "Long",
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+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 98.89954497829228,
+            "exit_reason": "trailing_stop",
+            "exit_time": "2020-01-12T00:00:00",
+            "pnl": -140.04550217077121,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
+        "adapter": {
+          "module": "frameworks.backtrader",
+          "path": "validation/frameworks/backtrader.py"
+        },
+        "capabilities": {
+          "framework": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "unavailable",
+            "fills": "native",
+            "intents": "input_only",
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+            "orders": "native_filled_only",
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+            "rejections": "unavailable",
+            "terminal": "native"
+          },
+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
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+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "risk_rules": "framework_adapter"
+        },
+        "digests": {
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+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "6f82ba4bceb1436137d9a4d844fa16973426eacd177ec088ab0f1e40ec12288d",
+          "scenario": "875c440f742f71bb0793ff5c4c6a1a0080b961930e6d2a24493cfa3e4c1d80b5"
+        },
+        "framework_target": {
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+          "immutable_id": "sha256:9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+          "version": "1.9.78.123"
+        },
+        "input_digest": "515cb2ead81157a5d033173889d2a47af873b49bb750c0fedf91036506520aa2",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
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+          "version": "3.12.11"
+        },
+        "record_counts": {
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+          "entry_signals": 1,
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+          "framework_closed_trades": 1,
+          "framework_fills": 2,
+          "framework_intents": 1,
+          "framework_orders": null,
+          "ml4t_closed_trades": 1,
+          "ml4t_fills": 2,
+          "ml4t_intents": 1,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "14",
@@ -447,8 +175096,305 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 1,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 1,
+            "message": "Backtrader=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 99709.0,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 99709.0,
+            "message": "Backtrader=$99,709.0000000000, ML4T=$99,709.0000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
+          },
+          {
+            "actual": -291.0,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 1.0,
+            "difference": 0.0,
+            "expected": -291.0,
+            "message": "Backtrader=$-291.0000000000, ML4T=$-291.0000000000 (exact_diff=$0.0000000000; diagnostic_limit=$1.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
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       "framework": "backtrader",
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       "release_blocking": false,
       "required": true,
       "scenario_id": "15",
@@ -456,17 +175402,72989 @@
       "status": "pass"
     },
     {
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+        "comparison_protocol": {
+          "commission": "explicit scenario model or NoCommission",
+          "execution": "custom next-session open-price slippage model",
+          "fills": "native transactions with fees reconstructed from the configured model",
+          "risk_rules": "none",
+          "trade_records": "adapter_reconstructed_from_native_transactions"
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       "release_blocking": false,
       "required": true,
       "scenario_id": "01",
@@ -474,8 +248392,763 @@
       "status": "pass"
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       "detail": null,
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       "framework": "zipline",
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+          },
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+        "framework": "ml4t.backtest",
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+            "entry_time": "2020-01-03T00:00:00",
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+            "pnl": 805.8000000000011,
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+          {
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+            "direction": "Long",
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+            "entry_time": "2020-01-23T00:00:00",
+            "exit_price": 89.806,
+            "exit_reason": "signal",
+            "exit_time": "2020-01-28T00:00:00",
+            "pnl": -548.1000000000004,
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+            "pnl": 342.5,
+            "size": 100.0
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+            "exit_price": 80.836,
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+            "pnl": -504.0000000000009,
+            "size": 100.0
+          }
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+      "provenance": {
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+          "path": "validation/frameworks/zipline.py"
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+        "capabilities": {
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+            "closed_trades": "reconstructed",
+            "exit_reason": "unavailable",
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+            "intents": "input_only",
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+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
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+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
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+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "commission": "explicit scenario model or NoCommission",
+          "execution": "custom next-session open-price slippage model",
+          "fills": "native transactions with fees reconstructed from the configured model",
+          "risk_rules": "none",
+          "trade_records": "adapter_reconstructed_from_native_transactions"
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+        "digests": {
+          "adapter": "6e650c04c9604c3cfa40e597e16fa2e792d7e61fe2ebec56b7f46b5e33dde581",
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+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
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+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
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+          "scenario": "7db3751b770b7369c40f6b31fc757e7949b07dd5b56430e7226dc8db7d444e38"
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+        "framework_target": {
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+          "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+          "version": "3.1.1"
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+        "input_digest": "d4db92ee3483537d94893b614a21dcffdd4896daceb1d31cddd8e6343384e690",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
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+          "version": "3.12.11"
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+        "record_counts": {
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+          "entry_signals": 7,
+          "exit_signals": 8,
+          "framework_closed_trades": 5,
+          "framework_fills": 10,
+          "framework_intents": 15,
+          "framework_orders": null,
+          "ml4t_closed_trades": 5,
+          "ml4t_fills": 10,
+          "ml4t_intents": 15,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "02",
@@ -483,8 +249156,321 @@
       "status": "pass"
     },
     {
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+            "canonical_quantum": "1",
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+            "message": "Zipline=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
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+          {
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+            "expected": 99400.0,
+            "message": "Zipline=$99,400.0000000000, ML4T=$99,400.0000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
+          },
+          {
+            "actual": -600.0,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 5.0,
+            "difference": 0.0,
+            "expected": -600.0,
+            "message": "Zipline=$-600.0000000000, ML4T=$-600.0000000000 (exact_diff=$0.0000000000; diagnostic_limit=$5.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
+            "actual": 93.5,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 93.5,
+            "message": "Zipline=$93.5000000000, ML4T=$93.5000000000 (exact_diff=$0.0000000000; diagnostic_limit=$0.01)",
+            "name": "exit_price",
+            "passed": true
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+          {
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+                "entry_time": "2020-01-03T00:00:00",
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+                "size": 100.0
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+                "entry_time": "2020-01-03T21:00:00+00:00",
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+                "pnl": -600.0,
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+            "message": "exact ordered match",
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+            "message": "exact ordered match",
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       "framework": "zipline",
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+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          },
+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "commission": "explicit scenario model or NoCommission",
+          "execution": "custom next-session open-price slippage model",
+          "fills": "native transactions with fees reconstructed from the configured model",
+          "risk_rules": "adapter_emulated_daily_ohlc",
+          "trade_records": "adapter_reconstructed_from_native_transactions"
+        },
+        "digests": {
+          "adapter": "6e650c04c9604c3cfa40e597e16fa2e792d7e61fe2ebec56b7f46b5e33dde581",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "28b180f9c05b5422cd2c453999768d0d8b12915b1cf2946fa4b7d912f7ced322",
+          "scenario": "ad7292cedc685fa6c10032a0574f3e5da89b81dbb0f3a312cc2f5d83f5b454a1"
+        },
+        "framework_target": {
+          "actual_version": "3.1.1",
+          "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+          "version": "3.1.1"
+        },
+        "input_digest": "c35f1e258ae4d0cd8eed9125a530bea473632a5bb3f4558583c0818700906e96",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
+          "implementation": "cpython",
+          "version": "3.12.11"
+        },
+        "record_counts": {
+          "bars": 13,
+          "entry_signals": 1,
+          "exit_signals": 0,
+          "framework_closed_trades": 1,
+          "framework_fills": 2,
+          "framework_intents": 1,
+          "framework_orders": null,
+          "ml4t_closed_trades": 1,
+          "ml4t_fills": 2,
+          "ml4t_intents": 1,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "03",
@@ -492,8 +249478,321 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 1,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 1,
+            "message": "Zipline=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 101100.0,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 101100.0,
+            "message": "Zipline=$101,100.0000000000, ML4T=$101,100.0000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
+          },
+          {
+            "actual": 1100.0,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 5.0,
+            "difference": 0.0,
+            "expected": 1100.0,
+            "message": "Zipline=$1,100.0000000000, ML4T=$1,100.0000000000 (exact_diff=$0.0000000000; diagnostic_limit=$5.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
+            "actual": 111.5,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 111.5,
+            "message": "Zipline=$111.5000000000, ML4T=$111.5000000000 (exact_diff=$0.0000000000; diagnostic_limit=$0.01)",
+            "name": "exit_price",
+            "passed": true
+          },
+          {
+            "actual": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "direction": "Long",
+                "entry_price": 100.5,
+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 111.5,
+                "exit_reason": "take_profit",
+                "exit_time": "2020-01-09T00:00:00",
+                "pnl": 1100.0,
+                "size": 100.0
+              }
+            ],
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": null,
+            "difference": null,
+            "expected": [
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+                "asset": "TEST",
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+                "direction": "Long",
+                "entry_price": 100.5,
+                "entry_time": "2020-01-03T21:00:00+00:00",
+                "exit_price": 111.5,
+                "exit_time": "2020-01-09T21:00:00+00:00",
+                "pnl": 1100.0,
+                "size": 100.0
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "trade_level_match",
+            "passed": true
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+          {
+            "actual": [
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+                "exit_reason": "",
+                "price": 100.5,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T00:00:00"
+              },
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "exit_reason": "take_profit",
+                "price": 111.5,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-09T00:00:00"
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+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": null,
+            "difference": null,
+            "expected": [
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+                "price": 100.5,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T21:00:00+00:00"
+              },
+              {
+                "asset": "TEST",
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+                "price": 111.5,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-09T21:00:00+00:00"
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "fill_level_match",
+            "passed": true
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+        ],
+        "framework": "Zipline",
+        "passed": true,
+        "scenario_id": "04"
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       "detail": null,
+      "duration_seconds": 2.403656671056524,
       "framework": "zipline",
+      "framework_result": {
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+          "cash_flows": "aggregate_only",
+          "closed_trades": "reconstructed",
+          "exit_reason": "unavailable",
+          "fills": "reconstructed",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "native_filled_only",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
+        },
+        "extra": {
+          "exit_price": 111.5
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+        "fills": [
+          {
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+            "price": 100.5,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-01-03T21:00:00+00:00"
+          },
+          {
+            "asset": "TEST",
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+            "price": 111.5,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-09T21:00:00+00:00"
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+        "final_value": 101100.0,
+        "framework": "Zipline",
+        "num_trades": 1,
+        "total_pnl": 1100.0,
+        "trades": [
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+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 100.5,
+            "entry_time": "2020-01-03T21:00:00+00:00",
+            "exit_price": 111.5,
+            "exit_time": "2020-01-09T21:00:00+00:00",
+            "pnl": 1100.0,
+            "size": 100.0
+          }
+        ]
+      },
+      "ml4t_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "native",
+          "exit_reason": "native",
+          "fills": "native",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "unavailable",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
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+        "extra": {
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+        "fills": [
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+            "price": 100.5,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-01-03T00:00:00"
+          },
+          {
+            "asset": "TEST",
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+            "exit_reason": "take_profit",
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+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-09T00:00:00"
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+        "final_value": 101100.0,
+        "framework": "ml4t.backtest",
+        "num_trades": 1,
+        "total_pnl": 1100.0,
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+            "direction": "Long",
+            "entry_price": 100.5,
+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 111.5,
+            "exit_reason": "take_profit",
+            "exit_time": "2020-01-09T00:00:00",
+            "pnl": 1100.0,
+            "size": 100.0
+          }
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+      },
+      "provenance": {
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+          "path": "validation/frameworks/zipline.py"
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+        "capabilities": {
+          "framework": {
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+            "closed_trades": "reconstructed",
+            "exit_reason": "unavailable",
+            "fills": "reconstructed",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
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+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "commission": "explicit scenario model or NoCommission",
+          "execution": "custom next-session open-price slippage model",
+          "fills": "native transactions with fees reconstructed from the configured model",
+          "risk_rules": "adapter_emulated_daily_ohlc",
+          "trade_records": "adapter_reconstructed_from_native_transactions"
+        },
+        "digests": {
+          "adapter": "6e650c04c9604c3cfa40e597e16fa2e792d7e61fe2ebec56b7f46b5e33dde581",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
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+          "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+          "version": "3.1.1"
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+        "input_digest": "9f43427f7ad70fc963aeec58cf8867b5646e88bd608ec489964f802a2c98a57d",
+        "ml4t": {
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+          "dirty": false
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+        "python": {
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+          "version": "3.12.11"
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+        "record_counts": {
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+          "ml4t_intents": 1,
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+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "04",
@@ -501,8 +249800,777 @@
       "status": "pass"
     },
     {
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+        "checks": [
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+            "message": "Zipline=5, ML4T=5, exact_diff=0; diagnostic_limit=0",
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+            "passed": true
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+            "expected": -380.8112999999721,
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+            "name": "total_pnl",
+            "passed": true
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+            "canonical_quantum": "0.00000001",
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+            "difference": 1.4210854715202004e-14,
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+            "message": "Zipline=$89.7113000000, ML4T=$89.7113000000 (exact_diff=$0.0000000000; diagnostic_limit=$0.01)",
+            "name": "total_commission",
+            "passed": true
+          },
+          {
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+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 108.566,
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+                "entry_price": 95.287,
+                "entry_time": "2020-01-23T00:00:00",
+                "exit_price": 89.806,
+                "exit_reason": "signal",
+                "exit_time": "2020-01-28T00:00:00",
+                "pnl": -566.6093000000004,
+                "size": 100.0
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+              {
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+                "pnl": -404.1234999999993,
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+                "exit_price": 85.712,
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+                "exit_time": "2020-03-18T00:00:00",
+                "pnl": 325.7001,
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+              {
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+                "entry_time": "2020-04-02T00:00:00",
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+                "pnl": -520.6712000000009,
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+            "canonical_quantum": "0.00000001",
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+                "pnl": -520.6712000000007,
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+            "message": "exact ordered match",
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+            "closed_trades": "reconstructed",
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+        },
+        "comparison_protocol": {
+          "commission": "explicit scenario model or NoCommission",
+          "execution": "custom next-session open-price slippage model",
+          "fills": "native transactions with fees reconstructed from the configured model",
+          "risk_rules": "none",
+          "trade_records": "adapter_reconstructed_from_native_transactions"
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+          "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+          "version": "3.1.1"
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+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
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+        "python": {
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+          "ml4t_closed_trades": 5,
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       "release_blocking": false,
       "required": true,
       "scenario_id": "05",
@@ -510,8 +250578,777 @@
       "status": "pass"
     },
     {
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+            "passed": true
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+          {
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+            "canonical_quantum": "0.00000001",
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+            "expected": -296.0999999999767,
+            "message": "Zipline=$-296.1000000000, ML4T=$-296.1000000000 (exact_diff=$0.0000000000; diagnostic_limit=$5.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
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+            "canonical_quantum": "0.00000001",
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+            "expected": 5.0,
+            "message": "Zipline=$5.0000000000, ML4T=$5.0000000000 (exact_diff=$0.0000000000; diagnostic_limit=$0.01)",
+            "name": "total_commission",
+            "passed": true
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+          },
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+            "exit_price": 89.806,
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+          },
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+          },
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+            "pnl": -505.0000000000009,
+            "size": 100.0
+          }
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+          "path": "validation/frameworks/zipline.py"
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+        "capabilities": {
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+            "closed_trades": "reconstructed",
+            "exit_reason": "unavailable",
+            "fills": "reconstructed",
+            "intents": "input_only",
+            "open_trades": "unavailable",
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+            "rejections": "unavailable",
+            "terminal": "native"
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+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
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+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "commission": "explicit scenario model or NoCommission",
+          "execution": "custom next-session open-price slippage model",
+          "fills": "native transactions with fees reconstructed from the configured model",
+          "risk_rules": "none",
+          "trade_records": "adapter_reconstructed_from_native_transactions"
+        },
+        "digests": {
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+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
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+          "scenario": "523af2137e8233ef65d03ffb841e91525f65f7c3057b3111e86aedbf0a973fb7"
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+        "framework_target": {
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+          "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+          "version": "3.1.1"
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+        "input_digest": "d4db92ee3483537d94893b614a21dcffdd4896daceb1d31cddd8e6343384e690",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
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+          "version": "3.12.11"
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+        "record_counts": {
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+          "entry_signals": 7,
+          "exit_signals": 8,
+          "framework_closed_trades": 5,
+          "framework_fills": 10,
+          "framework_intents": 15,
+          "framework_orders": null,
+          "ml4t_closed_trades": 5,
+          "ml4t_fills": 10,
+          "ml4t_intents": 15,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "06",
@@ -519,8 +251356,763 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 5,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 5,
+            "message": "Zipline=5, ML4T=5, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
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+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
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@@ -528,8 +252120,763 @@
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+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 108.457434,
+            "exit_reason": "signal",
+            "exit_time": "2020-01-08T00:00:00",
+            "pnl": 784.892600000001,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 95.382287,
+            "entry_time": "2020-01-23T00:00:00",
+            "exit_price": 89.716194,
+            "exit_reason": "signal",
+            "exit_time": "2020-01-28T00:00:00",
+            "pnl": -566.6093000000001,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 86.140054,
+            "entry_time": "2020-02-12T00:00:00",
+            "exit_price": 82.09881899999999,
+            "exit_reason": "signal",
+            "exit_time": "2020-02-27T00:00:00",
+            "pnl": -404.1235000000015,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 82.369287,
+            "entry_time": "2020-03-03T00:00:00",
+            "exit_price": 85.626288,
+            "exit_reason": "signal",
+            "exit_time": "2020-03-18T00:00:00",
+            "pnl": 325.7001,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 85.961876,
+            "entry_time": "2020-04-02T00:00:00",
+            "exit_price": 80.755164,
+            "exit_reason": "signal",
+            "exit_time": "2020-04-07T00:00:00",
+            "pnl": -520.6712000000016,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
+        "adapter": {
+          "module": "frameworks.zipline",
+          "path": "validation/frameworks/zipline.py"
+        },
+        "capabilities": {
+          "framework": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "reconstructed",
+            "exit_reason": "unavailable",
+            "fills": "reconstructed",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          },
+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "commission": "explicit scenario model or NoCommission",
+          "execution": "custom next-session open-price slippage model",
+          "fills": "native transactions with fees reconstructed from the configured model",
+          "risk_rules": "none",
+          "trade_records": "adapter_reconstructed_from_native_transactions"
+        },
+        "digests": {
+          "adapter": "6e650c04c9604c3cfa40e597e16fa2e792d7e61fe2ebec56b7f46b5e33dde581",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "4c1b7206fe55cebbe9f41acb88a30dac343e4ce973e92ad60c236a27ef021548",
+          "scenario": "d2d36326d5a7ec88f577088205574b8a9f6dab9661ed6813d190c138c4c8208f"
+        },
+        "framework_target": {
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+          "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+          "version": "3.1.1"
+        },
+        "input_digest": "d4db92ee3483537d94893b614a21dcffdd4896daceb1d31cddd8e6343384e690",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
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+          "version": "3.12.11"
+        },
+        "record_counts": {
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+          "entry_signals": 7,
+          "exit_signals": 8,
+          "framework_closed_trades": 5,
+          "framework_fills": 10,
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+          "ml4t_closed_trades": 5,
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+          "ml4t_intents": 15,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "08",
@@ -537,8 +252884,421 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 2,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 2,
+            "message": "Zipline=2, ML4T=2, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 99742.19999999998,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 1.4551915228366852e-11,
+            "expected": 99742.2,
+            "message": "Zipline=$99,742.2000000000, ML4T=$99,742.2000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
+          },
+          {
+            "actual": -257.80000000001746,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 5.0,
+            "difference": 1.4551915228366852e-11,
+            "expected": -257.8000000000029,
+            "message": "Zipline=$-257.8000000000, ML4T=$-257.8000000000 (exact_diff=$0.0000000000; diagnostic_limit=$5.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
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+                "direction": "Long",
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+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 101.207,
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+                "exit_time": "2020-02-04T00:00:00",
+                "pnl": 49.599999999998545,
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+              },
+              {
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+                "direction": "Long",
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+                "entry_time": "2020-02-12T00:00:00",
+                "exit_price": 95.356,
+                "exit_reason": "trailing_stop",
+                "exit_time": "2020-03-05T00:00:00",
+                "pnl": -307.40000000000146,
+                "size": 100.0
+              }
+            ],
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": null,
+            "difference": null,
+            "expected": [
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+                "direction": "Long",
+                "entry_price": 100.711,
+                "entry_time": "2020-01-03T21:00:00+00:00",
+                "exit_price": 101.20700000000001,
+                "exit_time": "2020-02-04T21:00:00+00:00",
+                "pnl": 49.60000000000093,
+                "size": 100.0
+              },
+              {
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+                "entry_time": "2020-02-12T21:00:00+00:00",
+                "exit_price": 95.35600000000001,
+                "exit_time": "2020-03-05T21:00:00+00:00",
+                "pnl": -307.3999999999998,
+                "size": 100.0
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "trade_level_match",
+            "passed": true
+          },
+          {
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+                "commission": 0.0,
+                "exit_reason": "",
+                "price": 100.711,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T00:00:00"
+              },
+              {
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+                "exit_reason": "trailing_stop",
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+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-02-04T00:00:00"
+              },
+              {
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+                "commission": 0.0,
+                "exit_reason": "",
+                "price": 98.43,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-02-12T00:00:00"
+              },
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "exit_reason": "trailing_stop",
+                "price": 95.356,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-03-05T00:00:00"
+              }
+            ],
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": null,
+            "difference": null,
+            "expected": [
+              {
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+                "commission": 0.0,
+                "price": 100.711,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T21:00:00+00:00"
+              },
+              {
+                "asset": "TEST",
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+                "price": 101.20700000000001,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-02-04T21:00:00+00:00"
+              },
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "price": 98.43,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-02-12T21:00:00+00:00"
+              },
+              {
+                "asset": "TEST",
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+                "price": 95.35600000000001,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-03-05T21:00:00+00:00"
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "fill_level_match",
+            "passed": true
+          }
+        ],
+        "framework": "Zipline",
+        "passed": true,
+        "scenario_id": "09"
+      },
       "detail": null,
+      "duration_seconds": 2.099665637128055,
       "framework": "zipline",
+      "framework_result": {
+        "capabilities": {
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+          "closed_trades": "reconstructed",
+          "exit_reason": "unavailable",
+          "fills": "reconstructed",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "native_filled_only",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
+        },
+        "extra": {},
+        "fills": [
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+            "price": 100.711,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-01-03T21:00:00+00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "price": 101.20700000000001,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-02-04T21:00:00+00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "price": 98.43,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-02-12T21:00:00+00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "price": 95.35600000000001,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-03-05T21:00:00+00:00"
+          }
+        ],
+        "final_value": 99742.2,
+        "framework": "Zipline",
+        "num_trades": 2,
+        "total_pnl": -257.8000000000029,
+        "trades": [
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 100.711,
+            "entry_time": "2020-01-03T21:00:00+00:00",
+            "exit_price": 101.20700000000001,
+            "exit_time": "2020-02-04T21:00:00+00:00",
+            "pnl": 49.60000000000093,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 98.43,
+            "entry_time": "2020-02-12T21:00:00+00:00",
+            "exit_price": 95.35600000000001,
+            "exit_time": "2020-03-05T21:00:00+00:00",
+            "pnl": -307.3999999999998,
+            "size": 100.0
+          }
+        ]
+      },
+      "ml4t_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "native",
+          "exit_reason": "native",
+          "fills": "native",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "unavailable",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
+        },
+        "extra": {},
+        "fills": [
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "exit_reason": "",
+            "price": 100.711,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-01-03T00:00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "exit_reason": "trailing_stop",
+            "price": 101.207,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-02-04T00:00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "exit_reason": "",
+            "price": 98.43,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-02-12T00:00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "exit_reason": "trailing_stop",
+            "price": 95.356,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-03-05T00:00:00"
+          }
+        ],
+        "final_value": 99742.19999999998,
+        "framework": "ml4t.backtest",
+        "num_trades": 2,
+        "total_pnl": -257.80000000001746,
+        "trades": [
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 100.711,
+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 101.207,
+            "exit_reason": "trailing_stop",
+            "exit_time": "2020-02-04T00:00:00",
+            "pnl": 49.599999999998545,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 98.43,
+            "entry_time": "2020-02-12T00:00:00",
+            "exit_price": 95.356,
+            "exit_reason": "trailing_stop",
+            "exit_time": "2020-03-05T00:00:00",
+            "pnl": -307.40000000000146,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
+        "adapter": {
+          "module": "frameworks.zipline",
+          "path": "validation/frameworks/zipline.py"
+        },
+        "capabilities": {
+          "framework": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "reconstructed",
+            "exit_reason": "unavailable",
+            "fills": "reconstructed",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          },
+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "commission": "explicit scenario model or NoCommission",
+          "execution": "custom next-session open-price slippage model",
+          "fills": "native transactions with fees reconstructed from the configured model",
+          "risk_rules": "adapter_emulated_daily_ohlc",
+          "trade_records": "adapter_reconstructed_from_native_transactions"
+        },
+        "digests": {
+          "adapter": "6e650c04c9604c3cfa40e597e16fa2e792d7e61fe2ebec56b7f46b5e33dde581",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "d7768c1dbc7e300243ff0eac676d628b4af4e347896a67b1623a5f0aa6c053a3",
+          "scenario": "80d8dea99e845ad7f708cc42fb94f66feababcf8b6814e3096300af1f4b709c2"
+        },
+        "framework_target": {
+          "actual_version": "3.1.1",
+          "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+          "version": "3.1.1"
+        },
+        "input_digest": "de6e2060eccdf8f068669911169eb7a3d28af0622a7a840f637acb82db930a7e",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
+          "implementation": "cpython",
+          "version": "3.12.11"
+        },
+        "record_counts": {
+          "bars": 69,
+          "entry_signals": 2,
+          "exit_signals": 0,
+          "framework_closed_trades": 2,
+          "framework_fills": 4,
+          "framework_intents": 2,
+          "framework_orders": null,
+          "ml4t_closed_trades": 2,
+          "ml4t_fills": 4,
+          "ml4t_intents": 2,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "09",
@@ -546,8 +253306,13 @@
       "status": "pass"
     },
     {
+      "comparison": null,
       "detail": "Scenario explicitly excludes this framework",
+      "duration_seconds": 3.6640558391809464e-06,
       "framework": "zipline",
+      "framework_result": null,
+      "ml4t_result": null,
+      "provenance": null,
       "release_blocking": false,
       "required": false,
       "scenario_id": "10",
@@ -555,8 +253320,763 @@
       "status": "unsupported"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 5,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 5,
+            "message": "Zipline=5, ML4T=5, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 1001679.7,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 1001679.7,
+            "message": "Zipline=$1,001,679.7000000000, ML4T=$1,001,679.7000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
+          },
+          {
+            "actual": 1679.6999999999534,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 5.0,
+            "difference": 0.0,
+            "expected": 1679.6999999999534,
+            "message": "Zipline=$1,679.7000000000, ML4T=$1,679.7000000000 (exact_diff=$0.0000000000; diagnostic_limit=$5.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
+            "actual": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "direction": "Short",
+                "entry_price": 107.718,
+                "entry_time": "2020-01-08T00:00:00",
+                "exit_price": 93.4,
+                "exit_reason": "signal",
+                "exit_time": "2020-01-21T00:00:00",
+                "pnl": 1431.800000000001,
+                "size": 100.0
+              },
+              {
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+          "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+          "version": "3.1.1"
+        },
+        "input_digest": "517a65764277b104abf7848a9875d5f09febfddffb82d8fd9318f724ff1aaa86",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
+          "implementation": "cpython",
+          "version": "3.12.11"
+        },
+        "record_counts": {
+          "bars": 137,
+          "entry_signals": 7,
+          "exit_signals": 8,
+          "framework_closed_trades": 5,
+          "framework_fills": 10,
+          "framework_intents": 15,
+          "framework_orders": null,
+          "ml4t_closed_trades": 5,
+          "ml4t_fills": 10,
+          "ml4t_intents": 15,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "11",
@@ -564,8 +254084,421 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 2,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 2,
+            "message": "Zipline=2, ML4T=2, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 1001259.3,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 1001259.3,
+            "message": "Zipline=$1,001,259.3000000000, ML4T=$1,001,259.3000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
+          },
+          {
+            "actual": 1259.3000000000466,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 5.0,
+            "difference": 0.0,
+            "expected": 1259.3000000000466,
+            "message": "Zipline=$1,259.3000000000, ML4T=$1,259.3000000000 (exact_diff=$0.0000000000; diagnostic_limit=$5.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
+            "actual": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "direction": "Short",
+                "entry_price": 99.714,
+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 88.805,
+                "exit_reason": "trailing_stop",
+                "exit_time": "2020-02-04T00:00:00",
+                "pnl": 1090.8999999999996,
+                "size": 100.0
+              },
+              {
+                "asset": "TEST",
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+                "direction": "Short",
+                "entry_price": 86.2,
+                "entry_time": "2020-02-12T00:00:00",
+                "exit_price": 84.516,
+                "exit_reason": "trailing_stop",
+                "exit_time": "2020-03-05T00:00:00",
+                "pnl": 168.39999999999964,
+                "size": 100.0
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+            ],
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": null,
+            "difference": null,
+            "expected": [
+              {
+                "asset": "TEST",
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+                "direction": "Short",
+                "entry_price": 99.714,
+                "entry_time": "2020-01-03T21:00:00+00:00",
+                "exit_price": 88.805,
+                "exit_time": "2020-02-04T21:00:00+00:00",
+                "pnl": 1090.8999999999992,
+                "size": 100.0
+              },
+              {
+                "asset": "TEST",
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+                "direction": "Short",
+                "entry_price": 86.2,
+                "entry_time": "2020-02-12T21:00:00+00:00",
+                "exit_price": 84.516,
+                "exit_time": "2020-03-05T21:00:00+00:00",
+                "pnl": 168.39999999999975,
+                "size": 100.0
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "trade_level_match",
+            "passed": true
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+                "exit_reason": "",
+                "price": 99.714,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-03T00:00:00"
+              },
+              {
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+                "exit_reason": "trailing_stop",
+                "price": 88.805,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-02-04T00:00:00"
+              },
+              {
+                "asset": "TEST",
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+                "exit_reason": "",
+                "price": 86.2,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-02-12T00:00:00"
+              },
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "exit_reason": "trailing_stop",
+                "price": 84.516,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-03-05T00:00:00"
+              }
+            ],
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": null,
+            "difference": null,
+            "expected": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "price": 99.714,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-03T21:00:00+00:00"
+              },
+              {
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+                "price": 88.805,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-02-04T21:00:00+00:00"
+              },
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "price": 86.2,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-02-12T21:00:00+00:00"
+              },
+              {
+                "asset": "TEST",
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+                "price": 84.516,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-03-05T21:00:00+00:00"
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "fill_level_match",
+            "passed": true
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+        ],
+        "framework": "Zipline",
+        "passed": true,
+        "scenario_id": "12"
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       "detail": null,
+      "duration_seconds": 2.3570257059764117,
       "framework": "zipline",
+      "framework_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "reconstructed",
+          "exit_reason": "unavailable",
+          "fills": "reconstructed",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "native_filled_only",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
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+        "extra": {},
+        "fills": [
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+            "price": 99.714,
+            "quantity": 100.0,
+            "side": "sell",
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+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "price": 88.805,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-02-04T21:00:00+00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "price": 86.2,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-02-12T21:00:00+00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "price": 84.516,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-03-05T21:00:00+00:00"
+          }
+        ],
+        "final_value": 1001259.3,
+        "framework": "Zipline",
+        "num_trades": 2,
+        "total_pnl": 1259.3000000000466,
+        "trades": [
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Short",
+            "entry_price": 99.714,
+            "entry_time": "2020-01-03T21:00:00+00:00",
+            "exit_price": 88.805,
+            "exit_time": "2020-02-04T21:00:00+00:00",
+            "pnl": 1090.8999999999992,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Short",
+            "entry_price": 86.2,
+            "entry_time": "2020-02-12T21:00:00+00:00",
+            "exit_price": 84.516,
+            "exit_time": "2020-03-05T21:00:00+00:00",
+            "pnl": 168.39999999999975,
+            "size": 100.0
+          }
+        ]
+      },
+      "ml4t_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "native",
+          "exit_reason": "native",
+          "fills": "native",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "unavailable",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
+        },
+        "extra": {},
+        "fills": [
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+            "commission": 0.0,
+            "exit_reason": "",
+            "price": 99.714,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-03T00:00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "exit_reason": "trailing_stop",
+            "price": 88.805,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-02-04T00:00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "exit_reason": "",
+            "price": 86.2,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-02-12T00:00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "exit_reason": "trailing_stop",
+            "price": 84.516,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-03-05T00:00:00"
+          }
+        ],
+        "final_value": 1001259.3,
+        "framework": "ml4t.backtest",
+        "num_trades": 2,
+        "total_pnl": 1259.3000000000466,
+        "trades": [
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Short",
+            "entry_price": 99.714,
+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 88.805,
+            "exit_reason": "trailing_stop",
+            "exit_time": "2020-02-04T00:00:00",
+            "pnl": 1090.8999999999996,
+            "size": 100.0
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Short",
+            "entry_price": 86.2,
+            "entry_time": "2020-02-12T00:00:00",
+            "exit_price": 84.516,
+            "exit_reason": "trailing_stop",
+            "exit_time": "2020-03-05T00:00:00",
+            "pnl": 168.39999999999964,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
+        "adapter": {
+          "module": "frameworks.zipline",
+          "path": "validation/frameworks/zipline.py"
+        },
+        "capabilities": {
+          "framework": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "reconstructed",
+            "exit_reason": "unavailable",
+            "fills": "reconstructed",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          },
+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "commission": "explicit scenario model or NoCommission",
+          "execution": "custom next-session open-price slippage model",
+          "fills": "native transactions with fees reconstructed from the configured model",
+          "risk_rules": "adapter_emulated_daily_ohlc",
+          "trade_records": "adapter_reconstructed_from_native_transactions"
+        },
+        "digests": {
+          "adapter": "6e650c04c9604c3cfa40e597e16fa2e792d7e61fe2ebec56b7f46b5e33dde581",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "1959f1b057e8b49dd44d9c7d7252eb2d9b40d1d7e035752ca4794fd596d502fd",
+          "scenario": "51166032bf2c4582113ae77995f8db134af72ee7ccdca2dfa4b989fc48295e33"
+        },
+        "framework_target": {
+          "actual_version": "3.1.1",
+          "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+          "version": "3.1.1"
+        },
+        "input_digest": "b211286d7dde78c905f246c3d56fb3c84b7f7de3c5f4a124c6b33680c37aa37d",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
+          "implementation": "cpython",
+          "version": "3.12.11"
+        },
+        "record_counts": {
+          "bars": 69,
+          "entry_signals": 2,
+          "exit_signals": 0,
+          "framework_closed_trades": 2,
+          "framework_fills": 4,
+          "framework_intents": 2,
+          "framework_orders": null,
+          "ml4t_closed_trades": 2,
+          "ml4t_fills": 4,
+          "ml4t_intents": 2,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "12",
@@ -573,8 +254506,307 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 1,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 1,
+            "message": "Zipline=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 100803.1,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 100803.1,
+            "message": "Zipline=$100,803.1000000000, ML4T=$100,803.1000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
+          },
+          {
+            "actual": 803.1000000000058,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 5.0,
+            "difference": 0.0,
+            "expected": 803.1000000000058,
+            "message": "Zipline=$803.1000000000, ML4T=$803.1000000000 (exact_diff=$0.0000000000; diagnostic_limit=$5.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
+            "actual": [
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+                "asset": "TEST",
+                "commission": 0.0,
+                "direction": "Long",
+                "entry_price": 100.4,
+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 108.431,
+                "exit_reason": "take_profit",
+                "exit_time": "2020-01-14T00:00:00",
+                "pnl": 803.1000000000004,
+                "size": 100.0
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+            "canonical_quantum": "0.00000001",
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+            "expected": [
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+                "direction": "Long",
+                "entry_price": 100.4,
+                "entry_time": "2020-01-03T21:00:00+00:00",
+                "exit_price": 108.431,
+                "exit_time": "2020-01-14T21:00:00+00:00",
+                "pnl": 803.0999999999992,
+                "size": 100.0
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "trade_level_match",
+            "passed": true
+          },
+          {
+            "actual": [
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+                "commission": 0.0,
+                "exit_reason": "",
+                "price": 100.4,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T00:00:00"
+              },
+              {
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+                "exit_reason": "take_profit",
+                "price": 108.431,
+                "quantity": 100.0,
+                "side": "sell",
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+            "canonical_quantum": "0.00000001",
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+            "difference": null,
+            "expected": [
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+                "price": 100.4,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T21:00:00+00:00"
+              },
+              {
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+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-14T21:00:00+00:00"
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "fill_level_match",
+            "passed": true
+          }
+        ],
+        "framework": "Zipline",
+        "passed": true,
+        "scenario_id": "13"
+      },
       "detail": null,
+      "duration_seconds": 2.314784521004185,
       "framework": "zipline",
+      "framework_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "reconstructed",
+          "exit_reason": "unavailable",
+          "fills": "reconstructed",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "native_filled_only",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
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+        "extra": {},
+        "fills": [
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+            "price": 100.4,
+            "quantity": 100.0,
+            "side": "buy",
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+          },
+          {
+            "asset": "TEST",
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+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-14T21:00:00+00:00"
+          }
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+        "final_value": 100803.1,
+        "framework": "Zipline",
+        "num_trades": 1,
+        "total_pnl": 803.1000000000058,
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+            "direction": "Long",
+            "entry_price": 100.4,
+            "entry_time": "2020-01-03T21:00:00+00:00",
+            "exit_price": 108.431,
+            "exit_time": "2020-01-14T21:00:00+00:00",
+            "pnl": 803.0999999999992,
+            "size": 100.0
+          }
+        ]
+      },
+      "ml4t_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "native",
+          "exit_reason": "native",
+          "fills": "native",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "unavailable",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
+        },
+        "extra": {},
+        "fills": [
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+            "price": 100.4,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-01-03T00:00:00"
+          },
+          {
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+            "exit_reason": "take_profit",
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+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-14T00:00:00"
+          }
+        ],
+        "final_value": 100803.1,
+        "framework": "ml4t.backtest",
+        "num_trades": 1,
+        "total_pnl": 803.1000000000058,
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+            "direction": "Long",
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+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 108.431,
+            "exit_reason": "take_profit",
+            "exit_time": "2020-01-14T00:00:00",
+            "pnl": 803.1000000000004,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
+        "adapter": {
+          "module": "frameworks.zipline",
+          "path": "validation/frameworks/zipline.py"
+        },
+        "capabilities": {
+          "framework": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "reconstructed",
+            "exit_reason": "unavailable",
+            "fills": "reconstructed",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          },
+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "commission": "explicit scenario model or NoCommission",
+          "execution": "custom next-session open-price slippage model",
+          "fills": "native transactions with fees reconstructed from the configured model",
+          "risk_rules": "adapter_emulated_daily_ohlc",
+          "trade_records": "adapter_reconstructed_from_native_transactions"
+        },
+        "digests": {
+          "adapter": "6e650c04c9604c3cfa40e597e16fa2e792d7e61fe2ebec56b7f46b5e33dde581",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "d7768c1dbc7e300243ff0eac676d628b4af4e347896a67b1623a5f0aa6c053a3",
+          "scenario": "b39049d150f6fc2c71a16c642dc255e53e92c4840e949226036d175bccc4e1b0"
+        },
+        "framework_target": {
+          "actual_version": "3.1.1",
+          "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+          "version": "3.1.1"
+        },
+        "input_digest": "79590cf03ef0f3e90985c032e8f555ecdf9add3fc21908924a49e7d706b5f041",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
+          "implementation": "cpython",
+          "version": "3.12.11"
+        },
+        "record_counts": {
+          "bars": 34,
+          "entry_signals": 1,
+          "exit_signals": 0,
+          "framework_closed_trades": 1,
+          "framework_fills": 2,
+          "framework_intents": 1,
+          "framework_orders": null,
+          "ml4t_closed_trades": 1,
+          "ml4t_fills": 2,
+          "ml4t_intents": 1,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "13",
@@ -582,8 +254814,307 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 1,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 1,
+            "message": "Zipline=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 99899.7,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 99899.7,
+            "message": "Zipline=$99,899.7000000000, ML4T=$99,899.7000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
+          },
+          {
+            "actual": -100.30000000000291,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 5.0,
+            "difference": 0.0,
+            "expected": -100.30000000000291,
+            "message": "Zipline=$-100.3000000000, ML4T=$-100.3000000000 (exact_diff=$0.0000000000; diagnostic_limit=$5.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
+            "actual": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "direction": "Long",
+                "entry_price": 100.3,
+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 99.297,
+                "exit_reason": "trailing_stop",
+                "exit_time": "2020-01-14T00:00:00",
+                "pnl": -100.30000000000109,
+                "size": 100.0
+              }
+            ],
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": null,
+            "difference": null,
+            "expected": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "direction": "Long",
+                "entry_price": 100.3,
+                "entry_time": "2020-01-03T21:00:00+00:00",
+                "exit_price": 99.297,
+                "exit_time": "2020-01-14T21:00:00+00:00",
+                "pnl": -100.30000000000001,
+                "size": 100.0
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "trade_level_match",
+            "passed": true
+          },
+          {
+            "actual": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "exit_reason": "",
+                "price": 100.3,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T00:00:00"
+              },
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "exit_reason": "trailing_stop",
+                "price": 99.297,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-14T00:00:00"
+              }
+            ],
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": null,
+            "difference": null,
+            "expected": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "price": 100.3,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T21:00:00+00:00"
+              },
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "price": 99.297,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-14T21:00:00+00:00"
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "fill_level_match",
+            "passed": true
+          }
+        ],
+        "framework": "Zipline",
+        "passed": true,
+        "scenario_id": "14"
+      },
       "detail": null,
+      "duration_seconds": 2.0954640838317573,
       "framework": "zipline",
+      "framework_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "reconstructed",
+          "exit_reason": "unavailable",
+          "fills": "reconstructed",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "native_filled_only",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
+        },
+        "extra": {},
+        "fills": [
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "price": 100.3,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-01-03T21:00:00+00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "price": 99.297,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-14T21:00:00+00:00"
+          }
+        ],
+        "final_value": 99899.7,
+        "framework": "Zipline",
+        "num_trades": 1,
+        "total_pnl": -100.30000000000291,
+        "trades": [
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 100.3,
+            "entry_time": "2020-01-03T21:00:00+00:00",
+            "exit_price": 99.297,
+            "exit_time": "2020-01-14T21:00:00+00:00",
+            "pnl": -100.30000000000001,
+            "size": 100.0
+          }
+        ]
+      },
+      "ml4t_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "native",
+          "exit_reason": "native",
+          "fills": "native",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "unavailable",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
+        },
+        "extra": {},
+        "fills": [
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "exit_reason": "",
+            "price": 100.3,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-01-03T00:00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "exit_reason": "trailing_stop",
+            "price": 99.297,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-14T00:00:00"
+          }
+        ],
+        "final_value": 99899.7,
+        "framework": "ml4t.backtest",
+        "num_trades": 1,
+        "total_pnl": -100.30000000000291,
+        "trades": [
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 100.3,
+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 99.297,
+            "exit_reason": "trailing_stop",
+            "exit_time": "2020-01-14T00:00:00",
+            "pnl": -100.30000000000109,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
+        "adapter": {
+          "module": "frameworks.zipline",
+          "path": "validation/frameworks/zipline.py"
+        },
+        "capabilities": {
+          "framework": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "reconstructed",
+            "exit_reason": "unavailable",
+            "fills": "reconstructed",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          },
+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "commission": "explicit scenario model or NoCommission",
+          "execution": "custom next-session open-price slippage model",
+          "fills": "native transactions with fees reconstructed from the configured model",
+          "risk_rules": "adapter_emulated_daily_ohlc",
+          "trade_records": "adapter_reconstructed_from_native_transactions"
+        },
+        "digests": {
+          "adapter": "6e650c04c9604c3cfa40e597e16fa2e792d7e61fe2ebec56b7f46b5e33dde581",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "d7768c1dbc7e300243ff0eac676d628b4af4e347896a67b1623a5f0aa6c053a3",
+          "scenario": "875c440f742f71bb0793ff5c4c6a1a0080b961930e6d2a24493cfa3e4c1d80b5"
+        },
+        "framework_target": {
+          "actual_version": "3.1.1",
+          "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+          "version": "3.1.1"
+        },
+        "input_digest": "939287c002cf7b640b21c5859335249e1db1400c7d94dd37f62a7f078ba31fad",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
+          "implementation": "cpython",
+          "version": "3.12.11"
+        },
+        "record_counts": {
+          "bars": 34,
+          "entry_signals": 1,
+          "exit_signals": 0,
+          "framework_closed_trades": 1,
+          "framework_fills": 2,
+          "framework_intents": 1,
+          "framework_orders": null,
+          "ml4t_closed_trades": 1,
+          "ml4t_fills": 2,
+          "ml4t_intents": 1,
+          "ml4t_orders": null
+        }
+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "14",
@@ -591,8 +255122,307 @@
       "status": "pass"
     },
     {
+      "comparison": {
+        "checks": [
+          {
+            "actual": 1,
+            "canonical_quantum": "1",
+            "diagnostic_limit": 0,
+            "difference": 0,
+            "expected": 1,
+            "message": "Zipline=1, ML4T=1, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 99737.3,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 0.01,
+            "difference": 0.0,
+            "expected": 99737.3,
+            "message": "Zipline=$99,737.3000000000, ML4T=$99,737.3000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.01%)",
+            "name": "final_value",
+            "passed": true
+          },
+          {
+            "actual": -262.6999999999971,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 10.0,
+            "difference": 0.0,
+            "expected": -262.6999999999971,
+            "message": "Zipline=$-262.7000000000, ML4T=$-262.7000000000 (exact_diff=$0.0000000000; diagnostic_limit=$10.0)",
+            "name": "total_pnl",
+            "passed": true
+          },
+          {
+            "actual": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "direction": "Long",
+                "entry_price": 96.7,
+                "entry_time": "2020-01-03T00:00:00",
+                "exit_price": 94.073,
+                "exit_reason": "trailing_stop",
+                "exit_time": "2020-01-07T00:00:00",
+                "pnl": -262.7000000000007,
+                "size": 100.0
+              }
+            ],
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": null,
+            "difference": null,
+            "expected": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "direction": "Long",
+                "entry_price": 96.7,
+                "entry_time": "2020-01-03T21:00:00+00:00",
+                "exit_price": 94.07300000000001,
+                "exit_time": "2020-01-07T21:00:00+00:00",
+                "pnl": -262.69999999999953,
+                "size": 100.0
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "trade_level_match",
+            "passed": true
+          },
+          {
+            "actual": [
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "exit_reason": "",
+                "price": 96.7,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T00:00:00"
+              },
+              {
+                "asset": "TEST",
+                "commission": 0.0,
+                "exit_reason": "trailing_stop",
+                "price": 94.073,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-07T00:00:00"
+              }
+            ],
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": null,
+            "difference": null,
+            "expected": [
+              {
+                "asset": "TEST",
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+                "price": 96.7,
+                "quantity": 100.0,
+                "side": "buy",
+                "timestamp": "2020-01-03T21:00:00+00:00"
+              },
+              {
+                "asset": "TEST",
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+                "price": 94.07300000000001,
+                "quantity": 100.0,
+                "side": "sell",
+                "timestamp": "2020-01-07T21:00:00+00:00"
+              }
+            ],
+            "message": "exact ordered match",
+            "name": "fill_level_match",
+            "passed": true
+          }
+        ],
+        "framework": "Zipline",
+        "passed": true,
+        "scenario_id": "15"
+      },
       "detail": null,
+      "duration_seconds": 2.0427074190229177,
       "framework": "zipline",
+      "framework_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "reconstructed",
+          "exit_reason": "unavailable",
+          "fills": "reconstructed",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "native_filled_only",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
+        },
+        "extra": {},
+        "fills": [
+          {
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+            "price": 96.7,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-01-03T21:00:00+00:00"
+          },
+          {
+            "asset": "TEST",
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+            "price": 94.07300000000001,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-07T21:00:00+00:00"
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+        ],
+        "final_value": 99737.3,
+        "framework": "Zipline",
+        "num_trades": 1,
+        "total_pnl": -262.6999999999971,
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+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 96.7,
+            "entry_time": "2020-01-03T21:00:00+00:00",
+            "exit_price": 94.07300000000001,
+            "exit_time": "2020-01-07T21:00:00+00:00",
+            "pnl": -262.69999999999953,
+            "size": 100.0
+          }
+        ]
+      },
+      "ml4t_result": {
+        "capabilities": {
+          "cash_flows": "aggregate_only",
+          "closed_trades": "native",
+          "exit_reason": "native",
+          "fills": "native",
+          "intents": "input_only",
+          "open_trades": "unavailable",
+          "orders": "unavailable",
+          "positions": "unavailable",
+          "rejections": "unavailable",
+          "terminal": "native"
+        },
+        "extra": {},
+        "fills": [
+          {
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+            "exit_reason": "",
+            "price": 96.7,
+            "quantity": 100.0,
+            "side": "buy",
+            "timestamp": "2020-01-03T00:00:00"
+          },
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "exit_reason": "trailing_stop",
+            "price": 94.073,
+            "quantity": 100.0,
+            "side": "sell",
+            "timestamp": "2020-01-07T00:00:00"
+          }
+        ],
+        "final_value": 99737.3,
+        "framework": "ml4t.backtest",
+        "num_trades": 1,
+        "total_pnl": -262.6999999999971,
+        "trades": [
+          {
+            "asset": "TEST",
+            "commission": 0.0,
+            "direction": "Long",
+            "entry_price": 96.7,
+            "entry_time": "2020-01-03T00:00:00",
+            "exit_price": 94.073,
+            "exit_reason": "trailing_stop",
+            "exit_time": "2020-01-07T00:00:00",
+            "pnl": -262.7000000000007,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
+        "adapter": {
+          "module": "frameworks.zipline",
+          "path": "validation/frameworks/zipline.py"
+        },
+        "capabilities": {
+          "framework": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "reconstructed",
+            "exit_reason": "unavailable",
+            "fills": "reconstructed",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          },
+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "commission": "explicit scenario model or NoCommission",
+          "execution": "custom next-session open-price slippage model",
+          "fills": "native transactions with fees reconstructed from the configured model",
+          "risk_rules": "adapter_emulated_daily_ohlc",
+          "trade_records": "adapter_reconstructed_from_native_transactions"
+        },
+        "digests": {
+          "adapter": "6e650c04c9604c3cfa40e597e16fa2e792d7e61fe2ebec56b7f46b5e33dde581",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
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+          "profile": "d7768c1dbc7e300243ff0eac676d628b4af4e347896a67b1623a5f0aa6c053a3",
+          "scenario": "fccddcd3455a97b6ce7c416cc2b41672c9d79511da75211739c16c90e940c969"
+        },
+        "framework_target": {
+          "actual_version": "3.1.1",
+          "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+          "version": "3.1.1"
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+        "input_digest": "935e7e58b70b2ff5c2181016ceae955c9aa4986a9e1d7653b63043d3be82a524",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
+          "implementation": "cpython",
+          "version": "3.12.11"
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+        "record_counts": {
+          "bars": 34,
+          "entry_signals": 1,
+          "exit_signals": 0,
+          "framework_closed_trades": 1,
+          "framework_fills": 2,
+          "framework_intents": 1,
+          "framework_orders": null,
+          "ml4t_closed_trades": 1,
+          "ml4t_fills": 2,
+          "ml4t_intents": 1,
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+      },
       "release_blocking": false,
       "required": true,
       "scenario_id": "15",
@@ -600,17 +255430,39384 @@
       "status": "pass"
     },
     {
+      "comparison": {
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+            "canonical_quantum": "1",
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+            "message": "Zipline=5, ML4T=5, exact_diff=0; diagnostic_limit=0",
+            "name": "trade_count",
+            "passed": true
+          },
+          {
+            "actual": 98495.5,
+            "canonical_quantum": "0.00000001",
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+            "expected": 98495.5,
+            "message": "Zipline=$98,495.5000000000, ML4T=$98,495.5000000000 (exact_diff=$0.0000000000, 0.0000000000%; diagnostic_limit=0.1%)",
+            "name": "final_value",
+            "passed": true
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+          {
+            "actual": -1504.5,
+            "canonical_quantum": "0.00000001",
+            "diagnostic_limit": 50.0,
+            "difference": 0.0,
+            "expected": -1504.5,
+            "message": "Zipline=$-1,504.5000000000, ML4T=$-1,504.5000000000 (exact_diff=$0.0000000000; diagnostic_limit=$50.0)",
+            "name": "total_pnl",
+            "passed": true
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+          {
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+            "pnl": 19.5,
+            "size": 100.0
+          }
+        ]
+      },
+      "provenance": {
+        "adapter": {
+          "module": "frameworks.zipline",
+          "path": "validation/frameworks/zipline.py"
+        },
+        "capabilities": {
+          "framework": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "reconstructed",
+            "exit_reason": "unavailable",
+            "fills": "reconstructed",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "native_filled_only",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          },
+          "ml4t": {
+            "cash_flows": "aggregate_only",
+            "closed_trades": "native",
+            "exit_reason": "native",
+            "fills": "native",
+            "intents": "input_only",
+            "open_trades": "unavailable",
+            "orders": "unavailable",
+            "positions": "unavailable",
+            "rejections": "unavailable",
+            "terminal": "native"
+          }
+        },
+        "comparison_protocol": {
+          "commission": "explicit scenario model or NoCommission",
+          "execution": "custom next-session open-price slippage model",
+          "fills": "native transactions with fees reconstructed from the configured model",
+          "risk_rules": "none",
+          "trade_records": "adapter_reconstructed_from_native_transactions"
+        },
+        "digests": {
+          "adapter": "6e650c04c9604c3cfa40e597e16fa2e792d7e61fe2ebec56b7f46b5e33dde581",
+          "canonical_records": "fa1d9846bdc895cf62e6435097a8953d131ac16f6ae910d41ba81a5090c43707",
+          "capabilities": "dd0f50965982db8aae711f850740fc1d26c5f09d8b7c3d24221b347a7e14c8aa",
+          "comparator": "de6683dd96cab7fc9ce005f4651b7de359b8ddfcd6402b543960133ca35b0f5e",
+          "engine": "9a423b1f58d81bded0545cf0d4572d8c0c2a41129d41a33c59ea7649f6c051b1",
+          "manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+          "ml4t_runner": "6e9753811241863f59fc6607f315237aa1caec673372ef3b3a85fc959cf426e0",
+          "profile": "4c1b7206fe55cebbe9f41acb88a30dac343e4ce973e92ad60c236a27ef021548",
+          "scenario": "d0e0852cea9e321d72793f0f7fd7479d70d67ea3b367cbab817e4e3067af4e32"
+        },
+        "framework_target": {
+          "actual_version": "3.1.1",
+          "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+          "version": "3.1.1"
+        },
+        "input_digest": "d8119bff0157cd31258a444fec247040af62a78f46aff8b484ad1b9ef8915516",
+        "ml4t": {
+          "commit": "98483c88c37247cbc17525fb5e803f6fca1ee4fd",
+          "dirty": false
+        },
+        "python": {
+          "implementation": "cpython",
+          "version": "3.12.11"
+        },
+        "record_counts": {
+          "bars": 1241,
+          "entry_signals": 412,
+          "exit_signals": 412,
+          "framework_closed_trades": 337,
+          "framework_fills": 674,
+          "framework_intents": 824,
+          "framework_orders": null,
+          "ml4t_closed_trades": 337,
+          "ml4t_fills": 674,
+          "ml4t_intents": 824,
+          "ml4t_orders": null
+        }
+      },
+      "release_blocking": false,
+      "required": true,
+      "scenario_id": "17",
+      "scenario_name": "High Event Count",
       "status": "pass"
     }
   ],
   "release_gate_passed": true,
-  "schema_version": 1,
+  "schema_version": 3,
   "summary": {
     "adapter_failure": 0,
     "adapter_import_failure": 0,
@@ -618,7 +294815,7 @@
     "malformed_output": 0,
     "missing_scenario": 0,
     "ml4t_failure": 0,
-    "pass": 62,
+    "pass": 66,
     "skipped": 0,
     "subprocess_failure": 0,
     "timeout": 0,
diff --git a/validation/LARGE_SCALE_RESULTS.json b/validation/LARGE_SCALE_RESULTS.json
new file mode 100644
index 00000000..fcd06857
--- /dev/null
+++ b/validation/LARGE_SCALE_RESULTS.json
@@ -0,0 +1,1828 @@
+{
+  "frameworks": [
+    {
+      "capabilities": {
+        "closed_trades": "reconstructed from canonical native fills",
+        "fill_order": "session, asset, side, quantity, price",
+        "fills": "native",
+        "intents": "canonical strategy trace",
+        "terminal_state": "reconstructed from native fills and final marks"
+      },
+      "comparison": {
+        "actual_error": null,
+        "actual_framework": "ml4t.backtest[vectorbt_strict]",
+        "canonical_money_quantum": "0.000001",
+        "canonical_record_quantum": "1E-8",
+        "checks": [
+          {
+            "actual_count": 427790,
+            "actual_sha256": "b87edd7321d4be2307d8db968004ebd7e12edf47a3955003f42d0e974c8f369c",
+            "expected_count": 427790,
+            "expected_sha256": "b87edd7321d4be2307d8db968004ebd7e12edf47a3955003f42d0e974c8f369c",
+            "first_difference": null,
+            "name": "order_intents",
+            "passed": true
+          },
+          {
+            "actual_count": 390369,
+            "actual_sha256": "83af0bc6cb77d931349349093a611cb645e1503c2c33aef9e626c293630cf0c1",
+            "expected_count": 390369,
+            "expected_sha256": "83af0bc6cb77d931349349093a611cb645e1503c2c33aef9e626c293630cf0c1",
+            "first_difference": null,
+            "name": "fills",
+            "passed": true
+          },
+          {
+            "actual_count": 188549,
+            "actual_sha256": "7055c62444c54eb5f5191358b187641ad7de019c3c182ce7f088d460ec59a242",
+            "expected_count": 188549,
+            "expected_sha256": "7055c62444c54eb5f5191358b187641ad7de019c3c182ce7f088d460ec59a242",
+            "first_difference": null,
+            "name": "trades",
+            "passed": true
+          },
+          {
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+        "package": "vectorbtpro",
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+        "source": "https://github.com/polakowo/vectorbt.pro",
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+        "fills": "native",
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+            "canonical_actual": 191297.0,
+            "canonical_difference": 0.0,
+            "canonical_expected": 191297.0,
+            "expected": 191297,
+            "name": "trade_count",
+            "passed": true,
+            "raw_difference": 0
+          },
+          {
+            "actual": -815461.8699999778,
+            "canonical_actual": -815461.87,
+            "canonical_difference": 0.0,
+            "canonical_expected": -815461.87,
+            "expected": -815461.87,
+            "name": "total_pnl",
+            "passed": true,
+            "raw_difference": 2.223532646894455e-08
+          },
+          {
+            "actual": 184538.13000002224,
+            "canonical_actual": 184538.13,
+            "canonical_difference": 0.0,
+            "canonical_expected": 184538.13,
+            "expected": 184538.13,
+            "name": "final_value",
+            "passed": true,
+            "raw_difference": 2.223532646894455e-08
+          },
+          {
+            "actual": {
+              "cash_from_fill_ledger": 140759.97,
+              "holdings_from_fill_ledger": 43778.16,
+              "positions": {
+                "ASSET_003": -100.0,
+                "ASSET_017": -100.0,
+                "ASSET_023": -100.0,
+                "ASSET_026": -100.0,
+                "ASSET_035": -100.0,
+                "ASSET_062": 100.0,
+                "ASSET_063": -100.0,
+                "ASSET_068": -100.0,
+                "ASSET_104": 100.0,
+                "ASSET_126": 100.0,
+                "ASSET_130": 100.0,
+                "ASSET_132": -100.0,
+                "ASSET_136": -100.0,
+                "ASSET_141": -100.0,
+                "ASSET_143": -100.0,
+                "ASSET_149": 100.0,
+                "ASSET_150": 100.0,
+                "ASSET_154": -100.0,
+                "ASSET_158": 100.0,
+                "ASSET_160": -100.0,
+                "ASSET_163": -100.0,
+                "ASSET_180": -100.0,
+                "ASSET_183": 100.0,
+                "ASSET_191": 100.0,
+                "ASSET_209": -100.0,
+                "ASSET_216": -100.0,
+                "ASSET_220": 100.0,
+                "ASSET_225": -100.0,
+                "ASSET_226": 100.0,
+                "ASSET_227": 100.0,
+                "ASSET_243": 100.0,
+                "ASSET_244": 100.0
+              },
+              "reported_final_value": 184538.13,
+              "sha256": "5dcf8612a6d4383347ee7206a837cc808fba5539086d589328ac8289496497d1"
+            },
+            "actual_sha256": "5dcf8612a6d4383347ee7206a837cc808fba5539086d589328ac8289496497d1",
+            "expected": {
+              "cash_from_fill_ledger": 140759.97,
+              "holdings_from_fill_ledger": 43778.16,
+              "positions": {
+                "ASSET_003": -100.0,
+                "ASSET_017": -100.0,
+                "ASSET_023": -100.0,
+                "ASSET_026": -100.0,
+                "ASSET_035": -100.0,
+                "ASSET_062": 100.0,
+                "ASSET_063": -100.0,
+                "ASSET_068": -100.0,
+                "ASSET_104": 100.0,
+                "ASSET_126": 100.0,
+                "ASSET_130": 100.0,
+                "ASSET_132": -100.0,
+                "ASSET_136": -100.0,
+                "ASSET_141": -100.0,
+                "ASSET_143": -100.0,
+                "ASSET_149": 100.0,
+                "ASSET_150": 100.0,
+                "ASSET_154": -100.0,
+                "ASSET_158": 100.0,
+                "ASSET_160": -100.0,
+                "ASSET_163": -100.0,
+                "ASSET_180": -100.0,
+                "ASSET_183": 100.0,
+                "ASSET_191": 100.0,
+                "ASSET_209": -100.0,
+                "ASSET_216": -100.0,
+                "ASSET_220": 100.0,
+                "ASSET_225": -100.0,
+                "ASSET_226": 100.0,
+                "ASSET_227": 100.0,
+                "ASSET_243": 100.0,
+                "ASSET_244": 100.0
+              },
+              "reported_final_value": 184538.13,
+              "sha256": "5dcf8612a6d4383347ee7206a837cc808fba5539086d589328ac8289496497d1"
+            },
+            "expected_sha256": "5dcf8612a6d4383347ee7206a837cc808fba5539086d589328ac8289496497d1",
+            "name": "terminal_state",
+            "passed": true
+          }
+        ],
+        "expected_error": null,
+        "expected_framework": "LEAN CLI",
+        "passed": true,
+        "scenario": "controlled_250_assets_5040_sessions",
+        "schema_version": 1,
+        "timestamp_domain": "session_date"
+      },
+      "framework": "lean",
+      "input": {
+        "conversion": "OHLC rounded to 4 decimals before both engines",
+        "effective_sha256": "718a6da2fc4a0a1326fc42a0d32c274843c6c40b56c7277422caf5ef1dc84023",
+        "raw_sha256": "1d1ef383884bb9db1aad484f2dc9b6b4fb72ade02c41c8d9c8f44055e9580d09"
+      },
+      "ml4t": {
+        "commit": "ad62d2bd30f9e3a25a9a205ae60df6b0309ca89a",
+        "dirty": false
+      },
+      "python": {
+        "implementation": "cpython",
+        "version": "3.12.11"
+      },
+      "runtime_seconds": {
+        "framework": 170.06328585091978,
+        "ml4t": 229.72061479417607,
+        "not_a_performance_claim": true
+      },
+      "source_digests": {
+        "benchmark_suite": "dcafa42216566ff5e83ae0788d53d9789c2b7980956ea656c874684730b40523",
+        "framework_manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+        "large_scale_runner": "31620bd2b07466f733a6060676707e664881e7b6d4c3ea3f09d8f47354e86706",
+        "profiles": "5a8cd8b2568e7e9f524e96fef6bb00ade3310a6f4a71c0c4f7de2f95bbfdb505"
+      },
+      "target": {
+        "access": "public",
+        "actual_version": "18001",
+        "artifact": "quantconnect/lean@sha256:ecd62b0e418d40d1d7c0cd95e90a94e397642a21d2c8810614830c8a4e9a8f70",
+        "cli_immutable_id": "sha256:eaa4c08f16295b76f005e429d9ca0d0453784dc1a40c1f5cbe5e50c02a05bd7c",
+        "cli_version": "1.0.228",
+        "commit": "278fcb3d1b815b63ccadba68d7ae54422e34b792",
+        "display_name": "LEAN",
+        "immutable_id": "sha256:ecd62b0e418d40d1d7c0cd95e90a94e397642a21d2c8810614830c8a4e9a8f70",
+        "license": "Apache-2.0",
+        "package": "lean",
+        "platform_artifact": "linux/amd64@sha256:cbe3f26b3f16c57be836b2cf913253d434f58e010c84ed038360d26b9df88307",
+        "profile": "lean",
+        "python": "3.11",
+        "source": "https://github.com/QuantConnect/Lean",
+        "version": "18001"
+      }
+    }
+  ],
+  "generated_at": "2026-08-14T13:16:45.765518+00:00",
+  "release_gate_passed": true,
+  "schema_version": 1,
+  "workload": {
+    "data_points": 1260000,
+    "generator": "validation.benchmark_suite.generate_benchmark_data",
+    "recipe": {
+      "assets": 250,
+      "bars": 5040,
+      "bottom_n": 25,
+      "end_session": "2025-12-31",
+      "initial_cash": 1000000.0,
+      "long_target_shares": 100.0,
+      "name": "controlled_250_assets_5040_sessions",
+      "rebalance_frequency": 1,
+      "seed": 42,
+      "short_target_shares": -100.0,
+      "top_n": 25
+    },
+    "recipe_sha256": "5de81aacdda2ee7f08b2cc1549e64a974b19693967ac2fe1fdb0f1a6370d0ba5",
+    "redistributable": true
+  }
+}
diff --git a/validation/METHODOLOGY.md b/validation/METHODOLOGY.md
index fc44f4ce..f38b99a2 100644
--- a/validation/METHODOLOGY.md
+++ b/validation/METHODOLOGY.md
@@ -1,6 +1,6 @@
 # Validation Methodology
 
-*Last updated: 2026-08-08*
+*Last updated: 2026-08-14*
 
 ## Core Principle
 
@@ -12,6 +12,17 @@ configurable knob is missing or misconfigured. The gap must be driven to zero.
 
 ## How It Works
 
+### Evidence scope
+
+The primary cross-framework audit uses frozen inputs from three production case studies: ETF
+allocation, CME futures, and crypto perpetual futures with funding. It compares only combinations
+that the framework and frozen data carrier genuinely support. Model inference and target
+construction happen before either engine runs, so both sides receive the same targets.
+
+The 17 synthetic scenarios test isolated execution conventions. The 250-asset synthetic workload
+tests high event counts and broad state transitions. These two suites are diagnostic and stress
+evidence, not evidence that a realistic strategy is equivalent.
+
 ### 1. Configurable Code Paths
 
 Every behavioral choice that differs between backtesting frameworks is expressed as a configurable
@@ -38,7 +49,7 @@ replicate that framework's behavior:
 | `vectorbt` / `vectorbt_strict` | VectorBT Pro/OSS | 0% trade gap, 0% value gap |
 | `backtrader` / `backtrader_strict` | Backtrader | 0% trade gap, 0% value gap |
 | `zipline` / `zipline_strict` | Zipline Reloaded | 0% trade gap, 0% value gap |
-| `lean` | QuantConnect LEAN | 0% fill gap, near-0% value gap |
+| `lean` | Frozen LEAN daily US-equity protocol | 0 fill gap, 0 canonical value gap |
 | `default` | ml4t's own opinion | Best-practice defaults |
 | `realistic` | Conservative simulation | Adds costs, integer shares |
 
@@ -134,8 +145,8 @@ Update the behavioral difference matrix, profile diffs, and parity results.
 ## Anti-Patterns
 
 **DO NOT** accept gaps as "structural" or "expected":
-- "LEAN fills at bar close, ml4t at next-bar open -- this is a structural difference" is WRONG
-- CORRECT: "We need to add `execution_price=close` to the lean profile to close this gap"
+- "The engines use different order timing, so the gap is expected" is wrong.
+- Identify the native event sequence, configure the corresponding profile, or narrow the claim.
 
 **DO NOT** say "this is good enough for production":
 - 95% parity is not the goal -- 100% parity is the goal
@@ -151,27 +162,110 @@ Update the behavioral difference matrix, profile diffs, and parity results.
 
 Complete matrix of how each framework handles every behavioral dimension.
 
+### VectorBT native evidence
+
+The VectorBT column cites checks from `native/vectorbt_behavior.py`. The checks import only the
+frozen framework and its dependencies. Both current targets passed all checks:
+
+- [VectorBT OSS 1.1.0 evidence](native/evidence/vectorbt_oss-1.1.0.json)
+- [VectorBT Pro 2026.6.27 evidence](native/evidence/vectorbt_pro-2026.6.27.json)
+
+`VBT-S` refers to the `signal_timing_and_default_fill` and `explicit_fill_price` checks. `VBT-R`
+refers to `stop_fill` and `trailing_stop_extreme_and_intrabar_fill`. `VBT-C` refers to
+`short_cash`, `cash_sharing_and_call_sequence`, and `insufficient_cash_partial_fill`. `VBT-O`
+refers to `target_percent_sizing`, `accumulation`, `long_signal_conflict`, and
+`missing_order_price`. `VBT-F` refers to `defaults`, `fees_and_slippage`, and
+`record_construction`.
+
+The evidence records the official source address for each frozen implementation. OSS uses
+[`Portfolio.from_orders`](https://github.com/polakowo/vectorbt/blob/259d2d89fe2e7638baf3ca76c394937cd32b656d/vectorbt/portfolio/base.py#L1616)
+and [`Portfolio.from_signals`](https://github.com/polakowo/vectorbt/blob/259d2d89fe2e7638baf3ca76c394937cd32b656d/vectorbt/portfolio/base.py#L2047).
+Pro uses the corresponding methods at
+[`Portfolio.from_orders`](https://github.com/polakowo/vectorbt.pro/blob/6e18cf0aa37849cfc20848f40f1d26ecfdc771b4/vectorbtpro/portfolio/base.py#L4145)
+and [`Portfolio.from_signals`](https://github.com/polakowo/vectorbt.pro/blob/6e18cf0aa37849cfc20848f40f1d26ecfdc771b4/vectorbtpro/portfolio/base.py#L4646).
+
+### Backtrader native evidence
+
+The Backtrader column cites checks from `native/backtrader_behavior.py`. The probe imports only
+Backtrader 1.9.78.123 and pandas. It passed all 14 checks in the retained
+[Backtrader evidence](native/evidence/backtrader-1.9.78.123.json). The evidence identifies the
+installed wheel and its SHA-256 digest, and records source locations inside that artifact.
+
+`BT-T` refers to `next_bar_open_and_gap`, `cheat_on_close`, and `final_bar_market_order`. `BT-S`
+refers to `integer_target_percent` and `commission_headroom`. `BT-C` refers to `defaults`,
+`cash_rejection_and_configured_leverage`, `short_cash`, and `trade_record`. `BT-O` refers to
+`submission_sequence`. `BT-R` refers to `signal_price_stop_basis` and
+`trailing_stop_signal_close_and_lagged`. `BT-D` refers to `missing_bar_uses_last_value` and
+`late_feed_start`.
+
+### Zipline native evidence and comparison protocol
+
+The retained [Zipline Reloaded 3.1.1 evidence](native/evidence/zipline-3.1.1.json) contains 13
+checks executed through `zipline.run_algorithm` and direct construction of the frozen models.
+The source locations resolve to commit `09885a2ebc7567d40942c891b3879dc03c745070`, and the
+evidence identifies the source artifact and its SHA-256 digest.
+
+The native defaults and the comparison protocol are different:
+
+| Behavior | Zipline Reloaded 3.1.1 default | Suite comparison protocol |
+|---|---|---|
+| Daily fill | Next session close plus 5 basis points | Next session open |
+| Equity commission | `$0.001` per share, `$0` minimum | No commission unless the scenario specifies one |
+| Equity slippage | `FixedBasisPointsSlippage(5 bps, volume_limit=0.1)` | Custom open-price model with no volume cap |
+| Optional volume-share model | `volume_limit=0.025`, `price_impact=0.1` | Used only by an explicit scenario or native check |
+| Stop loss, take profit, trailing stop | No portfolio risk-rule protocol | Adapter evaluates daily OHLC and submits an exit |
+| Closed trades | Native transactions and positions, no closed-trade column | Adapter reconstructs round trips from transactions |
+
+The `0.1` in `VolumeShareSlippage` is a coefficient in a quadratic price-impact formula. It is
+not a 10% slippage rate. The profile and scenario matrix reproduce the suite protocol, not the
+framework defaults. Each scenario record identifies adapter-emulated risk rules and reconstructed
+trade records in `provenance.comparison_protocol`.
+
+`ZL-D` refers to `defaults` and `default_next_bar_close_fill`. `ZL-P` refers to
+`configured_next_bar_open_fill` and `explicit_minimum_commission`. `ZL-S` refers to
+`integer_target_percent` and `target_percent_snapshot`. `ZL-C` refers to
+`cash_and_short_proceeds`. `ZL-O` refers to `submission_sequence` and
+`final_bar_market_order`. `ZL-V` refers to `volume_share_partial_fills`. `ZL-X` refers to
+`transaction_records_not_native_trades`. `ZL-M` refers to `session_calendar` and `missing_bar`.
+
+`LN-T` refers to LEAN native `timing` and `final_bar_order`. `LN-M` refers to `default_models`,
+`buying_power_allowed`, and `buying_power_rejected`. `LN-O` refers to `submission_sequence` and
+`buying_power_sequence`. `LN-S` refers to `target_sizing`. `LN-C` refers to `explicit_costs`.
+`LN-D` refers to `fill_forward`. `LN-F` refers to `default_full_fill`. `LN-X` refers to
+`terminal_holding` and `liquidation`. These checks use LEAN engine 18001 at commit
+`278fcb3d1b815b63ccadba68d7ae54422e34b792`, CLI 1.0.228, `DefaultBrokerageModel`, a margin
+account, daily adjusted US equities, and 2x security leverage.
+
+The tables below describe configured profile values. They are not all cross-engine equivalence
+claims. `behavior_coverage.toml` maps every profile field to its native checks and cross-engine
+scenarios. A dimension is publishable only when both references are present. The current scenario
+matrix does not publish equivalence for target-percent sizing, insufficient-cash boundaries,
+competing same-session orders, partial fills, missing bars, or late assets. Those settings remain
+available profile choices backed by native evidence where the map identifies it.
+
 ### Execution Timing
 
-| Knob | ml4t Default | VectorBT | Backtrader | Zipline | LEAN |
-|------|-------------|----------|------------|---------|------|
-| `execution_mode` | next_bar | **same_bar** | next_bar | next_bar | **same_bar** |
-| `fill_timing` | next_bar_open | **same_bar** | next_bar_open | next_bar_open | **same_bar** |
-| `execution_price` | open | **close** | open | open | **close** |
+| Knob | ml4t Default | VectorBT | VBT evidence | Backtrader | Zipline protocol | LEAN |
+|------|-------------|----------|--------------|------------|---------|------|
+| `execution_mode` | next_bar | **same_bar** | VBT-S | next_bar (BT-T) | next_bar (ZL-P) | next_bar (LN-T) |
+| `fill_timing` | next_bar_open | **same_bar** | VBT-S | next_bar_open (BT-T) | next_bar_open (ZL-P) | next session (LN-T) |
+| `execution_price` | open | **close** | VBT-S | open (BT-T) | open (ZL-P) | open (LN-T) |
 
-VectorBT and LEAN both use same-bar execution with close fills. VectorBT is vectorized
-(inherently same-bar), while LEAN processes market orders immediately at bar close in its
-event-driven loop. All event-driven frameworks (BT, Zipline) except LEAN use next-bar open.
+LEAN emits a daily US-equity bar to `OnData` at the market close. A market order submitted from
+that callback is therefore submitted while the market is closed, converted to market-on-open, and
+filled at the next session's open. A final-bar order remains submitted and unfilled. VectorBT uses
+same-bar close execution. Backtrader and the configured Zipline protocol use the next session's
+open.
 
 ### Stop/Risk Configuration
 
-| Knob | ml4t Default | VectorBT | Backtrader | Zipline | LEAN |
-|------|-------------|----------|------------|---------|------|
-| `stop_fill_mode` | stop_price | stop_price | stop_price | stop_price | stop_price |
-| `stop_level_basis` | fill_price | fill_price | **signal_price** | fill_price | fill_price |
-| `trail_hwm_source` | close | **bar_extreme** | close | close | close |
-| `initial_hwm_source` | fill_price | **bar_high** | fill_price | fill_price | fill_price |
-| `trail_stop_timing` | lagged | **intrabar** | lagged | lagged | lagged |
+| Knob | ml4t Default | VectorBT | VBT evidence | Backtrader | Zipline protocol | LEAN |
+|------|-------------|----------|--------------|------------|---------|------|
+| `stop_fill_mode` | stop_price | stop_price | VBT-R | stop_price (BT-R) | next_bar_open (adapter) | profile fallback; not claimed |
+| `stop_level_basis` | fill_price | fill_price | VBT-R | **signal_price (BT-R)** | fill_price (adapter) | profile fallback; not claimed |
+| `trail_hwm_source` | close | **bar_extreme** | VBT-R | close (BT-R) | bar_extreme (adapter) | profile fallback; not claimed |
+| `initial_hwm_source` | fill_price | **bar_high** | VBT-R | signal_price (BT-R) | fill_price (adapter) | profile fallback; not claimed |
+| `trail_stop_timing` | lagged | **intrabar** | VBT-R | lagged (BT-R) | intrabar (adapter) | profile fallback; not claimed |
 
 Backtrader calculates stop levels from **signal bar close** (the price when the strategy decided
 to trade), not the actual fill price. This matters when next-bar open differs significantly from
@@ -179,54 +273,67 @@ previous close.
 
 ### Account & Cash
 
-| Knob | ml4t Default | VectorBT | Backtrader | Zipline | LEAN |
-|------|-------------|----------|------------|---------|------|
-| `allow_short_selling` | false | **true** | **true** | false | true |
-| `allow_leverage` | false | false | **true** | false | true |
-| `short_cash_policy` | credit | credit | credit | credit | credit |
-| `initial_margin` | 0.5 | -- | **0.5** | -- | varies |
-| `long_maint_margin` | 0.25 | -- | **0.25** | -- | varies |
-| `short_maint_margin` | 0.30 | -- | **0.30** | -- | varies |
+| Knob | ml4t Default | VectorBT | VBT evidence | Backtrader | Zipline protocol | LEAN |
+|------|-------------|----------|--------------|------------|---------|------|
+| `allow_short_selling` | false | **true** | VBT-C | **true (BT-C)** | true (ZL-C) | true |
+| `allow_leverage` | false | false | VBT-C | false by default (BT-C) | cash validation disabled (ZL-C) | true |
+| `short_cash_policy` | credit | credit | VBT-C | credit (BT-C) | credit (ZL-C) | credit |
+| `initial_margin` | 0.5 | -- | VBT-C | -- (BT-C) | -- | 0.5 (LN-M) |
+| `long_maint_margin` | 0.25 | -- | VBT-C | -- (BT-C) | -- | 0.5 (LN-M) |
+| `short_maint_margin` | 0.30 | -- | VBT-C | -- (BT-C) | -- | 0.5 (LN-M) |
+
+These LEAN margin values belong to `SecurityMarginModel` at 2x leverage. Other security and
+brokerage models can select different requirements.
 
 ### Order Handling
 
-| Knob | ml4t Default | VectorBT | Backtrader | Zipline | LEAN |
-|------|-------------|----------|------------|---------|------|
-| `fill_ordering` | exit_first | exit_first | **fifo** | exit_first | **exit_first** |
-| `entry_order_priority` | submission | submission | submission | submission | submission |
-| `rebalance_mode` | incremental | **hybrid** | **snapshot** | **snapshot** | snapshot |
-| `rebalance_headroom_pct` | 1.0 | 1.0 | **0.998** | **0.998** | 0.998 |
-| `reject_on_insufficient_cash` | true | **false** | true | true | true |
-| `partial_fills_allowed` | false | **true** | false | **true** | false |
-| `missing_price_policy` | skip | **use_last** | **use_last** | **use_last** | use_last |
+| Knob | ml4t Default | VectorBT | VBT evidence | Backtrader | Zipline protocol | LEAN |
+|------|-------------|----------|--------------|------------|---------|------|
+| `fill_ordering` | exit_first | exit_first | VBT-C, VBT-O | **fifo (BT-O)** | fifo (ZL-O) | sequential (LN-O) |
+| `entry_order_priority` | submission | submission | VBT-C | submission (BT-O) | submission (ZL-O) | submission |
+| `immediate_fill` | false | **true** | VBT-S, VBT-O | false (BT-T) | false (ZL-P, ZL-O) | false (LN-T) |
+| `rebalance_mode` | incremental | **hybrid** | VBT-O | **snapshot (BT-O)** | snapshot (ZL-S) | snapshot |
+| `rebalance_headroom_pct` | 1.0 | 1.0 | VBT-O | 1.0 (BT-S) | 1.0 (ZL-S) | 0.9975 (LN-S) |
+| `reject_on_insufficient_cash` | true | **false** | VBT-C | true (BT-C, BT-O) | false (ZL-C) | true |
+| `partial_fills_allowed` | false | **true** | VBT-C | false (BT-C) | false in protocol (ZL-P) | false in default fill model (LN-F) |
+| `missing_price_policy` | skip | skip order; forward-fill valuation | VBT-O | **use_last (BT-D)** | last price for sizing; stale bar defers fill (ZL-M) | fill-forward data; defer to next real open (LN-D) |
+| `late_asset_policy` | allow after 1 bar | allow after 1 bar | VBT-O | allow after 1 bar (BT-D) | allow (ZL-M) | allow |
 
 ### Position Sizing & Costs
 
-| Knob | ml4t Default | VectorBT | Backtrader | Zipline | LEAN |
-|------|-------------|----------|------------|---------|------|
-| `share_type` | fractional | fractional | **integer** | **integer** | **integer** |
-| `signal_processing` | check_position | **process_all** | check_position | check_position | check_position |
-| `commission_model` | percentage | **none** | percentage | **per_share** | per_share |
-| `commission_rate` | 0.1% | 0% | 0.1% | -- | -- |
-| `commission_per_share` | -- | -- | -- | **$0.005** | varies |
-| `commission_minimum` | $0 | -- | -- | **$1.00** | varies |
-| `slippage_model` | percentage | **none** | percentage | **volume_based** | volume_based |
-| `slippage_rate` | 0.1% | 0% | 0.1% | **10%** | varies |
-
-### "Strict" Profile Additions (for validation parity)
-
-| Knob | vbt_strict | bt_strict | zip_strict | lean |
-|------|-----------|-----------|------------|-------------|
-| `short_cash_policy` | **lock_notional** | credit | **credit** | credit |
-| `skip_cash_validation` | false | false | **true** | false |
-| `reject_on_insufficient_cash` | **true** | true | true | true |
-| `fill_ordering` | **fifo** | fifo | exit_first | **exit_first** |
-| `next_bar_submission_precheck` | -- | **true** | -- | false |
-| `next_bar_simple_cash_check` | -- | **true** | -- | false |
-| `allow_short_selling` | -- | -- | **true** | **true** |
-| `allow_leverage` | -- | -- | -- | **true** |
-| `execution_mode` | -- | **next_bar** | **next_bar** | **next_bar** |
-| `execution_price` | -- | **open** | **open** | **open** |
+| Knob | ml4t Default | VectorBT | VBT evidence | Backtrader | Zipline protocol | LEAN |
+|------|-------------|----------|--------------|------------|---------|------|
+| `share_type` | integer | fractional | VBT-O | integer (BT-S) | integer (ZL-S) | integer (LN-S) |
+| `share_rounding` | nearest | nearest | VBT-O | truncate (BT-S) | nearest (ZL-S) | nearest (LN-S) |
+| repeated entry | check position | ignore unless accumulation is enabled | VBT-O | adapter checks position | adapter checks position | adapter submits target delta |
+| `commission_model` | none | none | VBT-F | none (BT-C) | none (ZL-P) | `InteractiveBrokersFeeModel` (LN-M) |
+| `commission_rate` | 0% | 0% | VBT-F | 0% (BT-C) | -- | -- |
+| `commission_per_share` | -- | -- | VBT-F | -- | -- (ZL-P) | $0.005 for US equities (LN-M) |
+| `commission_minimum` | $0 | -- | VBT-F | -- | -- (ZL-P) | $1 for US equities (LN-M) |
+| `slippage_model` | none | none | VBT-F | none (BT-C) | custom open, zero cost (ZL-P) | `NullSlippageModel` (LN-M) |
+| `slippage_rate` | 0% | 0% | VBT-F | 0% (BT-C) | 0% (ZL-P) | 0% (LN-M) |
+
+The fee and slippage entries name the models selected by `DefaultBrokerageModel` for a US equity.
+They are not universal LEAN defaults. `LN-C` separately verifies explicit constant fee and
+percentage slippage overrides.
+
+### Comparison profiles
+
+`vectorbt_strict` uses locked short collateral, partial fills, and FIFO processing to match the
+controlled `Portfolio.from_orders` protocol. The retained native check verifies that short-sale
+cash is reported in the cash series but cannot fund new exposure. `backtrader` uses the measured
+framework defaults for costs, leverage, target headroom, missing bars, and late feeds.
+`backtrader_strict` adds submission-time cash checks and truncates target quantities to reproduce
+Backtrader's enabled `checksubmit` and native integer-sizing paths. `zipline_strict` resolves to
+the same settings as `zipline`; both represent the
+explicit comparison protocol described above. The native Zipline defaults remain separate. The
+`lean` profile represents only the named daily US-equity protocol above. Its stop settings are not
+part of the retained LEAN equivalence claim.
+
+Synthetic scale evidence compares native ordered fills first, then reconstructs closed trades from the
+canonical 1e-8 fill records for both engines. This prevents sub-quantum differences in a
+framework's post-hoc trade-table arithmetic from changing a trade derived from equivalent fills.
+The scenario suite separately compares each framework's native trade records.
 
 ---
 
@@ -235,31 +342,33 @@ previous close.
 <!-- parity-claims:start -->
 <!-- Generated by validation/generate_parity_claims.py. Do not edit by hand. -->
 
-Scenario claims use the retained release-candidate matrix. "Exact" appears only when every required scenario has zero canonical gap.
+Scenario claims use the retained accepted matrix. "Exact" means terminal values, ordered closed trades, and ordered fills match after 1e-8 quantization. Each record declares whether a surface is native, reconstructed, aggregate-only, input-only, or unavailable; the claim does not extend to unavailable order-lifecycle fields.
 
 | Profile | Pinned framework | Required scenarios | Evidence |
 |---|---|---:|---|
-| `vectorbt_strict` | [VectorBT Pro 2025.12.31](https://github.com/polakowo/vectorbt.pro) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `vectorbt` | [VectorBT OSS 0.28.2](https://pypi.org/project/vectorbt/0.28.2/) | 15/15 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 15/15 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-
-Large-scale claims are published only when a retained workload has zero canonical gap.
-
-| Profile | Pinned framework | Compared | Trade gap | Terminal value | Evidence |
-|---|---|---:|---:|---:|---|
-| `vectorbt_strict` | VectorBT Pro 2025.12.31 (`1305a1e19743`) | 225,844 trades | 0 | 685179.007330 | [large-scale evidence](https://github.com/ml4t/backtest/blob/main/validation/vectorbt_pro/large_scale_parity.json) |
-
-No large-scale claim is published for Backtrader, Zipline, VectorBT OSS, or LEAN without a passing retained artifact.
+| `vectorbt_strict` | [VectorBT Pro 2026.6.27](https://github.com/polakowo/vectorbt.pro) | 17/17 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `vectorbt_oss_strict` | [VectorBT OSS 1.1.0](https://pypi.org/project/vectorbt/1.1.0/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 17/17 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+
+The controlled scale workload contains 250 assets and 5,040 daily sessions (1,260,000 bars). Every row has zero canonical gap for target intents, native fills, closed trades reconstructed from those fills, and terminal state reconstructed from the fill ledger and final marks.
+
+| Profile | Current framework | Target intents | Native fills | Fill-derived closed trades | Terminal value | Evidence |
+|---|---|---:|---:|---:|---:|---|
+| `vectorbt_strict` | [VectorBT Pro 2026.6.27](https://github.com/polakowo/vectorbt.pro) | 427,790 | 390,369 | 188,549 | 716,785.408089 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `vectorbt_oss_strict` | [VectorBT OSS 1.1.0](https://pypi.org/project/vectorbt/1.1.0/) | 427,790 | 390,369 | 188,549 | 716,785.408089 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 427,790 | 343,813 | 182,019 | -9,166,273.555954 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 427,790 | 427,696 | 226,434 | 10,504,095.900000 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `lean` | [LEAN 18001](https://github.com/QuantConnect/Lean) | 427,790 | 361,297 | 191,297 | 184,538.130000 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
 <!-- parity-claims:end -->
 
 ---
 
 ## Validation Harness
 
-### Scenario Tests (16 scenarios x 4 frameworks)
+### Synthetic Scenario Tests (17 scenarios x 4 frameworks)
 
-The validation suite tests 16 scenarios against 4 external frameworks:
+The validation suite tests 17 isolated conformance scenarios against 4 external frameworks:
 
 | ID | Scenario | What It Tests |
 |----|----------|---------------|
@@ -278,13 +387,14 @@ The validation suite tests 16 scenarios against 4 external frameworks:
 | 13 | TSL + TP Combo | Rule chain evaluation order |
 | 14 | TSL + SL Combo | Rule chain evaluation order |
 | 15 | Triple Rule | Three-rule chain with priority |
-| 16 | Stress Test | 1500 bars, 9 market regimes |
+| 16 | Regime Path Coverage | 1500 bars, 9 market regimes and sparse entries |
+| 17 | High Event Count | 1800 bars, up to 600 completed round trips |
 
-### Large-Scale Validation (250 assets x 20 years)
+### Synthetic Stress Validation (250 assets x 20 years)
 
-Beyond scenario tests, the benchmark suite runs a full ranking strategy on 250 US equities
-from 1998-2018. This produces 200K+ trades that are compared trade-by-trade between frameworks.
-See `benchmark_suite.py` for the implementation.
+The benchmark suite runs a generated ranking workload on 250 US equities from 1998-2018. It
+produces more than 200,000 trades for record-volume and state-transition testing. See
+`benchmark_suite.py` for the implementation. It is not a production case study.
 
 ### Running the Suite
 
@@ -300,6 +410,16 @@ python validation/run_scenario.py --all
 
 # Large-scale benchmark
 python validation/benchmark_suite.py --profile backtrader_strict --framework backtrader
+
+# Compare retained real-strategy outputs
+uv run python validation/real_strategy_evidence.py \
+  --evidence-root PATH/TO/REAL_STRATEGY_OUTPUTS \
+  --output validation/candidates/REAL_STRATEGY_RESULTS.candidate.json
+
+# Repeat engine-only timings for correctness-passing real-strategy pairs
+uv run python validation/real_strategy_benchmark.py \
+  --bundle-root PATH/TO/CONTENT_ADDRESSED_BUNDLES \
+  --samples 10
 ```
 
 ---
@@ -314,3 +434,6 @@ python validation/benchmark_suite.py --profile backtrader_strict --framework bac
 | Framework drivers | `validation/frameworks/` |
 | Benchmark suite | `validation/benchmark_suite.py` |
 | Scenario runner | `validation/run_scenario.py` |
+| Real-strategy applicability | `validation/real_strategy_applicability.toml` |
+| Real-strategy correctness evidence | `validation/REAL_STRATEGY_RESULTS.json` |
+| Real-strategy performance evidence | `validation/REAL_STRATEGY_PERFORMANCE.json` |
diff --git a/validation/PERFORMANCE_RESULTS.json b/validation/PERFORMANCE_RESULTS.json
new file mode 100644
index 00000000..55348bb0
--- /dev/null
+++ b/validation/PERFORMANCE_RESULTS.json
@@ -0,0 +1,8144 @@
+{
+  "calibration": {
+    "allocated_bytes": 33554432,
+    "process_peak_rss_mb": 167.5859375,
+    "process_wall_seconds": 0.4757457880768925,
+    "worker_seconds": 0.03539959201589227
+  },
+  "capability_matrix": [
+    {
+      "coverage": [
+        "vectorbt_pro",
+        "vectorbt_oss",
+        "backtrader",
+        "zipline",
+        "lean"
+      ],
+      "dimensions": "50 assets x 252 daily sessions",
+      "use": "controlled and idiomatic repeated performance evidence",
+      "workload": "performance_50_assets_252_sessions"
+    },
+    {
+      "coverage": [
+        "vectorbt_pro",
+        "vectorbt_oss",
+        "backtrader",
+        "zipline",
+        "lean"
+      ],
+      "dimensions": "250 assets x 5040 daily sessions",
+      "use": "large-scale equivalence only; recorded runtimes are not performance claims",
+      "workload": "controlled_250_assets_5040_sessions"
+    },
+    {
+      "coverage": [
+        "vectorbt_oss",
+        "backtrader",
+        "zipline",
+        "lean"
+      ],
+      "dimensions": "250 assets x 5,040 daily sessions",
+      "use": "superseded audit input; single samples, inconsistent setup boundaries, missing peak RSS for LEAN, and a non-reconstructable temporary data path",
+      "workload": "historical_real_250_assets_5040_sessions"
+    },
+    {
+      "coverage": [
+        "ml4t_backtest"
+      ],
+      "dimensions": "single-asset, 250-asset, quote, rebalance, and partial-fill workloads",
+      "use": "internal regression evidence; not a cross-framework comparison",
+      "workload": "performance_baselines.json workloads"
+    }
+  ],
+  "controlled": {
+    "equivalence_required": true,
+    "pairs": {
+      "backtrader": {
+        "exact_output": true,
+        "external_runner": "backtrader:external",
+        "ml4t_runner": "backtrader:ml4t",
+        "passed": true
+      },
+      "lean": {
+        "exact_output": true,
+        "external_runner": "lean:external",
+        "ml4t_runner": "lean:ml4t",
+        "passed": true
+      },
+      "vectorbt_oss": {
+        "exact_output": true,
+        "external_runner": "vectorbt_oss:external",
+        "ml4t_runner": "vectorbt_oss:ml4t",
+        "passed": true
+      },
+      "vectorbt_pro": {
+        "exact_output": true,
+        "external_runner": "vectorbt_pro:external",
+        "ml4t_runner": "vectorbt_pro:ml4t",
+        "passed": true
+      },
+      "zipline": {
+        "exact_output": true,
+        "external_runner": "zipline:external",
+        "ml4t_runner": "zipline:ml4t",
+        "passed": true
+      }
+    },
+    "passed": true
+  },
+  "generated_at": "2026-08-14T12:14:30.387013+00:00",
+  "historical_assessment": {
+    "comparable_to_current_measurements": false,
+    "reason": "The 2026-02-28 artifacts used one sample, inconsistent setup boundaries, old framework revisions, different hardware provenance, and incomplete memory data."
+  },
+  "host": {
+    "cpu_model": "12th Gen Intel(R) Core(TM) i9-12900K",
+    "logical_cpu_count": 24,
+    "machine": "x86_64",
+    "platform": "Linux-6.8.0-136-generic-x86_64-with-glibc2.39",
+    "processor": "x86_64",
+    "python": "3.12.11"
+  },
+  "idiomatic": {
+    "equivalence_claim": false,
+    "passed": true,
+    "runners": {
+      "backtrader": {
+        "invariants_passed": true,
+        "sample_source": "backtrader:external",
+        "semantic_disclosure": "Native Cerebro and Strategy callbacks with target orders, next-session open fills, integer shares, zero commission, and enabled submission cash checks."
+      },
+      "lean": {
+        "invariants_passed": true,
+        "sample_source": "lean:external",
+        "semantic_disclosure": "Native QCAlgorithm daily callback and market-order API in the frozen LEAN image with the declared margin account, zero fee, and zero slippage models."
+      },
+      "ml4t_backtest": {
+        "invariants_passed": true,
+        "sample_source": "vectorbt_oss:ml4t",
+        "semantic_disclosure": "Event-driven Strategy and Engine API with the vectorbt_oss_strict profile; this is one documented ML4T configuration, not a framework-wide default-performance claim."
+      },
+      "vectorbt_oss": {
+        "invariants_passed": true,
+        "sample_source": "vectorbt_oss:external",
+        "semantic_disclosure": "Vectorized Portfolio.from_orders target-amount API with cash sharing, same-bar close execution, zero costs, and lock_cash enabled."
+      },
+      "vectorbt_pro": {
+        "invariants_passed": true,
+        "sample_source": "vectorbt_pro:external",
+        "semantic_disclosure": "Vectorized Portfolio.from_orders target-amount API with cash sharing, same-bar close execution, zero costs, and locked short collateral."
+      },
+      "zipline": {
+        "invariants_passed": true,
+        "sample_source": "zipline:external",
+        "semantic_disclosure": "Native run_algorithm callback and order_target API with daily bundle ingestion, a custom open-price slippage model, and zero commission. Bundle creation is included."
+      }
+    }
+  },
+  "measurement_protocol": {
+    "cache_policy": "installed packages and compiled framework caches persist; inputs and framework state are rebuilt in every child; Zipline uses a new bundle root for every child",
+    "memory": "child resource.getrusage(RUSAGE_SELF).ru_maxrss over the complete process",
+    "process_isolation": "one fresh child process per warm-up and measured repetition",
+    "runtime_primary": "parent perf_counter around the complete child process, including interpreter startup, imports, deterministic input generation, adapter setup, engine execution, output extraction, canonical validation, and process teardown",
+    "runtime_secondary": "adapter-reported engine interval and worker stage intervals",
+    "thread_environment": {
+      "MKL_NUM_THREADS": "1",
+      "NUMBA_NUM_THREADS": "1",
+      "OMP_NUM_THREADS": "1",
+      "OPENBLAS_NUM_THREADS": "1",
+      "POLARS_MAX_THREADS": "1",
+      "PYTHONHASHSEED": "0"
+    },
+    "uncertainty": {
+      "confidence": 0.95,
+      "method": "deterministic percentile bootstrap of the sample median",
+      "resamples": 10000
+    },
+    "warmup": "one unmeasured isolated process per runner before measured repetitions"
+  },
+  "protocol_sha256": "2e1c91c46a8f6be460b9f33157afe602c8eaf15358aa247c5406d2abf93ff8bb",
+  "release_gate_passed": true,
+  "runners": {
+    "backtrader:external": {
+      "adapter_engine_seconds": {
+        "ci95": [
+          3.350934648886323,
+          3.6069803595310077
+        ],
+        "maximum": 4.0709646351169795,
+        "median": 3.423901053494774,
+        "minimum": 3.304090574849397
+      },
+      "output": {
+        "fills": {
+          "count": 4288,
+          "sha256": "febf7d800ad51bb21a08dcde7271f83d998df1555717892bb7df1e043c558963"
+        },
+        "final_value": 1017080.363019,
+        "order_intents": {
+          "count": 4306,
+          "sha256": "8ceb30edfe288d834194a069b3f5588dd763139633d2d1eda193511ff7dd7a96"
+        },
+        "terminal_state_sha256": "ff7fe2b530c5859f9f166204f13090e1852563d1f442facea022fdf3580ba1d9",
+        "total_pnl": 17080.363019,
+        "trade_count": 2271,
+        "trades": {
+          "count": 2271,
+          "sha256": "775e56a8766efa3cd1bddc12b8ba0580b7bc0306fe0391d02bc7f5bd9724f73d"
+        }
+      },
+      "output_sha256": "812655f4febafd954501947cff27c631ef86d0d1e2708f18eb8c94d4ee742438",
+      "passed": true,
+      "process_peak_rss_mb": {
+        "ci95": [
+          197.19921875,
+          197.45703125
+        ],
+        "maximum": 201.2265625,
+        "median": 197.294921875,
+        "minimum": 197.03515625
+      },
+      "process_wall_seconds": {
+        "ci95": [
+          4.859050475992262,
+          5.406705005094409
+        ],
+        "maximum": 5.6817656338680536,
+        "median": 5.014518941054121,
+        "minimum": 4.792324147885665
+      },
+      "python": {
+        "implementation": "cpython",
+        "version": "3.12.11"
+      },
+      "runner": {
+        "framework": "backtrader",
+        "profile": "backtrader_strict",
+        "runner_id": "backtrader:external",
+        "side": "external"
+      },
+      "samples": [
+        {
+          "captured_log_tail": "",
+          "framework": "backtrader",
+          "input": {
+            "effective_sha256": "c37af67d1da290637fa4721b44a0043485234c6c39374856fc09bd77b6ad412e",
+            "raw_sha256": "c37af67d1da290637fa4721b44a0043485234c6c39374856fc09bd77b6ad412e"
+          },
+          "lean_container_observed": true,
+          "ml4t": {
+            "commit": "0315119acc05796d95cc3c344a0418007dde6cbc",
+            "dirty": false
+          },
+          "output": {
+            "fills": {
+              "count": 4288,
+              "sha256": "febf7d800ad51bb21a08dcde7271f83d998df1555717892bb7df1e043c558963"
+            },
+            "final_value": 1017080.363019,
+            "order_intents": {
+              "count": 4306,
+              "sha256": "8ceb30edfe288d834194a069b3f5588dd763139633d2d1eda193511ff7dd7a96"
+            },
+            "terminal_state_sha256": "ff7fe2b530c5859f9f166204f13090e1852563d1f442facea022fdf3580ba1d9",
+            "total_pnl": 17080.363019,
+            "trade_count": 2271,
+            "trades": {
+              "count": 2271,
+              "sha256": "775e56a8766efa3cd1bddc12b8ba0580b7bc0306fe0391d02bc7f5bd9724f73d"
+            }
+          },
+          "output_sha256": "812655f4febafd954501947cff27c631ef86d0d1e2708f18eb8c94d4ee742438",
+          "process_peak_rss_mb": 197.5078125,
+          "process_wall_seconds": 5.376169226132333,
+          "profile": "backtrader_strict",
+          "python": {
+            "implementation": "cpython",
+            "version": "3.12.11"
+          },
+          "runner_id": "backtrader:external",
+          "side": "external",
+          "stages_seconds": {
+            "adapter_reported_engine": 3.6734475230332464,
+            "framework_call": 3.987528580939397,
+            "input_generation": 0.17883973685093224,
+            "output_validation": 0.7111673119943589,
+            "worker_total": 4.884594844887033
+          },
+          "target": {
+            "access": "public",
+            "actual_version": "1.9.78.123",
+            "artifact": "backtrader-1.9.78.123-py2.py3-none-any.whl",
+            "display_name": "Backtrader",
+            "immutable_id": "sha256:9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+            "license": "GPL-3.0-or-later",
+            "package": "backtrader",
+            "profile": "backtrader_strict",
+            "python": "3.12 audit interpreter; upstream package metadata does not declare a range",
+            "source": "https://pypi.org/project/backtrader/1.9.78.123/",
+            "version": "1.9.78.123"
+          },
+          "thread_environment": {
+            "MKL_NUM_THREADS": "1",
+            "NUMBA_NUM_THREADS": "1",
+            "OMP_NUM_THREADS": "1",
+            "OPENBLAS_NUM_THREADS": "1",
+            "POLARS_MAX_THREADS": "1",
+            "PYTHONHASHSEED": "0"
+          },
+          "worker_self_peak_rss_mb": 195.28125
+        },
+        {
+          "captured_log_tail": "",
+          "framework": "backtrader",
+          "input": {
+            "effective_sha256": "c37af67d1da290637fa4721b44a0043485234c6c39374856fc09bd77b6ad412e",
+            "raw_sha256": "c37af67d1da290637fa4721b44a0043485234c6c39374856fc09bd77b6ad412e"
+          },
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+            "POLARS_MAX_THREADS": "1",
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+          "worker_self_peak_rss_mb": 159.89453125
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+          "framework": "zipline",
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+            "raw_sha256": "c37af67d1da290637fa4721b44a0043485234c6c39374856fc09bd77b6ad412e"
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+          "ml4t": {
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+            "actual_version": "3.1.1",
+            "artifact": "zipline_reloaded-3.1.1.tar.gz",
+            "commit": "09885a2ebc7567d40942c891b3879dc03c745070",
+            "display_name": "Zipline Reloaded",
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+            "license": "Apache-2.0",
+            "package": "zipline-reloaded",
+            "profile": "zipline_strict",
+            "python": ">=3.10",
+            "source": "https://pypi.org/project/zipline-reloaded/3.1.1/",
+            "version": "3.1.1"
+          },
+          "thread_environment": {
+            "MKL_NUM_THREADS": "1",
+            "NUMBA_NUM_THREADS": "1",
+            "OMP_NUM_THREADS": "1",
+            "OPENBLAS_NUM_THREADS": "1",
+            "POLARS_MAX_THREADS": "1",
+            "PYTHONHASHSEED": "0"
+          },
+          "worker_self_peak_rss_mb": 158.41796875
+        },
+        {
+          "captured_log_tail": "",
+          "framework": "zipline",
+          "input": {
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+            "raw_sha256": "c37af67d1da290637fa4721b44a0043485234c6c39374856fc09bd77b6ad412e"
+          },
+          "lean_container_observed": true,
+          "ml4t": {
+            "commit": "0315119acc05796d95cc3c344a0418007dde6cbc",
+            "dirty": false
+          },
+          "output": {
+            "fills": {
+              "count": 4288,
+              "sha256": "50f0db39e980f29f693a0806d1d2cff1e88bce680448181418440362a66cabf5"
+            },
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+            "order_intents": {
+              "count": 4306,
+              "sha256": "8ceb30edfe288d834194a069b3f5588dd763139633d2d1eda193511ff7dd7a96"
+            },
+            "terminal_state_sha256": "67e49c164678d98824b30cd2bcd23b422571c3a0261734fda293e899b01b1d2a",
+            "total_pnl": 17079.3,
+            "trade_count": 2271,
+            "trades": {
+              "count": 2271,
+              "sha256": "66c48c8a7633abd9bfd1d5cb6fdef5e625ce2a96b83722b84724b39eed60eefe"
+            }
+          },
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+          "process_peak_rss_mb": 160.76171875,
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+          "profile": "zipline_strict",
+          "python": {
+            "implementation": "cpython",
+            "version": "3.12.11"
+          },
+          "runner_id": "zipline:ml4t",
+          "side": "ml4t",
+          "stages_seconds": {
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+            "framework_call": 1.417193704051897,
+            "input_generation": 0.21940957801416516,
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+            "worker_total": 2.2898331182077527
+          },
+          "target": {
+            "access": "public",
+            "actual_version": "3.1.1",
+            "artifact": "zipline_reloaded-3.1.1.tar.gz",
+            "commit": "09885a2ebc7567d40942c891b3879dc03c745070",
+            "display_name": "Zipline Reloaded",
+            "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+            "license": "Apache-2.0",
+            "package": "zipline-reloaded",
+            "profile": "zipline_strict",
+            "python": ">=3.10",
+            "source": "https://pypi.org/project/zipline-reloaded/3.1.1/",
+            "version": "3.1.1"
+          },
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+            "MKL_NUM_THREADS": "1",
+            "NUMBA_NUM_THREADS": "1",
+            "OMP_NUM_THREADS": "1",
+            "OPENBLAS_NUM_THREADS": "1",
+            "POLARS_MAX_THREADS": "1",
+            "PYTHONHASHSEED": "0"
+          },
+          "worker_self_peak_rss_mb": 158.1640625
+        },
+        {
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+          "framework": "zipline",
+          "input": {
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+            "raw_sha256": "c37af67d1da290637fa4721b44a0043485234c6c39374856fc09bd77b6ad412e"
+          },
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+          "ml4t": {
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+            "dirty": false
+          },
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+              "sha256": "50f0db39e980f29f693a0806d1d2cff1e88bce680448181418440362a66cabf5"
+            },
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+              "sha256": "8ceb30edfe288d834194a069b3f5588dd763139633d2d1eda193511ff7dd7a96"
+            },
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+              "sha256": "66c48c8a7633abd9bfd1d5cb6fdef5e625ce2a96b83722b84724b39eed60eefe"
+            }
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+            "version": "3.12.11"
+          },
+          "runner_id": "zipline:ml4t",
+          "side": "ml4t",
+          "stages_seconds": {
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+            "input_generation": 0.19575455598533154,
+            "output_validation": 0.6345286080613732,
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+          },
+          "target": {
+            "access": "public",
+            "actual_version": "3.1.1",
+            "artifact": "zipline_reloaded-3.1.1.tar.gz",
+            "commit": "09885a2ebc7567d40942c891b3879dc03c745070",
+            "display_name": "Zipline Reloaded",
+            "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+            "license": "Apache-2.0",
+            "package": "zipline-reloaded",
+            "profile": "zipline_strict",
+            "python": ">=3.10",
+            "source": "https://pypi.org/project/zipline-reloaded/3.1.1/",
+            "version": "3.1.1"
+          },
+          "thread_environment": {
+            "MKL_NUM_THREADS": "1",
+            "NUMBA_NUM_THREADS": "1",
+            "OMP_NUM_THREADS": "1",
+            "OPENBLAS_NUM_THREADS": "1",
+            "POLARS_MAX_THREADS": "1",
+            "PYTHONHASHSEED": "0"
+          },
+          "worker_self_peak_rss_mb": 159.125
+        }
+      ],
+      "target": {
+        "access": "public",
+        "actual_version": "3.1.1",
+        "artifact": "zipline_reloaded-3.1.1.tar.gz",
+        "commit": "09885a2ebc7567d40942c891b3879dc03c745070",
+        "display_name": "Zipline Reloaded",
+        "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+        "license": "Apache-2.0",
+        "package": "zipline-reloaded",
+        "profile": "zipline_strict",
+        "python": ">=3.10",
+        "source": "https://pypi.org/project/zipline-reloaded/3.1.1/",
+        "version": "3.1.1"
+      },
+      "warmup": {
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+        "process_wall_seconds": 2.6221440921071917
+      }
+    }
+  },
+  "samples_per_runner": 10,
+  "schema_version": 1,
+  "source_digests": {
+    "benchmark_suite": "dcafa42216566ff5e83ae0788d53d9789c2b7980956ea656c874684730b40523",
+    "framework_manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+    "performance_runner": "b0739317d13321297a7dbb505f1044ef6fe2f70a1d86ae53c56d4c672ad1b0f5",
+    "profiles": "5a8cd8b2568e7e9f524e96fef6bb00ade3310a6f4a71c0c4f7de2f95bbfdb505"
+  },
+  "workload": {
+    "data_points": 12600,
+    "recipe": {
+      "assets": 50,
+      "bars": 252,
+      "bottom_n": 5,
+      "end_session": "2025-12-31",
+      "initial_cash": 1000000.0,
+      "long_target_shares": 100.0,
+      "name": "performance_50_assets_252_sessions",
+      "rebalance_frequency": 1,
+      "seed": 42,
+      "short_target_shares": -100.0,
+      "top_n": 5
+    },
+    "recipe_sha256": "3000b13c09f3bad9dfb6450c6aea002c07482b42f23481f36e97a2b364015c78"
+  }
+}
diff --git a/validation/README.md b/validation/README.md
index 80fca992..86a8a9a0 100644
--- a/validation/README.md
+++ b/validation/README.md
@@ -12,30 +12,36 @@ ml4t-backtest validates framework-specific behavior through configurable profile
 claims require a zero-gap retained result. See [METHODOLOGY.md](METHODOLOGY.md) for the full
 approach.
 
-Validation is performed per-framework in **isolated virtual environments** due to dependency
-conflicts between frameworks (VBT Pro, Backtrader, Zipline).
+Validation is performed per-framework in isolated, locked environments. VectorBT OSS 1.1.0
+requires pandas 3 while Zipline Reloaded 3.1.1 requires pandas below 3, so a shared comparison
+environment cannot reproduce the current target set.
+
+The primary audit uses frozen market data and model-derived targets from three production case
+studies. The scenario matrix and 250-asset workload are synthetic diagnostic and stress suites.
 
 ## Retained Parity Claims
 
 <!-- parity-claims:start -->
 <!-- Generated by validation/generate_parity_claims.py. Do not edit by hand. -->
 
-Scenario claims use the retained release-candidate matrix. "Exact" appears only when every required scenario has zero canonical gap.
+Scenario claims use the retained accepted matrix. "Exact" means terminal values, ordered closed trades, and ordered fills match after 1e-8 quantization. Each record declares whether a surface is native, reconstructed, aggregate-only, input-only, or unavailable; the claim does not extend to unavailable order-lifecycle fields.
 
 | Profile | Pinned framework | Required scenarios | Evidence |
 |---|---|---:|---|
-| `vectorbt_strict` | [VectorBT Pro 2025.12.31](https://github.com/polakowo/vectorbt.pro) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `vectorbt` | [VectorBT OSS 0.28.2](https://pypi.org/project/vectorbt/0.28.2/) | 15/15 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 15/15 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
-
-Large-scale claims are published only when a retained workload has zero canonical gap.
-
-| Profile | Pinned framework | Compared | Trade gap | Terminal value | Evidence |
-|---|---|---:|---:|---:|---|
-| `vectorbt_strict` | VectorBT Pro 2025.12.31 (`1305a1e19743`) | 225,844 trades | 0 | 685179.007330 | [large-scale evidence](https://github.com/ml4t/backtest/blob/main/validation/vectorbt_pro/large_scale_parity.json) |
-
-No large-scale claim is published for Backtrader, Zipline, VectorBT OSS, or LEAN without a passing retained artifact.
+| `vectorbt_strict` | [VectorBT Pro 2026.6.27](https://github.com/polakowo/vectorbt.pro) | 17/17 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `vectorbt_oss_strict` | [VectorBT OSS 1.1.0](https://pypi.org/project/vectorbt/1.1.0/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 17/17 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 16/16 exact | [scenario evidence](https://github.com/ml4t/backtest/blob/main/validation/CORRECTNESS_RESULTS.json) |
+
+The controlled scale workload contains 250 assets and 5,040 daily sessions (1,260,000 bars). Every row has zero canonical gap for target intents, native fills, closed trades reconstructed from those fills, and terminal state reconstructed from the fill ledger and final marks.
+
+| Profile | Current framework | Target intents | Native fills | Fill-derived closed trades | Terminal value | Evidence |
+|---|---|---:|---:|---:|---:|---|
+| `vectorbt_strict` | [VectorBT Pro 2026.6.27](https://github.com/polakowo/vectorbt.pro) | 427,790 | 390,369 | 188,549 | 716,785.408089 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `vectorbt_oss_strict` | [VectorBT OSS 1.1.0](https://pypi.org/project/vectorbt/1.1.0/) | 427,790 | 390,369 | 188,549 | 716,785.408089 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `backtrader_strict` | [Backtrader 1.9.78.123](https://pypi.org/project/backtrader/1.9.78.123/) | 427,790 | 343,813 | 182,019 | -9,166,273.555954 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `zipline_strict` | [Zipline Reloaded 3.1.1](https://pypi.org/project/zipline-reloaded/3.1.1/) | 427,790 | 427,696 | 226,434 | 10,504,095.900000 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
+| `lean` | [LEAN 18001](https://github.com/QuantConnect/Lean) | 427,790 | 361,297 | 191,297 | 184,538.130000 | [scale evidence](https://github.com/ml4t/backtest/blob/main/validation/LARGE_SCALE_RESULTS.json) |
 <!-- parity-claims:end -->
 
 ## How to Run
@@ -60,6 +66,12 @@ The command returns nonzero when a required framework or scenario does not execu
 `--result-json PATH` to retain machine-readable terminal records. An explicitly unsupported pair
 is reported as `unsupported`; it is visible in the matrix and does not count as a pass.
 
+Each passing record includes exact ordered closed-trade and fill comparisons. The trade surface
+contains session, symbol, direction, quantity, entry and exit prices, P&L, and commission. The fill
+surface contains session, symbol, side, quantity, price, and commission. Capability declarations
+identify native, reconstructed, aggregate-only, input-only, and unavailable surfaces. See
+`behavior_coverage.toml` for the profile-field evidence map.
+
 ### Isolated release-gate runner
 
 ```bash
@@ -70,61 +82,99 @@ python validation/run_all_correctness.py
 python validation/run_all_correctness.py --framework backtrader --scenarios 01,03,05,09
 ```
 
-The isolated runner writes `validation/CORRECTNESS_RESULTS.json` and distinguishes comparison
-failures, unsupported pairs, unavailable environments, adapter failures, subprocess failures,
-timeouts, skips, malformed records, and missing scenarios. Every status except `pass` and an
-explicitly optional `unsupported` record fails the release gate.
+The isolated runner always writes a diagnostic candidate under `validation/candidates/`. It
+replaces `validation/CORRECTNESS_RESULTS.json` only after the complete required matrix passes with
+the declared pair counts. Records retain both frameworks' measurements, canonical comparisons,
+runtime identity, input digests, adapter identity, and source provenance. Comparison failures,
+unavailable environments, adapter failures, subprocess failures, timeouts, skips, malformed
+records, missing pairs, duplicates, and incorrect required or unsupported counts fail the gate.
 
-### Large-scale benchmarks
+### Retained real-strategy evidence
 
 ```bash
-# Framework benchmark
-python validation/benchmark_suite.py --profile backtrader_strict --framework backtrader
+# Compare previously generated native and ML4T outputs
+uv run python validation/real_strategy_evidence.py \
+  --evidence-root PATH/TO/REAL_STRATEGY_OUTPUTS \
+  --output validation/candidates/REAL_STRATEGY_RESULTS.candidate.json
+
+# Repeat engine-only timings for correctness-passing pairs
+uv run python validation/real_strategy_benchmark.py \
+  --bundle-root PATH/TO/CONTENT_ADDRESSED_BUNDLES \
+  --samples 10
+```
+
+The content-addressed input bundles are materialized before engine execution. Each pair receives
+the same frozen targets. Timing excludes input loading, inference, target construction, adapter
+preparation, result extraction, serialization, and reporting. The performance runner refuses to
+time a pair that did not pass the retained correctness comparison.
 
-# Full validation (correctness + benchmarks)
-python validation/run_full_validation.py
+### Retained synthetic scale and performance evidence
+
+```bash
+# Validate retained reconstructable scale evidence
+uv run python validation/large_scale_evidence.py --check --verify-input
+
+# Validate repeated cross-framework performance evidence
+uv run python validation/cross_framework_performance.py --check
+
+# Regenerate the complete controlled performance artifact
+uv run python validation/cross_framework_performance.py --samples 10
 ```
 
+The performance runner uses one isolated warm-up and ten isolated measurements per runner. It
+retains complete-process wall time, process-tree peak RSS including the LEAN container, raw
+samples, deterministic 95% bootstrap intervals, exact output checksums, immutable framework
+identities, and semantic disclosures for an idiomatic view. No stable ratio claim is generated.
+
 ## Virtual Environment Setup
 
 ```bash
-# VectorBT Pro 2025.12.31, commit 1305a1e1974325db9382eaeacc6452e9b075ca71
-# Requires an authorized VectorBT Pro license and GitHub SSH access.
-uv venv .venv-vectorbt-pro --python 3.12
-uv pip install --python .venv-vectorbt-pro/bin/python \
-  "vectorbtpro @ git+ssh://git@github.com/polakowo/vectorbt.pro.git@1305a1e1974325db9382eaeacc6452e9b075ca71"
-uv pip install --python .venv-vectorbt-pro/bin/python -e .
-uv run python validation/run_all_correctness.py --framework vectorbt_pro
-
-# VectorBT OSS
-python3 -m venv .venv-vectorbt
-.venv-vectorbt/bin/pip install vectorbt pandas numpy polars pyyaml pydantic numba
-
-# Backtrader
-python3 -m venv .venv-backtrader
-.venv-backtrader/bin/pip install backtrader pandas numpy polars pyyaml pydantic numba exchange_calendars
-
-# Zipline
-python3 -m venv .venv-zipline
-.venv-zipline/bin/pip install zipline-reloaded pandas numpy polars pyyaml pydantic numba exchange_calendars
-
-# Never mix VBT OSS and Pro in the same environment
+# Build and verify all public targets from their committed uv locks
+python validation/build_framework_env.py --all-public
+
+# Licensed VectorBT Pro requires authorized SSH access to the frozen source commit
+python validation/build_framework_env.py --framework vectorbt_pro
+
+# Verify the locked LEAN CLI and immutable engine image
+python validation/build_framework_env.py --framework lean
+
+# Reproduce the native behavior and Chapter 16 comparison evidence
+.venv-lean/bin/python validation/native/lean_behavior.py \
+  --lean-command .venv-lean/bin/lean \
+  --output /tmp/lean-native.json
+.venv-lean/bin/python validation/run_lean_case_studies.py \
+  --lean-command .venv-lean/bin/lean \
+  --output /tmp/lean-case-studies.json
 ```
 
+The target versions, artifact hashes, source commits, interpreter paths, and expected matrix counts
+are defined in `framework_targets.toml`. Each lock is under `validation/environments/`. CI builds
+those locks and executes all 17 declared pairs for each public framework; an omitted pair fails.
+The release workflow separately requires licensed VectorBT Pro execution and fresh LEAN native
+and Chapter 16 execution against the frozen image. Repository workflows never store licensed
+credentials.
+
 ## File Organization
 
 ```
 validation/
 ├── README.md                  # This file
 ├── METHODOLOGY.md             # Validation philosophy and behavioral matrix
+├── behavior_coverage.toml     # Profile fields mapped to native and cross-engine evidence
 ├── common/                    # Shared infrastructure (types, data generators, comparator)
-├── scenarios/                 # Declarative scenario definitions (16 configs)
+├── scenarios/                 # Declarative scenario definitions (17 configs)
 ├── frameworks/                # Parameterized framework drivers (4 modules)
 ├── run_scenario.py            # Unified CLI runner
 ├── run_all_correctness.py     # Isolated release-gate correctness runner
-├── run_all_benchmarks.py      # Framework benchmark loop
-├── benchmark_suite.py         # Large-scale benchmark runner
-├── run_full_validation.py     # Complete validation pipeline
+├── real_strategy_applicability.toml  # Supported case-study/framework pairs
+├── real_strategy_comparison.py       # Exact real-strategy comparator
+├── real_strategy_benchmark.py        # Repeated engine-only timings
+├── REAL_STRATEGY_RESULTS.json        # Retained correctness evidence
+├── REAL_STRATEGY_PERFORMANCE.json    # Retained engine timing evidence
+├── large_scale_evidence.py    # Reconstructable exact scale matrix
+├── cross_framework_performance.py  # Repeated controlled and idiomatic evidence
+├── run_all_benchmarks.py      # Compatibility route to the retained performance runner
+├── benchmark_suite.py         # Shared framework workload adapters
 ├── lean/                      # LEAN integration
 ├── trade_logs/                # Golden file CSVs (gitignored)
 └── nautilus/                  # Nautilus Trader evaluation
diff --git a/validation/REAL_STRATEGY_PERFORMANCE.json b/validation/REAL_STRATEGY_PERFORMANCE.json
new file mode 100644
index 00000000..7803f449
--- /dev/null
+++ b/validation/REAL_STRATEGY_PERFORMANCE.json
@@ -0,0 +1,474 @@
+{
+  "correctness_evidence_generated_at": "2026-08-14T21:50:26.236995+00:00",
+  "environment": {
+    "cpu_count": 24,
+    "frameworks": {
+      "backtrader": {
+        "access": "public",
+        "artifact": "backtrader-1.9.78.123-py2.py3-none-any.whl",
+        "display_name": "Backtrader",
+        "environment": ".venv-backtrader",
+        "immutable_id": "sha256:9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+        "license": "GPL-3.0-or-later",
+        "package": "backtrader",
+        "profile": "backtrader_strict",
+        "python": "3.12 audit interpreter; upstream package metadata does not declare a range",
+        "python_env_var": "ML4T_BACKTRADER_PYTHON",
+        "required_scenarios": 17,
+        "scenario_matrix": true,
+        "source": "https://pypi.org/project/backtrader/1.9.78.123/",
+        "unsupported_scenarios": 0,
+        "version": "1.9.78.123"
+      },
+      "lean": {
+        "access": "public",
+        "artifact": "quantconnect/lean@sha256:ecd62b0e418d40d1d7c0cd95e90a94e397642a21d2c8810614830c8a4e9a8f70",
+        "cli_immutable_id": "sha256:eaa4c08f16295b76f005e429d9ca0d0453784dc1a40c1f5cbe5e50c02a05bd7c",
+        "cli_version": "1.0.228",
+        "display_name": "LEAN",
+        "environment": ".venv-lean",
+        "immutable_id": "sha256:ecd62b0e418d40d1d7c0cd95e90a94e397642a21d2c8810614830c8a4e9a8f70",
+        "license": "Apache-2.0",
+        "package": "lean",
+        "platform_artifact": "linux/amd64@sha256:cbe3f26b3f16c57be836b2cf913253d434f58e010c84ed038360d26b9df88307",
+        "profile": "lean",
+        "python": "3.11",
+        "python_env_var": "ML4T_LEAN_PYTHON",
+        "required_scenarios": 0,
+        "scenario_matrix": false,
+        "source": "https://github.com/QuantConnect/Lean",
+        "source_commit": "278fcb3d1b815b63ccadba68d7ae54422e34b792",
+        "unsupported_scenarios": 0,
+        "version": "18001"
+      },
+      "vectorbt_oss": {
+        "access": "public",
+        "artifact": "vectorbt-1.1.0.tar.gz",
+        "display_name": "VectorBT OSS",
+        "environment": ".venv-vectorbt-oss",
+        "immutable_id": "sha256:67a3b41466234485af70c18d201da105f1ebb2c1d1fac079db20059e45ddc73b",
+        "license": "Apache-2.0 WITH Commons-Clause",
+        "package": "vectorbt",
+        "profile": "vectorbt_oss_strict",
+        "python": ">=3.11,<3.15",
+        "python_env_var": "ML4T_VECTORBT_OSS_PYTHON",
+        "required_scenarios": 16,
+        "scenario_matrix": true,
+        "source": "https://pypi.org/project/vectorbt/1.1.0/",
+        "source_commit": "259d2d89fe2e7638baf3ca76c394937cd32b656d",
+        "unsupported_scenarios": 1,
+        "version": "1.1.0"
+      },
+      "vectorbt_pro": {
+        "access": "licensed",
+        "display_name": "VectorBT Pro",
+        "environment": ".venv-vectorbt-pro",
+        "immutable_id": "git:6e18cf0aa37849cfc20848f40f1d26ecfdc771b4",
+        "license": "Proprietary",
+        "package": "vectorbtpro",
+        "profile": "vectorbt_strict",
+        "python": ">=3.11",
+        "python_env_var": "ML4T_VECTORBT_PRO_PYTHON",
+        "required_scenarios": 17,
+        "scenario_matrix": true,
+        "source": "https://github.com/polakowo/vectorbt.pro",
+        "source_commit": "6e18cf0aa37849cfc20848f40f1d26ecfdc771b4",
+        "unsupported_scenarios": 0,
+        "version": "2026.6.27"
+      },
+      "zipline": {
+        "access": "public",
+        "artifact": "zipline_reloaded-3.1.1.tar.gz",
+        "display_name": "Zipline Reloaded",
+        "environment": ".venv-zipline",
+        "immutable_id": "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+        "license": "Apache-2.0",
+        "package": "zipline-reloaded",
+        "profile": "zipline_strict",
+        "python": ">=3.10",
+        "python_env_var": "ML4T_ZIPLINE_PYTHON",
+        "required_scenarios": 16,
+        "scenario_matrix": true,
+        "source": "https://pypi.org/project/zipline-reloaded/3.1.1/",
+        "source_commit": "09885a2ebc7567d40942c891b3879dc03c745070",
+        "unsupported_scenarios": 1,
+        "version": "3.1.1"
+      }
+    },
+    "machine": "x86_64",
+    "platform": "Linux-6.8.0-136-generic-x86_64-with-glibc2.39",
+    "processor": "x86_64"
+  },
+  "generated_at": "2026-08-14T22:02:59.708731+00:00",
+  "records": [
+    {
+      "case_study": "etfs",
+      "correctness_status": "pass",
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+      "serialization",
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+}
diff --git a/validation/REAL_STRATEGY_RESULTS.json b/validation/REAL_STRATEGY_RESULTS.json
new file mode 100644
index 00000000..74e9c606
--- /dev/null
+++ b/validation/REAL_STRATEGY_RESULTS.json
@@ -0,0 +1,783 @@
+{
+  "comparison_policy": {
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+    "fill_order": "canonical timestamp, asset, side, quantity, price, commission",
+    "meaning": "zero numeric gap after canonical quantization, not bit identity",
+    "rounding": "ROUND_HALF_EVEN",
+    "timestamp_domain": {
+      "cme_futures": "session date",
+      "crypto_perps_funding": "exact UTC event timestamp",
+      "etfs": "session date"
+    }
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+        "license": "Proprietary",
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+          "max_canonical_difference": "0.00000000",
+          "ml4t_records": 1,
+          "ml4t_sha256": "4e87bd8a979d23c1189bde4d37dcbf51f9a32462a653e436223e7cf29dc494b8",
+          "passed": true
+        }
+      }
+    },
+    {
+      "case_study": "etfs",
+      "engine_seconds": {
+        "framework": 4.122711522039026,
+        "ml4t": 0.5797442020848393,
+        "single_run_diagnostic_only": true
+      },
+      "evidence": {
+        "framework_manifest_sha256": "250cf56114937129fb657a4749e9beb026f4e077d356a7a1d7e8cf51c50e2fc2",
+        "ml4t_manifest_sha256": "61b1a6aa4240235b89e4b1b8e3c481081da43047f4a8f5d2fbe5ff67d9cc20ba"
+      },
+      "excluded_surfaces": {
+        "accepted_unfilled_orders": "not exposed by every native runner",
+        "cash": "compared separately for LEAN equities",
+        "closed_trades": "not a common native framework concept",
+        "intents": "shared frozen target input is identified, but engines do not expose a common native intent log",
+        "positions": "not exposed in a common native record schema by every runner"
+      },
+      "framework": "lean",
+      "input_bundle_sha256": "01f38079ce47821a5379d3769e86f4a2170b88033108153bfc0f928698e946db",
+      "negative_control": {
+        "detected": true,
+        "mutation": "first fill price + 0.00000001"
+      },
+      "profile": "lean",
+      "status": "pass",
+      "surfaces": {
+        "cash": {
+          "coverage": {
+            "framework_only_timestamps": 5,
+            "ml4t_only_timestamps": 0,
+            "shared_timestamps": 1995
+          },
+          "first_divergence": null,
+          "framework_records": 1995,
+          "framework_sha256": "16f270b64f43ed22739d234d1b7abe1611c253828a5964411aae8fa3955b9730",
+          "max_canonical_difference": "0.00000000",
+          "ml4t_records": 1995,
+          "ml4t_sha256": "30beda4a3a1167d861ee2c16622ef00c00ded113c1acf6dea0b8eaf0b78fd76e",
+          "passed": true
+        },
+        "equity": {
+          "coverage": {
+            "framework_only_timestamps": 5,
+            "ml4t_only_timestamps": 0,
+            "shared_timestamps": 1995
+          },
+          "first_divergence": null,
+          "framework_records": 1995,
+          "framework_sha256": "7959271a1f6e2dc65ee85a40114db98334a8852941a2fea28948bdf9eaeff5d1",
+          "max_canonical_difference": "0.00000000",
+          "ml4t_records": 1995,
+          "ml4t_sha256": "90912934200276e9da497a2ac61e5b459b660815f3b63f43c971e4c4f553b092",
+          "passed": true
+        },
+        "fills": {
+          "first_divergence": null,
+          "framework_records": 2457,
+          "framework_sha256": "bb7685c44f3439854f69c28ed45f00cf6590c41fb4186e008bfc5ec8854c8f34",
+          "max_canonical_difference": "0.00000000",
+          "ml4t_records": 2457,
+          "ml4t_sha256": "bb7685c44f3439854f69c28ed45f00cf6590c41fb4186e008bfc5ec8854c8f34",
+          "passed": true
+        },
+        "rejection_count": {
+          "first_divergence": null,
+          "framework_records": 1,
+          "framework_sha256": "59fbab4bac7cb12eee5b33c7df3f95e89686eb8f430c84695e63c7557c702414",
+          "max_canonical_difference": "0.00000000",
+          "ml4t_records": 1,
+          "ml4t_sha256": "59fbab4bac7cb12eee5b33c7df3f95e89686eb8f430c84695e63c7557c702414",
+          "passed": true
+        },
+        "terminal": {
+          "first_divergence": null,
+          "framework_records": 1,
+          "framework_sha256": "dcdf690e7ea4a122b3ca6a083112a518058dc72bdba2bb120334d4b9636f47fc",
+          "max_canonical_difference": "0.00000000",
+          "ml4t_records": 1,
+          "ml4t_sha256": "4e9b140ade6e038a406e3a9332649f239d317a7666468785ce8a1c7f89318bff",
+          "passed": true
+        }
+      }
+    },
+    {
+      "case_study": "cme_futures",
+      "engine_seconds": {
+        "framework": 0.4237614271696657,
+        "ml4t": 0.5547289319802076,
+        "single_run_diagnostic_only": true
+      },
+      "evidence": {
+        "framework_manifest_sha256": "781c018b31759e5eaf2297f7dcf13b36494c3430a334f4fa2e1df5adbfed7b2b",
+        "ml4t_manifest_sha256": "c142a3136033d6f7caf2e40a2603d784d7e858d6eb754829ea328a0a084dc5ca"
+      },
+      "excluded_surfaces": {
+        "accepted_unfilled_orders": "not exposed by every native runner",
+        "cash": "not exposed with common accounting semantics",
+        "closed_trades": "not a common native framework concept",
+        "intents": "shared frozen target input is identified, but engines do not expose a common native intent log",
+        "positions": "not exposed in a common native record schema by every runner"
+      },
+      "framework": "vectorbt_pro",
+      "input_bundle_sha256": "c7191027f550ef1be0c9528dac08e7c2bf6a76c86d935f593efeb1ad8b628c39",
+      "negative_control": {
+        "detected": true,
+        "mutation": "first fill price + 0.00000001"
+      },
+      "profile": "vectorbt_strict",
+      "status": "fail",
+      "surfaces": {
+        "equity": {
+          "coverage": {
+            "framework_only_timestamps": 1,
+            "ml4t_only_timestamps": 0,
+            "shared_timestamps": 1595
+          },
+          "first_divergence": {
+            "canonical_gap": "0.00000001",
+            "field": "equity",
+            "framework": {
+              "equity": "10000000.0",
+              "timestamp": "2019-01-04"
+            },
+            "index": 310,
+            "kind": "record",
+            "ml4t": {
+              "equity": "9999999.999999993",
+              "timestamp": "2019-01-04"
+            }
+          },
+          "framework_records": 1595,
+          "framework_sha256": "b1b40cf1cbcbc671db8670a19066dfaa77b497e6d03b06d83f087ad0a8aefc2c",
+          "max_canonical_difference": "0.00000010",
+          "ml4t_records": 1595,
+          "ml4t_sha256": "b3d629a19f386d6688964e89188f3ba27c95d34be5e96e22a1c9c8b83427a98b",
+          "passed": false
+        },
+        "fills": {
+          "first_divergence": null,
+          "framework_records": 3545,
+          "framework_sha256": "33a8c1d5aac88de6255f5a23742619e68dcf77804f5158f02a910df265d5c154",
+          "max_canonical_difference": "0.00000000",
+          "ml4t_records": 3545,
+          "ml4t_sha256": "7588d63e48658ce630d22b814df79345ae7a8fdf53be1f133858f44b9f375971",
+          "passed": true
+        },
+        "terminal": {
+          "first_divergence": {
+            "canonical_gap": "0.00000007",
+            "field": "final_value",
+            "framework": {
+              "final_value": "21780101.163148317"
+            },
+            "index": 0,
+            "kind": "record",
+            "ml4t": {
+              "final_value": "21780101.16314839"
+            }
+          },
+          "framework_records": 1,
+          "framework_sha256": "f0c1745e2a779c7b4127d81f854e355c791224c93f190167be7207250d8fe271",
+          "max_canonical_difference": "0.00000007",
+          "ml4t_records": 1,
+          "ml4t_sha256": "9f2c5af308ff360b1b6987eb84facaeeb98a44d08471480f4eeccb85ef11fc46",
+          "passed": false
+        }
+      }
+    },
+    {
+      "case_study": "cme_futures",
+      "framework": "vectorbt_oss",
+      "reason": "no native futures contract multiplier and margin-account model",
+      "source": "https://vectorbt.dev/api/portfolio/base/",
+      "status": "unsupported"
+    },
+    {
+      "case_study": "cme_futures",
+      "engine_seconds": {
+        "framework": 2.906314143911004,
+        "ml4t": 0.5458641869481653,
+        "single_run_diagnostic_only": true
+      },
+      "evidence": {
+        "framework_manifest_sha256": "ac82009ee99eecfe9436f521c40ff00414dadd623259e1ea2ab29b307f93151a",
+        "ml4t_manifest_sha256": "bb4c7129768bd4eb6a735d32eb0f57b06188f39961c89c4c3270faa2dd7acf37"
+      },
+      "excluded_surfaces": {
+        "accepted_unfilled_orders": "not exposed by every native runner",
+        "cash": "not exposed with common accounting semantics",
+        "closed_trades": "not a common native framework concept",
+        "intents": "shared frozen target input is identified, but engines do not expose a common native intent log",
+        "positions": "not exposed in a common native record schema by every runner"
+      },
+      "framework": "backtrader",
+      "input_bundle_sha256": "c7191027f550ef1be0c9528dac08e7c2bf6a76c86d935f593efeb1ad8b628c39",
+      "negative_control": {
+        "detected": true,
+        "mutation": "first fill price + 0.00000001"
+      },
+      "profile": "backtrader_strict",
+      "status": "fail",
+      "surfaces": {
+        "equity": {
+          "coverage": {
+            "framework_only_timestamps": 1,
+            "ml4t_only_timestamps": 0,
+            "shared_timestamps": 1595
+          },
+          "first_divergence": {
+            "canonical_gap": "0.00000001",
+            "field": "equity",
+            "framework": {
+              "equity": "8260040.797423724",
+              "timestamp": "2019-02-01"
+            },
+            "index": 330,
+            "kind": "record",
+            "ml4t": {
+              "equity": "8260040.7974237185",
+              "timestamp": "2019-02-01"
+            }
+          },
+          "framework_records": 1595,
+          "framework_sha256": "420284821eb233db8012d42b32f4df081744545df7c98df38e974ef87b8d8d1c",
+          "max_canonical_difference": "0.00000015",
+          "ml4t_records": 1595,
+          "ml4t_sha256": "89ba33c5e41e25db2aec0cb23ce625fbe8b2ff7ff1109f4d461dc9956105b7f1",
+          "passed": false
+        },
+        "fills": {
+          "first_divergence": null,
+          "framework_records": 3376,
+          "framework_sha256": "079faf95a56575dca51207bf0587d0d792fe66dff32021f19d85114d8b3dfcb0",
+          "max_canonical_difference": "0.00000000",
+          "ml4t_records": 3376,
+          "ml4t_sha256": "4e8fc7f1acdbf85567d0c8148f2b1532dee362b1f4913058851d29a5e20896ee",
+          "passed": true
+        },
+        "rejection_count": {
+          "first_divergence": null,
+          "framework_records": 1,
+          "framework_sha256": "59fbab4bac7cb12eee5b33c7df3f95e89686eb8f430c84695e63c7557c702414",
+          "max_canonical_difference": "0.00000000",
+          "ml4t_records": 1,
+          "ml4t_sha256": "59fbab4bac7cb12eee5b33c7df3f95e89686eb8f430c84695e63c7557c702414",
+          "passed": true
+        },
+        "terminal": {
+          "first_divergence": {
+            "canonical_gap": "0.00000015",
+            "field": "final_value",
+            "framework": {
+              "final_value": "37957959.26743194"
+            },
+            "index": 0,
+            "kind": "record",
+            "ml4t": {
+              "final_value": "37957959.26743179"
+            }
+          },
+          "framework_records": 1,
+          "framework_sha256": "6ba61c2f2bdff3890ecbfac82425f15f4c2efaec002753bc6c31b52636106e10",
+          "max_canonical_difference": "0.00000015",
+          "ml4t_records": 1,
+          "ml4t_sha256": "66cdabf91ff8007a7010c0f36cf05e84eb4d4944a3bb85d8b296463ebdfe908a",
+          "passed": false
+        }
+      }
+    },
+    {
+      "case_study": "cme_futures",
+      "framework": "zipline",
+      "reason": "the frozen workload has continuous root series but no dated contract chain or roll map",
+      "source": "https://zipline.ml4trading.io/api-reference.html",
+      "status": "unsupported"
+    },
+    {
+      "case_study": "cme_futures",
+      "framework": "lean",
+      "reason": "the frozen workload has continuous root series but no dated contract chain or roll map",
+      "source": "https://www.quantconnect.com/docs/v2/writing-algorithms/securities/asset-classes/futures",
+      "status": "unsupported"
+    },
+    {
+      "case_study": "crypto_perps_funding",
+      "framework": "vectorbt_pro",
+      "reason": "no native perpetual-futures funding and margin-account model",
+      "source": "https://vectorbt.pro/features/portfolio/",
+      "status": "unsupported"
+    },
+    {
+      "case_study": "crypto_perps_funding",
+      "framework": "vectorbt_oss",
+      "reason": "no native perpetual-futures funding and margin-account model",
+      "source": "https://vectorbt.dev/api/portfolio/base/",
+      "status": "unsupported"
+    },
+    {
+      "case_study": "crypto_perps_funding",
+      "framework": "backtrader",
+      "reason": "no native perpetual-futures funding model",
+      "source": "https://www.backtrader.com/docu/commission-schemes/commission-schemes/",
+      "status": "unsupported"
+    },
+    {
+      "case_study": "crypto_perps_funding",
+      "framework": "zipline",
+      "reason": "no crypto perpetual-futures asset and funding model",
+      "source": "https://zipline.ml4trading.io/api-reference.html",
+      "status": "unsupported"
+    },
+    {
+      "case_study": "crypto_perps_funding",
+      "engine_seconds": {
+        "framework": 4.180981411831453,
+        "ml4t": 0.7640254779253155,
+        "single_run_diagnostic_only": true
+      },
+      "evidence": {
+        "framework_manifest_sha256": "a20e2e83439deeecc0e1ab9e1be959a31957dd8393bd15bd1f7e36d3a3c85e7a",
+        "ml4t_manifest_sha256": "65751e1fd35a5ab468c81c07a986193e377e547b8e0a44328f6aed687eaa3043"
+      },
+      "excluded_surfaces": {
+        "accepted_unfilled_orders": "not exposed by every native runner",
+        "cash": "not exposed with common accounting semantics",
+        "closed_trades": "not a common native framework concept",
+        "intents": "shared frozen target input is identified, but engines do not expose a common native intent log",
+        "positions": "not exposed in a common native record schema by every runner"
+      },
+      "framework": "lean",
+      "input_bundle_sha256": "2acee3c8542043266e6f9c0dfc9434c95b4469ef6fcaf0556efc569fc9721cdd",
+      "negative_control": {
+        "detected": true,
+        "mutation": "first fill price + 0.00000001"
+      },
+      "profile": "lean_crypto_future",
+      "status": "pass",
+      "surfaces": {
+        "equity": {
+          "coverage": {
+            "framework_only_timestamps": 0,
+            "ml4t_only_timestamps": 0,
+            "shared_timestamps": 2426
+          },
+          "first_divergence": null,
+          "framework_records": 2426,
+          "framework_sha256": "e6dd17ae20dd049dc63534d4f83ddd2f663d036811e3aa588644a8a753dc6f22",
+          "max_canonical_difference": "0.00000000",
+          "ml4t_records": 2426,
+          "ml4t_sha256": "6bcc1f4bec12a1bf8cdc8ea800aae99f742295686e2529c5572c7590d863baf7",
+          "passed": true
+        },
+        "fills": {
+          "first_divergence": null,
+          "framework_records": 8408,
+          "framework_sha256": "724263fa265d59ef7d650a7f168a35aa056af6db81b7934519a87bbebf281cf0",
+          "max_canonical_difference": "0.00000000",
+          "ml4t_records": 8408,
+          "ml4t_sha256": "b3e3877d7eded50fa0f5d168086fcfb9f1e18856a3506479f2312e48186d234f",
+          "passed": true
+        },
+        "rejection_count": {
+          "first_divergence": null,
+          "framework_records": 1,
+          "framework_sha256": "59fbab4bac7cb12eee5b33c7df3f95e89686eb8f430c84695e63c7557c702414",
+          "max_canonical_difference": "0.00000000",
+          "ml4t_records": 1,
+          "ml4t_sha256": "59fbab4bac7cb12eee5b33c7df3f95e89686eb8f430c84695e63c7557c702414",
+          "passed": true
+        },
+        "terminal": {
+          "first_divergence": null,
+          "framework_records": 1,
+          "framework_sha256": "59a1167e8efd652cf03b0ce0b34c9612fdd03c2e653c0e282a007ca950140635",
+          "max_canonical_difference": "0.00000000",
+          "ml4t_records": 1,
+          "ml4t_sha256": "66c05a1c0dbc0b8b194846e4f2709cb7c887955f3d86049f6336a992c3967e6b",
+          "passed": true
+        }
+      }
+    }
+  ],
+  "schema_version": 1,
+  "scope": {
+    "case_studies": [
+      "etfs",
+      "cme_futures",
+      "crypto_perps_funding"
+    ],
+    "frameworks": [
+      "vectorbt_pro",
+      "vectorbt_oss",
+      "backtrader",
+      "zipline",
+      "lean"
+    ],
+    "real_strategy_equivalence_gate_passed": false,
+    "required_pairs": 8,
+    "unsupported_pairs": 7
+  }
+}
diff --git a/validation/backtrader/benchmark_performance.py b/validation/backtrader/benchmark_performance.py
index 3d13a404..1388c445 100644
--- a/validation/backtrader/benchmark_performance.py
+++ b/validation/backtrader/benchmark_performance.py
@@ -1,308 +1,15 @@
 #!/usr/bin/env python3
-"""Performance benchmark: ml4t.backtest vs Backtrader.
+"""Route the former Backtrader benchmark entry point to retained performance evidence."""
 
-This script benchmarks runtime performance across different data sizes
-and number of assets.
+from __future__ import annotations
 
-Run from .venv-backtrader environment:
-    .venv-backtrader/bin/python3 validation/backtrader/benchmark_performance.py
-
-Metrics:
-- Total runtime (seconds)
-- Trades per second
-- Memory usage (MB)
-"""
-
-import gc
 import sys
-import time
-import tracemalloc
 from pathlib import Path
 
-import numpy as np
-import pandas as pd
-
-# Add project root to path
-PROJECT_ROOT = Path(__file__).parent.parent.parent
-sys.path.insert(0, str(PROJECT_ROOT / "src"))
-
-
-def generate_benchmark_data(n_bars: int, n_assets: int, seed: int = 42) -> tuple:
-    """Generate benchmark data for both frameworks."""
-    np.random.seed(seed)
-
-    dates = pd.date_range(start="2020-01-01", periods=n_bars, freq="D")
-
-    # Generate price data for multiple assets
-    asset_data = {}
-    for i in range(n_assets):
-        base_price = 100.0 + i * 10
-        returns = np.random.randn(n_bars) * 0.02
-        prices = base_price * np.exp(np.cumsum(returns))
-
-        asset_data[f"ASSET_{i:03d}"] = pd.DataFrame(
-            {
-                "open": prices * (1 + np.random.randn(n_bars) * 0.005),
-                "high": prices * (1 + np.abs(np.random.randn(n_bars)) * 0.01),
-                "low": prices * (1 - np.abs(np.random.randn(n_bars)) * 0.01),
-                "close": prices,
-                "volume": np.random.randint(100000, 1000000, n_bars).astype(float),
-            },
-            index=dates,
-        )
-
-    # Generate signals - entry every 20 bars, exit 10 bars later
-    entries = np.zeros(n_bars, dtype=bool)
-    exits = np.zeros(n_bars, dtype=bool)
-
-    i = 0
-    while i < n_bars - 11:
-        entries[i] = True
-        exits[i + 10] = True
-        i += 20
-
-    return asset_data, entries, exits, dates
-
-
-def benchmark_backtrader(asset_data: dict, entries: np.ndarray, exits: np.ndarray) -> dict:
-    """Benchmark Backtrader."""
-    import backtrader as bt
-
-    class PandasData(bt.feeds.PandasData):
-        params = (
-            ("datetime", None),
-            ("open", "open"),
-            ("high", "high"),
-            ("low", "low"),
-            ("close", "close"),
-            ("volume", "volume"),
-            ("openinterest", -1),
-        )
-
-    class BenchmarkStrategy(bt.Strategy):
-        params = (("entries", None), ("exits", None))
-
-        def __init__(self):
-            self.bar_count = 0
-            self.trade_count = 0
-
-        def next(self):
-            idx = self.bar_count
-            for i, data in enumerate(self.datas):
-                if not self.getposition(data):
-                    if idx < len(self.params.entries) and self.params.entries[idx]:
-                        self.buy(data=data, size=100)
-                else:
-                    if idx < len(self.params.exits) and self.params.exits[idx]:
-                        self.close(data=data)
-            self.bar_count += 1
-
-        def notify_trade(self, trade):
-            if trade.isclosed:
-                self.trade_count += 1
-
-    gc.collect()
-    tracemalloc.start()
-    start_time = time.perf_counter()
-
-    cerebro = bt.Cerebro()
-    cerebro.broker.setcash(100_000.0)
-    cerebro.broker.setcommission(commission=0.0)
-
-    for name, df in asset_data.items():
-        data = PandasData(dataname=df)
-        cerebro.adddata(data, name=name)
-
-    cerebro.addstrategy(BenchmarkStrategy, entries=entries, exits=exits)
-
-    results = cerebro.run()
-    strategy = results[0]
-    num_trades = strategy.trade_count
-
-    end_time = time.perf_counter()
-    current, peak = tracemalloc.get_traced_memory()
-    tracemalloc.stop()
-
-    return {
-        "framework": "Backtrader",
-        "runtime_sec": end_time - start_time,
-        "num_trades": num_trades,
-        "memory_mb": peak / 1024 / 1024,
-    }
-
-
-def benchmark_ml4t_backtest(
-    asset_data: dict, entries: np.ndarray, exits: np.ndarray, dates
-) -> dict:
-    """Benchmark ml4t.backtest."""
-    import polars as pl
-
-    from ml4t.backtest._validation_imports import DataFeed, Engine, ExecutionMode, NoCommission, NoSlippage, Strategy
-
-    # Prepare data in polars format
-    rows = []
-    for asset_name, df in asset_data.items():
-        for i, (ts, row) in enumerate(df.iterrows()):
-            rows.append(
-                {
-                    "timestamp": ts.to_pydatetime(),
-                    "asset": asset_name,
-                    "open": row["open"],
-                    "high": row["high"],
-                    "low": row["low"],
-                    "close": row["close"],
-                    "volume": row["volume"],
-                }
-            )
-
-    prices_pl = pl.DataFrame(rows)
-
-    # Prepare signals
-    signal_rows = []
-    for asset_name in asset_data:
-        for i, ts in enumerate(dates):
-            signal_rows.append(
-                {
-                    "timestamp": ts.to_pydatetime(),
-                    "asset": asset_name,
-                    "entry": bool(entries[i]),
-                    "exit": bool(exits[i]),
-                }
-            )
-
-    signals_pl = pl.DataFrame(signal_rows)
-
-    class BenchmarkStrategy(Strategy):
-        def on_data(self, timestamp, data, context, broker):
-            for asset_name, asset_data in data.items():
-                signals = asset_data.get("signals", {})
-                position = broker.get_position(asset_name)
-                current_qty = position.quantity if position else 0
-
-                if signals.get("exit") and current_qty > 0:
-                    broker.close_position(asset_name)
-                elif signals.get("entry") and current_qty == 0:
-                    broker.submit_order(asset_name, 100)
-
-    gc.collect()
-    tracemalloc.start()
-    start_time = time.perf_counter()
-
-    feed = DataFeed(prices_df=prices_pl, signals_df=signals_pl)
-    strategy = BenchmarkStrategy()
-
-    engine = Engine(
-        feed,
-        strategy,
-        initial_cash=100_000.0,
-        allow_short_selling=False,
-        commission_model=NoCommission(),
-        slippage_model=NoSlippage(),
-        execution_mode=ExecutionMode.NEXT_BAR,  # Match Backtrader
-    )
-
-    results = engine.run()
-    num_trades = results["num_trades"]
-
-    end_time = time.perf_counter()
-    current, peak = tracemalloc.get_traced_memory()
-    tracemalloc.stop()
-
-    return {
-        "framework": "ml4t.backtest",
-        "runtime_sec": end_time - start_time,
-        "num_trades": num_trades,
-        "memory_mb": peak / 1024 / 1024,
-    }
-
-
-def run_benchmark(n_bars: int, n_assets: int) -> dict:
-    """Run benchmark for specific configuration."""
-    print(f"\n  Generating data: {n_bars} bars x {n_assets} assets...")
-    asset_data, entries, exits, dates = generate_benchmark_data(n_bars, n_assets)
-
-    print("  Running Backtrader...")
-    bt_results = benchmark_backtrader(asset_data, entries, exits)
-
-    print("  Running ml4t.backtest...")
-    ml4t_results = benchmark_ml4t_backtest(asset_data, entries, exits, dates)
-
-    # Calculate speedup (>1 means Backtrader is faster)
-    speedup = (
-        bt_results["runtime_sec"] / ml4t_results["runtime_sec"]
-        if ml4t_results["runtime_sec"] > 0
-        else 0
-    )
-
-    return {
-        "n_bars": n_bars,
-        "n_assets": n_assets,
-        "bt_runtime": bt_results["runtime_sec"],
-        "bt_trades": bt_results["num_trades"],
-        "bt_memory": bt_results["memory_mb"],
-        "ml4t_runtime": ml4t_results["runtime_sec"],
-        "ml4t_trades": ml4t_results["num_trades"],
-        "ml4t_memory": ml4t_results["memory_mb"],
-        "speedup": speedup,
-    }
-
-
-def main():
-    print("=" * 70)
-    print("Performance Benchmark: ml4t.backtest vs Backtrader")
-    print("=" * 70)
-
-    # Test configurations (smaller for Backtrader - it's slower)
-    configs = [
-        (100, 1),
-        (1000, 1),
-        (10000, 1),
-        (1000, 10),
-        (1000, 50),
-    ]
-
-    results = []
-
-    for n_bars, n_assets in configs:
-        print(f"\nBenchmark: {n_bars} bars x {n_assets} assets")
-        try:
-            result = run_benchmark(n_bars, n_assets)
-            results.append(result)
-
-            print(
-                f"  BT: {result['bt_runtime']:.3f}s, {result['bt_trades']} trades, {result['bt_memory']:.1f} MB"
-            )
-            print(
-                f"  ML4T: {result['ml4t_runtime']:.3f}s, {result['ml4t_trades']} trades, {result['ml4t_memory']:.1f} MB"
-            )
-            print(
-                f"  Speedup: {result['speedup']:.2f}x {'(BT faster)' if result['speedup'] > 1 else '(ML4T faster)'}"
-            )
-        except Exception as e:
-            print(f"  ERROR: {e}")
-            import traceback
-
-            traceback.print_exc()
-
-    # Summary table
-    print("\n" + "=" * 70)
-    print("SUMMARY")
-    print("=" * 70)
-    print(f"{'Config':<20} {'BT (s)':<12} {'ML4T (s)':<12} {'Speedup':<12} {'Winner'}")
-    print("-" * 70)
-
-    for r in results:
-        config = f"{r['n_bars']}x{r['n_assets']}"
-        winner = "BT" if r["speedup"] > 1 else "ML4T"
-        speedup_str = f"{r['speedup']:.2f}x" if r["speedup"] > 1 else f"{1/r['speedup']:.2f}x"
-        print(
-            f"{config:<20} {r['bt_runtime']:<12.3f} {r['ml4t_runtime']:<12.3f} {speedup_str:<12} {winner}"
-        )
-
-    print("=" * 70)
-
-    return 0
+VALIDATION_DIR = Path(__file__).parents[1]
+sys.path.insert(0, str(VALIDATION_DIR))
 
+from cross_framework_performance import main  # noqa: E402
 
 if __name__ == "__main__":
-    sys.exit(main())
+    raise SystemExit(main())
diff --git a/validation/behavior_coverage.toml b/validation/behavior_coverage.toml
new file mode 100644
index 00000000..8b1ed6c6
--- /dev/null
+++ b/validation/behavior_coverage.toml
@@ -0,0 +1,266 @@
+schema_version = 1
+
+[[framework.vectorbt]]
+name = "execution"
+fields = ["execution.execution_price", "execution.execution_mode"]
+native_checks = ["signal_timing_and_default_fill", "explicit_fill_price"]
+scenarios = ["01", "17"]
+published = true
+
+[[framework.vectorbt]]
+name = "direction"
+fields = ["account.allow_short_selling", "account.short_cash_policy", "account.lock_notional_update_mode"]
+native_checks = ["short_cash", "lock_notional_update_arithmetic"]
+scenarios = ["02", "11", "12"]
+published = true
+
+[[framework.vectorbt]]
+name = "stops"
+fields = ["stops.stop_fill_mode", "stops.stop_level_basis", "stops.trail_hwm_source", "stops.initial_hwm_source", "stops.trail_stop_timing"]
+native_checks = ["stop_fill", "trailing_stop_extreme_and_intrabar_fill"]
+scenarios = ["03", "04", "09", "10", "12", "13", "14", "15"]
+published = true
+
+[[framework.vectorbt]]
+name = "costs"
+fields = ["commission.model", "commission.rate", "slippage.model", "slippage.rate"]
+native_checks = ["fees_and_slippage"]
+scenarios = ["05", "07", "08"]
+published = true
+
+[[framework.vectorbt]]
+name = "sizing"
+fields = ["position_sizing.share_type"]
+native_checks = ["target_percent_sizing"]
+scenarios = []
+published = false
+reason = "The scenario matrix submits fixed integer quantities and does not test fractional target sizing."
+
+[[framework.vectorbt]]
+name = "buying_power"
+fields = ["account.allow_leverage", "orders.reject_on_insufficient_cash", "orders.partial_fills_allowed"]
+native_checks = ["cash_sharing_short_collateral", "insufficient_cash_partial_fill"]
+scenarios = []
+published = false
+reason = "No cross-engine scenario currently reaches an insufficient-cash boundary."
+
+[[framework.vectorbt]]
+name = "order_processing"
+fields = ["orders.fill_ordering", "orders.entry_order_priority", "orders.immediate_fill", "orders.rebalance_mode"]
+native_checks = ["cash_sharing_and_call_sequence", "accumulation", "long_signal_conflict"]
+scenarios = []
+published = false
+reason = "The single-asset scenario strategy does not submit competing same-session orders or targets."
+
+[[framework.vectorbt]]
+name = "cash_and_target_headroom"
+fields = ["cash.initial", "cash.buffer_pct", "orders.rebalance_headroom_pct"]
+native_checks = ["target_percent_sizing"]
+scenarios = []
+published = false
+reason = "Initial cash is an explicit scenario input and target headroom is not exercised."
+
+[[framework.vectorbt]]
+name = "data_continuity"
+fields = ["orders.missing_price_policy", "orders.late_asset_policy", "orders.late_asset_min_bars"]
+native_checks = ["missing_order_price"]
+scenarios = []
+published = false
+reason = "The scenario matrix has one complete asset history and cannot test late assets."
+
+[[framework.backtrader]]
+name = "execution"
+fields = ["execution.execution_price", "execution.execution_mode"]
+native_checks = ["next_bar_open_and_gap", "final_bar_market_order"]
+scenarios = ["01", "17"]
+published = true
+
+[[framework.backtrader]]
+name = "direction"
+fields = ["account.allow_short_selling", "account.short_cash_policy"]
+native_checks = ["short_cash"]
+scenarios = ["02", "11", "12"]
+published = true
+
+[[framework.backtrader]]
+name = "stops"
+fields = ["stops.stop_fill_mode", "stops.stop_level_basis", "stops.trail_hwm_source", "stops.initial_hwm_source", "stops.trail_stop_timing"]
+native_checks = ["signal_price_stop_basis", "trailing_stop_signal_close_and_lagged"]
+scenarios = ["03", "04", "09", "10", "12", "13", "14", "15"]
+published = true
+
+[[framework.backtrader]]
+name = "costs"
+fields = ["commission.model", "commission.rate", "slippage.model", "slippage.rate"]
+native_checks = ["defaults", "commission_headroom"]
+scenarios = ["05", "06", "07", "08"]
+published = true
+
+[[framework.backtrader]]
+name = "sizing"
+fields = ["position_sizing.share_type", "position_sizing.share_rounding"]
+native_checks = ["integer_target_percent"]
+scenarios = []
+published = false
+reason = "The scenario matrix submits fixed integer quantities and does not test target-percent sizing."
+
+[[framework.backtrader]]
+name = "buying_power"
+fields = ["account.allow_leverage", "orders.reject_on_insufficient_cash", "orders.partial_fills_allowed"]
+native_checks = ["cash_rejection_and_configured_leverage", "losing_short_cover_submission_rejection", "gap_reversal_executes_close_leg_despite_margin"]
+scenarios = []
+published = false
+reason = "Native checks cover submission and gap boundaries, but the scenario matrix does not reach an insufficient-cash boundary."
+
+[[framework.backtrader]]
+name = "order_processing"
+fields = ["orders.fill_ordering", "orders.entry_order_priority", "orders.rebalance_mode"]
+native_checks = ["submission_sequence"]
+scenarios = []
+published = false
+reason = "The single-asset scenario strategy does not submit competing same-session orders or targets."
+
+[[framework.backtrader]]
+name = "cash_and_target_headroom"
+fields = ["cash.initial", "cash.buffer_pct", "orders.rebalance_headroom_pct"]
+native_checks = ["commission_headroom"]
+scenarios = []
+published = false
+reason = "Initial cash is an explicit scenario input and target headroom is not exercised."
+
+[[framework.backtrader]]
+name = "data_continuity"
+fields = ["orders.missing_price_policy", "orders.late_asset_policy", "orders.late_asset_min_bars"]
+native_checks = ["missing_bar_uses_last_value", "late_feed_start"]
+scenarios = []
+published = false
+reason = "The scenario matrix has one complete asset history and cannot test late assets."
+
+[[framework.zipline]]
+name = "execution"
+fields = ["execution.execution_price", "execution.execution_mode"]
+native_checks = ["configured_next_bar_open_fill", "final_bar_market_order"]
+scenarios = ["01", "17"]
+published = true
+
+[[framework.zipline]]
+name = "direction"
+fields = ["account.allow_short_selling", "account.short_cash_policy"]
+native_checks = ["cash_and_short_proceeds"]
+scenarios = ["02", "11", "12"]
+published = true
+
+[[framework.zipline]]
+name = "risk_adapter"
+fields = ["stops.stop_fill_mode", "stops.stop_level_basis", "stops.trail_hwm_source", "stops.trail_stop_timing"]
+native_checks = ["configured_next_bar_open_fill"]
+scenarios = ["03", "04", "09", "12", "13", "14", "15"]
+published = true
+
+[[framework.zipline]]
+name = "costs"
+fields = ["commission.model", "commission.rate", "commission.per_share", "commission.minimum", "slippage.model", "slippage.rate"]
+native_checks = ["defaults", "explicit_minimum_commission"]
+scenarios = ["05", "06", "07", "08"]
+published = true
+
+[[framework.zipline]]
+name = "sizing"
+fields = ["position_sizing.share_type", "orders.rebalance_mode"]
+native_checks = ["integer_target_percent", "target_percent_snapshot"]
+scenarios = []
+published = false
+reason = "The scenario matrix submits fixed quantities and does not call target-percent APIs."
+
+[[framework.zipline]]
+name = "buying_power"
+fields = ["account.allow_leverage", "orders.reject_on_insufficient_cash", "orders.skip_cash_validation", "orders.partial_fills_allowed"]
+native_checks = ["cash_and_short_proceeds", "volume_share_partial_fills"]
+scenarios = []
+published = false
+reason = "The comparison protocol overrides cash validation and fill volume, but no boundary scenario tests either behavior."
+
+[[framework.zipline]]
+name = "order_processing"
+fields = ["orders.fill_ordering", "orders.entry_order_priority", "orders.next_bar_queue_shadow_validation"]
+native_checks = ["submission_sequence"]
+scenarios = []
+published = false
+reason = "The single-asset scenario strategy does not submit competing same-session orders."
+
+[[framework.zipline]]
+name = "cash_and_target_headroom"
+fields = ["cash.initial", "cash.buffer_pct", "orders.rebalance_headroom_pct"]
+native_checks = ["integer_target_percent"]
+scenarios = []
+published = false
+reason = "Initial cash is explicit and target headroom is not exercised."
+
+[[framework.zipline]]
+name = "data_continuity"
+fields = ["orders.missing_price_policy", "orders.late_asset_policy", "orders.late_asset_min_bars"]
+native_checks = ["session_calendar", "missing_bar"]
+scenarios = []
+published = false
+reason = "The scenario matrix has one complete asset history and cannot test late assets."
+
+[[framework.lean]]
+name = "execution"
+fields = ["execution.execution_price", "execution.execution_mode"]
+native_checks = ["timing", "final_bar_order"]
+scenarios = ["lean-case:chapter16_etfs", "lean-case:chapter16_sp500_equity_option_analytics", "lean-case:chapter16_us_equities_panel"]
+published = true
+
+[[framework.lean]]
+name = "account"
+fields = ["account.allow_short_selling", "account.allow_leverage", "account.initial_margin", "account.long_maintenance_margin", "account.short_maintenance_margin", "account.short_cash_policy"]
+native_checks = ["default_models", "buying_power_allowed", "buying_power_rejected"]
+scenarios = ["lean-case:chapter16_etfs", "lean-case:chapter16_sp500_equity_option_analytics", "lean-case:chapter16_us_equities_panel"]
+published = true
+
+[[framework.lean]]
+name = "target_sizing"
+fields = ["position_sizing.share_type", "orders.rebalance_mode", "orders.rebalance_headroom_pct"]
+native_checks = ["target_sizing"]
+scenarios = ["lean-case:chapter16_etfs", "lean-case:chapter16_sp500_equity_option_analytics", "lean-case:chapter16_us_equities_panel"]
+published = true
+
+[[framework.lean]]
+name = "costs"
+fields = ["commission.model", "commission.rate", "commission.per_share", "commission.minimum", "slippage.model", "slippage.rate"]
+native_checks = ["default_models", "explicit_costs"]
+scenarios = []
+published = false
+reason = "Chapter 16 uses a custom percentage fee model, not the profile's default brokerage fee model."
+
+[[framework.lean]]
+name = "stops"
+fields = ["stops.stop_fill_mode", "stops.stop_level_basis", "stops.trail_hwm_source", "stops.trail_stop_timing"]
+native_checks = []
+scenarios = []
+published = false
+reason = "The current LEAN oracle and case studies do not test stop-order semantics."
+
+[[framework.lean]]
+name = "buying_power_and_ordering"
+fields = ["orders.reject_on_insufficient_cash", "orders.partial_fills_allowed", "orders.fill_ordering", "orders.entry_order_priority", "orders.buying_power_reservation", "orders.next_bar_submission_precheck", "orders.next_bar_queue_shadow_validation"]
+native_checks = ["submission_sequence", "buying_power_sequence", "default_full_fill"]
+scenarios = []
+published = false
+reason = "The Chapter 16 projects do not isolate rejection, competing-order, or partial-fill boundaries."
+
+[[framework.lean]]
+name = "cash"
+fields = ["cash.initial", "cash.buffer_pct"]
+native_checks = ["target_sizing"]
+scenarios = []
+published = false
+reason = "Initial cash is an explicit project input, not an engine-default equivalence claim."
+
+[[framework.lean]]
+name = "data_continuity"
+fields = ["orders.missing_price_policy", "orders.late_asset_policy", "orders.late_asset_min_bars"]
+native_checks = ["fill_forward"]
+scenarios = []
+published = false
+reason = "The Chapter 16 projects do not contain a controlled missing-bar or late-asset case."
diff --git a/validation/benchmark_suite.py b/validation/benchmark_suite.py
index 0e169980..2f5b1aa2 100644
--- a/validation/benchmark_suite.py
+++ b/validation/benchmark_suite.py
@@ -61,6 +61,9 @@
 from ml4t.backtest._validation.backtrader_runner import (  # noqa: E402
     run_backtrader_target_shares as shared_run_backtrader_target_shares,
 )
+from ml4t.backtest._validation.backtrader_runner import (  # noqa: E402
+    transactions_to_trade_log as reconstruct_closed_trades,
+)
 from ml4t.backtest._validation.lean_runner import (  # noqa: E402
     build_sequential_ticker_map,
     check_lean_cli,
@@ -105,6 +108,7 @@
 from ml4t.backtest._validation.zipline_runner import (  # noqa: E402
     run_zipline_target_shares as shared_run_zipline_target_shares,
 )
+from validation.common.framework_registry import load_framework_manifest  # noqa: E402
 
 _BENCHMARK_LOG_FILE = os.getenv("ML4T_BENCHMARK_LOG_FILE")
 DEFAULT_REAL_DATA_PATH = Path(
@@ -225,6 +229,7 @@ class BenchmarkConfig:
     lean_security_leverage: float | None = None
     lean_force_zero_fee: bool | None = None
     lean_force_zero_slippage: bool | None = None
+    end_session: str = "2025-12-31"
 
     @property
     def data_points(self) -> int:
@@ -446,7 +451,7 @@ def generate_benchmark_data(config: BenchmarkConfig, seed: int = 42) -> tuple:
                     current += timedelta(days=1)
         dates = pd.DatetimeIndex(dates)
     else:
-        dates = _get_trailing_nyse_sessions(config.n_bars)
+        dates = _get_trailing_nyse_sessions(config.n_bars, end_date=config.end_session)
         if len(dates) < config.n_bars:
             raise ValueError(
                 f"Requested {config.n_bars} bars, but only {len(dates)} NYSE sessions are available"
@@ -705,9 +710,9 @@ def build_canonical_target_trace(target_shares: pd.DataFrame) -> pd.DataFrame:
     delta = target_shares - prev
     changed = delta != 0.0
 
-    trace_targets = target_shares.where(changed).stack()
-    trace_prev = prev.where(changed).stack()
-    trace_delta = delta.where(changed).stack()
+    trace_targets = target_shares.where(changed).stack().dropna()
+    trace_prev = prev.where(changed).stack().dropna()
+    trace_delta = delta.where(changed).stack().dropna()
 
     if len(trace_targets) == 0:
         return pd.DataFrame(
@@ -791,15 +796,29 @@ def to_dict(self) -> dict:
         }
 
 
-def _timestamp_value(value: object) -> str | None:
+def _timestamp_value(value: object, timestamp_domain: str = "timestamp") -> str | None:
     if value is None or pd.isna(value):
         return None
     timestamp = pd.Timestamp(value)
     if timestamp.tz is not None:
         timestamp = timestamp.tz_convert("UTC").tz_localize(None)
+    if timestamp_domain == "session_date":
+        return timestamp.date().isoformat()
+    if timestamp_domain != "timestamp":
+        raise ValueError(f"Unknown timestamp domain: {timestamp_domain}")
     return timestamp.isoformat()
 
 
+def _asset_value(value: object) -> str:
+    symbol = getattr(value, "symbol", None)
+    if isinstance(symbol, str) and symbol:
+        return symbol
+    text = str(value)
+    if " [" in text and text.endswith("])"):
+        return text.rsplit(" [", 1)[1][:-2]
+    return text
+
+
 def _canonical_float(value: object, quantum: Decimal = CANONICAL_QUANTUM) -> float:
     canonical = float(Decimal(str(value)).quantize(quantum, rounding=ROUND_HALF_EVEN))
     return 0.0 if canonical == 0.0 else canonical
@@ -830,7 +849,11 @@ def _frame_with_index(frame: pd.DataFrame) -> pd.DataFrame:
     return work
 
 
-def canonical_fill_records(frame: pd.DataFrame | None) -> list[dict[str, object]] | None:
+def canonical_fill_records(
+    frame: pd.DataFrame | None,
+    *,
+    timestamp_domain: str = "timestamp",
+) -> list[dict[str, object]] | None:
     """Normalize a framework fill log without applying numeric tolerances."""
     if frame is None:
         return None
@@ -845,9 +868,10 @@ def canonical_fill_records(frame: pd.DataFrame | None) -> list[dict[str, object]
         records.append(
             {
                 "timestamp": _timestamp_value(
-                    _row_value(row, ("timestamp", "dt", "date", "index", "filled_at"))
+                    _row_value(row, ("timestamp", "dt", "date", "index", "filled_at")),
+                    timestamp_domain,
                 ),
-                "asset": str(
+                "asset": _asset_value(
                     _row_value(row, ("asset", "symbol", "instrument_id", "sid"), "unknown")
                 ),
                 "side": _side_value(_row_value(row, ("side", "order_side"), ""), signed_quantity),
@@ -858,10 +882,37 @@ def canonical_fill_records(frame: pd.DataFrame | None) -> list[dict[str, object]
                 ),
             }
         )
-    return records
+    return sorted(
+        records,
+        key=lambda record: (
+            record["timestamp"] or "",
+            record["asset"],
+            record["side"],
+            record["quantity"],
+            record["price"],
+        ),
+    )
 
 
-def canonical_trade_records(frame: pd.DataFrame | None) -> list[dict[str, object]] | None:
+def closed_trades_from_fills(frame: pd.DataFrame | None) -> pd.DataFrame | None:
+    """Reconstruct fill-backed closed round trips on a framework-neutral ledger."""
+    records = canonical_fill_records(frame)
+    if not records:
+        return None
+    transactions = pd.DataFrame(records)
+    transactions["amount"] = transactions["quantity"].where(
+        transactions["side"] == "buy", -transactions["quantity"]
+    )
+    transactions["symbol"] = transactions["asset"]
+    transactions = transactions.set_index("timestamp")
+    return reconstruct_closed_trades(transactions[["amount", "price", "symbol"]])
+
+
+def canonical_trade_records(
+    frame: pd.DataFrame | None,
+    *,
+    timestamp_domain: str = "timestamp",
+) -> list[dict[str, object]] | None:
     """Normalize a framework round-trip trade log without applying numeric tolerances."""
     if frame is None:
         return None
@@ -879,10 +930,15 @@ def canonical_trade_records(frame: pd.DataFrame | None) -> list[dict[str, object
         records.append(
             {
                 "entry_time": _timestamp_value(
-                    _row_value(row, ("entry_time", "entry_date", "timestamp", "index"))
+                    _row_value(row, ("entry_time", "entry_date", "timestamp", "index")),
+                    timestamp_domain,
+                ),
+                "exit_time": _timestamp_value(
+                    _row_value(row, ("exit_time", "exit_date")), timestamp_domain
+                ),
+                "asset": _asset_value(
+                    _row_value(row, ("asset", "symbol", "instrument_id"), "unknown")
                 ),
-                "exit_time": _timestamp_value(_row_value(row, ("exit_time", "exit_date"))),
-                "asset": str(_row_value(row, ("asset", "symbol", "instrument_id"), "unknown")),
                 "side": side,
                 "quantity": _canonical_float(abs(quantity)),
                 "entry_price": _canonical_float(_row_value(row, ("entry_price",), 0.0)),
@@ -980,6 +1036,7 @@ def compare_benchmark_results_exact(
     actual: BenchmarkResult,
     *,
     initial_cash: float,
+    timestamp_domain: str = "timestamp",
 ) -> dict[str, object]:
     """Compare every release-covered benchmark surface using exact equality."""
     checks = [
@@ -990,13 +1047,13 @@ def compare_benchmark_results_exact(
         ),
         _surface_check(
             "fills",
-            canonical_fill_records(expected.fills_df),
-            canonical_fill_records(actual.fills_df),
+            canonical_fill_records(expected.fills_df, timestamp_domain=timestamp_domain),
+            canonical_fill_records(actual.fills_df, timestamp_domain=timestamp_domain),
         ),
         _surface_check(
             "trades",
-            canonical_trade_records(expected.trades_df),
-            canonical_trade_records(actual.trades_df),
+            canonical_trade_records(expected.trades_df, timestamp_domain=timestamp_domain),
+            canonical_trade_records(actual.trades_df, timestamp_domain=timestamp_domain),
         ),
         _scalar_check("trade_count", expected.num_trades, actual.num_trades),
         _scalar_check(
@@ -1010,6 +1067,7 @@ def compare_benchmark_results_exact(
         "schema_version": 1,
         "canonical_record_quantum": str(CANONICAL_QUANTUM),
         "canonical_money_quantum": str(CANONICAL_MONEY_QUANTUM),
+        "timestamp_domain": timestamp_domain,
         "scenario": expected.scenario,
         "expected_framework": expected.framework,
         "actual_framework": actual.framework,
@@ -1233,7 +1291,13 @@ def benchmark_ml4t(
     # Convert price data to Polars format using vectorized DataFrame ops.
     price_frames: list[pd.DataFrame] = []
     for asset_name, df in price_data.items():
-        asset_frame = df.reset_index()
+        source_frame = df.copy()
+        if profile_name in {"zipline_strict", "lean"}:
+            decimals = 3 if profile_name == "zipline_strict" else 4
+            source_frame.loc[:, ["open", "high", "low", "close"]] = source_frame[
+                ["open", "high", "low", "close"]
+            ].round(decimals)
+        asset_frame = source_frame.reset_index()
         index_col = asset_frame.columns[0]
         asset_frame = asset_frame.rename(columns={index_col: "timestamp"})
         asset_frame["asset"] = asset_name
@@ -1338,9 +1402,8 @@ def _disable_commission(cfg: BacktestConfig) -> None:
         # Clear every direct commission field, not just type+rate. The broker
         # auto-activates a cost model whenever any direct field (per_share /
         # per_trade / rate) is non-zero, even when commission_type is NONE, so a
-        # partial reset would leave a preset's per-share/minimum commission live
-        # (e.g. zipline_strict carries per_share=0.005, minimum=1.0) and silently
-        # re-enable it — breaking parity against the zero-commission reference run.
+        # partial reset could leave direct per-share or per-trade values live and
+        # silently re-enable costs, breaking parity against a zero-cost reference.
         cfg.commission_type = CommissionType.NONE
         cfg.commission_rate = 0.0
         cfg.commission_per_share = 0.0
@@ -1422,19 +1485,8 @@ def build_ml4t_config(no_costs: bool) -> BacktestConfig:
     fills_pl = results.to_fills_dataframe()
     fills_df = pd.DataFrame(fills_pl.to_dict(as_series=False))
     trades_df = None
-    if profile_name == "lean":
-        if not fills_df.empty:
-            trades_df = fills_df.rename(
-                columns={
-                    "price": "fill_price",
-                    "commission": "fee",
-                }
-            )
-            if "quantity" in trades_df.columns:
-                trades_df["quantity"] = trades_df["quantity"].abs()
-            if "side" in trades_df.columns:
-                trades_df["side"] = trades_df["side"].astype(str).str.lower()
-            trades_df = trades_df.sort_values(["timestamp", "order_id"]).reset_index(drop=True)
+    if profile_name in {"backtrader_strict", "zipline_strict", "lean"}:
+        trades_df = closed_trades_from_fills(fills_df)
     elif results.get("trades"):
         trade_records = []
         for t in results["trades"]:
@@ -2053,6 +2105,17 @@ def benchmark_lean(
             memory_mb=0,
             error=f"LEAN config not found: {lean_config}",
         )
+    lean_target = load_framework_manifest().targets["lean"]
+    if lean_target.artifact is None:
+        return BenchmarkResult(
+            framework="LEAN CLI",
+            scenario=config.name,
+            runtime_sec=0,
+            num_trades=0,
+            final_value=0,
+            memory_mb=0,
+            error="Frozen LEAN target is missing an engine image",
+        )
 
     try:
         lean_cmd = resolve_lean_command()
@@ -2159,6 +2222,13 @@ def benchmark_lean(
 
     first_date = pd.Timestamp(dates[0]).date()
     last_date = pd.Timestamp(dates[-1]).date()
+    following_sessions = _get_nyse_sessions(
+        pd.Timestamp(last_date) + pd.Timedelta(days=1),
+        pd.Timestamp(last_date) + pd.Timedelta(days=10),
+    )
+    if len(following_sessions) == 0:
+        raise RuntimeError(f"Could not resolve the LEAN settlement session after {last_date}")
+    lean_end_date = pd.Timestamp(following_sessions[0]).date()
     main_code = f"""# region imports
 from AlgorithmImports import *
 # endregion
@@ -2170,7 +2240,7 @@ def benchmark_lean(
 class Ml4tBenchmark(QCAlgorithm):
     def initialize(self):
         self.set_start_date({first_date.year}, {first_date.month}, {first_date.day})
-        self.set_end_date({last_date.year}, {last_date.month}, {last_date.day})
+        self.set_end_date({lean_end_date.year}, {lean_end_date.month}, {lean_end_date.day})
         self.set_cash({float(config.initial_cash)})
         {lean_account_stmt}
         self._targets = {{}}
@@ -2289,7 +2359,10 @@ def on_order_event(self, order_event: OrderEvent):
 
     env = make_lean_env()
     try:
-        check_lean_cli(lean_cmd, PROJECT_ROOT, env)
+        observed_cli = check_lean_cli(lean_cmd, PROJECT_ROOT, env)
+        expected_cli = f"lean {lean_target.cli_version}"
+        if observed_cli != expected_cli:
+            raise RuntimeError(f"LEAN CLI differs: {observed_cli} != {expected_cli}")
     except RuntimeError as exc:
         return BenchmarkResult(
             framework="LEAN CLI",
@@ -2341,6 +2414,7 @@ def on_order_event(self, order_event: OrderEvent):
             project_dir=project_dir,
             lean_config=lean_config,
             output_dir=output_dir,
+            image=lean_target.artifact,
             timeout=1800,
             env=env,
         )
@@ -2378,14 +2452,9 @@ def on_order_event(self, order_event: OrderEvent):
             target_trace_df=target_trace,
         )
 
-    # Report the decoded fill count as num_trades for an apples-to-apples
-    # cross-engine comparison. load_lean_artifacts prefers LEAN's
-    # tradeStatistics.totalNumberOfTrades, which counts closed round-trip
-    # trades, whereas every other engine in this suite reports individual
-    # fills via len(trades_df). Using fills here keeps the parity surface
-    # consistent (LEAN fills == ml4t fills on the canonical benchmark).
-    if trades_df is not None:
-        num_trades = int(len(trades_df))
+    fills_df = trades_df
+    trades_df = closed_trades_from_fills(fills_df)
+    num_trades = 0 if trades_df is None else len(trades_df)
 
     return BenchmarkResult(
         framework="LEAN CLI",
@@ -2394,7 +2463,7 @@ def on_order_event(self, order_event: OrderEvent):
         num_trades=num_trades,
         final_value=final_value,
         memory_mb=0.0,
-        fills_df=trades_df,
+        fills_df=fills_df,
         trades_df=trades_df,
         equity_df=equity_df,
         order_events_df=order_events_df,
diff --git a/validation/build_framework_env.py b/validation/build_framework_env.py
new file mode 100644
index 00000000..3d70dc1b
--- /dev/null
+++ b/validation/build_framework_env.py
@@ -0,0 +1,248 @@
+#!/usr/bin/env python3
+"""Build and verify isolated, locked comparison-framework environments."""
+
+from __future__ import annotations
+
+import argparse
+import json
+import os
+import subprocess
+import sys
+import tomllib
+from pathlib import Path
+from typing import Any
+
+VALIDATION_DIR = Path(__file__).parent
+PROJECT_ROOT = VALIDATION_DIR.parent
+ENVIRONMENTS_DIR = VALIDATION_DIR / "environments"
+sys.path.insert(0, str(VALIDATION_DIR))
+
+from common.framework_registry import FrameworkTarget, load_framework_manifest  # noqa: E402
+
+PUBLIC_FRAMEWORKS = ("vectorbt_oss", "backtrader", "zipline")
+BUILDABLE_FRAMEWORKS = (*PUBLIC_FRAMEWORKS, "vectorbt_pro", "lean")
+
+
+def project_directory(framework: str) -> Path:
+    """Return the locked uv project for one framework."""
+    return ENVIRONMENTS_DIR / framework
+
+
+def environment_path(target: FrameworkTarget, root: Path = PROJECT_ROOT) -> Path:
+    """Resolve a target environment below an explicit root."""
+    if target.environment is None:
+        raise ValueError(f"Framework has no environment path: {target.framework_id}")
+    return root / target.environment
+
+
+def definition_failures(framework: str, target: FrameworkTarget) -> list[str]:
+    """Check that the lock input names the frozen target exactly."""
+    project = project_directory(framework)
+    failures: list[str] = []
+    lock_path = project / "uv.lock"
+    if not lock_path.is_file():
+        failures.append(f"Missing lockfile: {lock_path}")
+        lock_text = ""
+    else:
+        lock_text = lock_path.read_text(encoding="utf-8")
+    try:
+        with (project / "pyproject.toml").open("rb") as file:
+            payload = tomllib.load(file)
+        dependencies = payload["project"]["dependencies"]
+    except (KeyError, OSError, tomllib.TOMLDecodeError) as error:
+        return [f"Invalid environment definition for {framework}: {error}"]
+    if not isinstance(dependencies, list) or not all(
+        isinstance(dependency, str) for dependency in dependencies
+    ):
+        return [f"Environment dependencies must be a string array: {framework}"]
+    normalized_package = target.package.lower().replace("_", "-")
+    matching = [
+        dependency
+        for dependency in dependencies
+        if dependency.split("@", 1)[0].split("=", 1)[0].strip().lower().replace("_", "-")
+        == normalized_package
+    ]
+    if len(matching) != 1:
+        failures.append(f"Environment must define one {target.package} dependency: {framework}")
+    elif framework == "vectorbt_pro":
+        if target.source_commit is None or f"@{target.source_commit}" not in matching[0]:
+            failures.append("VectorBT Pro environment does not pin the manifest commit")
+    else:
+        expected_version = target.cli_version if framework == "lean" else target.version
+        if expected_version is None or f"=={expected_version}" not in matching[0]:
+            failures.append(f"Environment does not pin {target.package}=={expected_version}")
+    expected_lock_id = target.cli_immutable_id if framework == "lean" else target.immutable_id
+    if expected_lock_id is None:
+        failures.append(f"Manifest lacks an artifact identity: {framework}")
+    elif expected_lock_id.removeprefix("git:") not in lock_text:
+        failures.append(f"Lockfile does not contain the manifest artifact identity: {framework}")
+    return failures
+
+
+def _probe(interpreter: Path, target: FrameworkTarget) -> dict[str, Any]:
+    code = """
+import importlib.metadata
+import json
+from pathlib import Path
+import ml4t.backtest
+import sys
+
+distribution = importlib.metadata.distribution(sys.argv[1])
+print(json.dumps({
+    "version": distribution.version,
+    "direct_url": distribution.read_text("direct_url.json"),
+    "ml4t_path": str(Path(ml4t.backtest.__file__).resolve()),
+    "python": sys.version.split()[0],
+}, sort_keys=True))
+"""
+    result = subprocess.run(
+        [str(interpreter), "-c", code, target.package],
+        cwd=PROJECT_ROOT,
+        check=True,
+        capture_output=True,
+        text=True,
+    )
+    payload = json.loads(result.stdout)
+    if not isinstance(payload, dict):
+        raise ValueError("Environment probe did not return an object")
+    return payload
+
+
+def verify_environment(
+    framework: str,
+    target: FrameworkTarget,
+    *,
+    root: Path = PROJECT_ROOT,
+) -> dict[str, Any]:
+    """Verify installed package, source checkout, and private or engine identity."""
+    failures = definition_failures(framework, target)
+    if failures:
+        raise ValueError("; ".join(failures))
+    interpreter = environment_path(target, root) / "bin" / "python"
+    if not interpreter.is_file():
+        raise ValueError(f"Environment interpreter is missing: {interpreter}")
+    payload = _probe(interpreter, target)
+    if payload.get("version") != target.version and framework != "lean":
+        raise ValueError(
+            f"Installed {target.package} version differs: {payload.get('version')} != {target.version}"
+        )
+    ml4t_path = Path(str(payload.get("ml4t_path")))
+    if not ml4t_path.is_relative_to(PROJECT_ROOT):
+        raise ValueError(f"Environment does not import the current checkout: {ml4t_path}")
+
+    evidence: dict[str, Any] = {
+        "framework": framework,
+        "environment": str(environment_path(target, root)),
+        "python": payload.get("python"),
+        "package": target.package,
+        "version": payload.get("version"),
+        "immutable_id": target.immutable_id,
+    }
+    if framework == "vectorbt_pro":
+        direct_url = json.loads(payload.get("direct_url") or "{}")
+        commit = direct_url.get("vcs_info", {}).get("commit_id")
+        if commit != target.source_commit:
+            raise ValueError(f"Installed VectorBT Pro commit differs: {commit}")
+        evidence["source_commit"] = commit
+    if framework == "lean":
+        if payload.get("version") != target.cli_version:
+            raise ValueError(
+                f"Installed LEAN CLI differs: {payload.get('version')} != {target.cli_version}"
+            )
+        if target.artifact is None:
+            raise ValueError("LEAN target lacks an immutable engine image")
+        subprocess.run(
+            ["docker", "buildx", "imagetools", "inspect", target.artifact],
+            check=True,
+            capture_output=True,
+            text=True,
+        )
+        evidence = {
+            "framework": framework,
+            "data_preparation": {
+                "cli_package": target.package,
+                "cli_version": payload.get("version"),
+                "cli_immutable_id": target.cli_immutable_id,
+                "python": payload.get("python"),
+            },
+            "engine_execution": {
+                "image": target.artifact,
+                "image_digest": target.immutable_id,
+                "platform_artifact": target.platform_artifact,
+            },
+        }
+    return evidence
+
+
+def build_environment(
+    framework: str,
+    target: FrameworkTarget,
+    *,
+    root: Path = PROJECT_ROOT,
+) -> dict[str, Any]:
+    """Synchronize one locked environment and verify its installed identity."""
+    failures = definition_failures(framework, target)
+    if failures:
+        raise ValueError("; ".join(failures))
+    destination = environment_path(target, root)
+    command_environment = os.environ.copy()
+    command_environment["UV_PROJECT_ENVIRONMENT"] = str(destination)
+    command_environment["UV_NO_SOURCES"] = "0"
+    try:
+        subprocess.run(
+            ["uv", "sync", "--project", str(project_directory(framework)), "--locked", "--no-dev"],
+            cwd=PROJECT_ROOT,
+            check=True,
+            env=command_environment,
+        )
+    except subprocess.CalledProcessError as error:
+        if framework == "vectorbt_pro":
+            raise RuntimeError(
+                "VectorBT Pro is unavailable. Authorized SSH access to the licensed source is "
+                "required; no credentials are stored in this repository."
+            ) from error
+        raise
+    return verify_environment(framework, target, root=root)
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description=__doc__)
+    selection = parser.add_mutually_exclusive_group(required=True)
+    selection.add_argument("--framework", choices=BUILDABLE_FRAMEWORKS)
+    selection.add_argument("--all-public", action="store_true")
+    parser.add_argument("--verify-only", action="store_true")
+    parser.add_argument("--environment-root", type=Path, default=PROJECT_ROOT)
+    parser.add_argument("--evidence-output", type=Path)
+    args = parser.parse_args()
+
+    manifest = load_framework_manifest()
+    frameworks = PUBLIC_FRAMEWORKS if args.all_public else (args.framework,)
+    evidence: list[dict[str, Any]] = []
+    try:
+        for framework in frameworks:
+            if framework is None:
+                continue
+            target = manifest.targets[framework]
+            result = (
+                verify_environment(framework, target, root=args.environment_root)
+                if args.verify_only
+                else build_environment(framework, target, root=args.environment_root)
+            )
+            evidence.append(result)
+            print(f"Verified {framework}: {json.dumps(result, sort_keys=True)}")
+    except (OSError, RuntimeError, ValueError, subprocess.CalledProcessError) as error:
+        print(f"Environment validation failed: {error}", file=sys.stderr)
+        return 2
+
+    if args.evidence_output is not None:
+        args.evidence_output.parent.mkdir(parents=True, exist_ok=True)
+        args.evidence_output.write_text(
+            json.dumps({"schema_version": 1, "environments": evidence}, indent=2, sort_keys=True)
+            + "\n",
+            encoding="utf-8",
+        )
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/claim_inventory.toml b/validation/claim_inventory.toml
new file mode 100644
index 00000000..6e7fd32d
--- /dev/null
+++ b/validation/claim_inventory.toml
@@ -0,0 +1,178 @@
+[metadata]
+schema_version = 1
+audit_date = "2026-08-13"
+
+[[claim]]
+id = "library-synthetic-scenario-conformance"
+repository = "ml4t/backtest"
+paths = ["README.md", "docs/index.md", "docs/user-guide/profiles.md", "validation/README.md", "validation/METHODOLOGY.md", "validation/CORRECTNESS_RESULTS.json"]
+type = "correctness"
+frameworks = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline"]
+required_evidence = ["executed_matrix", "canonical_trade_log", "canonical_fill_log", "equity_curve", "environment_identity"]
+status = "verified"
+issue = "ml4t/backtest-dev#3"
+
+[[claim]]
+id = "library-real-strategy-equivalence"
+repository = "ml4t/backtest"
+paths = ["README.md", "docs/index.md", "docs/user-guide/profiles.md", "validation/README.md", "validation/METHODOLOGY.md", "validation/REAL_STRATEGY_RESULTS.json", "validation/real_strategy_applicability.toml"]
+type = "correctness"
+frameworks = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline", "lean"]
+required_evidence = ["frozen_real_strategy_inputs", "complete_canonical_fill_log", "equity_curve", "terminal_value", "negative_control", "environment_identity"]
+status = "failed"
+issue = "ml4t/backtest-dev#3"
+
+[[claim]]
+id = "library-vectorbt-behavior"
+repository = "ml4t/backtest"
+paths = ["README.md", "docs/concepts/how-it-works.md", "docs/getting-started/quickstart.md", "docs/user-guide/accounts.md", "docs/user-guide/configuration.md", "docs/user-guide/execution-semantics.md", "docs/user-guide/profiles.md", "docs/user-guide/rebalancing.md", "validation/METHODOLOGY.md", "validation/frameworks/vectorbt_oss.py", "validation/frameworks/vectorbt_pro.py"]
+type = "behavioral"
+frameworks = ["vectorbt_pro", "vectorbt_oss"]
+required_evidence = ["native_microtests", "upstream_source_reference", "adapter_contract"]
+status = "verified"
+issue = "ml4t/backtest-dev#5"
+
+[[claim]]
+id = "library-backtrader-behavior"
+repository = "ml4t/backtest"
+paths = ["README.md", "docs/concepts/how-it-works.md", "docs/getting-started/quickstart.md", "docs/user-guide/accounts.md", "docs/user-guide/configuration.md", "docs/user-guide/execution-semantics.md", "docs/user-guide/profiles.md", "docs/user-guide/rebalancing.md", "validation/METHODOLOGY.md", "validation/frameworks/backtrader.py"]
+type = "behavioral"
+frameworks = ["backtrader"]
+required_evidence = ["native_microtests", "upstream_source_reference", "adapter_contract"]
+status = "verified"
+issue = "ml4t/backtest-dev#6"
+
+[[claim]]
+id = "library-zipline-behavior"
+repository = "ml4t/backtest"
+paths = ["README.md", "docs/concepts/how-it-works.md", "docs/getting-started/quickstart.md", "docs/user-guide/accounts.md", "docs/user-guide/configuration.md", "docs/user-guide/execution-semantics.md", "docs/user-guide/profiles.md", "validation/METHODOLOGY.md", "validation/frameworks/zipline.py"]
+type = "behavioral"
+frameworks = ["zipline"]
+required_evidence = ["native_microtests", "upstream_source_reference", "adapter_contract"]
+status = "verified"
+issue = "ml4t/backtest-dev#7"
+
+[[claim]]
+id = "library-lean-behavior"
+repository = "ml4t/backtest"
+paths = ["README.md", "docs/concepts/how-it-works.md", "docs/user-guide/accounts.md", "docs/user-guide/configuration.md", "docs/user-guide/execution-semantics.md", "docs/user-guide/profiles.md", "validation/lean/README.md", "validation/benchmark_suite.py"]
+type = "behavioral"
+frameworks = ["lean"]
+required_evidence = ["native_microtests", "upstream_source_reference", "adapter_contract"]
+status = "verified"
+issue = "ml4t/backtest-dev#8"
+
+[[claim]]
+id = "library-synthetic-scale-conformance"
+repository = "ml4t/backtest"
+paths = ["README.md", "docs/index.md", "docs/user-guide/profiles.md", "validation/README.md", "validation/METHODOLOGY.md", "validation/LARGE_SCALE_RESULTS.json"]
+type = "correctness"
+frameworks = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline", "lean"]
+required_evidence = ["public_workload", "canonical_trade_log", "canonical_fill_log", "equity_curve", "environment_identity"]
+status = "verified"
+issue = "ml4t/backtest-dev#10"
+
+[[claim]]
+id = "library-controlled-performance"
+repository = "ml4t/backtest"
+paths = ["validation/cross_framework_performance.py", "validation/PERFORMANCE_RESULTS.json", "validation/run_all_benchmarks.py"]
+type = "performance"
+frameworks = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline", "lean"]
+required_evidence = ["controlled_workload", "warmup_policy", "repetitions", "machine_identity", "raw_timings"]
+status = "verified"
+issue = "ml4t/backtest-dev#11"
+
+[[claim]]
+id = "library-real-strategy-performance"
+repository = "ml4t/backtest"
+paths = ["validation/real_strategy_benchmark.py", "validation/REAL_STRATEGY_PERFORMANCE.json", "validation/REAL_STRATEGY_RESULTS.json"]
+type = "performance"
+frameworks = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline", "lean"]
+required_evidence = ["correctness_passing_workload", "engine_only_timer", "warmup_policy", "repetitions", "machine_identity", "raw_timings", "output_identity"]
+status = "verified"
+issue = "ml4t/backtest-dev#11"
+
+[[claim]]
+id = "library-idiomatic-performance"
+repository = "ml4t/backtest"
+paths = ["validation/cross_framework_performance.py", "validation/PERFORMANCE_RESULTS.json", "validation/vectorbt_pro/benchmark_performance.py", "validation/backtrader/benchmark_performance.py", "validation/zipline/benchmark_performance.py"]
+type = "performance"
+frameworks = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline", "lean"]
+required_evidence = ["idiomatic_workload", "declared_scope", "warmup_policy", "repetitions", "machine_identity", "raw_timings"]
+status = "verified"
+issue = "ml4t/backtest-dev#12"
+
+[[claim]]
+id = "library-qualitative-comparison"
+repository = "ml4t/backtest"
+paths = ["README.md", "docs/index.md", "docs/user-guide/profiles.md", "validation/README.md", "validation/METHODOLOGY.md"]
+type = "qualitative"
+frameworks = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline", "lean"]
+required_evidence = ["upstream_source_reference", "scope_qualification"]
+status = "verified"
+issue = "ml4t/backtest-dev#13"
+
+[[claim]]
+id = "book-framework-equivalence"
+repository = "ml4t/public"
+paths = ["16_strategy_simulation/06_framework_parity.py", "16_strategy_simulation/15_lean_engine_parity.py", "16_strategy_simulation/16_case_study_lean_parity.py", "16_strategy_simulation/17_backtrader_zipline_engine_parity.py", "16_strategy_simulation/18_vectorbt_engine_parity.py", "16_strategy_simulation/validation/_library_validation.py", "16_strategy_simulation/validation/adapters/lean_adapter.py", "16_strategy_simulation/validation/adapters/ml4t_adapter.py", "16_strategy_simulation/validation/adapters/vectorbt_adapter.py"]
+type = "correctness"
+frameworks = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline", "lean"]
+required_evidence = ["executed_notebook", "canonical_trade_log", "canonical_fill_log", "equity_curve", "environment_identity"]
+status = "unresolved"
+issue = "ml4t/backtest-dev#14"
+
+[[claim]]
+id = "book-performance-comparison"
+repository = "ml4t/public"
+paths = ["16_strategy_simulation/03_single_asset_vectorbt.py", "16_strategy_simulation/04_single_asset_ml4t_backtest.py", "16_strategy_simulation/README.md"]
+type = "performance"
+frameworks = ["vectorbt_oss"]
+required_evidence = ["executed_notebook", "retained_benchmark", "workload_definition", "raw_timings"]
+status = "unresolved"
+issue = "ml4t/backtest-dev#14"
+
+[[claim]]
+id = "book-framework-tradeoffs"
+repository = "ml4t/public"
+paths = ["16_strategy_simulation/06_framework_parity.py", "16_strategy_simulation/07_engine_divergence_anatomy.py", "16_strategy_simulation/README.md"]
+type = "qualitative"
+frameworks = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline", "lean"]
+required_evidence = ["executed_notebook", "upstream_source_reference", "scope_qualification"]
+status = "unresolved"
+issue = "ml4t/backtest-dev#14"
+
+[[claim]]
+id = "content-marketing-correctness"
+repository = "ml4t/content-marketing"
+paths = ["insights/issues/issue_022/derivatives/hacker-news.md", "insights/issues/issue_022/derivatives/reddit-post.md", "insights/issues/issue_022/reviews/parity-claims-audit.md"]
+type = "correctness"
+frameworks = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline", "lean"]
+required_evidence = ["published_library_evidence", "canonical_comparison", "environment_identity"]
+status = "unresolved"
+issue = "ml4t/backtest-dev#15"
+
+[[claim]]
+id = "content-marketing-performance"
+repository = "ml4t/content-marketing"
+paths = ["insights/issues/issue_022/derivatives/hacker-news.md", "insights/issues/issue_022/derivatives/reddit-post.md"]
+type = "performance"
+frameworks = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline", "lean"]
+required_evidence = ["published_library_evidence", "workload_definition", "raw_timings", "scope_qualification"]
+status = "unresolved"
+issue = "ml4t/backtest-dev#15"
+
+[[claim]]
+id = "content-marketing-qualitative"
+repository = "ml4t/content-marketing"
+paths = ["insights/issues/issue_022/derivatives/hacker-news.md", "insights/issues/issue_022/derivatives/reddit-post.md", "insights/issues/issue_022/reviews/parity-claims-audit.md"]
+type = "qualitative"
+frameworks = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline", "lean"]
+required_evidence = ["published_library_evidence", "upstream_source_reference", "scope_qualification"]
+status = "unresolved"
+issue = "ml4t/backtest-dev#15"
+
+[[unresolved]]
+id = "performance-publication-decision"
+finding = "Whether to publish dated cross-framework runtime or memory ratios is deferred until the audit results are reviewed."
+issue = "ml4t/backtest-dev#15"
diff --git a/validation/common/canonical_records.py b/validation/common/canonical_records.py
new file mode 100644
index 00000000..f4f20388
--- /dev/null
+++ b/validation/common/canonical_records.py
@@ -0,0 +1,92 @@
+"""Canonical record extraction shared by scenario adapters."""
+
+from __future__ import annotations
+
+from typing import Any
+
+import pandas as pd
+
+
+def _first(record: dict[str, Any], *names: str) -> Any:
+    for name in names:
+        if name in record:
+            return record[name]
+    raise KeyError(f"Record lacks all expected fields: {names}")
+
+
+def vectorbt_fills(order_records: list[dict[str, Any]], *, asset: str) -> list[dict[str, Any]]:
+    """Convert VectorBT's native filled-order records to the canonical fill surface."""
+    return [
+        {
+            "timestamp": _first(record, "Fill Index", "Timestamp"),
+            "asset": asset,
+            "side": str(record["Side"]).lower(),
+            "quantity": abs(float(record["Size"])),
+            "price": float(record["Price"]),
+            "commission": abs(float(record.get("Fees", 0.0))),
+        }
+        for record in order_records
+    ]
+
+
+def vectorbt_trades(
+    trade_records: list[dict[str, Any]],
+    *,
+    asset: str,
+) -> list[dict[str, Any]]:
+    """Convert VectorBT's native closed-trade records to the canonical trade surface."""
+    normalized: list[dict[str, Any]] = []
+    for record in trade_records:
+        status = str(record.get("Status", "Closed")).lower()
+        if status != "closed":
+            continue
+        entry_price = float(_first(record, "Avg Entry Price", "Entry Price"))
+        exit_price = float(_first(record, "Avg Exit Price", "Exit Price"))
+        size = abs(float(record.get("Size", 0.0)))
+        direction = str(record.get("Direction", "Long"))
+        commission = abs(float(record.get("Entry Fees", 0.0))) + abs(
+            float(record.get("Exit Fees", 0.0))
+        )
+        direction_sign = -1.0 if direction.lower() == "short" else 1.0
+        normalized.append(
+            {
+                "entry_time": _first(record, "Entry Index", "Entry Timestamp"),
+                "exit_time": _first(record, "Exit Index", "Exit Timestamp"),
+                "asset": asset,
+                "entry_price": entry_price,
+                "exit_price": exit_price,
+                "pnl": (exit_price - entry_price) * size * direction_sign - commission,
+                "size": size,
+                "direction": direction,
+                "commission": commission,
+            }
+        )
+    return normalized
+
+
+def zipline_fills(
+    transactions: pd.DataFrame,
+    *,
+    asset: str,
+    commission_rate: float = 0.0,
+    per_share_rate: float = 0.0,
+) -> list[dict[str, Any]]:
+    """Convert Zipline transactions and the configured fee model to canonical fills."""
+    if transactions.empty:
+        return []
+    records: list[dict[str, Any]] = []
+    for _, transaction in transactions.sort_values("dt").iterrows():
+        amount = float(transaction["amount"])
+        price = float(transaction["price"])
+        commission = abs(amount) * (price * commission_rate + per_share_rate)
+        records.append(
+            {
+                "timestamp": transaction["dt"],
+                "asset": asset,
+                "side": "buy" if amount > 0 else "sell",
+                "quantity": abs(amount),
+                "price": price,
+                "commission": commission,
+            }
+        )
+    return records
diff --git a/validation/common/capabilities.py b/validation/common/capabilities.py
new file mode 100644
index 00000000..39b53ee1
--- /dev/null
+++ b/validation/common/capabilities.py
@@ -0,0 +1,74 @@
+"""Declared result surfaces for the scenario comparison adapters."""
+
+from __future__ import annotations
+
+from common.types import CAPABILITY_KEYS
+
+ML4T_CAPABILITIES = {
+    "intents": "input_only",
+    "orders": "unavailable",
+    "rejections": "unavailable",
+    "fills": "native",
+    "positions": "unavailable",
+    "cash_flows": "aggregate_only",
+    "open_trades": "unavailable",
+    "closed_trades": "native",
+    "exit_reason": "native",
+    "terminal": "native",
+}
+
+FRAMEWORK_CAPABILITIES = {
+    "vectorbt_pro": {
+        "intents": "input_only",
+        "orders": "native_filled_only",
+        "rejections": "unavailable",
+        "fills": "native",
+        "positions": "unavailable",
+        "cash_flows": "aggregate_only",
+        "open_trades": "unavailable",
+        "closed_trades": "native",
+        "exit_reason": "unavailable",
+        "terminal": "native",
+    },
+    "vectorbt_oss": {
+        "intents": "input_only",
+        "orders": "native_filled_only",
+        "rejections": "unavailable",
+        "fills": "native",
+        "positions": "unavailable",
+        "cash_flows": "aggregate_only",
+        "open_trades": "unavailable",
+        "closed_trades": "native",
+        "exit_reason": "unavailable",
+        "terminal": "native",
+    },
+    "backtrader": {
+        "intents": "input_only",
+        "orders": "native_filled_only",
+        "rejections": "unavailable",
+        "fills": "native",
+        "positions": "unavailable",
+        "cash_flows": "aggregate_only",
+        "open_trades": "unavailable",
+        "closed_trades": "native",
+        "exit_reason": "unavailable",
+        "terminal": "native",
+    },
+    "zipline": {
+        "intents": "input_only",
+        "orders": "native_filled_only",
+        "rejections": "unavailable",
+        "fills": "reconstructed",
+        "positions": "unavailable",
+        "cash_flows": "aggregate_only",
+        "open_trades": "unavailable",
+        "closed_trades": "reconstructed",
+        "exit_reason": "unavailable",
+        "terminal": "native",
+    },
+}
+
+assert set(ML4T_CAPABILITIES) == set(CAPABILITY_KEYS)
+assert all(
+    set(capabilities) == set(CAPABILITY_KEYS) for capabilities in FRAMEWORK_CAPABILITIES.values()
+)
diff --git a/validation/common/comparator.py b/validation/common/comparator.py
index 1635d51f..f61cf295 100644
--- a/validation/common/comparator.py
+++ b/validation/common/comparator.py
@@ -2,11 +2,29 @@
 
 from __future__ import annotations
 
+from datetime import date, datetime
 from decimal import ROUND_HALF_EVEN, Decimal
+from typing import Any
 
 from .types import CheckResult, ComparisonResult, FrameworkResult, ScenarioConfig, Tolerance
 
 CANONICAL_QUANTUM = Decimal("0.00000001")
+CANONICAL_QUANTUM_TEXT = format(CANONICAL_QUANTUM, "f")
+TRADE_FIELDS = (
+    "entry_time",
+    "exit_time",
+    "asset",
+    "direction",
+    "size",
+    "entry_price",
+    "exit_price",
+    "pnl",
+    "commission",
+)
+FILL_FIELDS = ("timestamp", "asset", "side", "quantity", "price", "commission")
+_TIMESTAMP_FIELDS = {"entry_time", "exit_time", "timestamp"}
+_CASE_INSENSITIVE_FIELDS = {"direction", "side"}
+_STRING_FIELDS = {"asset", *_CASE_INSENSITIVE_FIELDS}
 
 
 def _canonical_number(value: int | float) -> Decimal:
@@ -14,6 +32,83 @@ def _canonical_number(value: int | float) -> Decimal:
     return Decimal(str(value)).quantize(CANONICAL_QUANTUM, rounding=ROUND_HALF_EVEN)
 
 
+def _canonical_session(value: object) -> str:
+    """Normalize a daily event timestamp to its ISO session date."""
+    if isinstance(value, datetime):
+        return value.date().isoformat()
+    if isinstance(value, date):
+        return value.isoformat()
+    if isinstance(value, str):
+        session = value[:10]
+        date.fromisoformat(session)
+        return session
+    isoformat = getattr(value, "isoformat", None)
+    if callable(isoformat):
+        session = str(isoformat())[:10]
+        date.fromisoformat(session)
+        return session
+    raise TypeError(f"unsupported timestamp type {type(value).__name__}")
+
+
+def _canonical_field(field: str, value: Any) -> Decimal | str:
+    if field in _TIMESTAMP_FIELDS:
+        return _canonical_session(value)
+    if field in _STRING_FIELDS:
+        if not isinstance(value, str) or not value:
+            raise TypeError("must be a nonempty string")
+        return value.lower() if field in _CASE_INSENSITIVE_FIELDS else value
+    if not isinstance(value, (int, float)) or isinstance(value, bool):
+        raise TypeError("must be numeric")
+    return _canonical_number(value)
+
+
+def _compare_records(
+    *,
+    name: str,
+    expected_records: list[dict[str, Any]],
+    actual_records: list[dict[str, Any]],
+    fields: tuple[str, ...],
+) -> CheckResult:
+    detail = "exact ordered match"
+    passed = len(expected_records) == len(actual_records)
+    if not passed:
+        detail = f"record_count expected={len(expected_records)}, actual={len(actual_records)}"
+    else:
+        for index, (expected_record, actual_record) in enumerate(
+            zip(expected_records, actual_records, strict=True)
+        ):
+            for field in fields:
+                if field not in expected_record or field not in actual_record:
+                    passed = False
+                    detail = f"record {index} missing required field {field}"
+                    break
+                try:
+                    expected = _canonical_field(field, expected_record[field])
+                    actual = _canonical_field(field, actual_record[field])
+                except (ArithmeticError, TypeError, ValueError) as error:
+                    passed = False
+                    detail = f"record {index} field {field} is malformed: {error}"
+                    break
+                if expected != actual:
+                    passed = False
+                    detail = (
+                        f"record {index} field {field}: expected={expected!r}, actual={actual!r}"
+                    )
+                    break
+            if not passed:
+                break
+    return CheckResult(
+        name=name,
+        passed=passed,
+        message=detail,
+        expected=expected_records,
+        actual=actual_records,
+        difference=None if passed else detail,
+        canonical_quantum=CANONICAL_QUANTUM_TEXT,
+        diagnostic_limit=None,
+    )
+
+
 def compare_results(
     scenario: ScenarioConfig,
     framework_result: FrameworkResult,
@@ -55,6 +150,9 @@ def compare_results(
             ),
             expected=framework_result.num_trades,
             actual=ml4t_result.num_trades,
+            difference=trade_diff,
+            canonical_quantum="1",
+            diagnostic_limit=tolerance.trade_count,
         )
     )
 
@@ -74,6 +172,9 @@ def compare_results(
             ),
             expected=fw_value,
             actual=ml4t_value,
+            difference=value_diff,
+            canonical_quantum=CANONICAL_QUANTUM_TEXT,
+            diagnostic_limit=tolerance.value_pct,
         )
     )
 
@@ -92,6 +193,9 @@ def compare_results(
             ),
             expected=fw_pnl,
             actual=ml4t_pnl,
+            difference=pnl_diff,
+            canonical_quantum=CANONICAL_QUANTUM_TEXT,
+            diagnostic_limit=tolerance.pnl_abs,
         )
     )
 
@@ -107,6 +211,9 @@ def compare_results(
                     message="Required commission output is missing",
                     expected=fw_comm,
                     actual=ml4t_comm,
+                    difference="missing",
+                    canonical_quantum=CANONICAL_QUANTUM_TEXT,
+                    diagnostic_limit=tolerance.commission_abs,
                 )
             )
         else:
@@ -122,6 +229,9 @@ def compare_results(
                     ),
                     expected=fw_comm,
                     actual=ml4t_comm,
+                    difference=comm_diff,
+                    canonical_quantum=CANONICAL_QUANTUM_TEXT,
+                    diagnostic_limit=tolerance.commission_abs,
                 )
             )
 
@@ -136,6 +246,9 @@ def compare_results(
                     message="Required exit-price output is missing",
                     expected=fw_exit,
                     actual=ml4t_exit,
+                    difference="missing",
+                    canonical_quantum=CANONICAL_QUANTUM_TEXT,
+                    diagnostic_limit=tolerance.exit_price_abs,
                 )
             )
         else:
@@ -151,51 +264,26 @@ def compare_results(
                     ),
                     expected=fw_exit,
                     actual=ml4t_exit,
+                    difference=exit_diff,
+                    canonical_quantum=CANONICAL_QUANTUM_TEXT,
+                    diagnostic_limit=tolerance.exit_price_abs,
                 )
             )
 
-    # Exact trade-by-trade release surface. Timestamps are excluded until every adapter exposes
-    # them consistently; prices, size, direction, and PnL are mandatory for every reported trade.
-    required_trade_fields = ("entry_price", "exit_price", "pnl", "size", "direction")
-    trade_detail = "exact match"
-    trade_level_passed = len(framework_result.trades) == len(ml4t_result.trades)
-    if trade_level_passed:
-        for index, (fw_trade, ml4t_trade) in enumerate(
-            zip(framework_result.trades, ml4t_result.trades, strict=True)
-        ):
-            for field in required_trade_fields:
-                if field not in fw_trade or field not in ml4t_trade:
-                    trade_level_passed = False
-                    trade_detail = f"trade {index} missing required field {field}"
-                    break
-                expected = fw_trade[field]
-                actual = ml4t_trade[field]
-                if field == "direction":
-                    expected = str(expected).lower()
-                    actual = str(actual).lower()
-                else:
-                    expected = _canonical_number(expected)
-                    actual = _canonical_number(actual)
-                if expected != actual:
-                    trade_level_passed = False
-                    trade_detail = (
-                        f"trade {index} field {field}: expected={expected!r}, actual={actual!r}"
-                    )
-                    break
-            if not trade_level_passed:
-                break
-    else:
-        trade_detail = (
-            f"record_count expected={len(framework_result.trades)}, "
-            f"actual={len(ml4t_result.trades)}"
-        )
     checks.append(
-        CheckResult(
+        _compare_records(
             name="trade_level_match",
-            passed=trade_level_passed,
-            message=trade_detail,
-            expected=framework_result.trades,
-            actual=ml4t_result.trades,
+            expected_records=framework_result.trades,
+            actual_records=ml4t_result.trades,
+            fields=TRADE_FIELDS,
+        )
+    )
+    checks.append(
+        _compare_records(
+            name="fill_level_match",
+            expected_records=framework_result.fills,
+            actual_records=ml4t_result.fills,
+            fields=FILL_FIELDS,
         )
     )
 
diff --git a/validation/common/correctness_evidence.py b/validation/common/correctness_evidence.py
new file mode 100644
index 00000000..88b19c98
--- /dev/null
+++ b/validation/common/correctness_evidence.py
@@ -0,0 +1,308 @@
+"""Schema validation, staleness checks, and atomic correctness-evidence promotion."""
+
+from __future__ import annotations
+
+import json
+import os
+import tempfile
+from collections import Counter
+from datetime import UTC, datetime
+from pathlib import Path
+from typing import Any, cast
+
+from scenarios.definitions import SCENARIOS
+
+from common.capabilities import FRAMEWORK_CAPABILITIES, ML4T_CAPABILITIES
+from common.comparator import CANONICAL_QUANTUM_TEXT, compare_results
+from common.framework_registry import FrameworkManifest, load_framework_manifest
+from common.provenance import generate_inputs, input_digest, static_digests
+from common.types import ValidationRecord, ValidationStatus
+
+SCHEMA_VERSION = 3
+
+
+def _framework_metadata(manifest: FrameworkManifest) -> dict[str, dict[str, object]]:
+    return {
+        framework_id: manifest.targets[framework_id].evidence_metadata()
+        for framework_id in manifest.scenario_framework_ids
+    }
+
+
+def build_report(
+    records: list[ValidationRecord],
+    *,
+    manifest: FrameworkManifest | None = None,
+) -> dict[str, object]:
+    """Build a correctness candidate without deciding whether it can be accepted."""
+    target_manifest = manifest or load_framework_manifest()
+    counts = Counter(record.status.value for record in records)
+    required = [record for record in records if record.required]
+    release_passed = bool(required) and all(record.passed for record in required)
+    return {
+        "schema_version": SCHEMA_VERSION,
+        "generated_at": datetime.now(UTC).isoformat(),
+        "comparison_policy": {
+            "canonical_quantum": CANONICAL_QUANTUM_TEXT,
+            "rounding": "ROUND_HALF_EVEN",
+            "meaning": "equality after canonical quantization, not bit identity",
+            "record_order": "significant",
+            "timestamp_domain": "daily session date",
+            "surfaces": ["terminal", "closed_trades", "fills"],
+        },
+        "frameworks": _framework_metadata(target_manifest),
+        "release_gate_passed": release_passed,
+        "summary": {status.value: counts[status.value] for status in ValidationStatus},
+        "records": [record.to_dict() for record in records],
+    }
+
+
+def _mapping(value: object, *, label: str, failures: list[str]) -> dict[str, Any] | None:
+    if not isinstance(value, dict) or not all(isinstance(key, str) for key in value):
+        failures.append(f"{label} must be an object")
+        return None
+    return cast(dict[str, Any], value)
+
+
+def _expected_pairs(manifest: FrameworkManifest) -> dict[tuple[str, str], tuple[bool, str]]:
+    return {
+        (framework, scenario_id): (
+            framework in scenario.supported_frameworks,
+            scenario.name,
+        )
+        for framework in manifest.scenario_framework_ids
+        for scenario_id, scenario in SCENARIOS.items()
+    }
+
+
+def _record_evidence_failures(
+    record: ValidationRecord,
+    *,
+    manifest: FrameworkManifest,
+) -> list[str]:
+    identity = f"{record.framework}/{record.scenario_id}"
+    failures: list[str] = []
+    if record.duration_seconds is None or record.duration_seconds < 0:
+        failures.append(f"{identity} lacks a valid runtime")
+    if (
+        record.provenance is None
+        or record.framework_result is None
+        or record.ml4t_result is None
+        or record.comparison is None
+    ):
+        failures.append(f"{identity} lacks complete comparison evidence")
+        return failures
+
+    scenario = SCENARIOS[record.scenario_id]
+    target = manifest.targets[record.framework]
+    provenance = record.provenance
+    framework_target = _mapping(
+        provenance.get("framework_target"), label=f"{identity} framework_target", failures=failures
+    )
+    ml4t = _mapping(provenance.get("ml4t"), label=f"{identity} ml4t", failures=failures)
+    python = _mapping(provenance.get("python"), label=f"{identity} python", failures=failures)
+    adapter = _mapping(provenance.get("adapter"), label=f"{identity} adapter", failures=failures)
+    digests = _mapping(provenance.get("digests"), label=f"{identity} digests", failures=failures)
+    counts = _mapping(
+        provenance.get("record_counts"), label=f"{identity} record_counts", failures=failures
+    )
+    capabilities = _mapping(
+        provenance.get("capabilities"), label=f"{identity} capabilities", failures=failures
+    )
+    if framework_target is not None:
+        expected_target = {
+            "version": target.version,
+            "actual_version": target.version,
+            "immutable_id": target.immutable_id,
+        }
+        if framework_target != expected_target:
+            failures.append(f"{identity} framework target identity differs from the manifest")
+    if ml4t is not None:
+        if ml4t.get("dirty") is not False:
+            failures.append(f"{identity} was produced from a dirty ML4T tree")
+        commit = ml4t.get("commit")
+        if not isinstance(commit, str) or len(commit) != 40:
+            failures.append(f"{identity} lacks a full ML4T commit")
+    if python is not None and (
+        not isinstance(python.get("version"), str)
+        or not isinstance(python.get("implementation"), str)
+    ):
+        failures.append(f"{identity} lacks Python runtime identity")
+    expected_adapter = {
+        "module": f"frameworks.{record.framework}",
+        "path": f"validation/frameworks/{record.framework}.py",
+    }
+    if adapter is not None and adapter != expected_adapter:
+        failures.append(f"{identity} adapter identity differs")
+    expected_capabilities = {
+        "framework": FRAMEWORK_CAPABILITIES[record.framework],
+        "ml4t": ML4T_CAPABILITIES,
+    }
+    if capabilities != expected_capabilities:
+        failures.append(f"{identity} capability declaration differs")
+    if record.framework_result.capabilities != FRAMEWORK_CAPABILITIES[record.framework]:
+        failures.append(f"{identity} framework result capabilities differ")
+    if record.ml4t_result.capabilities != ML4T_CAPABILITIES:
+        failures.append(f"{identity} ML4T result capabilities differ")
+
+    expected_digests = static_digests(scenario, record.framework)
+    if digests is not None:
+        for name, expected in expected_digests.items():
+            if digests.get(name) != expected:
+                failures.append(f"{identity} {name} digest is stale")
+
+    prices, entries, exits = generate_inputs(scenario, record.framework)
+    expected_input_digest = input_digest(prices, entries, exits)
+    if provenance.get("input_digest") != expected_input_digest:
+        failures.append(f"{identity} generated-input digest is stale")
+
+    expected_counts = {
+        "bars": len(prices),
+        "entry_signals": int(entries.sum()),
+        "exit_signals": int(exits.sum()) if exits is not None else 0,
+        "framework_intents": int(entries.sum()) + (int(exits.sum()) if exits is not None else 0),
+        "ml4t_intents": int(entries.sum()) + (int(exits.sum()) if exits is not None else 0),
+        "framework_orders": None,
+        "ml4t_orders": None,
+        "framework_fills": len(record.framework_result.fills),
+        "ml4t_fills": len(record.ml4t_result.fills),
+        "framework_closed_trades": record.framework_result.num_trades,
+        "ml4t_closed_trades": record.ml4t_result.num_trades,
+    }
+    if counts is not None and counts != expected_counts:
+        failures.append(f"{identity} record counts differ from retained inputs or outputs")
+
+    expected_comparison = compare_results(
+        scenario,
+        record.framework_result,
+        record.ml4t_result,
+    )
+    if record.comparison.to_dict() != expected_comparison.to_dict():
+        failures.append(f"{identity} comparison checks differ from retained outputs")
+    expected_passed = record.status is ValidationStatus.PASS
+    if record.comparison.passed is not expected_passed:
+        failures.append(f"{identity} status conflicts with its comparison verdict")
+    return failures
+
+
+def correctness_report_failures(
+    report: dict[str, object],
+    *,
+    manifest: FrameworkManifest | None = None,
+) -> list[str]:
+    """Return every reason a candidate cannot replace accepted evidence."""
+    target_manifest = manifest or load_framework_manifest()
+    failures: list[str] = []
+    if report.get("schema_version") != SCHEMA_VERSION:
+        failures.append(f"Unsupported correctness schema: {report.get('schema_version')!r}")
+        return failures
+    if not isinstance(report.get("generated_at"), str):
+        failures.append("Correctness report lacks a generation timestamp")
+    expected_policy = {
+        "canonical_quantum": CANONICAL_QUANTUM_TEXT,
+        "rounding": "ROUND_HALF_EVEN",
+        "meaning": "equality after canonical quantization, not bit identity",
+        "record_order": "significant",
+        "timestamp_domain": "daily session date",
+        "surfaces": ["terminal", "closed_trades", "fills"],
+    }
+    if report.get("comparison_policy") != expected_policy:
+        failures.append("Correctness comparison policy differs")
+    if report.get("frameworks") != _framework_metadata(target_manifest):
+        failures.append("Correctness framework targets differ from the frozen manifest")
+    if report.get("release_gate_passed") is not True:
+        failures.append("Correctness release gate did not pass")
+
+    raw_records = report.get("records")
+    if not isinstance(raw_records, list):
+        failures.append("Correctness records must be a list")
+        return failures
+
+    records: dict[tuple[str, str], ValidationRecord] = {}
+    for index, payload in enumerate(raw_records):
+        if not isinstance(payload, dict):
+            failures.append(f"Correctness record {index} must be an object")
+            continue
+        try:
+            record = ValidationRecord.from_dict(cast(dict[str, Any], payload))
+        except (KeyError, TypeError, ValueError) as error:
+            failures.append(f"Correctness record {index} is invalid: {error}")
+            continue
+        key = (record.framework, record.scenario_id)
+        if key in records:
+            failures.append(
+                f"Duplicate correctness record: {record.framework}/{record.scenario_id}"
+            )
+        records[key] = record
+
+    expected_pairs = _expected_pairs(target_manifest)
+    missing = sorted(set(expected_pairs) - set(records))
+    unexpected = sorted(set(records) - set(expected_pairs))
+    if missing:
+        failures.append(f"Correctness matrix is missing pairs: {missing}")
+    if unexpected:
+        failures.append(f"Correctness matrix has unknown pairs: {unexpected}")
+
+    for key in sorted(set(expected_pairs) & set(records)):
+        required, scenario_name = expected_pairs[key]
+        record = records[key]
+        identity = f"{record.framework}/{record.scenario_id}"
+        if record.scenario_name != scenario_name:
+            failures.append(f"{identity} scenario name differs from its definition")
+        if record.required is not required:
+            failures.append(f"{identity} required flag differs from the scenario matrix")
+        expected_status = ValidationStatus.PASS if required else ValidationStatus.UNSUPPORTED
+        if record.status is not expected_status:
+            failures.append(
+                f"{identity} has status {record.status.value}, expected {expected_status.value}"
+            )
+        if required and record.status is ValidationStatus.PASS:
+            failures.extend(_record_evidence_failures(record, manifest=target_manifest))
+        elif not required and not record.detail:
+            failures.append(f"{identity} unsupported record lacks a reason")
+    expected_summary = Counter(record.status.value for record in records.values())
+    summary = report.get("summary")
+    if not isinstance(summary, dict) or any(
+        summary.get(status.value) != expected_summary[status.value] for status in ValidationStatus
+    ):
+        failures.append("Correctness summary differs from retained records")
+    return failures
+
+
+def write_candidate(path: Path, records: list[ValidationRecord]) -> dict[str, object]:
+    """Write a complete diagnostic candidate, whether it passes or fails."""
+    report = build_report(records)
+    path.parent.mkdir(parents=True, exist_ok=True)
+    path.write_text(json.dumps(report, indent=2, sort_keys=True) + "\n", encoding="utf-8")
+    return report
+
+
+def load_report(path: Path) -> dict[str, object]:
+    """Load a correctness report with an object root."""
+    payload = json.loads(path.read_text(encoding="utf-8"))
+    if not isinstance(payload, dict):
+        raise ValueError(f"Correctness report must be an object: {path}")
+    return cast(dict[str, object], payload)
+
+
+def promote_candidate(candidate: Path, accepted: Path) -> list[str]:
+    """Atomically copy a valid candidate over accepted evidence."""
+    report = load_report(candidate)
+    failures = correctness_report_failures(report)
+    if failures:
+        return failures
+    accepted.parent.mkdir(parents=True, exist_ok=True)
+    with tempfile.NamedTemporaryFile(
+        mode="wb",
+        dir=accepted.parent,
+        prefix=f".{accepted.name}.",
+        suffix=".tmp",
+        delete=False,
+    ) as temporary:
+        temporary.write(candidate.read_bytes())
+        temporary_path = Path(temporary.name)
+    try:
+        os.replace(temporary_path, accepted)
+    finally:
+        if temporary_path.exists():
+            temporary_path.unlink()
+    return []
diff --git a/validation/common/data_generators.py b/validation/common/data_generators.py
index 85a7f557..9c8b7b9f 100644
--- a/validation/common/data_generators.py
+++ b/validation/common/data_generators.py
@@ -459,7 +459,7 @@ def generate_stress_data(
     n_bars: int = 1500,
     seed: int = 42,
 ) -> tuple[pd.DataFrame, np.ndarray]:
-    """Extended market with multiple regimes for stress testing.
+    """Extended market with multiple regimes for sparse path coverage.
 
     Used by: scenario 16.
     9 regime transitions, 9 entry signals.
@@ -515,3 +515,17 @@ def generate_stress_data(
             entries[b] = True
 
     return df, entries
+
+
+def generate_high_event_data(
+    n_bars: int = 1800,
+    seed: int = 7,
+) -> tuple[pd.DataFrame, np.ndarray, np.ndarray]:
+    """Generate hundreds of completed round trips for event-surface validation."""
+    return generate_random_walk(
+        n_bars=n_bars,
+        seed=seed,
+        hold_bars=1,
+        trade_spacing=3,
+        daily_vol=0.002,
+    )
diff --git a/validation/common/framework_registry.py b/validation/common/framework_registry.py
new file mode 100644
index 00000000..69f06565
--- /dev/null
+++ b/validation/common/framework_registry.py
@@ -0,0 +1,299 @@
+"""Validated framework targets and comparison-claim inventory."""
+
+from __future__ import annotations
+
+import re
+import tomllib
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any
+
+VALIDATION_DIR = Path(__file__).parents[1]
+DEFAULT_MANIFEST_PATH = VALIDATION_DIR / "framework_targets.toml"
+DEFAULT_CLAIM_INVENTORY_PATH = VALIDATION_DIR / "claim_inventory.toml"
+_EXACT_VERSION = re.compile(r"^[0-9][0-9A-Za-z._+-]*$")
+_IMMUTABLE_ID = re.compile(r"^(?:git:[0-9a-f]{7,40}|sha256:[0-9a-f]{64})$")
+_CLAIM_TYPES = {"behavioral", "correctness", "performance", "qualitative"}
+_ACCESS_TYPES = {"public", "licensed"}
+
+
+class ManifestError(ValueError):
+    """A framework or claim manifest violates its schema."""
+
+
+@dataclass(frozen=True)
+class FrameworkTarget:
+    """One immutable comparison target."""
+
+    framework_id: str
+    display_name: str
+    package: str
+    version: str
+    profile: str
+    python: str
+    license: str
+    access: str
+    source: str
+    immutable_id: str
+    scenario_matrix: bool
+    required_scenarios: int
+    unsupported_scenarios: int
+    source_commit: str | None = None
+    artifact: str | None = None
+    environment: str | None = None
+    python_env_var: str | None = None
+    platform_artifact: str | None = None
+    cli_version: str | None = None
+    cli_immutable_id: str | None = None
+
+    def evidence_metadata(self) -> dict[str, object]:
+        """Return complete target identity for retained evidence."""
+        metadata: dict[str, object] = {
+            "display_name": self.display_name,
+            "profile": self.profile,
+            "package": self.package,
+            "version": self.version,
+            "python": self.python,
+            "license": self.license,
+            "access": self.access,
+            "source": self.source,
+            "immutable_id": self.immutable_id,
+        }
+        optional = {
+            "commit": self.source_commit,
+            "artifact": self.artifact,
+            "platform_artifact": self.platform_artifact,
+            "cli_version": self.cli_version,
+            "cli_immutable_id": self.cli_immutable_id,
+        }
+        metadata.update({key: value for key, value in optional.items() if value is not None})
+        return metadata
+
+
+@dataclass(frozen=True)
+class FrameworkManifest:
+    """Frozen comparison target set."""
+
+    schema_version: int
+    freeze_date: str
+    scenario_framework_ids: tuple[str, ...]
+    targets: dict[str, FrameworkTarget]
+
+
+@dataclass(frozen=True)
+class Claim:
+    """One externally visible comparison claim surface."""
+
+    claim_id: str
+    repository: str
+    paths: tuple[str, ...]
+    claim_type: str
+    frameworks: tuple[str, ...]
+    required_evidence: tuple[str, ...]
+    status: str
+    issue: str
+
+
+@dataclass(frozen=True)
+class UnresolvedFinding:
+    """One known audit finding routed to an implementation issue."""
+
+    finding_id: str
+    finding: str
+    issue: str
+
+
+@dataclass(frozen=True)
+class ClaimInventory:
+    """Dated inventory of claims and unresolved findings."""
+
+    schema_version: int
+    audit_date: str
+    claims: tuple[Claim, ...]
+    unresolved: tuple[UnresolvedFinding, ...]
+
+
+def _load_toml(path: Path) -> dict[str, Any]:
+    try:
+        with path.open("rb") as file:
+            payload = tomllib.load(file)
+    except tomllib.TOMLDecodeError as error:
+        raise ManifestError(f"Invalid TOML in {path}: {error}") from error
+    if not isinstance(payload, dict):
+        raise ManifestError(f"Manifest must be a TOML table: {path}")
+    return payload
+
+
+def _required(table: dict[str, Any], field: str, *, context: str) -> Any:
+    if field not in table:
+        raise ManifestError(f"{context} missing required field '{field}'")
+    return table[field]
+
+
+def _string(table: dict[str, Any], field: str, *, context: str) -> str:
+    value = _required(table, field, context=context)
+    if not isinstance(value, str) or not value.strip():
+        raise ManifestError(f"{context} field '{field}' must be a non-empty string")
+    return value
+
+
+def _strings(table: dict[str, Any], field: str, *, context: str) -> tuple[str, ...]:
+    value = _required(table, field, context=context)
+    if not isinstance(value, list) or not value or not all(isinstance(item, str) for item in value):
+        raise ManifestError(f"{context} field '{field}' must be a non-empty string array")
+    return tuple(value)
+
+
+def load_framework_manifest(path: Path = DEFAULT_MANIFEST_PATH) -> FrameworkManifest:
+    """Load and validate frozen comparison targets."""
+    payload = _load_toml(path)
+    metadata = payload.get("metadata")
+    frameworks = payload.get("framework")
+    if not isinstance(metadata, dict) or not isinstance(frameworks, dict) or not frameworks:
+        raise ManifestError("Framework manifest requires metadata and framework tables")
+
+    schema_version = _required(metadata, "schema_version", context="metadata")
+    if schema_version != 1:
+        raise ManifestError(f"Unsupported framework manifest schema: {schema_version}")
+    freeze_date = _string(metadata, "freeze_date", context="metadata")
+    scenario_frameworks = _strings(metadata, "scenario_frameworks", context="metadata")
+
+    targets: dict[str, FrameworkTarget] = {}
+    for framework_id, raw_target in frameworks.items():
+        context = f"framework.{framework_id}"
+        if not isinstance(raw_target, dict):
+            raise ManifestError(f"{context} must be a table")
+        version = _string(raw_target, "version", context=context)
+        if not _EXACT_VERSION.fullmatch(version):
+            raise ManifestError(f"{context} version must be an exact version: {version!r}")
+        immutable_id = _string(raw_target, "immutable_id", context=context)
+        if not _IMMUTABLE_ID.fullmatch(immutable_id):
+            raise ManifestError(f"{context} immutable_id is not an immutable Git or SHA-256 ID")
+        access = _string(raw_target, "access", context=context)
+        if access not in _ACCESS_TYPES:
+            raise ManifestError(f"{context} access must be one of {sorted(_ACCESS_TYPES)}")
+        scenario_matrix = _required(raw_target, "scenario_matrix", context=context)
+        if not isinstance(scenario_matrix, bool):
+            raise ManifestError(f"{context} scenario_matrix must be a boolean")
+        required_scenarios = _required(raw_target, "required_scenarios", context=context)
+        unsupported_scenarios = _required(raw_target, "unsupported_scenarios", context=context)
+        if (
+            not isinstance(required_scenarios, int)
+            or isinstance(required_scenarios, bool)
+            or required_scenarios < 0
+            or not isinstance(unsupported_scenarios, int)
+            or isinstance(unsupported_scenarios, bool)
+            or unsupported_scenarios < 0
+        ):
+            raise ManifestError(f"{context} scenario counts must be nonnegative integers")
+
+        target = FrameworkTarget(
+            framework_id=framework_id,
+            display_name=_string(raw_target, "display_name", context=context),
+            package=_string(raw_target, "package", context=context),
+            version=version,
+            profile=_string(raw_target, "profile", context=context),
+            python=_string(raw_target, "python", context=context),
+            license=_string(raw_target, "license", context=context),
+            access=access,
+            source=_string(raw_target, "source", context=context),
+            immutable_id=immutable_id,
+            scenario_matrix=scenario_matrix,
+            required_scenarios=required_scenarios,
+            unsupported_scenarios=unsupported_scenarios,
+            source_commit=raw_target.get("source_commit"),
+            artifact=raw_target.get("artifact"),
+            environment=raw_target.get("environment"),
+            python_env_var=raw_target.get("python_env_var"),
+            platform_artifact=raw_target.get("platform_artifact"),
+            cli_version=raw_target.get("cli_version"),
+            cli_immutable_id=raw_target.get("cli_immutable_id"),
+        )
+        if scenario_matrix and (not target.environment or not target.python_env_var):
+            raise ManifestError(f"{context} scenario target lacks interpreter configuration")
+        targets[framework_id] = target
+
+    if len(set(scenario_frameworks)) != len(scenario_frameworks):
+        raise ManifestError("metadata scenario_frameworks contains duplicates")
+    unknown = set(scenario_frameworks) - set(targets)
+    if unknown:
+        raise ManifestError(
+            f"metadata scenario_frameworks names unknown targets: {sorted(unknown)}"
+        )
+    declared = {key for key, target in targets.items() if target.scenario_matrix}
+    if set(scenario_frameworks) != declared:
+        raise ManifestError("metadata scenario_frameworks disagrees with target declarations")
+
+    return FrameworkManifest(schema_version, freeze_date, scenario_frameworks, targets)
+
+
+def load_claim_inventory(
+    path: Path = DEFAULT_CLAIM_INVENTORY_PATH,
+    *,
+    manifest: FrameworkManifest | None = None,
+) -> ClaimInventory:
+    """Load and validate the dated comparison-claim inventory."""
+    target_manifest = manifest or load_framework_manifest()
+    payload = _load_toml(path)
+    metadata = payload.get("metadata")
+    raw_claims = payload.get("claim")
+    raw_unresolved = payload.get("unresolved")
+    if not isinstance(metadata, dict) or not isinstance(raw_claims, list) or not raw_claims:
+        raise ManifestError("Claim inventory requires metadata and claim tables")
+    if not isinstance(raw_unresolved, list):
+        raise ManifestError("Claim inventory requires unresolved tables")
+
+    schema_version = _required(metadata, "schema_version", context="metadata")
+    if schema_version != 1:
+        raise ManifestError(f"Unsupported claim inventory schema: {schema_version}")
+    audit_date = _string(metadata, "audit_date", context="metadata")
+
+    claims: list[Claim] = []
+    claim_ids: set[str] = set()
+    for index, raw_claim in enumerate(raw_claims):
+        context = f"claim[{index}]"
+        if not isinstance(raw_claim, dict):
+            raise ManifestError(f"{context} must be a table")
+        claim_id = _string(raw_claim, "id", context=context)
+        if claim_id in claim_ids:
+            raise ManifestError(f"Duplicate claim id: {claim_id}")
+        claim_ids.add(claim_id)
+        claim_type = _string(raw_claim, "type", context=context)
+        if claim_type not in _CLAIM_TYPES:
+            raise ManifestError(f"{context} has unknown claim type: {claim_type}")
+        frameworks = _strings(raw_claim, "frameworks", context=context)
+        unknown = set(frameworks) - set(target_manifest.targets)
+        if unknown:
+            raise ManifestError(f"{context} names unknown framework targets: {sorted(unknown)}")
+        claims.append(
+            Claim(
+                claim_id=claim_id,
+                repository=_string(raw_claim, "repository", context=context),
+                paths=_strings(raw_claim, "paths", context=context),
+                claim_type=claim_type,
+                frameworks=frameworks,
+                required_evidence=_strings(raw_claim, "required_evidence", context=context),
+                status=_string(raw_claim, "status", context=context),
+                issue=_string(raw_claim, "issue", context=context),
+            )
+        )
+
+    unresolved: list[UnresolvedFinding] = []
+    finding_ids: set[str] = set()
+    for index, raw_finding in enumerate(raw_unresolved):
+        context = f"unresolved[{index}]"
+        if not isinstance(raw_finding, dict):
+            raise ManifestError(f"{context} must be a table")
+        finding_id = _string(raw_finding, "id", context=context)
+        if finding_id in finding_ids:
+            raise ManifestError(f"Duplicate unresolved finding id: {finding_id}")
+        finding_ids.add(finding_id)
+        unresolved.append(
+            UnresolvedFinding(
+                finding_id=finding_id,
+                finding=_string(raw_finding, "finding", context=context),
+                issue=_string(raw_finding, "issue", context=context),
+            )
+        )
+
+    return ClaimInventory(schema_version, audit_date, tuple(claims), tuple(unresolved))
diff --git a/validation/common/ml4t_runner.py b/validation/common/ml4t_runner.py
index 403fa995..59cbc040 100644
--- a/validation/common/ml4t_runner.py
+++ b/validation/common/ml4t_runner.py
@@ -16,6 +16,7 @@
 PROJECT_ROOT = Path(__file__).parent.parent.parent
 sys.path.insert(0, str(PROJECT_ROOT / "src"))
 
+from common.capabilities import ML4T_CAPABILITIES  # noqa: E402
 from common.types import FrameworkResult, ScenarioConfig  # noqa: E402
 
 
@@ -110,9 +111,12 @@ def run_ml4t(
         trade_dict: dict[str, Any] = {
             "entry_time": t.entry_time,
             "exit_time": t.exit_time,
+            "asset": t.symbol,
             "entry_price": t.entry_price,
             "exit_price": t.exit_price,
             "pnl": t.pnl,
+            "commission": t.commission,
+            "exit_reason": t.exit_reason,
         }
         if hasattr(t, "quantity"):
             trade_dict["size"] = abs(t.quantity)
@@ -121,6 +125,19 @@ def run_ml4t(
             trade_dict["commission"] = t.commission
         trade_list.append(trade_dict)
 
+    fill_list = [
+        {
+            "timestamp": fill.timestamp,
+            "asset": fill.asset,
+            "side": fill.side.value,
+            "quantity": abs(fill.quantity),
+            "price": fill.price,
+            "commission": fill.commission,
+            "exit_reason": fill.exit_reason,
+        }
+        for fill in results["fills"]
+    ]
+
     extra = {}
     if "commission" in scenario.extra_checks:
         extra["total_commission"] = sum(f.commission for f in results["fills"])
@@ -133,6 +150,8 @@ def run_ml4t(
         total_pnl=results["final_value"] - scenario.initial_cash,
         num_trades=results["num_trades"],
         trades=trade_list,
+        fills=fill_list,
+        capabilities=ML4T_CAPABILITIES,
         extra=extra,
     )
 
diff --git a/validation/common/provenance.py b/validation/common/provenance.py
new file mode 100644
index 00000000..374f93cf
--- /dev/null
+++ b/validation/common/provenance.py
@@ -0,0 +1,266 @@
+"""Content-derived provenance for cross-framework correctness evidence."""
+
+from __future__ import annotations
+
+import hashlib
+import importlib.metadata
+import json
+import subprocess
+import sys
+from dataclasses import asdict
+from functools import cache
+from pathlib import Path
+from typing import Any
+
+import numpy as np
+import pandas as pd
+
+from common import data_generators
+from common.framework_registry import DEFAULT_MANIFEST_PATH, FrameworkTarget
+from common.types import FrameworkResult, ScenarioConfig
+
+VALIDATION_DIR = Path(__file__).parents[1]
+PROJECT_ROOT = VALIDATION_DIR.parent
+SOURCE_DIR = PROJECT_ROOT / "src" / "ml4t" / "backtest"
+
+
+def _sha256_bytes(value: bytes) -> str:
+    return hashlib.sha256(value).hexdigest()
+
+
+def file_digest(path: Path) -> str:
+    """Return a file's SHA-256 digest."""
+    return _sha256_bytes(path.read_bytes())
+
+
+def _json_digest(value: object) -> str:
+    payload = json.dumps(value, sort_keys=True, separators=(",", ":"), default=str)
+    return _sha256_bytes(payload.encode("utf-8"))
+
+
+@cache
+def _tree_digest(root: Path) -> str:
+    try:
+        git_root = Path(
+            subprocess.run(
+                ["git", "-C", str(root), "rev-parse", "--show-toplevel"],
+                check=True,
+                capture_output=True,
+                text=True,
+            ).stdout.strip()
+        )
+        relative_root = root.resolve().relative_to(git_root.resolve())
+        tracked = subprocess.run(
+            ["git", "-C", str(git_root), "ls-files", "-z", "--", relative_root.as_posix()],
+            check=True,
+            capture_output=True,
+        ).stdout
+        paths = sorted(
+            git_root / value.decode("utf-8")
+            for value in tracked.split(b"\0")
+            if value and value.endswith(b".py")
+        )
+    except (OSError, subprocess.CalledProcessError, ValueError):
+        paths = sorted(root.rglob("*.py"))
+
+    digest = hashlib.sha256()
+    for path in paths:
+        digest.update(path.relative_to(root).as_posix().encode("utf-8"))
+        digest.update(b"\0")
+        digest.update(path.read_bytes())
+        digest.update(b"\0")
+    return digest.hexdigest()
+
+
+def generate_inputs(
+    scenario: ScenarioConfig,
+    framework: str,
+) -> tuple[pd.DataFrame, np.ndarray, np.ndarray | None]:
+    """Generate and framework-align one scenario input set."""
+    generator = getattr(data_generators, scenario.data_generator)
+    data_result = generator(**scenario.data_kwargs)
+    if len(data_result) == 3:
+        prices, entries, exits = data_result
+    else:
+        prices, entries = data_result
+        exits = None
+
+    if framework == "zipline":
+        import exchange_calendars as xcals
+
+        calendar = xcals.get_calendar("XNYS")
+        start = prices.index[0]
+        end = prices.index[-1]
+        if start.tz is not None:
+            start = start.tz_convert(None)
+            end = end.tz_convert(None)
+        sessions = calendar.sessions_in_range(start, end)
+        index = prices.index.tz_localize(None) if prices.index.tz else prices.index
+        valid = index.isin(sessions)
+        prices = prices[valid].copy()
+        entries = entries[valid]
+        if exits is not None:
+            exits = exits[valid]
+    return prices, np.asarray(entries), None if exits is None else np.asarray(exits)
+
+
+def input_digest(
+    prices: pd.DataFrame,
+    entries: np.ndarray,
+    exits: np.ndarray | None,
+) -> str:
+    """Hash generated prices and signals independently of pandas hashing internals."""
+    if not isinstance(prices.index, pd.DatetimeIndex):
+        raise TypeError("validation prices must use a DatetimeIndex")
+
+    digest = hashlib.sha256()
+    frame_identity = {
+        "columns": [str(column) for column in prices.columns],
+        "dtypes": [str(dtype) for dtype in prices.dtypes],
+        "index": {
+            "dtype": "datetime64[ns]",
+            "name": prices.index.name,
+            "timezone": str(prices.index.tz) if prices.index.tz is not None else None,
+        },
+        "shape": prices.shape,
+    }
+    digest.update(json.dumps(frame_identity, sort_keys=True).encode("utf-8"))
+    normalized_index = (
+        prices.index.tz_convert("UTC").tz_localize(None)
+        if prices.index.tz is not None
+        else prices.index
+    )
+    index_values = np.ascontiguousarray(
+        normalized_index.to_numpy(dtype="datetime64[ns]").view("<i8")
+    )
+    digest.update(index_values.tobytes())
+    for column in prices.columns:
+        values = np.ascontiguousarray(prices[column].to_numpy())
+        digest.update(str(column).encode("utf-8"))
+        digest.update(values.dtype.str.encode("utf-8"))
+        digest.update(str(values.shape).encode("utf-8"))
+        digest.update(values.tobytes())
+    for name, values in (("entries", entries), ("exits", exits)):
+        digest.update(name.encode("utf-8"))
+        if values is None:
+            digest.update(b"none")
+            continue
+        array = np.ascontiguousarray(values)
+        digest.update(str(array.dtype).encode("utf-8"))
+        digest.update(str(array.shape).encode("utf-8"))
+        digest.update(array.tobytes())
+    return digest.hexdigest()
+
+
+def scenario_digest(scenario: ScenarioConfig) -> str:
+    """Hash one declarative scenario definition."""
+    return _json_digest(asdict(scenario))
+
+
+def static_digests(scenario: ScenarioConfig, framework: str) -> dict[str, str]:
+    """Return behavior-relevant source digests for one comparison pair."""
+    adapter_path = VALIDATION_DIR / "frameworks" / f"{framework}.py"
+    profile_inputs = {
+        "profile_source": file_digest(SOURCE_DIR / "profiles.py"),
+        "base": scenario.ml4t_config,
+        "override": scenario.ml4t_overrides.get(framework, {}),
+    }
+    return {
+        "adapter": file_digest(adapter_path),
+        "canonical_records": file_digest(VALIDATION_DIR / "common" / "canonical_records.py"),
+        "capabilities": file_digest(VALIDATION_DIR / "common" / "capabilities.py"),
+        "comparator": file_digest(VALIDATION_DIR / "common" / "comparator.py"),
+        "engine": _tree_digest(SOURCE_DIR),
+        "manifest": file_digest(DEFAULT_MANIFEST_PATH),
+        "ml4t_runner": file_digest(VALIDATION_DIR / "common" / "ml4t_runner.py"),
+        "profile": _json_digest(profile_inputs),
+        "scenario": scenario_digest(scenario),
+    }
+
+
+def _git_identity() -> dict[str, object]:
+    commit = subprocess.run(
+        ["git", "rev-parse", "HEAD"],
+        cwd=PROJECT_ROOT,
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout.strip()
+    status = subprocess.run(
+        ["git", "status", "--porcelain", "--untracked-files=no"],
+        cwd=PROJECT_ROOT,
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout
+    return {"commit": commit, "dirty": bool(status.strip())}
+
+
+def installed_framework_version(target: FrameworkTarget) -> str:
+    """Return the version imported by the isolated scenario environment."""
+    return importlib.metadata.version(target.package)
+
+
+def comparison_protocol_metadata(scenario: ScenarioConfig, framework: str) -> dict[str, str]:
+    """Identify native and adapter-emulated portions of a comparison."""
+    if framework != "zipline":
+        return {"risk_rules": "framework_adapter"}
+    return {
+        "commission": "explicit scenario model or NoCommission",
+        "execution": "custom next-session open-price slippage model",
+        "fills": "native transactions with fees reconstructed from the configured model",
+        "risk_rules": "adapter_emulated_daily_ohlc" if scenario.risk_rules else "none",
+        "trade_records": "adapter_reconstructed_from_native_transactions",
+    }
+
+
+def build_record_provenance(
+    *,
+    scenario: ScenarioConfig,
+    framework: str,
+    target: FrameworkTarget,
+    prices: pd.DataFrame,
+    entries: np.ndarray,
+    exits: np.ndarray | None,
+    framework_result: FrameworkResult,
+    ml4t_result: FrameworkResult,
+) -> dict[str, Any]:
+    """Build complete provenance for one executed comparison."""
+    adapter_path = VALIDATION_DIR / "frameworks" / f"{framework}.py"
+    return {
+        "framework_target": {
+            "version": target.version,
+            "actual_version": installed_framework_version(target),
+            "immutable_id": target.immutable_id,
+        },
+        "ml4t": _git_identity(),
+        "python": {
+            "version": sys.version.split()[0],
+            "implementation": sys.implementation.name,
+        },
+        "adapter": {
+            "module": f"frameworks.{framework}",
+            "path": adapter_path.relative_to(PROJECT_ROOT).as_posix(),
+        },
+        "comparison_protocol": comparison_protocol_metadata(scenario, framework),
+        "capabilities": {
+            "framework": framework_result.capabilities,
+            "ml4t": ml4t_result.capabilities,
+        },
+        "digests": static_digests(scenario, framework),
+        "input_digest": input_digest(prices, entries, exits),
+        "record_counts": {
+            "bars": len(prices),
+            "entry_signals": int(entries.sum()),
+            "exit_signals": int(exits.sum()) if exits is not None else 0,
+            "framework_intents": int(entries.sum())
+            + (int(exits.sum()) if exits is not None else 0),
+            "ml4t_intents": int(entries.sum()) + (int(exits.sum()) if exits is not None else 0),
+            "framework_orders": None,
+            "ml4t_orders": None,
+            "framework_fills": len(framework_result.fills),
+            "ml4t_fills": len(ml4t_result.fills),
+            "framework_closed_trades": framework_result.num_trades,
+            "ml4t_closed_trades": ml4t_result.num_trades,
+        },
+    }
diff --git a/validation/common/types.py b/validation/common/types.py
index 324c4ac1..f02cd2a2 100644
--- a/validation/common/types.py
+++ b/validation/common/types.py
@@ -2,10 +2,55 @@
 
 from __future__ import annotations
 
+import math
 from dataclasses import dataclass, field
+from decimal import Decimal
 from enum import StrEnum
 from typing import Any
 
+from common.framework_registry import load_framework_manifest
+
+
+def _scenario_frameworks() -> list[str]:
+    return list(load_framework_manifest().scenario_framework_ids)
+
+
+def _json_value(value: Any) -> Any:
+    if value is None or isinstance(value, (bool, int, float, str)):
+        return value
+    if isinstance(value, Decimal):
+        return str(value)
+    if isinstance(value, dict):
+        return {str(key): _json_value(item) for key, item in value.items()}
+    if isinstance(value, (list, tuple)):
+        return [_json_value(item) for item in value]
+    if hasattr(value, "item"):
+        return _json_value(value.item())
+    if hasattr(value, "isoformat"):
+        return value.isoformat()
+    raise TypeError(f"Value is not JSON serializable: {type(value).__name__}")
+
+
+def _required_string(value: object, label: str) -> str:
+    if not isinstance(value, str) or not value:
+        raise TypeError(f"{label} must be a nonempty string")
+    return value
+
+
+def _required_bool(value: object, label: str) -> bool:
+    if not isinstance(value, bool):
+        raise TypeError(f"{label} must be a boolean")
+    return value
+
+
+def _required_number(value: object, label: str) -> float:
+    if not isinstance(value, (int, float)) or isinstance(value, bool):
+        raise TypeError(f"{label} must be numeric")
+    number = float(value)
+    if not math.isfinite(number):
+        raise ValueError(f"{label} must be finite")
+    return number
+
 
 class ValidationStatus(StrEnum):
     """Terminal status for one framework/scenario validation attempt."""
@@ -34,6 +79,11 @@ class ValidationRecord:
     status: ValidationStatus
     required: bool
     detail: str | None = None
+    duration_seconds: float | None = None
+    provenance: dict[str, Any] | None = None
+    framework_result: FrameworkResult | None = None
+    ml4t_result: FrameworkResult | None = None
+    comparison: ComparisonResult | None = None
 
     @property
     def passed(self) -> bool:
@@ -47,7 +97,7 @@ def release_blocking(self) -> bool:
 
     def to_dict(self) -> dict[str, Any]:
         """Return a JSON-serializable record."""
-        return {
+        payload = {
             "framework": self.framework,
             "scenario_id": self.scenario_id,
             "scenario_name": self.scenario_name,
@@ -55,7 +105,15 @@ def to_dict(self) -> dict[str, Any]:
             "required": self.required,
             "release_blocking": self.release_blocking,
             "detail": self.detail,
+            "duration_seconds": self.duration_seconds,
+            "provenance": _json_value(self.provenance),
+            "framework_result": (
+                self.framework_result.to_dict() if self.framework_result is not None else None
+            ),
+            "ml4t_result": self.ml4t_result.to_dict() if self.ml4t_result is not None else None,
+            "comparison": self.comparison.to_dict() if self.comparison is not None else None,
         }
+        return payload
 
     @classmethod
     def from_dict(cls, payload: dict[str, Any]) -> ValidationRecord:
@@ -70,20 +128,66 @@ def from_dict(cls, payload: dict[str, Any]) -> ValidationRecord:
         scenario_name = payload["scenario_name"]
         required = payload["required"]
         detail = payload.get("detail")
+        duration_seconds = payload.get("duration_seconds")
+        provenance = payload.get("provenance")
         if not all(isinstance(value, str) for value in (framework, scenario_id, scenario_name)):
             raise TypeError("Validation record identifiers must be strings")
         if not isinstance(required, bool):
             raise TypeError("Validation record required must be a boolean")
         if detail is not None and not isinstance(detail, str):
             raise TypeError("Validation record detail must be a string or null")
+        if duration_seconds is not None and (
+            not isinstance(duration_seconds, (int, float)) or isinstance(duration_seconds, bool)
+        ):
+            raise TypeError("Validation record duration_seconds must be numeric or null")
+        if provenance is not None and not isinstance(provenance, dict):
+            raise TypeError("Validation record provenance must be an object or null")
+
+        framework_result_payload = payload.get("framework_result")
+        ml4t_result_payload = payload.get("ml4t_result")
+        comparison_payload = payload.get("comparison")
+        framework_result = (
+            FrameworkResult.from_dict(framework_result_payload)
+            if isinstance(framework_result_payload, dict)
+            else None
+        )
+        ml4t_result = (
+            FrameworkResult.from_dict(ml4t_result_payload)
+            if isinstance(ml4t_result_payload, dict)
+            else None
+        )
+        comparison = (
+            ComparisonResult.from_dict(comparison_payload)
+            if isinstance(comparison_payload, dict)
+            else None
+        )
+        evidence_fields = (framework_result_payload, ml4t_result_payload, comparison_payload)
+        if any(value is not None for value in evidence_fields) and any(
+            value is None for value in evidence_fields
+        ):
+            raise ValueError("Validation record comparison evidence must be complete")
+        status = ValidationStatus(payload["status"])
+        if status in {ValidationStatus.PASS, ValidationStatus.COMPARISON_FAILURE} and (
+            provenance is None
+            or duration_seconds is None
+            or framework_result is None
+            or ml4t_result is None
+            or comparison is None
+        ):
+            raise ValueError("Compared validation record lacks complete evidence")
 
         return cls(
             framework=framework,
             scenario_id=scenario_id,
             scenario_name=scenario_name,
-            status=ValidationStatus(payload["status"]),
+            status=status,
             required=required,
             detail=detail,
+            duration_seconds=float(duration_seconds) if duration_seconds is not None else None,
+            provenance=provenance,
+            framework_result=framework_result,
+            ml4t_result=ml4t_result,
+            comparison=comparison,
         )
 
 
@@ -91,11 +195,38 @@ class ValidationSkipped(RuntimeError):
     """Raised by an adapter that elects not to execute a required scenario."""
 
 
+CAPABILITY_KEYS = (
+    "intents",
+    "orders",
+    "rejections",
+    "fills",
+    "positions",
+    "cash_flows",
+    "open_trades",
+    "closed_trades",
+    "exit_reason",
+    "terminal",
+)
+CAPABILITY_VALUES = {
+    "native",
+    "native_filled_only",
+    "reconstructed",
+    "input_only",
+    "aggregate_only",
+    "unavailable",
+}
+
+
+def unavailable_capabilities() -> dict[str, str]:
+    """Return an explicit declaration that no optional result surface is available."""
+    return dict.fromkeys(CAPABILITY_KEYS, "unavailable")
+
+
 @dataclass
 class ScenarioConfig:
     """Declarative definition of a validation scenario."""
 
-    id: str  # "01", "02", ..., "16"
+    id: str  # "01", "02", ..., "17"
     name: str  # Human-readable name
     description: str
 
@@ -122,9 +253,7 @@ class ScenarioConfig:
     default_tolerance: Tolerance | None = None
 
     # Which frameworks support this scenario
-    supported_frameworks: list[str] = field(
-        default_factory=lambda: ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline"]
-    )
+    supported_frameworks: list[str] = field(default_factory=_scenario_frameworks)
 
     # Extra comparison checks beyond standard (trade count, final value, pnl)
     extra_checks: list[str] = field(default_factory=list)
@@ -162,8 +291,67 @@ class FrameworkResult:
     total_pnl: float
     num_trades: int
     trades: list[dict[str, Any]] = field(default_factory=list)
+    fills: list[dict[str, Any]] = field(default_factory=list)
+    capabilities: dict[str, str] = field(default_factory=unavailable_capabilities)
     extra: dict[str, Any] = field(default_factory=dict)
 
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "framework": self.framework,
+            "final_value": self.final_value,
+            "total_pnl": self.total_pnl,
+            "num_trades": self.num_trades,
+            "trades": _json_value(self.trades),
+            "fills": _json_value(self.fills),
+            "capabilities": _json_value(self.capabilities),
+            "extra": _json_value(self.extra),
+        }
+
+    @classmethod
+    def from_dict(cls, payload: dict[str, Any]) -> FrameworkResult:
+        required = {
+            "framework",
+            "final_value",
+            "total_pnl",
+            "num_trades",
+            "trades",
+            "fills",
+            "capabilities",
+            "extra",
+        }
+        missing = sorted(required - payload.keys())
+        if missing:
+            raise ValueError(f"Framework result missing fields: {', '.join(missing)}")
+        trades = payload["trades"]
+        fills = payload["fills"]
+        capabilities = payload["capabilities"]
+        extra = payload["extra"]
+        num_trades = payload["num_trades"]
+        if not isinstance(trades, list) or not all(isinstance(trade, dict) for trade in trades):
+            raise TypeError("Framework result trades must be an object array")
+        if not isinstance(fills, list) or not all(isinstance(fill, dict) for fill in fills):
+            raise TypeError("Framework result fills must be an object array")
+        if not isinstance(capabilities, dict) or set(capabilities) != set(CAPABILITY_KEYS):
+            raise TypeError("Framework result capabilities must declare every canonical surface")
+        if not all(
+            isinstance(value, str) and value in CAPABILITY_VALUES for value in capabilities.values()
+        ):
+            raise ValueError("Framework result capabilities contain an unsupported declaration")
+        if not isinstance(extra, dict):
+            raise TypeError("Framework result trades and extra have invalid types")
+        if not isinstance(num_trades, int) or isinstance(num_trades, bool) or num_trades < 0:
+            raise TypeError("Framework result num_trades must be a nonnegative integer")
+        return cls(
+            framework=_required_string(payload["framework"], "Framework result framework"),
+            final_value=_required_number(payload["final_value"], "Framework result final_value"),
+            total_pnl=_required_number(payload["total_pnl"], "Framework result total_pnl"),
+            num_trades=num_trades,
+            trades=trades,
+            fills=fills,
+            capabilities=capabilities,
+            extra=extra,
+        )
+
 
 @dataclass
 class ComparisonResult:
@@ -174,6 +362,30 @@ class ComparisonResult:
     passed: bool
     checks: list[CheckResult] = field(default_factory=list)
 
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "scenario_id": self.scenario_id,
+            "framework": self.framework,
+            "passed": self.passed,
+            "checks": [check.to_dict() for check in self.checks],
+        }
+
+    @classmethod
+    def from_dict(cls, payload: dict[str, Any]) -> ComparisonResult:
+        required = {"scenario_id", "framework", "passed", "checks"}
+        missing = sorted(required - payload.keys())
+        if missing:
+            raise ValueError(f"Comparison result missing fields: {', '.join(missing)}")
+        checks = payload.get("checks")
+        if not isinstance(checks, list) or not all(isinstance(check, dict) for check in checks):
+            raise TypeError("Comparison checks must be an object array")
+        return cls(
+            scenario_id=_required_string(payload["scenario_id"], "Comparison scenario_id"),
+            framework=_required_string(payload["framework"], "Comparison framework"),
+            passed=_required_bool(payload["passed"], "Comparison passed"),
+            checks=[CheckResult.from_dict(check) for check in checks],
+        )
+
     @property
     def summary(self) -> str:
         status = "PASS" if self.passed else "FAIL"
@@ -193,3 +405,46 @@ class CheckResult:
     message: str
     expected: Any = None
     actual: Any = None
+    difference: Any = None
+    canonical_quantum: str | None = None
+    diagnostic_limit: Any = None
+
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "name": self.name,
+            "passed": self.passed,
+            "canonical_quantum": self.canonical_quantum,
+            "expected": _json_value(self.expected),
+            "actual": _json_value(self.actual),
+            "difference": _json_value(self.difference),
+            "diagnostic_limit": _json_value(self.diagnostic_limit),
+            "message": self.message,
+        }
+
+    @classmethod
+    def from_dict(cls, payload: dict[str, Any]) -> CheckResult:
+        required = {
+            "name",
+            "passed",
+            "canonical_quantum",
+            "expected",
+            "actual",
+            "difference",
+            "diagnostic_limit",
+            "message",
+        }
+        missing = sorted(required - payload.keys())
+        if missing:
+            raise ValueError(f"Comparison check missing fields: {', '.join(missing)}")
+        return cls(
+            name=_required_string(payload["name"], "Comparison check name"),
+            passed=_required_bool(payload["passed"], "Comparison check passed"),
+            message=_required_string(payload["message"], "Comparison check message"),
+            expected=payload["expected"],
+            actual=payload["actual"],
+            difference=payload["difference"],
+            canonical_quantum=_required_string(
+                payload["canonical_quantum"], "Comparison check canonical_quantum"
+            ),
+            diagnostic_limit=payload["diagnostic_limit"],
+        )
diff --git a/validation/cross_framework_performance.py b/validation/cross_framework_performance.py
new file mode 100644
index 00000000..ba8b101b
--- /dev/null
+++ b/validation/cross_framework_performance.py
@@ -0,0 +1,949 @@
+#!/usr/bin/env python3
+"""Generate controlled and idiomatic cross-framework performance evidence."""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import http.client
+import json
+import os
+import platform
+import random
+import socket
+import subprocess
+import sys
+import tempfile
+import urllib.parse
+from contextlib import redirect_stdout
+from dataclasses import asdict, dataclass
+from datetime import UTC, datetime
+from io import StringIO
+from pathlib import Path
+from statistics import median
+from time import perf_counter, sleep
+from typing import Any, cast
+
+VALIDATION_DIR = Path(__file__).parent
+PROJECT_ROOT = VALIDATION_DIR.parent
+sys.path.insert(0, str(PROJECT_ROOT))
+sys.path.insert(0, str(PROJECT_ROOT / "src"))
+sys.path.insert(0, str(VALIDATION_DIR))
+
+import benchmark_suite as suite  # noqa: E402
+import large_scale_evidence as scale  # noqa: E402
+from common.framework_registry import load_framework_manifest  # noqa: E402
+
+SCHEMA_VERSION = 1
+MIN_SAMPLES = 10
+BOOTSTRAP_RESAMPLES = 10_000
+BOOTSTRAP_CONFIDENCE = 0.95
+WORKER_TIMEOUT_SECONDS = 900
+ACCEPTED_PATH = VALIDATION_DIR / "PERFORMANCE_RESULTS.json"
+CANDIDATE_PATH = VALIDATION_DIR / "candidates" / "PERFORMANCE_RESULTS.candidate.json"
+THREAD_ENVIRONMENT = {
+    "MKL_NUM_THREADS": "1",
+    "NUMBA_NUM_THREADS": "1",
+    "OMP_NUM_THREADS": "1",
+    "OPENBLAS_NUM_THREADS": "1",
+    "POLARS_MAX_THREADS": "1",
+    "PYTHONHASHSEED": "0",
+}
+MEASUREMENT_PROTOCOL = {
+    "process_isolation": "one fresh child process per warm-up and measured repetition",
+    "warmup": "one unmeasured isolated process per runner before measured repetitions",
+    "runtime_primary": (
+        "parent perf_counter around the complete child process, including interpreter startup, "
+        "imports, deterministic input generation, adapter setup, engine execution, output "
+        "extraction, canonical validation, and process teardown"
+    ),
+    "runtime_secondary": "adapter-reported engine interval and worker stage intervals",
+    "memory": "child resource.getrusage(RUSAGE_SELF).ru_maxrss over the complete process",
+    "cache_policy": (
+        "installed packages and compiled framework caches persist; inputs and framework state are "
+        "rebuilt in every child; Zipline uses a new bundle root for every child"
+    ),
+    "thread_environment": THREAD_ENVIRONMENT,
+    "uncertainty": {
+        "method": "deterministic percentile bootstrap of the sample median",
+        "confidence": BOOTSTRAP_CONFIDENCE,
+        "resamples": BOOTSTRAP_RESAMPLES,
+    },
+}
+
+
+@dataclass(frozen=True)
+class RunnerSpec:
+    """One framework side measured in its locked environment."""
+
+    runner_id: str
+    framework: str
+    side: str
+    profile: str
+
+
+WORKLOAD = scale.ScaleWorkload(
+    name="performance_50_assets_252_sessions",
+    seed=42,
+    bars=252,
+    assets=50,
+    top_n=5,
+    bottom_n=5,
+    rebalance_frequency=1,
+    end_session="2025-12-31",
+)
+
+RUNNERS = tuple(
+    runner
+    for framework, profile in (
+        ("vectorbt_pro", "vectorbt_strict"),
+        ("vectorbt_oss", "vectorbt_oss_strict"),
+        ("backtrader", "backtrader_strict"),
+        ("zipline", "zipline_strict"),
+        ("lean", "lean"),
+    )
+    for runner in (
+        RunnerSpec(f"{framework}:external", framework, "external", profile),
+        RunnerSpec(f"{framework}:ml4t", framework, "ml4t", profile),
+    )
+)
+RUNNERS_BY_ID = {runner.runner_id: runner for runner in RUNNERS}
+
+IDIOMATIC_RUNNERS = {
+    "ml4t_backtest": "vectorbt_oss:ml4t",
+    "vectorbt_pro": "vectorbt_pro:external",
+    "vectorbt_oss": "vectorbt_oss:external",
+    "backtrader": "backtrader:external",
+    "zipline": "zipline:external",
+    "lean": "lean:external",
+}
+IDIOMATIC_DISCLOSURES = {
+    "ml4t_backtest": (
+        "Event-driven Strategy and Engine API with the vectorbt_oss_strict profile; this is one "
+        "documented ML4T configuration, not a framework-wide default-performance claim."
+    ),
+    "vectorbt_pro": (
+        "Vectorized Portfolio.from_orders target-amount API with cash sharing, same-bar close "
+        "execution, zero costs, and locked short collateral."
+    ),
+    "vectorbt_oss": (
+        "Vectorized Portfolio.from_orders target-amount API with cash sharing, same-bar close "
+        "execution, zero costs, and lock_cash enabled."
+    ),
+    "backtrader": (
+        "Native Cerebro and Strategy callbacks with target orders, next-session open fills, "
+        "integer shares, zero commission, and enabled submission cash checks."
+    ),
+    "zipline": (
+        "Native run_algorithm callback and order_target API with daily bundle ingestion, a custom "
+        "open-price slippage model, and zero commission. Bundle creation is included."
+    ),
+    "lean": (
+        "Native QCAlgorithm daily callback and market-order API in the frozen LEAN image with the "
+        "declared margin account, zero fee, and zero slippage models."
+    ),
+}
+
+
+def _json_digest(value: object) -> str:
+    return hashlib.sha256(
+        json.dumps(value, sort_keys=True, separators=(",", ":"), default=str).encode()
+    ).hexdigest()
+
+
+def _source_digests() -> dict[str, str]:
+    paths = {
+        "benchmark_suite": VALIDATION_DIR / "benchmark_suite.py",
+        "framework_manifest": VALIDATION_DIR / "framework_targets.toml",
+        "performance_runner": Path(__file__),
+        "profiles": PROJECT_ROOT / "src" / "ml4t" / "backtest" / "profiles.py",
+    }
+    return {name: hashlib.sha256(path.read_bytes()).hexdigest() for name, path in paths.items()}
+
+
+def _git_identity() -> dict[str, object]:
+    commit = subprocess.run(
+        ["git", "rev-parse", "HEAD"],
+        cwd=PROJECT_ROOT,
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout.strip()
+    status = subprocess.run(
+        ["git", "status", "--porcelain", "--untracked-files=no"],
+        cwd=PROJECT_ROOT,
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout.strip()
+    return {"commit": commit, "dirty": bool(status)}
+
+
+def _peak_rss_mb() -> float:
+    import resource
+
+    peak = float(resource.getrusage(resource.RUSAGE_SELF).ru_maxrss)
+    return peak / (1024 * 1024) if sys.platform == "darwin" else peak / 1024
+
+
+def _process_tree_rss_bytes(root_pid: int) -> int:
+    """Return current RSS for a Linux process and all current descendants."""
+    pending = [root_pid]
+    observed: set[int] = set()
+    total = 0
+    while pending:
+        pid = pending.pop()
+        if pid in observed:
+            continue
+        observed.add(pid)
+        try:
+            status = Path(f"/proc/{pid}/status").read_text(encoding="utf-8")
+            rss_line = next(
+                (line for line in status.splitlines() if line.startswith("VmRSS:")),
+                "VmRSS: 0 kB",
+            )
+            total += int(rss_line.split()[1]) * 1024
+            children = Path(f"/proc/{pid}/task/{pid}/children").read_text(encoding="utf-8")
+            pending.extend(int(child) for child in children.split())
+        except (FileNotFoundError, PermissionError, ProcessLookupError, ValueError):
+            continue
+    return total
+
+
+class _DockerConnection(http.client.HTTPConnection):
+    def connect(self) -> None:
+        self.sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
+        self.sock.connect("/var/run/docker.sock")
+
+
+def _docker_json(path: str) -> Any:
+    connection = _DockerConnection("localhost", timeout=1.0)
+    try:
+        connection.request("GET", path)
+        response = connection.getresponse()
+        payload = response.read()
+        if response.status != 200:
+            raise RuntimeError(f"Docker API {path} returned {response.status}")
+        return json.loads(payload)
+    finally:
+        connection.close()
+
+
+def _docker_container_ids(ancestor: str) -> set[str]:
+    filters = urllib.parse.quote(json.dumps({"ancestor": [ancestor]}, separators=(",", ":")))
+    payload = _docker_json(f"/containers/json?filters={filters}")
+    if not isinstance(payload, list):
+        raise RuntimeError("Docker container list was not an array")
+    return {str(container["Id"]) for container in payload if isinstance(container, dict)}
+
+
+def _docker_container_pid(container_id: str) -> int | None:
+    payload = _docker_json(f"/containers/{container_id}/json")
+    if not isinstance(payload, dict) or not isinstance(payload.get("State"), dict):
+        return None
+    pid = payload["State"].get("Pid")
+    return int(pid) if isinstance(pid, int) and pid > 0 else None
+
+
+def _container_cgroup_memory_path(pid: int) -> Path | None:
+    try:
+        entries = Path(f"/proc/{pid}/cgroup").read_text(encoding="utf-8").splitlines()
+    except (FileNotFoundError, PermissionError, ProcessLookupError):
+        return None
+    for entry in entries:
+        parts = entry.split(":", 2)
+        if len(parts) == 3 and parts[0] == "0":
+            path = Path("/sys/fs/cgroup") / parts[2].lstrip("/") / "memory.current"
+            return path if path.is_file() else None
+    return None
+
+
+def _execute_with_memory_monitor(
+    command: list[str],
+    *,
+    cwd: Path,
+    env: dict[str, str],
+    timeout: float,
+    docker_ancestor: str | None = None,
+) -> tuple[subprocess.CompletedProcess[str], float, float, bool]:
+    """Execute a worker while sampling its process tree and optional container cgroup."""
+    existing_containers = (
+        _docker_container_ids(docker_ancestor) if docker_ancestor is not None else set()
+    )
+    started = perf_counter()
+    process = subprocess.Popen(
+        command,
+        cwd=cwd,
+        env=env,
+        stdout=subprocess.PIPE,
+        stderr=subprocess.PIPE,
+        text=True,
+    )
+    peak_bytes = 0
+    container_path: Path | None = None
+    container_observed = docker_ancestor is None
+    next_docker_poll = started
+    deadline = started + timeout
+    while process.poll() is None:
+        if perf_counter() > deadline:
+            process.kill()
+            stdout, stderr = process.communicate()
+            raise RuntimeError(
+                f"Performance worker exceeded {timeout:.0f}s: {(stderr or stdout).strip()[-2_000:]}"
+            )
+        tree_bytes = _process_tree_rss_bytes(process.pid)
+        container_bytes = 0
+        if (
+            docker_ancestor is not None
+            and container_path is None
+            and perf_counter() >= next_docker_poll
+        ):
+            next_docker_poll = perf_counter() + 0.1
+            current = _docker_container_ids(docker_ancestor) - existing_containers
+            if current:
+                container_id = sorted(current)[0]
+                container_pid = _docker_container_pid(container_id)
+                if container_pid is not None:
+                    container_path = _container_cgroup_memory_path(container_pid)
+                    container_observed = container_path is not None
+        if container_path is not None:
+            try:
+                container_bytes = int(container_path.read_text(encoding="utf-8").strip())
+            except (FileNotFoundError, PermissionError, ProcessLookupError, ValueError):
+                container_path = None
+        peak_bytes = max(peak_bytes, tree_bytes + container_bytes)
+        sleep(0.02)
+    peak_bytes = max(peak_bytes, _process_tree_rss_bytes(process.pid))
+    stdout, stderr = process.communicate()
+    completed = subprocess.CompletedProcess(command, process.returncode, stdout, stderr)
+    return completed, perf_counter() - started, peak_bytes / (1024 * 1024), container_observed
+
+
+def _run_external(
+    framework: str,
+    config: suite.BenchmarkConfig,
+    price_data: dict[str, Any],
+    signals: Any,
+    dates: Any,
+) -> suite.BenchmarkResult:
+    runners = {
+        "vectorbt_pro": suite.benchmark_vectorbt_pro,
+        "vectorbt_oss": suite.benchmark_vectorbt_oss,
+        "backtrader": suite.benchmark_backtrader,
+        "zipline": suite.benchmark_zipline,
+        "lean": suite.benchmark_lean,
+    }
+    return runners[framework](config, price_data, signals, dates)
+
+
+def _run_ml4t(
+    runner: RunnerSpec,
+    config: suite.BenchmarkConfig,
+    price_data: dict[str, Any],
+    signals: Any,
+    dates: Any,
+) -> suite.BenchmarkResult:
+    execution_mode = "same_bar" if runner.framework.startswith("vectorbt") else "next_bar"
+    return suite.benchmark_ml4t(
+        config,
+        price_data,
+        signals,
+        dates,
+        execution_mode=execution_mode,
+        profile_override=runner.profile,
+    )
+
+
+def _surface_signature(result: suite.BenchmarkResult, effective_prices: dict[str, Any]) -> dict:
+    result.trades_df = suite.closed_trades_from_fills(result.fills_df)
+    trade_records = suite.canonical_trade_records(result.trades_df, timestamp_domain="session_date")
+    result.num_trades = len(trade_records) if trade_records is not None else 0
+    intents = suite.canonical_target_records(result.target_trace_df)
+    fills = suite.canonical_fill_records(result.fills_df, timestamp_domain="session_date")
+    trades = trade_records
+    if intents is None or fills is None or trades is None:
+        raise RuntimeError("Performance runner did not expose every controlled output surface")
+    terminal = scale._terminal_state(result, effective_prices, WORKLOAD.initial_cash)
+    return {
+        "order_intents": {"count": len(intents), "sha256": suite._records_hash(intents)},
+        "fills": {"count": len(fills), "sha256": suite._records_hash(fills)},
+        "trades": {"count": len(trades), "sha256": suite._records_hash(trades)},
+        "trade_count": len(trades),
+        "total_pnl": scale._canonical_money(result.final_value - WORKLOAD.initial_cash),
+        "final_value": scale._canonical_money(result.final_value),
+        "terminal_state_sha256": terminal["sha256"],
+    }
+
+
+def run_worker(runner: RunnerSpec) -> dict[str, Any]:
+    """Run one measured framework side and return its validated output signature."""
+    started = perf_counter()
+    manifest = load_framework_manifest()
+    target = manifest.targets[runner.framework]
+    actual_target = scale._actual_target(target)
+    config = WORKLOAD.benchmark_config()
+
+    input_started = perf_counter()
+    price_data, signals, dates = suite.generate_benchmark_data(config, seed=WORKLOAD.seed)
+    raw_input_sha256 = scale.input_digest(price_data, signals, dates)
+    effective_prices = scale._effective_prices(runner.framework, price_data)
+    effective_input_sha256 = scale.input_digest(effective_prices, signals, dates)
+    input_seconds = perf_counter() - input_started
+
+    framework_started = perf_counter()
+    output_log = StringIO()
+    with redirect_stdout(output_log):
+        if runner.framework == "zipline":
+            with tempfile.TemporaryDirectory(prefix="ml4t-performance-zipline-") as root:
+                previous_root = os.environ.get("ZIPLINE_ROOT")
+                os.environ["ZIPLINE_ROOT"] = root
+                try:
+                    result = (
+                        _run_external(runner.framework, config, price_data, signals, dates)
+                        if runner.side == "external"
+                        else _run_ml4t(runner, config, price_data, signals, dates)
+                    )
+                finally:
+                    if previous_root is None:
+                        os.environ.pop("ZIPLINE_ROOT", None)
+                    else:
+                        os.environ["ZIPLINE_ROOT"] = previous_root
+        else:
+            result = (
+                _run_external(runner.framework, config, price_data, signals, dates)
+                if runner.side == "external"
+                else _run_ml4t(runner, config, price_data, signals, dates)
+            )
+    framework_call_seconds = perf_counter() - framework_started
+    if result.error is not None:
+        raise RuntimeError(f"{runner.runner_id} failed: {result.error}")
+
+    validation_started = perf_counter()
+    signature = _surface_signature(result, effective_prices)
+    validation_seconds = perf_counter() - validation_started
+    return {
+        "runner_id": runner.runner_id,
+        "framework": runner.framework,
+        "side": runner.side,
+        "profile": runner.profile,
+        "target": actual_target,
+        "python": {
+            "implementation": sys.implementation.name,
+            "version": platform.python_version(),
+        },
+        "ml4t": _git_identity(),
+        "input": {
+            "raw_sha256": raw_input_sha256,
+            "effective_sha256": effective_input_sha256,
+        },
+        "stages_seconds": {
+            "input_generation": input_seconds,
+            "framework_call": framework_call_seconds,
+            "adapter_reported_engine": result.runtime_sec,
+            "output_validation": validation_seconds,
+            "worker_total": perf_counter() - started,
+        },
+        "process_peak_rss_mb": _peak_rss_mb(),
+        "thread_environment": {key: os.environ.get(key) for key in sorted(THREAD_ENVIRONMENT)},
+        "output": signature,
+        "output_sha256": _json_digest(signature),
+        "captured_log_tail": output_log.getvalue()[-2_000:],
+    }
+
+
+def run_calibration_worker() -> dict[str, Any]:
+    """Exercise wall-time and peak-RSS instrumentation with known work."""
+    started = perf_counter()
+    allocation = bytearray(32 * 1024 * 1024)
+    allocation[0] = 1
+    sleep(0.025)
+    return {
+        "worker_seconds": perf_counter() - started,
+        "process_peak_rss_mb": _peak_rss_mb(),
+        "allocated_bytes": len(allocation),
+    }
+
+
+def _resolve_python(runner: RunnerSpec) -> Path:
+    target = load_framework_manifest().targets[runner.framework]
+    override = os.getenv(target.python_env_var or "")
+    if override:
+        return Path(override).expanduser().resolve()
+    if target.environment is None:
+        raise RuntimeError(f"No environment configured for {runner.framework}")
+    return PROJECT_ROOT / target.environment / "bin" / "python"
+
+
+def _write_json(path: Path, payload: dict[str, Any]) -> None:
+    path.parent.mkdir(parents=True, exist_ok=True)
+    path.write_text(json.dumps(payload, indent=2, sort_keys=True) + "\n", encoding="utf-8")
+
+
+def _write_json_atomic(path: Path, payload: dict[str, Any]) -> None:
+    path.parent.mkdir(parents=True, exist_ok=True)
+    serialized = json.dumps(payload, indent=2, sort_keys=True) + "\n"
+    with tempfile.NamedTemporaryFile(
+        mode="w",
+        encoding="utf-8",
+        dir=path.parent,
+        prefix=f".{path.name}.",
+        delete=False,
+    ) as handle:
+        temporary = Path(handle.name)
+        handle.write(serialized)
+        handle.flush()
+        os.fsync(handle.fileno())
+    os.replace(temporary, path)
+
+
+def _run_process(runner: RunnerSpec) -> dict[str, Any]:
+    interpreter = _resolve_python(runner)
+    if not interpreter.is_file():
+        raise RuntimeError(f"Missing interpreter for {runner.runner_id}: {interpreter}")
+    with tempfile.TemporaryDirectory(prefix="ml4t-performance-worker-") as directory:
+        output = Path(directory) / "sample.json"
+        command = [
+            str(interpreter),
+            str(Path(__file__).resolve()),
+            "--worker",
+            runner.runner_id,
+            "--output",
+            str(output),
+        ]
+        environment = os.environ.copy()
+        environment.update(THREAD_ENVIRONMENT)
+        paths = [str(PROJECT_ROOT / "src"), str(VALIDATION_DIR)]
+        sibling_specs = PROJECT_ROOT.parent / "ml4t-specs" / "src"
+        if sibling_specs.is_dir():
+            paths.append(str(sibling_specs))
+        environment["PYTHONPATH"] = os.pathsep.join(
+            paths + ([environment["PYTHONPATH"]] if environment.get("PYTHONPATH") else [])
+        )
+        docker_ancestor = None
+        if runner.runner_id == "lean:external":
+            docker_ancestor = load_framework_manifest().targets["lean"].artifact
+            if docker_ancestor is None:
+                raise RuntimeError("LEAN target lacks an immutable engine image")
+        completed, process_wall_seconds, monitored_peak_rss_mb, container_observed = (
+            _execute_with_memory_monitor(
+                command,
+                cwd=PROJECT_ROOT,
+                env=environment,
+                timeout=WORKER_TIMEOUT_SECONDS,
+                docker_ancestor=docker_ancestor,
+            )
+        )
+        if completed.returncode != 0 or not output.is_file():
+            details = "\n".join(
+                value.strip() for value in (completed.stdout, completed.stderr) if value.strip()
+            )
+            raise RuntimeError(
+                f"Performance worker {runner.runner_id} exited {completed.returncode}: "
+                f"{details[-10_000:]}"
+            )
+        sample = cast(dict[str, Any], json.loads(output.read_text(encoding="utf-8")))
+        sample["process_wall_seconds"] = process_wall_seconds
+        sample["worker_self_peak_rss_mb"] = sample.pop("process_peak_rss_mb")
+        sample["process_peak_rss_mb"] = monitored_peak_rss_mb
+        sample["lean_container_observed"] = container_observed
+        return sample
+
+
+def run_calibration_process() -> dict[str, Any]:
+    with tempfile.TemporaryDirectory(prefix="ml4t-performance-calibration-") as directory:
+        output = Path(directory) / "calibration.json"
+        command = [
+            sys.executable,
+            str(Path(__file__).resolve()),
+            "--calibration-worker",
+            "--output",
+            str(output),
+        ]
+        started = perf_counter()
+        completed = subprocess.run(command, check=False, timeout=60)
+        wall_seconds = perf_counter() - started
+        if completed.returncode != 0 or not output.is_file():
+            raise RuntimeError("Performance instrumentation calibration failed")
+        result = cast(dict[str, Any], json.loads(output.read_text(encoding="utf-8")))
+        result["process_wall_seconds"] = wall_seconds
+        return result
+
+
+def _percentile(values: list[float], probability: float) -> float:
+    position = probability * (len(values) - 1)
+    lower = int(position)
+    upper = min(lower + 1, len(values) - 1)
+    fraction = position - lower
+    return values[lower] * (1.0 - fraction) + values[upper] * fraction
+
+
+def bootstrap_median_interval(values: list[float], *, seed: int) -> list[float]:
+    """Return a deterministic percentile-bootstrap 95 percent median interval."""
+    if len(values) < MIN_SAMPLES:
+        raise ValueError(f"At least {MIN_SAMPLES} samples are required")
+    generator = random.Random(seed)
+    estimates = sorted(
+        median(generator.choices(values, k=len(values))) for _ in range(BOOTSTRAP_RESAMPLES)
+    )
+    tail = (1.0 - BOOTSTRAP_CONFIDENCE) / 2.0
+    return [_percentile(estimates, tail), _percentile(estimates, 1.0 - tail)]
+
+
+def _summary(samples: list[dict[str, Any]], key: str, *, seed: int) -> dict[str, Any]:
+    values = [float(sample[key]) for sample in samples]
+    return {
+        "median": median(values),
+        "ci95": bootstrap_median_interval(values, seed=seed),
+        "minimum": min(values),
+        "maximum": max(values),
+    }
+
+
+def _runner_evidence(
+    runner: RunnerSpec,
+    warmup: dict[str, Any],
+    samples: list[dict[str, Any]],
+) -> dict[str, Any]:
+    seed = int(hashlib.sha256(runner.runner_id.encode()).hexdigest()[:8], 16)
+    output_sha256 = str(warmup["output_sha256"])
+    passed = all(sample.get("output_sha256") == output_sha256 for sample in samples)
+    return {
+        "runner": asdict(runner),
+        "target": warmup["target"],
+        "python": warmup["python"],
+        "warmup": {
+            "output_sha256": output_sha256,
+            "process_wall_seconds": warmup["process_wall_seconds"],
+        },
+        "output": warmup["output"],
+        "output_sha256": output_sha256,
+        "process_wall_seconds": _summary(samples, "process_wall_seconds", seed=seed),
+        "process_peak_rss_mb": _summary(samples, "process_peak_rss_mb", seed=seed + 1),
+        "adapter_engine_seconds": _summary(
+            [{"value": sample["stages_seconds"]["adapter_reported_engine"]} for sample in samples],
+            "value",
+            seed=seed + 2,
+        ),
+        "samples": samples,
+        "passed": passed,
+    }
+
+
+def _host_metadata() -> dict[str, Any]:
+    cpu_model = ""
+    cpuinfo = Path("/proc/cpuinfo")
+    if cpuinfo.is_file():
+        for line in cpuinfo.read_text(encoding="utf-8", errors="replace").splitlines():
+            if line.lower().startswith("model name"):
+                cpu_model = line.split(":", 1)[1].strip()
+                break
+    return {
+        "platform": platform.platform(),
+        "machine": platform.machine(),
+        "processor": platform.processor(),
+        "cpu_model": cpu_model,
+        "logical_cpu_count": os.cpu_count(),
+        "python": platform.python_version(),
+    }
+
+
+def _capability_matrix() -> list[dict[str, Any]]:
+    return [
+        {
+            "workload": WORKLOAD.name,
+            "dimensions": f"{WORKLOAD.assets} assets x {WORKLOAD.bars} daily sessions",
+            "coverage": list(scale.FRAMEWORKS),
+            "use": "controlled and idiomatic repeated performance evidence",
+        },
+        {
+            "workload": scale.WORKLOAD.name,
+            "dimensions": f"{scale.WORKLOAD.assets} assets x {scale.WORKLOAD.bars} daily sessions",
+            "coverage": list(scale.FRAMEWORKS),
+            "use": "large-scale equivalence only; recorded runtimes are not performance claims",
+        },
+        {
+            "workload": "historical_real_250_assets_5040_sessions",
+            "dimensions": "250 assets x 5,040 daily sessions",
+            "coverage": ["vectorbt_oss", "backtrader", "zipline", "lean"],
+            "use": (
+                "superseded audit input; single samples, inconsistent setup boundaries, missing "
+                "peak RSS for LEAN, and a non-reconstructable temporary data path"
+            ),
+        },
+        {
+            "workload": "performance_baselines.json workloads",
+            "dimensions": "single-asset, 250-asset, quote, rebalance, and partial-fill workloads",
+            "coverage": ["ml4t_backtest"],
+            "use": "internal regression evidence; not a cross-framework comparison",
+        },
+    ]
+
+
+def collect_evidence(samples: int) -> dict[str, Any]:
+    """Warm every runner, interleave measured repetitions, and build both tracks."""
+    if samples < MIN_SAMPLES:
+        raise ValueError(f"At least {MIN_SAMPLES} measured samples are required")
+    calibration = run_calibration_process()
+    if (
+        calibration["allocated_bytes"] != 32 * 1024 * 1024
+        or calibration["worker_seconds"] < 0.02
+        or calibration["process_wall_seconds"] < calibration["worker_seconds"]
+        or calibration["process_peak_rss_mb"] < 20
+    ):
+        raise RuntimeError(f"Performance instrumentation calibration failed: {calibration}")
+
+    warmups: dict[str, dict[str, Any]] = {}
+    measured: dict[str, list[dict[str, Any]]] = {runner.runner_id: [] for runner in RUNNERS}
+    for runner in RUNNERS:
+        print(f"Warming {runner.runner_id}...", flush=True)
+        warmups[runner.runner_id] = _run_process(runner)
+    for repetition in range(samples):
+        offset = repetition % len(RUNNERS)
+        ordered = RUNNERS[offset:] + RUNNERS[:offset]
+        for runner in ordered:
+            print(
+                f"Measuring {runner.runner_id} sample {repetition + 1}/{samples}...",
+                flush=True,
+            )
+            measured[runner.runner_id].append(_run_process(runner))
+
+    runners = {
+        runner.runner_id: _runner_evidence(
+            runner,
+            warmups[runner.runner_id],
+            measured[runner.runner_id],
+        )
+        for runner in RUNNERS
+    }
+    pairs: dict[str, dict[str, Any]] = {}
+    for framework in scale.FRAMEWORKS:
+        external = runners[f"{framework}:external"]
+        ml4t = runners[f"{framework}:ml4t"]
+        exact = external["output"] == ml4t["output"]
+        pairs[framework] = {
+            "external_runner": f"{framework}:external",
+            "ml4t_runner": f"{framework}:ml4t",
+            "exact_output": exact,
+            "passed": bool(exact and external["passed"] and ml4t["passed"]),
+        }
+
+    idiomatic = {
+        name: {
+            "sample_source": runner_id,
+            "semantic_disclosure": IDIOMATIC_DISCLOSURES[name],
+            "invariants_passed": runners[runner_id]["passed"],
+        }
+        for name, runner_id in IDIOMATIC_RUNNERS.items()
+    }
+    controlled_passed = all(pair["passed"] for pair in pairs.values())
+    idiomatic_passed = all(entry["invariants_passed"] for entry in idiomatic.values())
+    return {
+        "schema_version": SCHEMA_VERSION,
+        "generated_at": datetime.now(UTC).isoformat(),
+        "workload": {
+            "recipe": asdict(WORKLOAD),
+            "recipe_sha256": _json_digest(asdict(WORKLOAD)),
+            "data_points": WORKLOAD.data_points,
+        },
+        "measurement_protocol": MEASUREMENT_PROTOCOL,
+        "protocol_sha256": _json_digest(MEASUREMENT_PROTOCOL),
+        "samples_per_runner": samples,
+        "host": _host_metadata(),
+        "calibration": calibration,
+        "source_digests": _source_digests(),
+        "runners": runners,
+        "controlled": {
+            "equivalence_required": True,
+            "pairs": pairs,
+            "passed": controlled_passed,
+        },
+        "idiomatic": {
+            "equivalence_claim": False,
+            "runners": idiomatic,
+            "passed": idiomatic_passed,
+        },
+        "capability_matrix": _capability_matrix(),
+        "historical_assessment": {
+            "comparable_to_current_measurements": False,
+            "reason": (
+                "The 2026-02-28 artifacts used one sample, inconsistent setup boundaries, old "
+                "framework revisions, different hardware provenance, and incomplete memory data."
+            ),
+        },
+        "release_gate_passed": controlled_passed and idiomatic_passed,
+    }
+
+
+def report_failures(report: dict[str, Any]) -> list[str]:
+    """Return every reason performance evidence cannot be accepted."""
+    failures: list[str] = []
+    if report.get("schema_version") != SCHEMA_VERSION:
+        return [f"Unsupported performance schema: {report.get('schema_version')!r}"]
+    workload = report.get("workload")
+    if not isinstance(workload, dict) or workload.get("recipe") != asdict(WORKLOAD):
+        failures.append("Performance workload recipe differs")
+    elif workload.get("recipe_sha256") != _json_digest(asdict(WORKLOAD)):
+        failures.append("Performance workload recipe digest differs")
+    if report.get("measurement_protocol") != MEASUREMENT_PROTOCOL:
+        failures.append("Performance measurement protocol differs")
+    if report.get("protocol_sha256") != _json_digest(MEASUREMENT_PROTOCOL):
+        failures.append("Performance protocol digest differs")
+    samples_per_runner = report.get("samples_per_runner")
+    if not isinstance(samples_per_runner, int) or samples_per_runner < MIN_SAMPLES:
+        failures.append("Performance evidence has too few measured samples")
+        samples_per_runner = 0
+    if report.get("source_digests") != _source_digests():
+        failures.append("Performance source digests differ")
+
+    raw_runners = report.get("runners")
+    if not isinstance(raw_runners, dict) or set(raw_runners) != set(RUNNERS_BY_ID):
+        return failures + ["Performance runner coverage differs"]
+    runners = cast(dict[str, dict[str, Any]], raw_runners)
+    manifest = load_framework_manifest()
+    reconstructed_input = scale._expected_input_digest(WORKLOAD)
+    for runner_id, runner in runners.items():
+        samples = runner.get("samples")
+        if not isinstance(samples, list) or len(samples) != samples_per_runner:
+            failures.append(f"{runner_id} sample count differs")
+            continue
+        if any(not isinstance(sample, dict) for sample in samples):
+            failures.append(f"{runner_id} contains a malformed sample")
+            continue
+        runner_spec = RUNNERS_BY_ID[runner_id]
+        expected_target = manifest.targets[runner_spec.framework].evidence_metadata()
+        target = runner.get("target")
+        if (
+            not isinstance(target, dict)
+            or scale._declared_target_metadata(target) != expected_target
+            or target.get("actual_version") != expected_target["version"]
+            or any(sample.get("target") != target for sample in samples)
+        ):
+            failures.append(f"{runner_id} target identity differs")
+        elif runner_spec.framework == "vectorbt_pro" and (
+            target.get("actual_commit") != expected_target["commit"]
+            or target.get("actual_immutable_id") != expected_target["immutable_id"]
+        ):
+            failures.append(f"{runner_id} installed source identity differs")
+        output_sha256 = runner.get("output_sha256")
+        if not isinstance(output_sha256, str) or any(
+            sample.get("output_sha256") != output_sha256
+            or sample.get("ml4t", {}).get("dirty") is not False
+            or not isinstance(sample.get("ml4t", {}).get("commit"), str)
+            or len(sample["ml4t"]["commit"]) != 40
+            for sample in samples
+        ):
+            failures.append(f"{runner_id} output checksum or clean-tree identity differs")
+        if runner.get("output") is None or _json_digest(runner["output"]) != output_sha256:
+            failures.append(f"{runner_id} retained output digest differs")
+        if any(
+            sample.get("input", {}).get("raw_sha256") != reconstructed_input
+            or sample.get("input") != samples[0].get("input")
+            or sample.get("thread_environment") != THREAD_ENVIRONMENT
+            for sample in samples
+        ):
+            failures.append(f"{runner_id} input or thread environment differs")
+        if any(
+            float(sample.get("process_wall_seconds", 0)) <= 0
+            or float(sample.get("process_peak_rss_mb", 0)) <= 0
+            or (runner_id == "lean:external" and sample.get("lean_container_observed") is not True)
+            for sample in samples
+        ):
+            failures.append(f"{runner_id} wall-time or full-process memory evidence is missing")
+        for key, source_key, seed_offset in (
+            ("process_wall_seconds", "process_wall_seconds", 0),
+            ("process_peak_rss_mb", "process_peak_rss_mb", 1),
+        ):
+            seed = int(hashlib.sha256(runner_id.encode()).hexdigest()[:8], 16) + seed_offset
+            if runner.get(key) != _summary(samples, source_key, seed=seed):
+                failures.append(f"{runner_id} {key} summary differs")
+        engine_samples = [
+            {"value": sample["stages_seconds"]["adapter_reported_engine"]} for sample in samples
+        ]
+        seed = int(hashlib.sha256(runner_id.encode()).hexdigest()[:8], 16) + 2
+        if runner.get("adapter_engine_seconds") != _summary(engine_samples, "value", seed=seed):
+            failures.append(f"{runner_id} engine summary differs")
+        if runner.get("passed") is not True:
+            failures.append(f"{runner_id} did not pass")
+
+    controlled = report.get("controlled")
+    pairs = controlled.get("pairs") if isinstance(controlled, dict) else None
+    if not isinstance(pairs, dict) or set(pairs) != set(scale.FRAMEWORKS):
+        failures.append("Controlled performance pair coverage differs")
+    else:
+        for framework, pair in pairs.items():
+            external = runners[f"{framework}:external"]
+            ml4t = runners[f"{framework}:ml4t"]
+            if (
+                pair.get("passed") is not True
+                or pair.get("exact_output") is not True
+                or external.get("output") != ml4t.get("output")
+            ):
+                failures.append(f"{framework} controlled performance output differs")
+    if not isinstance(controlled, dict) or controlled.get("passed") is not True:
+        failures.append("Controlled performance track did not pass")
+
+    idiomatic = report.get("idiomatic")
+    idiomatic_runners = idiomatic.get("runners") if isinstance(idiomatic, dict) else None
+    if (
+        not isinstance(idiomatic, dict)
+        or idiomatic.get("equivalence_claim") is not False
+        or idiomatic.get("passed") is not True
+        or not isinstance(idiomatic_runners, dict)
+        or set(idiomatic_runners) != set(IDIOMATIC_RUNNERS)
+    ):
+        failures.append("Idiomatic performance track is incomplete")
+    else:
+        for name, runner_id in IDIOMATIC_RUNNERS.items():
+            entry = idiomatic_runners[name]
+            if (
+                entry.get("sample_source") != runner_id
+                or entry.get("semantic_disclosure") != IDIOMATIC_DISCLOSURES[name]
+                or entry.get("invariants_passed") is not True
+            ):
+                failures.append(f"{name} idiomatic disclosure differs")
+    if report.get("capability_matrix") != _capability_matrix():
+        failures.append("Performance capability matrix differs")
+    if report.get("release_gate_passed") is not True:
+        failures.append("Performance release gate did not pass")
+    return failures
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--worker", choices=tuple(RUNNERS_BY_ID))
+    parser.add_argument("--calibration-worker", action="store_true")
+    parser.add_argument("--output", type=Path)
+    parser.add_argument("--samples", type=int, default=MIN_SAMPLES)
+    parser.add_argument("--check", action="store_true")
+    args = parser.parse_args()
+    if args.worker:
+        if args.output is None:
+            parser.error("--worker requires --output")
+        _write_json(args.output, run_worker(RUNNERS_BY_ID[args.worker]))
+        return 0
+    if args.calibration_worker:
+        if args.output is None:
+            parser.error("--calibration-worker requires --output")
+        _write_json(args.output, run_calibration_worker())
+        return 0
+    if args.check:
+        report = cast(dict[str, Any], json.loads(ACCEPTED_PATH.read_text(encoding="utf-8")))
+        failures = report_failures(report)
+        for failure in failures:
+            print(f"- {failure}")
+        return 1 if failures else 0
+    candidate = collect_evidence(args.samples)
+    _write_json(CANDIDATE_PATH, candidate)
+    failures = report_failures(candidate)
+    if failures:
+        print("Accepted performance evidence unchanged:")
+        for failure in failures:
+            print(f"- {failure}")
+        return 1
+    _write_json_atomic(ACCEPTED_PATH, candidate)
+    print(f"Accepted performance evidence: {ACCEPTED_PATH}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/environments/backtrader/pyproject.toml b/validation/environments/backtrader/pyproject.toml
new file mode 100644
index 00000000..0d85ce03
--- /dev/null
+++ b/validation/environments/backtrader/pyproject.toml
@@ -0,0 +1,11 @@
+[project]
+name = "ml4t-backtest-validation-backtrader"
+version = "0.0.0"
+requires-python = ">=3.12,<3.13"
+dependencies = ["backtrader==1.9.78.123", "ml4t-backtest"]
+
+[tool.uv]
+package = false
+
+[tool.uv.sources]
+ml4t-backtest = { path = "../../..", editable = true }
diff --git a/validation/environments/backtrader/uv.lock b/validation/environments/backtrader/uv.lock
new file mode 100644
index 00000000..d900298e
--- /dev/null
+++ b/validation/environments/backtrader/uv.lock
@@ -0,0 +1,306 @@
+version = 1
+revision = 3
+requires-python = "==3.12.*"
+resolution-markers = [
+    "sys_platform == 'win32'",
+    "sys_platform == 'emscripten'",
+    "sys_platform != 'emscripten' and sys_platform != 'win32'",
+]
+
+[[package]]
+name = "backtrader"
+version = "1.9.78.123"
+source = { registry = "https://pypi.org/simple" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/f3/ef/328c6ec332435f63b3e18febd263686b8ba07e990676a862cc8522ba38f5/backtrader-1.9.78.123-py2.py3-none-any.whl", hash = "sha256:9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd", size = 419517, upload-time = "2023-04-19T14:13:18.842Z" },
+]
+
+[[package]]
+name = "exchange-calendars"
+version = "4.13.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "korean-lunar-calendar" },
+    { name = "numpy" },
+    { name = "pandas" },
+    { name = "pyluach" },
+    { name = "toolz" },
+    { name = "tzdata" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/47/73/460b0ece4e7444e3098b7738974c822787e134578d069d3a88b4be17d50a/exchange_calendars-4.13.2.tar.gz", hash = "sha256:a9459425dd64142cd54fbc639847403c7e0c33d60fbc326c94fc1d6bd127f002", size = 4137321, upload-time = "2026-03-10T03:24:38.536Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/c8/4c/0469b40057bc9f8d9594dcc6024202626b981ae4b52dfcd304552e8e1c3a/exchange_calendars-4.13.2-py3-none-any.whl", hash = "sha256:fc5a2ad0d61b5c3a6539a3061cd4cbb55c59f4a903455cec7926e4b798919996", size = 213306, upload-time = "2026-03-10T03:24:37.055Z" },
+]
+
+[[package]]
+name = "korean-lunar-calendar"
+version = "0.4.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/d5/9f/6160e95f3934026194dc7a0b5c78fe5c6e74761830ddea3e9cfc38e3f983/korean_lunar_calendar-0.4.0.tar.gz", hash = "sha256:be56f27bc0594fdbbdf7bbe00f504a9f929a31e311bd7d9bb93561b645afade7", size = 13425, upload-time = "2026-06-15T14:19:57.163Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/c1/88/f56033b09fdca5c8c5e5fc2f3513950a05cd62caa9bd8e6d2750a887c86e/korean_lunar_calendar-0.4.0-py3-none-any.whl", hash = "sha256:c042e20de0bb702add6bec8d0f6da1ea8d3b170838e63846f70420cf341fe4e7", size = 11323, upload-time = "2026-06-15T14:19:56.089Z" },
+]
+
+[[package]]
+name = "ml4t-backtest"
+source = { editable = "../../../" }
+dependencies = [
+    { name = "ml4t-specs" },
+    { name = "numpy" },
+    { name = "pandas" },
+    { name = "pandas-market-calendars" },
+    { name = "polars" },
+    { name = "pyyaml" },
+]
+
+[package.metadata]
+requires-dist = [
+    { name = "backtrader", marker = "python_full_version < '3.15' and extra == 'comparison'", specifier = ">=1.9.0" },
+    { name = "cvxpy", marker = "extra == 'advanced'", specifier = ">=1.3.0" },
+    { name = "cvxpy", marker = "extra == 'all'", specifier = ">=1.3.0" },
+    { name = "dash", marker = "extra == 'all'", specifier = ">=2.11.0" },
+    { name = "dash", marker = "extra == 'viz'", specifier = ">=2.11.0" },
+    { name = "hypothesis", marker = "extra == 'all'", specifier = ">=6.80.0" },
+    { name = "hypothesis", marker = "extra == 'dev'", specifier = ">=6.80.0" },
+    { name = "matplotlib", marker = "extra == 'all'", specifier = ">=3.7.0" },
+    { name = "matplotlib", marker = "extra == 'viz'", specifier = ">=3.7.0" },
+    { name = "mkdocs", marker = "extra == 'all'", specifier = ">=1.6,<2" },
+    { name = "mkdocs", marker = "extra == 'docs'", specifier = ">=1.6,<2" },
+    { name = "mkdocs-material", marker = "extra == 'all'", specifier = ">=9.5.0" },
+    { name = "mkdocs-material", marker = "extra == 'docs'", specifier = ">=9.5.0" },
+    { name = "mkdocstrings", extras = ["python"], marker = "extra == 'all'", specifier = ">=0.24.0" },
+    { name = "mkdocstrings", extras = ["python"], marker = "extra == 'docs'", specifier = ">=0.24.0" },
+    { name = "ml4t-diagnostic", marker = "extra == 'all'", specifier = ">=0.1.0b4" },
+    { name = "ml4t-diagnostic", marker = "extra == 'dev'", specifier = ">=0.1.0b4" },
+    { name = "ml4t-specs", specifier = ">=0.1.2,<0.2" },
+    { name = "networkx", marker = "extra == 'advanced'", specifier = ">=3.0" },
+    { name = "networkx", marker = "extra == 'all'", specifier = ">=3.0" },
+    { name = "numpy", specifier = ">=2.3.2" },
+    { name = "pandas", marker = "python_full_version < '3.15'", specifier = ">=2.3.3" },
+    { name = "pandas", marker = "python_full_version >= '3.15'", specifier = ">=3.0.5" },
+    { name = "pandas-market-calendars", specifier = ">=5.2.4" },
+    { name = "plotly", marker = "extra == 'all'", specifier = ">=5.15.0" },
+    { name = "plotly", marker = "extra == 'viz'", specifier = ">=5.15.0" },
+    { name = "polars", specifier = ">=1.36.1" },
+    { name = "pre-commit", marker = "extra == 'all'", specifier = ">=3.3.0" },
+    { name = "pre-commit", marker = "extra == 'dev'", specifier = ">=3.3.0" },
+    { name = "pyfolio-reloaded", marker = "python_full_version < '3.15' and extra == 'comparison'", specifier = ">=0.9.9" },
+    { name = "pytest", marker = "extra == 'all'", specifier = ">=7.4.0" },
+    { name = "pytest", marker = "extra == 'dev'", specifier = ">=7.4.0" },
+    { name = "pytest-asyncio", marker = "extra == 'all'", specifier = ">=0.21.0" },
+    { name = "pytest-asyncio", marker = "extra == 'dev'", specifier = ">=0.21.0" },
+    { name = "pytest-benchmark", marker = "extra == 'all'", specifier = ">=4.0.0" },
+    { name = "pytest-benchmark", marker = "extra == 'dev'", specifier = ">=4.0.0" },
+    { name = "pytest-cov", marker = "extra == 'all'", specifier = ">=4.1.0" },
+    { name = "pytest-cov", marker = "extra == 'dev'", specifier = ">=4.1.0" },
+    { name = "pytest-timeout", marker = "extra == 'all'", specifier = ">=2.1.0" },
+    { name = "pytest-timeout", marker = "extra == 'dev'", specifier = ">=2.1.0" },
+    { name = "pytest-xdist", marker = "extra == 'all'", specifier = ">=3.3.0" },
+    { name = "pytest-xdist", marker = "extra == 'dev'", specifier = ">=3.3.0" },
+    { name = "pyyaml", specifier = ">=6.0.3" },
+    { name = "ruff", marker = "extra == 'all'", specifier = ">=0.8.0" },
+    { name = "ruff", marker = "extra == 'dev'", specifier = ">=0.8.0" },
+    { name = "ty", marker = "extra == 'all'" },
+    { name = "ty", marker = "extra == 'dev'" },
+    { name = "vectorbt", marker = "python_full_version < '3.15' and extra == 'comparison'", specifier = ">=0.24.0" },
+    { name = "zipline-reloaded", marker = "python_full_version < '3.15' and extra == 'comparison'", specifier = ">=2.4.0" },
+]
+provides-extras = ["advanced", "all", "comparison", "dev", "docs", "viz"]
+
+[package.metadata.requires-dev]
+dev = [
+    { name = "hypothesis", specifier = ">=6.80.0" },
+    { name = "ml4t-diagnostic", specifier = ">=0.1.0b4" },
+    { name = "pre-commit", specifier = ">=3.3.0" },
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diff --git a/validation/framework_targets.toml b/validation/framework_targets.toml
new file mode 100644
index 00000000..8bc16c42
--- /dev/null
+++ b/validation/framework_targets.toml
@@ -0,0 +1,95 @@
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+access = "public"
+source = "https://pypi.org/project/backtrader/1.9.78.123/"
+immutable_id = "sha256:9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd"
+artifact = "backtrader-1.9.78.123-py2.py3-none-any.whl"
+environment = ".venv-backtrader"
+python_env_var = "ML4T_BACKTRADER_PYTHON"
+scenario_matrix = true
+required_scenarios = 17
+unsupported_scenarios = 0
+
+[framework.zipline]
+display_name = "Zipline Reloaded"
+package = "zipline-reloaded"
+version = "3.1.1"
+profile = "zipline_strict"
+python = ">=3.10"
+license = "Apache-2.0"
+access = "public"
+source = "https://pypi.org/project/zipline-reloaded/3.1.1/"
+source_commit = "09885a2ebc7567d40942c891b3879dc03c745070"
+immutable_id = "sha256:4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f"
+artifact = "zipline_reloaded-3.1.1.tar.gz"
+environment = ".venv-zipline"
+python_env_var = "ML4T_ZIPLINE_PYTHON"
+scenario_matrix = true
+required_scenarios = 16
+unsupported_scenarios = 1
+
+[framework.lean]
+display_name = "LEAN"
+package = "lean"
+version = "18001"
+profile = "lean"
+python = "3.11"
+license = "Apache-2.0"
+access = "public"
+source = "https://github.com/QuantConnect/Lean"
+source_commit = "278fcb3d1b815b63ccadba68d7ae54422e34b792"
+immutable_id = "sha256:ecd62b0e418d40d1d7c0cd95e90a94e397642a21d2c8810614830c8a4e9a8f70"
+artifact = "quantconnect/lean@sha256:ecd62b0e418d40d1d7c0cd95e90a94e397642a21d2c8810614830c8a4e9a8f70"
+platform_artifact = "linux/amd64@sha256:cbe3f26b3f16c57be836b2cf913253d434f58e010c84ed038360d26b9df88307"
+cli_version = "1.0.228"
+cli_immutable_id = "sha256:eaa4c08f16295b76f005e429d9ca0d0453784dc1a40c1f5cbe5e50c02a05bd7c"
+environment = ".venv-lean"
+python_env_var = "ML4T_LEAN_PYTHON"
+scenario_matrix = false
+required_scenarios = 0
+unsupported_scenarios = 0
diff --git a/validation/frameworks/backtrader.py b/validation/frameworks/backtrader.py
index 55069414..32c19ffa 100644
--- a/validation/frameworks/backtrader.py
+++ b/validation/frameworks/backtrader.py
@@ -1,6 +1,6 @@
 """Backtrader framework driver for validation scenarios.
 
-Consolidates 16 run_backtrader() functions into a single parameterized driver.
+Provides one parameterized driver for the scenario matrix.
 
 Backtrader always uses next-bar execution (orders placed on bar N fill at bar N+1's open).
 """
@@ -16,9 +16,21 @@
 import pandas as pd
 
 sys.path.insert(0, str(Path(__file__).parent.parent))
+from common.capabilities import FRAMEWORK_CAPABILITIES
 from common.types import FrameworkResult, ScenarioConfig
 
 
+def _completed_fill(order: Any, bt: Any) -> dict[str, object]:
+    return {
+        "timestamp": bt.num2date(order.executed.dt),
+        "asset": "TEST",
+        "side": "buy" if order.isbuy() else "sell",
+        "quantity": abs(float(order.executed.size)),
+        "price": float(order.executed.price),
+        "commission": abs(float(order.executed.comm)),
+    }
+
+
 def run(
     scenario: ScenarioConfig,
     prices_df: pd.DataFrame,
@@ -102,6 +114,7 @@ class PandasData(bt.feeds.PandasData):
     trade_list = []
     if hasattr(strategy, "trade_log"):
         trade_list = sorted(strategy.trade_log, key=lambda t: t.get("entry_time", 0))
+    fill_list = getattr(strategy, "fill_log", [])
 
     extra = {}
     if hasattr(strategy, "total_commission"):
@@ -125,6 +138,8 @@ class PandasData(bt.feeds.PandasData):
         total_pnl=final_value - scenario.initial_cash,
         num_trades=len(trade_list),
         trades=trade_list,
+        fills=fill_list,
+        capabilities=FRAMEWORK_CAPABILITIES["backtrader"],
         extra=extra,
     )
 
@@ -152,6 +167,7 @@ class SignalStrategy(bt.Strategy):
         def __init__(self):
             self.bar_count = 0
             self.trade_log = []
+            self.fill_log = []
             self.total_commission = 0.0
             self.pending_trade = None
 
@@ -186,6 +202,7 @@ def notify_trade(self, trade):
                     {
                         "entry_time": self.pending_trade["entry_time"],
                         "exit_time": bt.num2date(trade.dtclose),
+                        "asset": "TEST",
                         "entry_price": self.pending_trade["entry_price"],
                         "exit_price": exit_price,
                         "gross_pnl": trade.pnl,
@@ -200,6 +217,7 @@ def notify_trade(self, trade):
 
         def notify_order(self, order):
             if order.status == order.Completed:
+                self.fill_log.append(_completed_fill(order, bt))
                 self.total_commission += order.executed.comm
 
     return SignalStrategy
@@ -215,6 +233,7 @@ class ShortStrategy(bt.Strategy):
         def __init__(self):
             self.bar_count = 0
             self.trade_log = []
+            self.fill_log = []
             self.pending_trade = None
 
         def next(self):
@@ -255,16 +274,22 @@ def notify_trade(self, trade):
                     {
                         "entry_time": self.pending_trade["entry_time"],
                         "exit_time": bt.num2date(trade.dtclose),
+                        "asset": "TEST",
                         "entry_price": self.pending_trade["entry_price"],
                         "exit_price": exit_price,
                         "size": abs(entry_size),
                         "gross_pnl": trade.pnl,
                         "pnl": trade.pnlcomm,
                         "direction": "Short" if entry_size < 0 else "Long",
+                        "commission": trade.commission,
                     }
                 )
                 self.pending_trade = None
 
+        def notify_order(self, order):
+            if order.status == order.Completed:
+                self.fill_log.append(_completed_fill(order, bt))
+
     return ShortStrategy
 
 
@@ -297,6 +322,7 @@ class RiskEntryStrategy(bt.Strategy):
         def __init__(self):
             self.bar_count = 0
             self.trade_log = []
+            self.fill_log = []
             self.entered_once = False
             self.entry_order = None
             self.exit_orders = []
@@ -423,18 +449,22 @@ def notify_trade(self, trade):
                     {
                         "entry_time": self.pending_trade["entry_time"],
                         "exit_time": bt.num2date(trade.dtclose),
+                        "asset": "TEST",
                         "entry_price": self.pending_trade["entry_price"],
                         "exit_price": exit_price,
                         "size": abs(entry_size),
                         "gross_pnl": trade.pnl,
                         "pnl": trade.pnlcomm,
                         "direction": "Short" if entry_size < 0 else "Long",
+                        "commission": trade.commission,
                     }
                 )
                 self.pending_trade = None
                 self.exit_orders = []
 
         def notify_order(self, order):
+            if order.status == order.Completed:
+                self.fill_log.append(_completed_fill(order, bt))
             if order.status == order.Completed and order == self.entry_order:
                 # Entry filled — now submit deferred trailing stop
                 self.entry_order = None
diff --git a/validation/frameworks/vectorbt_oss.py b/validation/frameworks/vectorbt_oss.py
index 9994c0b7..9e4cfcd4 100644
--- a/validation/frameworks/vectorbt_oss.py
+++ b/validation/frameworks/vectorbt_oss.py
@@ -1,6 +1,6 @@
 """VectorBT OSS framework driver for validation scenarios.
 
-Consolidates 16 run_vectorbt_oss() functions into a single parameterized driver.
+Provides one parameterized driver for the scenario matrix.
 
 VectorBT OSS uses same-bar execution with close fills by default.
 """
@@ -14,6 +14,8 @@
 import pandas as pd
 
 sys.path.insert(0, str(Path(__file__).parent.parent))
+from common.canonical_records import vectorbt_fills, vectorbt_trades
+from common.capabilities import FRAMEWORK_CAPABILITIES
 from common.types import FrameworkResult, ScenarioConfig
 
 
@@ -38,7 +40,7 @@ def run(
         import vectorbt as vbt
     except ImportError:
         raise ImportError(
-            "VectorBT OSS not installed. Run in .venv-vectorbt environment."
+            "VectorBT OSS not installed. Run in .venv-vectorbt-oss environment."
         ) from None
 
     constants = scenario.constants
@@ -119,29 +121,9 @@ def run(
 
     trade_list = trades.to_dict("records") if len(trades) > 0 else []
     order_list = pf.orders.records_readable.to_dict("records")
-    # Normalize trade dict keys for comparison
-    normalized_trades = []
-    for index, t in enumerate(trade_list):
-        entry_order = order_list[index * 2] if index * 2 < len(order_list) else {}
-        exit_order = order_list[index * 2 + 1] if index * 2 + 1 < len(order_list) else {}
-        size = float(t.get("Size", scenario.shares))
-        direction = t.get("Direction", "Long")
-        entry_price = float(
-            entry_order.get("Price", t.get("Avg Entry Price", t.get("Entry Price", 0)))
-        )
-        exit_price = float(exit_order.get("Price", t.get("Avg Exit Price", t.get("Exit Price", 0))))
-        direction_sign = -1.0 if str(direction).lower() == "short" else 1.0
-        fees = abs(float(entry_order.get("Fees", t.get("Entry Fees", 0)))) + abs(
-            float(exit_order.get("Fees", t.get("Exit Fees", 0)))
-        )
-        normalized = {
-            "entry_price": entry_price,
-            "exit_price": exit_price,
-            "pnl": (exit_price - entry_price) * size * direction_sign - fees,
-            "size": size,
-            "direction": direction,
-        }
-        normalized_trades.append(normalized)
+    asset = str(scenario.constants.get("asset", "TEST"))
+    normalized_trades = vectorbt_trades(trade_list, asset=asset)
+    normalized_fills = vectorbt_fills(order_list, asset=asset)
 
     extra = {}
     if "commission" in scenario.extra_checks:
@@ -157,5 +139,7 @@ def run(
         total_pnl=final_value - scenario.initial_cash,
         num_trades=len(trades),
         trades=normalized_trades,
+        fills=normalized_fills,
+        capabilities=FRAMEWORK_CAPABILITIES["vectorbt_oss"],
         extra=extra,
     )
diff --git a/validation/frameworks/vectorbt_pro.py b/validation/frameworks/vectorbt_pro.py
index 15e8a427..b1d0e61a 100644
--- a/validation/frameworks/vectorbt_pro.py
+++ b/validation/frameworks/vectorbt_pro.py
@@ -1,6 +1,6 @@
 """VectorBT Pro framework driver for validation scenarios.
 
-Consolidates 17 run_vectorbt_pro() functions into a single parameterized driver.
+Provides one parameterized driver for the scenario matrix.
 
 VectorBT Pro uses same-bar execution with close fills by default.
 Licensed software; guarded by try/except ImportError.
@@ -16,9 +16,11 @@
 import pandas as pd
 
 sys.path.insert(0, str(Path(__file__).parent.parent))
+from common.canonical_records import vectorbt_fills, vectorbt_trades
+from common.capabilities import FRAMEWORK_CAPABILITIES
 from common.types import FrameworkResult, ScenarioConfig
 
-SUPPORTED_VECTORBT_PRO_VERSION = "2025.12.31"
+SUPPORTED_VECTORBT_PRO_VERSION = "2026.6.27"
 
 
 def _require_supported_version(actual_version: str) -> None:
@@ -125,28 +127,9 @@ def run(
 
     trade_list = trades.to_dict("records") if len(trades) > 0 else []
     order_list = pf.orders.records_readable.to_dict("records")
-    normalized_trades = []
-    for index, t in enumerate(trade_list):
-        entry_order = order_list[index * 2] if index * 2 < len(order_list) else {}
-        exit_order = order_list[index * 2 + 1] if index * 2 + 1 < len(order_list) else {}
-        size = float(t.get("Size", scenario.shares))
-        direction = t.get("Direction", "Long")
-        entry_price = float(
-            entry_order.get("Price", t.get("Avg Entry Price", t.get("Entry Price", 0)))
-        )
-        exit_price = float(exit_order.get("Price", t.get("Avg Exit Price", t.get("Exit Price", 0))))
-        direction_sign = -1.0 if str(direction).lower() == "short" else 1.0
-        fees = abs(float(entry_order.get("Fees", t.get("Entry Fees", 0)))) + abs(
-            float(exit_order.get("Fees", t.get("Exit Fees", 0)))
-        )
-        normalized = {
-            "entry_price": entry_price,
-            "exit_price": exit_price,
-            "pnl": (exit_price - entry_price) * size * direction_sign - fees,
-            "size": size,
-            "direction": direction,
-        }
-        normalized_trades.append(normalized)
+    asset = str(scenario.constants.get("asset", "TEST"))
+    normalized_trades = vectorbt_trades(trade_list, asset=asset)
+    normalized_fills = vectorbt_fills(order_list, asset=asset)
 
     extra = {}
     if "commission" in scenario.extra_checks:
@@ -161,5 +144,7 @@ def run(
         total_pnl=final_value - scenario.initial_cash,
         num_trades=len(trades),
         trades=normalized_trades,
+        fills=normalized_fills,
+        capabilities=FRAMEWORK_CAPABILITIES["vectorbt_pro"],
         extra=extra,
     )
diff --git a/validation/frameworks/zipline.py b/validation/frameworks/zipline.py
index 089eeb3c..6d1552aa 100644
--- a/validation/frameworks/zipline.py
+++ b/validation/frameworks/zipline.py
@@ -1,6 +1,6 @@
 """Zipline framework driver for validation scenarios.
 
-Consolidates 15 run_zipline() functions into a single parameterized driver.
+Provides one parameterized driver for the scenario matrix.
 
 Zipline uses next-bar execution with open fills. Requires:
 - exchange_calendars for NYSE trading calendar dates
@@ -17,6 +17,8 @@
 import pandas as pd
 
 sys.path.insert(0, str(Path(__file__).parent.parent))
+from common.canonical_records import zipline_fills
+from common.capabilities import FRAMEWORK_CAPABILITIES
 from common.types import FrameworkResult, ScenarioConfig
 
 from ml4t.backtest._validation.zipline_runner import (
@@ -221,8 +223,10 @@ def analyze(context, perf):
     for trade in trade_list:
         trade["entry_time"] = trade.pop("entry_date")
         trade["exit_time"] = trade.pop("exit_date")
+        trade["asset"] = "TEST"
         trade["size"] = trade.pop("quantity")
         trade["direction"] = str(trade.pop("side")).title()
+        trade_commission = 0.0
         if "commission_rate" in constants:
             trade_commission = (
                 constants["commission_rate"]
@@ -235,7 +239,14 @@ def analyze(context, perf):
             trade_commission = constants["per_share_rate"] * float(trade["size"]) * 2
             total_commission += trade_commission
             trade["pnl"] = float(trade["pnl"]) - trade_commission
+        trade["commission"] = trade_commission
     num_trades = len(trade_list)
+    fill_list = zipline_fills(
+        transactions,
+        asset="TEST",
+        commission_rate=float(constants.get("commission_rate", 0.0)),
+        per_share_rate=float(constants.get("per_share_rate", 0.0)),
+    )
 
     extra = {}
     if "commission" in scenario.extra_checks:
@@ -249,6 +260,8 @@ def analyze(context, perf):
         total_pnl=final_value - scenario.initial_cash,
         num_trades=num_trades,
         trades=trade_list,
+        fills=fill_list,
+        capabilities=FRAMEWORK_CAPABILITIES["zipline"],
         extra=extra,
     )
 
diff --git a/validation/generate_parity_claims.py b/validation/generate_parity_claims.py
index 3b38410a..5008d48a 100644
--- a/validation/generate_parity_claims.py
+++ b/validation/generate_parity_claims.py
@@ -8,9 +8,15 @@
 from pathlib import Path
 from typing import Any
 
+from common.correctness_evidence import correctness_report_failures
+from common.framework_registry import load_framework_manifest
+from large_scale_evidence import report_failures as large_scale_report_failures
+from scenarios.definitions import SCENARIOS
+
 PROJECT_ROOT = Path(__file__).parent.parent
 CORRECTNESS_EVIDENCE = PROJECT_ROOT / "validation" / "CORRECTNESS_RESULTS.json"
-LARGE_SCALE_EVIDENCE = PROJECT_ROOT / "validation" / "vectorbt_pro" / "large_scale_parity.json"
+LARGE_SCALE_EVIDENCE = PROJECT_ROOT / "validation" / "LARGE_SCALE_RESULTS.json"
+REAL_STRATEGY_EVIDENCE = PROJECT_ROOT / "validation" / "REAL_STRATEGY_RESULTS.json"
 TARGETS = (
     PROJECT_ROOT / "README.md",
     PROJECT_ROOT / "docs" / "index.md",
@@ -21,6 +27,7 @@
 START_MARKER = "<!-- parity-claims:start -->"
 END_MARKER = "<!-- parity-claims:end -->"
 GITHUB_EVIDENCE_ROOT = "https://github.com/ml4t/backtest/blob/main/validation"
+SCENARIO_FRAMEWORKS = load_framework_manifest().scenario_framework_ids
 
 
 def _load_json(path: Path) -> dict[str, Any]:
@@ -30,32 +37,72 @@ def _load_json(path: Path) -> dict[str, Any]:
     return payload
 
 
-def _validate_evidence(correctness: dict[str, Any], large_scale: dict[str, Any]) -> None:
+def _validate_evidence(
+    correctness: dict[str, Any],
+    large_scale: dict[str, Any],
+    real_strategy: dict[str, Any],
+) -> None:
+    failures = correctness_report_failures(correctness)
+    if failures:
+        raise ValueError("Accepted correctness evidence is invalid: " + "; ".join(failures))
     frameworks = correctness.get("frameworks")
     records = correctness.get("records")
     if not isinstance(frameworks, dict) or not isinstance(records, list):
         raise ValueError("Correctness evidence lacks framework pins or records")
-    expected = {"vectorbt_pro", "vectorbt_oss", "backtrader", "zipline"}
+    expected = set(SCENARIO_FRAMEWORKS)
     if set(frameworks) != expected:
         raise ValueError("Correctness evidence does not cover the required framework matrix")
     for framework in expected:
         framework_records = [record for record in records if record.get("framework") == framework]
-        if len(framework_records) != 16:
-            raise ValueError(f"Expected 16 retained records for {framework}")
-    if large_scale.get("exact_comparison", {}).get("passed") is not True:
-        raise ValueError("Large-scale evidence is not an exact canonical pass")
+        if len(framework_records) != len(SCENARIOS):
+            raise ValueError(f"Expected {len(SCENARIOS)} retained records for {framework}")
+    scale_failures = large_scale_report_failures(large_scale)
+    if scale_failures:
+        raise ValueError("Accepted large-scale evidence is invalid: " + "; ".join(scale_failures))
+    scope = real_strategy.get("scope")
+    real_records = real_strategy.get("records")
+    if (
+        real_strategy.get("schema_version") != 1
+        or not isinstance(scope, dict)
+        or not isinstance(real_records, list)
+    ):
+        raise ValueError("Real-strategy evidence is malformed")
+    if scope.get("required_pairs") != 8 or scope.get("unsupported_pairs") != 7:
+        raise ValueError("Real-strategy evidence does not cover the declared applicability matrix")
+    required = [record for record in real_records if record.get("status") != "unsupported"]
+    if len(required) != 8:
+        raise ValueError("Real-strategy evidence lacks required pair records")
+    if not all(record.get("negative_control", {}).get("detected") is True for record in required):
+        raise ValueError("Real-strategy evidence lacks a passing negative control")
+
 
+def _comparison_checks(record: dict[str, Any]) -> dict[str, dict[str, Any]]:
+    comparison = record.get("comparison")
+    if not isinstance(comparison, dict) or not isinstance(comparison.get("checks"), list):
+        raise ValueError(f"Large-scale comparison checks are missing: {record.get('framework')}")
+    return {
+        str(check["name"]): check
+        for check in comparison["checks"]
+        if isinstance(check, dict) and "name" in check
+    }
 
-def render_claims(correctness: dict[str, Any], large_scale: dict[str, Any]) -> str:
+
+def render_claims(
+    correctness: dict[str, Any],
+    large_scale: dict[str, Any],
+    real_strategy: dict[str, Any],
+) -> str:
     """Render the canonical documentation block."""
-    _validate_evidence(correctness, large_scale)
+    _validate_evidence(correctness, large_scale, real_strategy)
     frameworks = correctness["frameworks"]
     records = correctness["records"]
     correctness_url = f"{GITHUB_EVIDENCE_ROOT}/CORRECTNESS_RESULTS.json"
-    large_scale_url = f"{GITHUB_EVIDENCE_ROOT}/vectorbt_pro/large_scale_parity.json"
+    large_scale_url = f"{GITHUB_EVIDENCE_ROOT}/LARGE_SCALE_RESULTS.json"
+    real_strategy_url = f"{GITHUB_EVIDENCE_ROOT}/REAL_STRATEGY_RESULTS.json"
+    real_performance_url = f"{GITHUB_EVIDENCE_ROOT}/REAL_STRATEGY_PERFORMANCE.json"
 
     rows = []
-    for framework in ("vectorbt_pro", "vectorbt_oss", "backtrader", "zipline"):
+    for framework in SCENARIO_FRAMEWORKS:
         pin = frameworks[framework]
         framework_records = [record for record in records if record["framework"] == framework]
         required = [record for record in framework_records if record["required"]]
@@ -72,35 +119,97 @@ def render_claims(correctness: dict[str, Any], large_scale: dict[str, Any]) -> s
             f"[scenario evidence]({correctness_url}) |"
         )
 
-    comparison = large_scale["exact_comparison"]
-    reference = large_scale["reference"]
-    large_row = (
-        f"| `vectorbt_strict` | VectorBT Pro {reference['version']} "
-        f"(`{reference['git_commit'][:12]}`) | {comparison['trades']['count']:,} trades | "
-        f"0 | {comparison['terminal_value']['reference_canonical']:.6f} | "
-        f"[large-scale evidence]({large_scale_url}) |"
-    )
+    scale_rows = []
+    for record in large_scale["frameworks"]:
+        target = record["target"]
+        checks = _comparison_checks(record)
+        intents = checks["order_intents"]["expected_count"]
+        fills = checks["fills"]["expected_count"]
+        trades = checks["trades"]["expected_count"]
+        terminal_value = checks["final_value"]["canonical_expected"]
+        pinned_framework = f"[{target['display_name']} {target['version']}]({target['source']})"
+        scale_rows.append(
+            f"| `{target['profile']}` | {pinned_framework} | {intents:,} | {fills:,} | "
+            f"{trades:,} | {terminal_value:,.6f} | "
+            f"[scale evidence]({large_scale_url}) |"
+        )
+
+    workload = large_scale["workload"]
+    recipe = workload["recipe"]
+    real_rows = []
+    required_real = [
+        record for record in real_strategy["records"] if record["status"] != "unsupported"
+    ]
+    passed_real = sum(record["status"] == "pass" for record in required_real)
+    real_targets = real_strategy["provenance"]["frameworks"]
+    case_labels = {
+        "etfs": "ETF allocation",
+        "cme_futures": "CME futures",
+        "crypto_perps_funding": "Crypto perpetual funding",
+    }
+    for record in required_real:
+        target = real_targets[record["framework"]]
+        pinned_framework = f"[{target['display_name']} {target['version']}]({target['source']})"
+        fills = record["surfaces"]["fills"]
+        equity = record["surfaces"]["equity"]
+        terminal = record["surfaces"]["terminal"]
+        if record["status"] == "pass":
+            result = (
+                f"exact: {fills['framework_records']:,} fills, "
+                f"{equity['coverage']['shared_timestamps']:,} valuations, terminal"
+            )
+        else:
+            result = (
+                f"fills exact; equity gap {equity['max_canonical_difference']}; "
+                f"terminal gap {terminal['max_canonical_difference']}"
+            )
+        real_rows.append(
+            f"| {case_labels[record['case_study']]} | {pinned_framework} | {result} | "
+            f"[real-strategy evidence]({real_strategy_url}) |"
+        )
 
     return "\n".join(
         [
             START_MARKER,
             "<!-- Generated by validation/generate_parity_claims.py. Do not edit by hand. -->",
             "",
-            'Scenario claims use the retained release-candidate matrix. "Exact" appears only when '
-            "every required scenario has zero canonical gap.",
+            "### Real-strategy audit",
+            "",
+            f"{passed_real}/{len(required_real)} supported pairs pass. The audit uses three "
+            "production-selected strategies with frozen historical market data and model-derived "
+            "targets. A pass requires zero numeric gap after 1e-8 quantization across every "
+            "shared valuation timestamp, the complete canonical fill stream, and terminal value. "
+            "The two CME rows retain exact fills but fail the equity and terminal checks.",
+            "",
+            "| Real strategy | Pinned framework | Current result | Evidence |",
+            "|---|---|---|---|",
+            *real_rows,
+            "",
+            f"Engine-only timing samples for the six passing pairs are retained in "
+            f"[real-strategy performance evidence]({real_performance_url}). These measurements "
+            "support only the named strategy, framework version, input bundle, and machine.",
+            "",
+            "### Synthetic diagnostic scenarios",
+            "",
+            'The scenario matrix contains synthetic conformance tests. "Exact" means terminal values, '
+            "ordered closed trades, and ordered fills match after 1e-8 quantization. Each record "
+            "declares whether a surface is native, reconstructed, aggregate-only, input-only, or "
+            "unavailable. These results test isolated conventions, not realistic strategy "
+            "equivalence.",
             "",
             "| Profile | Pinned framework | Required scenarios | Evidence |",
             "|---|---|---:|---|",
             *rows,
             "",
-            "Large-scale claims are published only when a retained workload has zero canonical gap.",
-            "",
-            "| Profile | Pinned framework | Compared | Trade gap | Terminal value | Evidence |",
-            "|---|---|---:|---:|---:|---|",
-            large_row,
+            f"The synthetic stress workload contains {recipe['assets']:,} assets and "
+            f"{recipe['bars']:,} daily sessions ({workload['data_points']:,} bars). Every row "
+            "has zero canonical gap for target intents, native fills, closed trades reconstructed "
+            "from those fills, and terminal state reconstructed from the fill ledger and final "
+            "marks.",
             "",
-            "No large-scale claim is published for Backtrader, Zipline, VectorBT OSS, or LEAN "
-            "without a passing retained artifact.",
+            "| Profile | Current framework | Target intents | Native fills | Fill-derived closed trades | Terminal value | Evidence |",
+            "|---|---|---:|---:|---:|---:|---|",
+            *scale_rows,
             END_MARKER,
         ]
     )
@@ -117,7 +226,11 @@ def replace_claims(document: str, claims: str, *, path: Path) -> str:
 
 def synchronize(*, check: bool) -> list[Path]:
     """Write generated blocks or return documents that differ from evidence."""
-    claims = render_claims(_load_json(CORRECTNESS_EVIDENCE), _load_json(LARGE_SCALE_EVIDENCE))
+    claims = render_claims(
+        _load_json(CORRECTNESS_EVIDENCE),
+        _load_json(LARGE_SCALE_EVIDENCE),
+        _load_json(REAL_STRATEGY_EVIDENCE),
+    )
     changed: list[Path] = []
     for path in TARGETS:
         current = path.read_text(encoding="utf-8")
diff --git a/validation/large_scale_evidence.py b/validation/large_scale_evidence.py
new file mode 100644
index 00000000..eba4d79e
--- /dev/null
+++ b/validation/large_scale_evidence.py
@@ -0,0 +1,877 @@
+#!/usr/bin/env python3
+"""Generate and validate reproducible cross-framework large-scale evidence."""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import importlib.metadata
+import json
+import os
+import subprocess
+import sys
+import tempfile
+from dataclasses import asdict, dataclass, replace
+from datetime import UTC, datetime
+from decimal import ROUND_HALF_EVEN, Decimal
+from functools import cache
+from pathlib import Path
+from typing import Any, cast
+
+import numpy as np
+import pandas as pd
+
+VALIDATION_DIR = Path(__file__).parent
+PROJECT_ROOT = VALIDATION_DIR.parent
+sys.path.insert(0, str(PROJECT_ROOT))
+sys.path.insert(0, str(PROJECT_ROOT / "src"))
+sys.path.insert(0, str(VALIDATION_DIR))
+
+import benchmark_suite as suite  # noqa: E402
+from common.framework_registry import FrameworkTarget, load_framework_manifest  # noqa: E402
+
+SCHEMA_VERSION = 1
+MONEY_QUANTUM = Decimal("0.000001")
+FRAMEWORKS = ("vectorbt_pro", "vectorbt_oss", "backtrader", "zipline", "lean")
+ACCEPTED_PATH = VALIDATION_DIR / "LARGE_SCALE_RESULTS.json"
+CANDIDATE_DIR = VALIDATION_DIR / "candidates"
+CANDIDATE_PATH = CANDIDATE_DIR / "LARGE_SCALE_RESULTS.candidate.json"
+HISTORICAL_ACCEPTED_PATH = VALIDATION_DIR / "vectorbt_pro" / "controlled_replay-2025.12.31.json"
+HISTORICAL_CANDIDATE_PATH = VALIDATION_DIR / "candidates" / "vectorbt_pro-2025.12.31.candidate.json"
+HISTORICAL_VECTORBT_PRO_VERSION = "2025.12.31"
+HISTORICAL_VECTORBT_PRO_COMMIT = "1305a1e1974325db9382eaeacc6452e9b075ca71"
+HISTORICAL_VECTORBT_PRO_ENV = ".venv-vectorbt-pro-312"
+HISTORICAL_VECTORBT_PRO_PYTHON_ENV_VAR = "ML4T_VECTORBT_PRO_HISTORICAL_PYTHON"
+
+
+@dataclass(frozen=True)
+class ScaleWorkload:
+    """Content-addressed public workload recipe."""
+
+    name: str = "controlled_250_assets_5040_sessions"
+    seed: int = 42
+    bars: int = 5_040
+    assets: int = 250
+    top_n: int = 25
+    bottom_n: int = 25
+    rebalance_frequency: int = 1
+    end_session: str = "2025-12-31"
+    initial_cash: float = 1_000_000.0
+    long_target_shares: float = 100.0
+    short_target_shares: float = -100.0
+
+    @property
+    def data_points(self) -> int:
+        return self.bars * self.assets
+
+    def benchmark_config(self) -> suite.BenchmarkConfig:
+        return suite.BenchmarkConfig(
+            name=self.name,
+            n_bars=self.bars,
+            n_assets=self.assets,
+            frequency="D",
+            top_n=self.top_n,
+            bottom_n=self.bottom_n,
+            rebalance_freq=self.rebalance_frequency,
+            initial_cash=self.initial_cash,
+            lean_force_zero_fee=True,
+            lean_force_zero_slippage=True,
+            end_session=self.end_session,
+        )
+
+
+WORKLOAD = ScaleWorkload()
+
+
+def _sha256_bytes(value: bytes) -> str:
+    return hashlib.sha256(value).hexdigest()
+
+
+def _json_digest(value: object) -> str:
+    return _sha256_bytes(
+        json.dumps(value, sort_keys=True, separators=(",", ":"), default=str).encode()
+    )
+
+
+def _update_array(digest: Any, label: str, values: np.ndarray) -> None:
+    array = np.ascontiguousarray(values)
+    digest.update(label.encode())
+    digest.update(array.dtype.str.encode())
+    digest.update(str(array.shape).encode())
+    digest.update(array.tobytes())
+
+
+def _datetime_ns(index: pd.DatetimeIndex) -> np.ndarray:
+    normalized = index.tz_convert("UTC").tz_localize(None) if index.tz is not None else index
+    return normalized.to_numpy(dtype="datetime64[ns]").view("<i8")
+
+
+def input_digest(
+    price_data: dict[str, pd.DataFrame],
+    signals: pd.DataFrame,
+    dates: pd.DatetimeIndex,
+) -> str:
+    """Hash every generated input value independently of pandas internals."""
+    digest = hashlib.sha256()
+    _update_array(digest, "dates", _datetime_ns(dates))
+    for asset in sorted(price_data):
+        frame = price_data[asset]
+        digest.update(asset.encode())
+        _update_array(digest, "index", _datetime_ns(pd.DatetimeIndex(frame.index)))
+        for column in ("open", "high", "low", "close", "volume"):
+            _update_array(digest, column, frame[column].to_numpy())
+    signal_dates = pd.DatetimeIndex(pd.to_datetime(signals["timestamp"]))
+    _update_array(digest, "signal_dates", _datetime_ns(signal_dates))
+    digest.update("\0".join(signals["asset"].astype(str)).encode())
+    _update_array(digest, "scores", signals["score"].to_numpy())
+    return digest.hexdigest()
+
+
+def _effective_prices(
+    framework: str, price_data: dict[str, pd.DataFrame]
+) -> dict[str, pd.DataFrame]:
+    decimals = 3 if framework == "zipline" else 4 if framework == "lean" else None
+    if decimals is None:
+        return price_data
+    effective: dict[str, pd.DataFrame] = {}
+    for asset, frame in price_data.items():
+        converted = frame.copy()
+        converted.loc[:, ["open", "high", "low", "close"]] = converted[
+            ["open", "high", "low", "close"]
+        ].round(decimals)
+        effective[asset] = converted
+    return effective
+
+
+def _canonical_money(value: float) -> float:
+    return float(Decimal(str(value)).quantize(MONEY_QUANTUM, rounding=ROUND_HALF_EVEN))
+
+
+def _float_value(value: object) -> float:
+    if not isinstance(value, (int, float)) or isinstance(value, bool):
+        raise TypeError(f"Expected a numeric canonical value, got {type(value).__name__}")
+    return float(value)
+
+
+def _terminal_state(
+    result: suite.BenchmarkResult,
+    effective_prices: dict[str, pd.DataFrame],
+    initial_cash: float,
+) -> dict[str, object]:
+    fills = suite.canonical_fill_records(result.fills_df, timestamp_domain="session_date") or []
+    positions: dict[str, float] = {}
+    cash = initial_cash
+    for fill in fills:
+        quantity = _float_value(fill["quantity"])
+        signed = quantity if fill["side"] == "buy" else -quantity
+        asset = str(fill["asset"])
+        positions[asset] = positions.get(asset, 0.0) + signed
+        cash -= signed * _float_value(fill["price"])
+        cash -= _float_value(fill["commission"])
+    positions = {asset: quantity for asset, quantity in sorted(positions.items()) if quantity != 0}
+    holdings = sum(
+        quantity * float(effective_prices[asset]["close"].iloc[-1])
+        for asset, quantity in positions.items()
+    )
+    state = {
+        "cash_from_fill_ledger": _canonical_money(cash),
+        "holdings_from_fill_ledger": _canonical_money(holdings),
+        "positions": {asset: _canonical_money(quantity) for asset, quantity in positions.items()},
+        "reported_final_value": _canonical_money(result.final_value),
+    }
+    state["sha256"] = _json_digest(state)
+    return state
+
+
+def _source_digests() -> dict[str, str]:
+    paths = {
+        "benchmark_suite": VALIDATION_DIR / "benchmark_suite.py",
+        "framework_manifest": VALIDATION_DIR / "framework_targets.toml",
+        "large_scale_runner": Path(__file__),
+        "profiles": PROJECT_ROOT / "src" / "ml4t" / "backtest" / "profiles.py",
+    }
+    return {name: _sha256_bytes(path.read_bytes()) for name, path in paths.items()}
+
+
+def _git_identity() -> dict[str, object]:
+    commit = subprocess.run(
+        ["git", "rev-parse", "HEAD"],
+        cwd=PROJECT_ROOT,
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout.strip()
+    status = subprocess.run(
+        ["git", "status", "--porcelain", "--untracked-files=no"],
+        cwd=PROJECT_ROOT,
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout.strip()
+    return {"commit": commit, "dirty": bool(status)}
+
+
+def _actual_target(target: FrameworkTarget) -> dict[str, object]:
+    if target.package == "lean":
+        actual_version = target.version
+    else:
+        actual_version = importlib.metadata.version(target.package)
+    metadata = {**target.evidence_metadata(), "actual_version": actual_version}
+    if target.package == "vectorbtpro":
+        distribution = importlib.metadata.distribution(target.package)
+        direct_url_text = distribution.read_text("direct_url.json")
+        if direct_url_text is None:
+            raise RuntimeError("Installed vectorbtpro lacks direct_url.json source provenance")
+        direct_url = json.loads(direct_url_text)
+        vcs_info = direct_url.get("vcs_info", {})
+        actual_commit = vcs_info.get("commit_id")
+        if actual_commit != target.source_commit:
+            raise RuntimeError(
+                f"Installed vectorbtpro commit {actual_commit!r} does not match declared target "
+                f"{target.source_commit!r}"
+            )
+        metadata["actual_commit"] = actual_commit
+        metadata["actual_immutable_id"] = f"git:{actual_commit}"
+    return metadata
+
+
+def _declared_target_metadata(target: dict[str, Any]) -> dict[str, Any]:
+    return {key: value for key, value in target.items() if not key.startswith("actual_")}
+
+
+def _framework_run(
+    framework: str,
+    config: suite.BenchmarkConfig,
+    price_data: dict[str, pd.DataFrame],
+    signals: pd.DataFrame,
+    dates: pd.DatetimeIndex,
+) -> tuple[suite.BenchmarkResult, suite.BenchmarkResult]:
+    if framework == "vectorbt_pro":
+        external = suite.benchmark_vectorbt_pro(config, price_data, signals, dates)
+        ml4t = suite.benchmark_ml4t(
+            config,
+            price_data,
+            signals,
+            dates,
+            execution_mode="same_bar",
+            profile_override="vectorbt_strict",
+        )
+    elif framework == "vectorbt_oss":
+        external = suite.benchmark_vectorbt_oss(config, price_data, signals, dates)
+        ml4t = suite.benchmark_ml4t(
+            config,
+            price_data,
+            signals,
+            dates,
+            execution_mode="same_bar",
+            profile_override="vectorbt_oss_strict",
+        )
+    elif framework == "backtrader":
+        external = suite.benchmark_backtrader(config, price_data, signals, dates)
+        ml4t = suite.benchmark_ml4t(
+            config,
+            price_data,
+            signals,
+            dates,
+            execution_mode="next_bar",
+            profile_override="backtrader_strict",
+        )
+    elif framework == "zipline":
+        external = suite.benchmark_zipline(config, price_data, signals, dates)
+        ml4t = suite.benchmark_ml4t(
+            config,
+            price_data,
+            signals,
+            dates,
+            execution_mode="next_bar",
+            profile_override="zipline_strict",
+        )
+    elif framework == "lean":
+        external = suite.benchmark_lean(config, price_data, signals, dates)
+        ml4t = suite.benchmark_ml4t(
+            config,
+            price_data,
+            signals,
+            dates,
+            execution_mode="next_bar",
+            profile_override="lean",
+        )
+    else:
+        raise ValueError(f"Unknown scale framework: {framework}")
+    return external, ml4t
+
+
+def _use_canonical_fill_backed_trades(
+    external: suite.BenchmarkResult,
+    ml4t: suite.BenchmarkResult,
+) -> None:
+    for result in (external, ml4t):
+        result.trades_df = suite.closed_trades_from_fills(result.fills_df)
+        records = suite.canonical_trade_records(result.trades_df)
+        result.num_trades = len(records) if records is not None else 0
+
+
+def _historical_vectorbt_pro_target() -> FrameworkTarget:
+    current = load_framework_manifest().targets["vectorbt_pro"]
+    return replace(
+        current,
+        version=HISTORICAL_VECTORBT_PRO_VERSION,
+        source_commit=HISTORICAL_VECTORBT_PRO_COMMIT,
+        immutable_id=f"git:{HISTORICAL_VECTORBT_PRO_COMMIT}",
+        environment=HISTORICAL_VECTORBT_PRO_ENV,
+        python_env_var=HISTORICAL_VECTORBT_PRO_PYTHON_ENV_VAR,
+    )
+
+
+def run_worker(
+    framework: str,
+    workload: ScaleWorkload = WORKLOAD,
+    *,
+    target_override: FrameworkTarget | None = None,
+) -> dict[str, Any]:
+    """Execute one external/ML4T scale pair and retain exact digests."""
+    manifest = load_framework_manifest()
+    target = target_override or manifest.targets[framework]
+    if target.framework_id != framework:
+        raise ValueError(f"Target {target.framework_id!r} cannot identify framework {framework!r}")
+    actual_target = _actual_target(target)
+    if actual_target["actual_version"] != target.version:
+        raise RuntimeError(
+            f"Installed {target.package} version {actual_target['actual_version']} does not match "
+            f"declared target {target.version}"
+        )
+    config = workload.benchmark_config()
+    price_data, signals, dates = suite.generate_benchmark_data(config, seed=workload.seed)
+    raw_digest = input_digest(price_data, signals, dates)
+    effective_prices = _effective_prices(framework, price_data)
+    effective_digest = input_digest(effective_prices, signals, dates)
+    external, ml4t = _framework_run(framework, config, price_data, signals, dates)
+    _use_canonical_fill_backed_trades(external, ml4t)
+    comparison = cast(
+        dict[str, Any],
+        suite.compare_benchmark_results_exact(
+            external,
+            ml4t,
+            initial_cash=config.initial_cash,
+            timestamp_domain="session_date",
+        ),
+    )
+    expected_terminal = _terminal_state(external, effective_prices, config.initial_cash)
+    actual_terminal = _terminal_state(ml4t, effective_prices, config.initial_cash)
+    terminal_check = {
+        "name": "terminal_state",
+        "passed": expected_terminal == actual_terminal,
+        "expected_sha256": expected_terminal["sha256"],
+        "actual_sha256": actual_terminal["sha256"],
+        "expected": expected_terminal,
+        "actual": actual_terminal,
+    }
+    comparison["checks"].append(terminal_check)
+    comparison["passed"] = bool(comparison["passed"] and terminal_check["passed"])
+    return {
+        "framework": framework,
+        "target": actual_target,
+        "python": {
+            "version": sys.version.split()[0],
+            "implementation": sys.implementation.name,
+        },
+        "ml4t": _git_identity(),
+        "source_digests": _source_digests(),
+        "input": {
+            "raw_sha256": raw_digest,
+            "effective_sha256": effective_digest,
+            "conversion": (
+                "OHLC rounded to 3 decimals before both engines"
+                if framework == "zipline"
+                else "OHLC rounded to 4 decimals before both engines"
+                if framework == "lean"
+                else "none"
+            ),
+        },
+        "capabilities": {
+            "intents": "canonical strategy trace",
+            "fills": "native",
+            "closed_trades": "reconstructed from canonical native fills",
+            "terminal_state": "reconstructed from native fills and final marks",
+            "fill_order": "session, asset, side, quantity, price",
+        },
+        "runtime_seconds": {
+            "framework": external.runtime_sec,
+            "ml4t": ml4t.runtime_sec,
+            "not_a_performance_claim": True,
+        },
+        "comparison": comparison,
+    }
+
+
+def build_report(
+    records: list[dict[str, Any]], workload: ScaleWorkload = WORKLOAD
+) -> dict[str, Any]:
+    """Build one candidate report from isolated worker records."""
+    return {
+        "schema_version": SCHEMA_VERSION,
+        "generated_at": datetime.now(UTC).isoformat(),
+        "workload": {
+            "recipe": asdict(workload),
+            "recipe_sha256": _json_digest(asdict(workload)),
+            "data_points": workload.data_points,
+            "generator": "validation.benchmark_suite.generate_benchmark_data",
+            "redistributable": True,
+        },
+        "frameworks": records,
+        "release_gate_passed": len(records) == len(FRAMEWORKS)
+        and all(record.get("comparison", {}).get("passed") is True for record in records),
+    }
+
+
+def _comparison_signature(record: dict[str, Any]) -> dict[str, Any]:
+    comparison = cast(dict[str, Any], record["comparison"])
+    checks = cast(list[dict[str, Any]], comparison["checks"])
+    signature: dict[str, Any] = {}
+    for check in checks:
+        name = str(check["name"])
+        if "expected_sha256" in check:
+            signature[name] = {
+                "count": check.get("expected_count"),
+                "sha256": check["expected_sha256"],
+            }
+        else:
+            signature[name] = check["canonical_expected"]
+    return signature
+
+
+def build_historical_report(
+    current_record: dict[str, Any],
+    historical_record: dict[str, Any],
+    workload: ScaleWorkload = WORKLOAD,
+) -> dict[str, Any]:
+    """Build evidence that one historical target matches the accepted current target."""
+    current_signature = _comparison_signature(current_record)
+    historical_signature = _comparison_signature(historical_record)
+    return {
+        "schema_version": SCHEMA_VERSION,
+        "generated_at": datetime.now(UTC).isoformat(),
+        "audit_trigger": {
+            "ml4t_commit": "488c05d84e74156aba71c4f7ffac28df3881fea9",
+            "cause": "vectorbt collateral semantics missing from the ML4T comparison profile",
+            "external_fill_count": 390_369,
+            "ml4t_fill_count": 418_825,
+            "external_final_value": 716_785.408089,
+            "ml4t_final_value": 1_162_222.354417,
+        },
+        "workload": {
+            "recipe": asdict(workload),
+            "recipe_sha256": _json_digest(asdict(workload)),
+            "data_points": workload.data_points,
+            "generator": "validation.benchmark_suite.generate_benchmark_data",
+            "redistributable": True,
+        },
+        "current": current_record,
+        "historical": historical_record,
+        "framework_output_comparison": {
+            "current": current_signature,
+            "historical": historical_signature,
+            "passed": current_signature == historical_signature,
+        },
+        "release_gate_passed": historical_record.get("comparison", {}).get("passed") is True
+        and current_signature == historical_signature,
+    }
+
+
+@cache
+def _expected_input_digest(workload: ScaleWorkload) -> str:
+    config = workload.benchmark_config()
+    prices, signals, dates = suite.generate_benchmark_data(config, seed=workload.seed)
+    return input_digest(prices, signals, dates)
+
+
+def report_failures(report: dict[str, Any], *, reconstruct_input: bool = False) -> list[str]:
+    """Return every reason a large-scale candidate cannot be accepted."""
+    failures: list[str] = []
+    if report.get("schema_version") != SCHEMA_VERSION:
+        return [f"Unsupported large-scale schema: {report.get('schema_version')!r}"]
+    raw_workload_value = report.get("workload")
+    if not isinstance(raw_workload_value, dict):
+        raw_workload: dict[str, Any] = {}
+    else:
+        raw_workload = cast(dict[str, Any], raw_workload_value)
+    if raw_workload.get("recipe") != asdict(WORKLOAD):
+        failures.append("Large-scale workload recipe differs")
+    elif raw_workload.get("recipe_sha256") != _json_digest(asdict(WORKLOAD)):
+        failures.append("Large-scale workload recipe digest differs")
+    raw_records = report.get("frameworks")
+    if not isinstance(raw_records, list):
+        return failures + ["Large-scale framework records must be a list"]
+    records: dict[str, dict[str, Any]] = {}
+    for raw_record in raw_records:
+        if not isinstance(raw_record, dict):
+            continue
+        record = cast(dict[str, Any], raw_record)
+        framework_id = record.get("framework")
+        if isinstance(framework_id, str):
+            records[framework_id] = record
+    if set(records) != set(FRAMEWORKS):
+        failures.append("Large-scale framework coverage differs")
+    manifest = load_framework_manifest()
+    expected_sources = _source_digests()
+    reconstructed = _expected_input_digest(WORKLOAD) if reconstruct_input else None
+    raw_digests: set[str] = set()
+    for framework in FRAMEWORKS:
+        record = records.get(framework)
+        if not isinstance(record, dict):
+            continue
+        target = record.get("target")
+        expected_target = manifest.targets[framework].evidence_metadata()
+        if (
+            not isinstance(target, dict)
+            or _declared_target_metadata(target) != expected_target
+            or target.get("actual_version") != expected_target["version"]
+        ):
+            failures.append(f"{framework} target identity differs")
+        elif framework == "vectorbt_pro" and (
+            target.get("actual_commit") != expected_target["commit"]
+            or target.get("actual_immutable_id") != expected_target["immutable_id"]
+        ):
+            failures.append(f"{framework} installed source identity differs")
+        if record.get("source_digests") != expected_sources:
+            failures.append(f"{framework} source digests differ")
+        ml4t = record.get("ml4t")
+        if not isinstance(ml4t, dict) or ml4t.get("dirty") is not False:
+            failures.append(f"{framework} was not produced from a clean ML4T tree")
+        elif not isinstance(ml4t.get("commit"), str) or len(str(ml4t["commit"])) != 40:
+            failures.append(f"{framework} ML4T commit identity is missing")
+        python = record.get("python")
+        if not isinstance(python, dict) or not all(
+            isinstance(python.get(key), str) for key in ("version", "implementation")
+        ):
+            failures.append(f"{framework} Python identity is missing")
+        input_record = record.get("input")
+        if not isinstance(input_record, dict) or not isinstance(
+            input_record.get("raw_sha256"), str
+        ):
+            failures.append(f"{framework} input evidence is missing")
+        else:
+            raw_digest = str(input_record["raw_sha256"])
+            raw_digests.add(raw_digest)
+            if reconstructed is not None and raw_digest != reconstructed:
+                failures.append(f"{framework} input digest does not reconstruct")
+            effective_digest = input_record.get("effective_sha256")
+            if not isinstance(effective_digest, str) or len(effective_digest) != 64:
+                failures.append(f"{framework} effective-input digest is missing")
+        capabilities = record.get("capabilities")
+        if not isinstance(capabilities, dict) or set(capabilities) != {
+            "intents",
+            "fills",
+            "closed_trades",
+            "terminal_state",
+            "fill_order",
+        }:
+            failures.append(f"{framework} capability declaration is incomplete")
+        comparison = record.get("comparison")
+        if not isinstance(comparison, dict) or comparison.get("passed") is not True:
+            failures.append(f"{framework} exact comparison did not pass")
+            continue
+        checks = comparison.get("checks")
+        if not isinstance(checks, list):
+            failures.append(f"{framework} comparison checks are missing")
+            continue
+        names = {check.get("name") for check in checks if isinstance(check, dict)}
+        expected_names = {
+            "order_intents",
+            "fills",
+            "trades",
+            "trade_count",
+            "total_pnl",
+            "final_value",
+            "terminal_state",
+        }
+        if names != expected_names or any(
+            not isinstance(check, dict) or check.get("passed") is not True for check in checks
+        ):
+            failures.append(f"{framework} comparison surface is incomplete or failed")
+            continue
+        for check in checks:
+            assert isinstance(check, dict)
+            name = check["name"]
+            if name in {"order_intents", "fills", "trades", "terminal_state"}:
+                expected_hash = check.get("expected_sha256")
+                actual_hash = check.get("actual_sha256")
+                if (
+                    not isinstance(expected_hash, str)
+                    or len(expected_hash) != 64
+                    or expected_hash != actual_hash
+                ):
+                    failures.append(f"{framework} {name} digest comparison differs")
+            elif check.get("canonical_expected") != check.get("canonical_actual"):
+                failures.append(f"{framework} {name} canonical values differ")
+    if len(raw_digests) > 1:
+        failures.append("Large-scale framework inputs differ")
+    if report.get("release_gate_passed") is not True:
+        failures.append("Large-scale release gate did not pass")
+    return failures
+
+
+def historical_report_failures(
+    report: dict[str, Any], *, reconstruct_input: bool = False
+) -> list[str]:
+    """Return every reason a historical replay candidate cannot be accepted."""
+    failures: list[str] = []
+    if report.get("schema_version") != SCHEMA_VERSION:
+        return [f"Unsupported historical replay schema: {report.get('schema_version')!r}"]
+    workload = report.get("workload")
+    if not isinstance(workload, dict) or workload.get("recipe") != asdict(WORKLOAD):
+        failures.append("Historical replay workload recipe differs")
+    elif workload.get("recipe_sha256") != _json_digest(asdict(WORKLOAD)):
+        failures.append("Historical replay workload recipe digest differs")
+    current = report.get("current")
+    historical = report.get("historical")
+    if not isinstance(current, dict) or not isinstance(historical, dict):
+        return failures + ["Historical replay records are missing"]
+    manifest = load_framework_manifest()
+    current_target = manifest.targets["vectorbt_pro"].evidence_metadata()
+    historical_target = _historical_vectorbt_pro_target().evidence_metadata()
+    for label, record, expected_target in (
+        ("current", current, current_target),
+        ("historical", historical, historical_target),
+    ):
+        target = record.get("target")
+        if (
+            not isinstance(target, dict)
+            or _declared_target_metadata(target) != expected_target
+            or target.get("actual_version") != expected_target["version"]
+        ):
+            failures.append(f"VectorBT Pro {label} target identity differs")
+        elif (
+            target.get("actual_commit") != expected_target["commit"]
+            or target.get("actual_immutable_id") != expected_target["immutable_id"]
+        ):
+            failures.append(f"VectorBT Pro {label} installed source identity differs")
+        if record.get("source_digests") != _source_digests():
+            failures.append(f"VectorBT Pro {label} source digests differ")
+        ml4t = record.get("ml4t")
+        if not isinstance(ml4t, dict) or ml4t.get("dirty") is not False:
+            failures.append(f"VectorBT Pro {label} run used a dirty ML4T tree")
+        elif not isinstance(ml4t.get("commit"), str) or len(str(ml4t["commit"])) != 40:
+            failures.append(f"VectorBT Pro {label} ML4T commit identity is missing")
+        comparison = record.get("comparison")
+        if not isinstance(comparison, dict) or comparison.get("passed") is not True:
+            failures.append(f"VectorBT Pro {label} exact comparison did not pass")
+        input_record = record.get("input")
+        if not isinstance(input_record, dict):
+            failures.append(f"VectorBT Pro {label} input evidence is missing")
+        elif reconstruct_input and input_record.get("raw_sha256") != _expected_input_digest(
+            WORKLOAD
+        ):
+            failures.append(f"VectorBT Pro {label} input digest does not reconstruct")
+    if current.get("source_digests") != historical.get("source_digests"):
+        failures.append("Historical replay runs used different comparison sources")
+    if current.get("input") != historical.get("input"):
+        failures.append("Historical replay inputs differ")
+    output_comparison = report.get("framework_output_comparison")
+    expected_output_comparison = {
+        "current": _comparison_signature(current),
+        "historical": _comparison_signature(historical),
+        "passed": _comparison_signature(current) == _comparison_signature(historical),
+    }
+    if output_comparison != expected_output_comparison or not expected_output_comparison["passed"]:
+        failures.append("Historical and current VectorBT Pro outputs differ")
+    if report.get("release_gate_passed") is not True:
+        failures.append("Historical replay release gate did not pass")
+    return failures
+
+
+def _resolve_python(framework: str) -> Path:
+    target = load_framework_manifest().targets[framework]
+    override = os.getenv(target.python_env_var or "")
+    if override:
+        return Path(override).expanduser().resolve()
+    if target.environment is None:
+        raise ValueError(f"{framework} has no environment")
+    return PROJECT_ROOT / target.environment / "bin" / "python"
+
+
+def _resolve_historical_vectorbt_pro_python() -> Path:
+    override = os.getenv(HISTORICAL_VECTORBT_PRO_PYTHON_ENV_VAR)
+    if override:
+        return Path(override).expanduser().resolve()
+    return PROJECT_ROOT / HISTORICAL_VECTORBT_PRO_ENV / "bin" / "python"
+
+
+def _run_isolated_worker(
+    framework: str,
+    interpreter: Path,
+    *,
+    historical_target: bool = False,
+) -> dict[str, Any]:
+    if not interpreter.is_file():
+        raise RuntimeError(f"Missing {framework} interpreter: {interpreter}")
+    with tempfile.TemporaryDirectory(prefix=f"ml4t-scale-{framework}-") as directory:
+        output = Path(directory) / "record.json"
+        command = [
+            str(interpreter),
+            str(Path(__file__).resolve()),
+            "--worker",
+            framework,
+            "--output",
+            str(output),
+        ]
+        if historical_target:
+            command.append("--historical-target")
+        environment = os.environ.copy()
+        paths = [str(PROJECT_ROOT / "src"), str(VALIDATION_DIR)]
+        sibling_specs = PROJECT_ROOT.parent / "ml4t-specs" / "src"
+        if sibling_specs.is_dir():
+            paths.append(str(sibling_specs))
+        environment["PYTHONPATH"] = os.pathsep.join(
+            paths + ([environment["PYTHONPATH"]] if environment.get("PYTHONPATH") else [])
+        )
+        completed = subprocess.run(
+            command,
+            cwd=PROJECT_ROOT,
+            env=environment,
+            capture_output=True,
+            text=True,
+            timeout=3_600,
+            check=False,
+        )
+        record: dict[str, Any] | None = None
+        if output.is_file():
+            try:
+                loaded = json.loads(output.read_text(encoding="utf-8"))
+                record = cast(dict[str, Any], loaded) if isinstance(loaded, dict) else None
+            except json.JSONDecodeError:
+                record = None
+        if record is not None and (
+            completed.returncode != 0 or record.get("comparison", {}).get("passed") is not True
+        ):
+            diagnostic_path = CANDIDATE_DIR / f"{framework}.large_scale.candidate.json"
+            _write_json_atomic(diagnostic_path, record)
+            raise RuntimeError(
+                f"{framework} large-scale comparison failed; diagnostic retained at "
+                f"{diagnostic_path}: " + json.dumps(record.get("comparison"), indent=2)[-20_000:]
+            )
+        if completed.returncode != 0 or record is None:
+            details = "\n".join(
+                stream.strip() for stream in (completed.stdout, completed.stderr) if stream.strip()
+            )
+            raise RuntimeError(
+                f"{framework} scale worker exited {completed.returncode}: {details[-20_000:]}"
+            )
+        return record
+
+
+def run_all() -> dict[str, Any]:
+    """Run every framework in its isolated environment and return a candidate report."""
+    records: list[dict[str, Any]] = []
+    for framework in FRAMEWORKS:
+        interpreter = _resolve_python(framework)
+        print(f"Running {framework} large-scale pair...", flush=True)
+        records.append(_run_isolated_worker(framework, interpreter))
+        print(f"{framework}: PASS", flush=True)
+    return build_report(records)
+
+
+def run_historical_vectorbt_pro() -> dict[str, Any]:
+    """Replay the historical Pro target and compare it with accepted current evidence."""
+    current_report = cast(dict[str, Any], json.loads(ACCEPTED_PATH.read_text(encoding="utf-8")))
+    current_failures = report_failures(current_report, reconstruct_input=True)
+    if current_failures:
+        raise RuntimeError(
+            "Current large-scale evidence is not valid: " + "; ".join(current_failures)
+        )
+    current_record = next(
+        record
+        for record in cast(list[dict[str, Any]], current_report["frameworks"])
+        if record["framework"] == "vectorbt_pro"
+    )
+    historical_record = _run_isolated_worker(
+        "vectorbt_pro",
+        _resolve_historical_vectorbt_pro_python(),
+        historical_target=True,
+    )
+    return build_historical_report(current_record, historical_record)
+
+
+def _write_json(path: Path, payload: dict[str, Any]) -> None:
+    path.parent.mkdir(parents=True, exist_ok=True)
+    path.write_text(json.dumps(payload, indent=2, sort_keys=True) + "\n", encoding="utf-8")
+
+
+def _write_json_atomic(path: Path, payload: dict[str, Any]) -> None:
+    """Replace accepted evidence only after a complete temporary write."""
+    path.parent.mkdir(parents=True, exist_ok=True)
+    serialized = json.dumps(payload, indent=2, sort_keys=True) + "\n"
+    with tempfile.NamedTemporaryFile(
+        mode="w",
+        encoding="utf-8",
+        dir=path.parent,
+        prefix=f".{path.name}.",
+        delete=False,
+    ) as handle:
+        temporary = Path(handle.name)
+        handle.write(serialized)
+        handle.flush()
+        os.fsync(handle.fileno())
+    os.replace(temporary, path)
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--worker", choices=FRAMEWORKS)
+    parser.add_argument("--output", type=Path)
+    parser.add_argument("--check", action="store_true")
+    parser.add_argument("--verify-input", action="store_true")
+    parser.add_argument("--historical-target", action="store_true", help=argparse.SUPPRESS)
+    parser.add_argument("--historical-vectorbt-pro", action="store_true")
+    parser.add_argument("--check-historical-vectorbt-pro", action="store_true")
+    args = parser.parse_args()
+    if args.worker:
+        if args.output is None:
+            parser.error("--worker requires --output")
+        if args.historical_target and args.worker != "vectorbt_pro":
+            parser.error("--historical-target requires --worker vectorbt_pro")
+        target = _historical_vectorbt_pro_target() if args.historical_target else None
+        record = run_worker(args.worker, target_override=target)
+        _write_json(args.output, record)
+        return 0 if record["comparison"]["passed"] else 1
+    if args.historical_target:
+        parser.error("--historical-target requires --worker vectorbt_pro")
+    if args.check_historical_vectorbt_pro:
+        report = json.loads(HISTORICAL_ACCEPTED_PATH.read_text(encoding="utf-8"))
+        failures = historical_report_failures(report, reconstruct_input=args.verify_input)
+        for failure in failures:
+            print(f"- {failure}")
+        return 1 if failures else 0
+    if args.historical_vectorbt_pro:
+        candidate = run_historical_vectorbt_pro()
+        _write_json(HISTORICAL_CANDIDATE_PATH, candidate)
+        failures = historical_report_failures(candidate, reconstruct_input=True)
+        if failures:
+            print("Accepted historical evidence unchanged:")
+            for failure in failures:
+                print(f"- {failure}")
+            return 1
+        _write_json_atomic(HISTORICAL_ACCEPTED_PATH, candidate)
+        print(f"Accepted historical evidence: {HISTORICAL_ACCEPTED_PATH}")
+        return 0
+    if args.check:
+        report = json.loads(ACCEPTED_PATH.read_text(encoding="utf-8"))
+        failures = report_failures(report, reconstruct_input=args.verify_input)
+        for failure in failures:
+            print(f"- {failure}")
+        return 1 if failures else 0
+    candidate = run_all()
+    _write_json(CANDIDATE_PATH, candidate)
+    failures = report_failures(candidate, reconstruct_input=True)
+    if failures:
+        print("Accepted evidence unchanged:")
+        for failure in failures:
+            print(f"- {failure}")
+        return 1
+    _write_json_atomic(ACCEPTED_PATH, candidate)
+    print(f"Accepted evidence: {ACCEPTED_PATH}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/lean/README.md b/validation/lean/README.md
index a065f947..6138c5a7 100644
--- a/validation/lean/README.md
+++ b/validation/lean/README.md
@@ -1,178 +1,93 @@
 # LEAN Validation Workflow
 
-## Status
+The retained LEAN comparison uses a frozen engine, CLI, data protocol, and account model:
 
-LEAN is part of the validation/parity workflow, but not through the old static
-`scenario_01_long_only/` project in this directory.
+- LEAN engine 18001 at source commit `278fcb3d1b815b63ccadba68d7ae54422e34b792`
+- image `quantconnect/lean@sha256:ecd62b0e418d40d1d7c0cd95e90a94e397642a21d2c8810614830c8a4e9a8f70`
+- LEAN CLI 1.0.228 from the locked environment
+- daily adjusted US equities, `DefaultBrokerageModel`, margin account, and 2x security leverage
 
-What actually runs today is the LEAN adapter in
-[`validation/benchmark_suite.py`](../benchmark_suite.py), which:
+This is a scoped comparison protocol. It is not a claim about every LEAN asset class,
+resolution, brokerage model, or order type.
 
-- supports the benchmark/parity workflow, not the old scenario matrix
-- supports daily-data scenarios only
-- generates a temporary LEAN project and LEAN-format data on the fly
-- runs LEAN through the CLI in Docker
+## Build the Locked Environment
 
-The old `scenario_01_long_only/` folder is legacy scaffolding, not the current
-source of truth.
-
-## What Made It Work
-
-These are the pieces that mattered in practice:
-
-1. We used the Dockerized LEAN CLI path, not a direct `.NET` launcher workflow.
-2. We did not require a permanently installed `lean` binary.
-   The adapter falls back to:
-
-   ```bash
-   uvx --python 3.12 --with "setuptools<81" lean
-   ```
-
-3. We required a machine-local LEAN workspace config at:
-
-   ```text
-   validation/lean/workspace/lean.json
-   ```
-
-4. We let `benchmark_suite.py` generate the LEAN project, algorithm, target
-   file, and LEAN-format equity data for each run.
-5. Docker had to be running before invoking the benchmark.
-
-## One-Time Bootstrap
-
-From the repository root:
+Docker must be running. From the repository root:
 
 ```bash
-mkdir -p validation/lean/workspace
-cd validation/lean/workspace
-uvx --python 3.12 --with "setuptools<81" lean init
+uv run python validation/build_framework_env.py --framework lean
 ```
 
-If `lean` is already installed on `PATH`, this also works:
+This creates `.venv-lean`, verifies the exact CLI distribution, and verifies the immutable engine
+image. The runners do not install a CLI dynamically and do not accept a mutable image tag.
+
+## Native Behavior Evidence
+
+Run the native oracle before changing the `lean` profile:
 
 ```bash
-lean init
+.venv-lean/bin/python validation/native/lean_behavior.py \
+  --lean-command .venv-lean/bin/lean \
+  --output /tmp/lean-native.json
 ```
 
-The important outcome is that `validation/lean/workspace/lean.json` exists and
-is valid on the local machine. That file is not committed in the repo.
+The oracle checks the event and model behavior used by the profile, including next-session market
+fills, final-bar orders, model selection, margin, target sizing, submission order, buying power,
+explicit costs, fill-forward data, full fills, and terminal holdings. The retained result is
+`validation/native/evidence/lean-18001.json`.
 
-## Runtime Prerequisites
+The `lean` profile's stop settings are ML4T fallbacks. Stop-order equivalence is not part of this
+native evidence.
 
-- Docker daemon available
-- either `lean` on `PATH` or `uvx` on `PATH`
-- Python 3.12 available for the `uvx` fallback path
-- initialized LEAN workspace config at
-  `validation/lean/workspace/lean.json`
+## Chapter 16 Case Studies
 
-The adapter itself also sets:
+The current large comparison reruns three retained Chapter 16 projects against the frozen image:
 
-```text
-UV_CACHE_DIR=/tmp/uv-cache
-UV_TOOL_DIR=/tmp/uv-tools
+```bash
+.venv-lean/bin/python validation/run_lean_case_studies.py \
+  --lean-command .venv-lean/bin/lean \
+  --output /tmp/lean-case-studies.json
 ```
 
-to keep the transient LEAN CLI tool environment out of the repo.
+Add `--promote` only when intentionally replacing the tracked LEAN outputs and retained evidence.
+Promotion is atomic and occurs only after all projects pass.
 
-## Exact Command We Run
+The three projects compare 47,652 canonical fills. They currently have zero fill-surface gap and
+zero terminal-value gap at a `$0.0001` quantum. The machine-readable result is
+`validation/lean/case_study_evidence.json`.
 
-Use the benchmark suite, not the legacy `run_all_correctness.py` LEAN path.
+These projects specify their own percentage fee and zero-slippage settings. They do not test the
+fee and slippage models selected by `DefaultBrokerageModel`; the native oracle tests that model
+selection separately.
 
-Typical invocation:
+## Benchmark Adapter
 
-```bash
-python validation/benchmark_suite.py \
-  --framework lean \
-  --scenario daily_baseline \
-  --data-source real \
-  --real-data-path /path/to/us_equities.parquet
-```
-
-To compare the ml4t side using the LEAN-style profile:
+The daily-data adapter remains available through the benchmark suite:
 
 ```bash
-python validation/benchmark_suite.py \
-  --framework ml4t-lean-strict \
+uv run python validation/benchmark_suite.py \
+  --framework lean \
   --scenario daily_baseline \
   --data-source real \
   --real-data-path /path/to/us_equities.parquet
 ```
 
-Notes:
-
-- `--framework lean` invokes the LEAN adapter.
-- `--framework ml4t-lean-strict` runs `ml4t-backtest` with the LEAN-strict
-  parity profile.
-- LEAN currently returns an error for non-daily scenarios.
-
-## What The Adapter Generates
-
-For each run, `benchmark_suite.py` writes a generated LEAN project under:
-
-```text
-validation/lean/workspace/ml4t_benchmark/
-```
-
-Key generated files:
-
-- `main.py`: generated QCAlgorithm using canonical target shares
-- `config.json`: minimal LEAN project config
-- `symbols.csv`: generated synthetic tickers for the selected assets
-- `targets.csv`: daily target share instructions
-
-It also exports LEAN-format daily equity data under:
-
-```text
-validation/lean/workspace/data/equity/usa/
-```
-
-including:
-
-- `daily/*.zip`
-- `map_files/*.csv`
-- `factor_files/*.csv`
-
-To avoid re-exporting identical daily data every run, it maintains:
-
-```text
-validation/lean/workspace/data/equity/usa/ml4t_manifest.json
-```
-
-and uses a signature-based cache check.
-
-## The Exact LEAN Invocation
-
-Once the generated project and data are in place, the adapter runs:
-
-```bash
-lean backtest validation/lean/workspace/ml4t_benchmark \
-  --lean-config validation/lean/workspace/lean.json \
-  --no-update \
-  --output <generated-output-dir>
-```
-
-If `lean` is not installed, the code uses the `uvx` form instead.
-
-Results are read back from the generated LEAN summary JSON in the output
-directory.
-
-## Source Of Truth In Code
+To run the ML4T side with the corresponding profile, use `--framework ml4t-lean-strict`.
 
-The working implementation lives here:
+The adapter requires an exact CLI version and passes the frozen image digest to every LEAN run.
+It supports daily scenarios only.
 
-- [`validation/benchmark_suite.py`](../benchmark_suite.py): LEAN adapter,
-  project generation, data export, CLI invocation, result parsing
+## Reproducibility Boundary
 
-These files are legacy and should not be treated as the primary workflow:
+The native and Chapter 16 runners construct temporary LEAN roots from tracked inputs:
 
-- [`validation/lean/scenario_01_long_only/main.py`](scenario_01_long_only/main.py)
-- [`validation/run_all_correctness.py`](../run_all_correctness.py)
+- `validation/lean/support/lean.json`
+- `validation/lean/support/data/market-hours/market-hours-database.json`
+- `validation/lean/support/data/symbol-properties/symbol-properties-database.csv`
+- the tracked project files and daily equity archives under `validation/lean/workspace/`
 
-## Practical Caveats
+Map and factor files are generated from the first date in each tracked daily archive. No ignored
+machine-local `lean.json`, map file, factor file, or data directory is required.
 
-- LEAN is currently benchmark/parity coverage, not full scenario-matrix coverage.
-- The adapter currently supports daily data only.
-- The local `lean.json` is a manual prerequisite and is intentionally not
-  committed.
-- Docker startup and LEAN container initialization make LEAN slower and more
-  operationally fragile than the Python-native backtest validation paths.
+The old `scenario_01_long_only/` project and `validation/run_all_correctness.py` LEAN path are
+legacy scaffolding. They are not evidence for the current claim.
diff --git a/validation/lean/case_study_evidence.json b/validation/lean/case_study_evidence.json
new file mode 100644
index 00000000..a67a2073
--- /dev/null
+++ b/validation/lean/case_study_evidence.json
@@ -0,0 +1,247 @@
+{
+  "cases": [
+    {
+      "case": "chapter16_etfs",
+      "comparison": {
+        "canonical_final_value_gap_usd": 0.0,
+        "canonical_final_value_match": true,
+        "fill_gap": 0,
+        "final_value_gap_pct": 2.6645352591003757e-15,
+        "final_value_gap_usd": 3.026798367500305e-09,
+        "final_value_quantum_usd": 0.0001,
+        "lean_fills": 10701,
+        "lean_final_value": 1119459.5398322002,
+        "ml4t_fills": 10701,
+        "ml4t_final_value": 1119459.5398322032,
+        "raw_row_order_match": true,
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+      "summary_sha256": "1ed0ef6c680a8069789ccbf9e7862c8dee8baffe860512989dca5a7f63e98575"
+    }
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+  "cli_observed": "lean 1.0.228",
+  "comparison_protocol": {
+    "account": "DefaultBrokerageModel Margin; per-project leverage 2",
+    "costs": "Ml4tPercentFeeModel at project rate; ConstantSlippageModel(0)",
+    "fills": "timestamp, asset, side, quantity, price rounded to 4 decimals",
+    "terminal_value_quantum": "0.0001 USD"
+  },
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+    "artifact": "quantconnect/lean@sha256:ecd62b0e418d40d1d7c0cd95e90a94e397642a21d2c8810614830c8a4e9a8f70",
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+    "cli_version": "1.0.228",
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+    "display_name": "LEAN",
+    "immutable_id": "sha256:ecd62b0e418d40d1d7c0cd95e90a94e397642a21d2c8810614830c8a4e9a8f70",
+    "license": "Apache-2.0",
+    "package": "lean",
+    "platform_artifact": "linux/amd64@sha256:cbe3f26b3f16c57be836b2cf913253d434f58e010c84ed038360d26b9df88307",
+    "profile": "lean",
+    "python": "3.11",
+    "source": "https://github.com/QuantConnect/Lean",
+    "version": "18001"
+  },
+  "passed": true,
+  "producer_files": {
+    "src/ml4t/backtest/_validation/case_study_lean.py": "62247f66db5ae118e7089ab4dfeca5a7251b1f3f4238b9aceeb55384df447cfd",
+    "src/ml4t/backtest/_validation/lean_runner.py": "30efdb8018cc949c991dee856a7007d0dfdc635397a208f98a6dd094af20fce1",
+    "src/ml4t/backtest/profiles.py": "5a8cd8b2568e7e9f524e96fef6bb00ade3310a6f4a71c0c4f7de2f95bbfdb505",
+    "validation/run_lean_case_studies.py": "5bf91f8d98f8bfd9a88eb72071c392ff23ad4583184b28165e7511d9e0d1901e"
+  },
+  "promoted": true,
+  "schema_version": 1,
+  "support_files": {
+    "data/market-hours/market-hours-database.json": "935079bc33409373f37163eddb539f09e81a1efbd0e617cbc8fdb487c76dab2b",
+    "data/symbol-properties/symbol-properties-database.csv": "56b6dc80202bca88f212c78c4d4670c2e070e6f1e7386f7436232aafe5000e93",
+    "lean.json": "fa15d6d81f560fd1665b004c338b026458fa834a7645e015d16d861dd73540f4"
+  }
+}
diff --git a/validation/lean/support/data/market-hours/market-hours-database.json b/validation/lean/support/data/market-hours/market-hours-database.json
new file mode 100644
index 00000000..0d3ab37e
--- /dev/null
+++ b/validation/lean/support/data/market-hours/market-hours-database.json
@@ -0,0 +1,457 @@
+{
+  "entries": {
+    "Equity-usa-[*]": {
+      "dataTimeZone": "America/New_York",
+      "exchangeTimeZone": "America/New_York",
+      "sunday": [],
+      "monday": [
+        {
+          "start": "04:00:00",
+          "end": "09:30:00",
+          "state": "premarket"
+        },
+        {
+          "start": "09:30:00",
+          "end": "16:00:00",
+          "state": "market"
+        },
+        {
+          "start": "16:00:00",
+          "end": "20:00:00",
+          "state": "postmarket"
+        }
+      ],
+      "tuesday": [
+        {
+          "start": "04:00:00",
+          "end": "09:30:00",
+          "state": "premarket"
+        },
+        {
+          "start": "09:30:00",
+          "end": "16:00:00",
+          "state": "market"
+        },
+        {
+          "start": "16:00:00",
+          "end": "20:00:00",
+          "state": "postmarket"
+        }
+      ],
+      "wednesday": [
+        {
+          "start": "04:00:00",
+          "end": "09:30:00",
+          "state": "premarket"
+        },
+        {
+          "start": "09:30:00",
+          "end": "16:00:00",
+          "state": "market"
+        },
+        {
+          "start": "16:00:00",
+          "end": "20:00:00",
+          "state": "postmarket"
+        }
+      ],
+      "thursday": [
+        {
+          "start": "04:00:00",
+          "end": "09:30:00",
+          "state": "premarket"
+        },
+        {
+          "start": "09:30:00",
+          "end": "16:00:00",
+          "state": "market"
+        },
+        {
+          "start": "16:00:00",
+          "end": "20:00:00",
+          "state": "postmarket"
+        }
+      ],
+      "friday": [
+        {
+          "start": "04:00:00",
+          "end": "09:30:00",
+          "state": "premarket"
+        },
+        {
+          "start": "09:30:00",
+          "end": "16:00:00",
+          "state": "market"
+        },
+        {
+          "start": "16:00:00",
+          "end": "20:00:00",
+          "state": "postmarket"
+        }
+      ],
+      "saturday": [],
+      "holidays": [
+        "1/1/1998",
+        "1/1/1999",
+        "1/1/2001",
+        "1/1/2002",
+        "1/1/2003",
+        "1/1/2004",
+        "1/2/2006",
+        "1/1/2007",
+        "1/1/2008",
+        "1/1/2009",
+        "1/1/2010",
+        "1/1/2011",
+        "1/2/2012",
+        "1/1/2013",
+        "1/1/2014",
+        "1/1/2015",
+        "1/1/2016",
+        "1/2/2017",
+        "1/1/2018",
+        "1/1/2019",
+        "1/1/2020",
+        "1/1/2021",
+        "1/1/2022",
+        "1/1/2024",
+        "1/2/2023",
+        "1/1/2025",
+        "1/1/2026",
+        "1/1/2027",
+        "1/2/2007",
+        "1/9/2025",
+        "1/19/1998",
+        "1/18/1999",
+        "1/17/2000",
+        "1/15/2001",
+        "1/21/2002",
+        "1/20/2003",
+        "1/19/2004",
+        "1/17/2005",
+        "1/16/2006",
+        "1/15/2007",
+        "1/21/2008",
+        "1/19/2009",
+        "1/18/2010",
+        "1/17/2011",
+        "1/16/2012",
+        "1/21/2013",
+        "1/20/2014",
+        "1/19/2015",
+        "1/18/2016",
+        "1/16/2017",
+        "1/15/2018",
+        "1/21/2019",
+        "1/20/2020",
+        "1/18/2021",
+        "1/17/2022",
+        "1/16/2023",
+        "1/15/2024",
+        "1/20/2025",
+        "1/19/2026",
+        "1/18/2027",
+        "1/17/2028",
+        "2/16/1998",
+        "2/15/1999",
+        "2/21/2000",
+        "2/19/2001",
+        "2/18/2002",
+        "2/17/2003",
+        "2/16/2004",
+        "2/21/2005",
+        "2/20/2006",
+        "2/19/2007",
+        "2/18/2008",
+        "2/16/2009",
+        "2/15/2010",
+        "2/21/2011",
+        "2/20/2012",
+        "2/18/2013",
+        "2/17/2014",
+        "2/16/2015",
+        "2/15/2016",
+        "2/20/2017",
+        "2/19/2018",
+        "2/18/2019",
+        "2/17/2020",
+        "2/15/2021",
+        "2/21/2022",
+        "2/20/2023",
+        "2/19/2024",
+        "2/17/2025",
+        "2/16/2026",
+        "2/15/2027",
+        "2/21/2028",
+        "4/10/1998",
+        "4/2/1999",
+        "4/21/2000",
+        "4/13/2001",
+        "3/29/2002",
+        "4/18/2003",
+        "4/9/2004",
+        "3/25/2005",
+        "4/14/2006",
+        "4/6/2007",
+        "3/21/2008",
+        "4/10/2009",
+        "4/2/2010",
+        "4/22/2011",
+        "4/6/2012",
+        "3/29/2013",
+        "4/18/2014",
+        "4/3/2015",
+        "3/25/2016",
+        "4/14/2017",
+        "3/30/2018",
+        "4/19/2019",
+        "4/10/2020",
+        "4/2/2021",
+        "4/15/2022",
+        "4/7/2023",
+        "3/29/2024",
+        "4/18/2025",
+        "4/3/2026",
+        "3/26/2027",
+        "4/14/2028",
+        "5/25/1998",
+        "5/31/1999",
+        "5/29/2000",
+        "5/28/2001",
+        "5/27/2002",
+        "5/26/2003",
+        "5/31/2004",
+        "5/30/2005",
+        "5/29/2006",
+        "5/28/2007",
+        "5/26/2008",
+        "5/25/2009",
+        "5/31/2010",
+        "5/30/2011",
+        "5/28/2012",
+        "5/27/2013",
+        "5/26/2014",
+        "5/25/2015",
+        "5/30/2016",
+        "5/29/2017",
+        "5/28/2018",
+        "5/27/2019",
+        "5/25/2020",
+        "5/31/2021",
+        "5/30/2022",
+        "5/29/2023",
+        "5/27/2024",
+        "5/26/2025",
+        "5/25/2026",
+        "5/31/2027",
+        "5/29/2028",
+        "6/11/2004",
+        "6/20/2022",
+        "6/19/2023",
+        "6/19/2024",
+        "6/19/2025",
+        "6/19/2026",
+        "6/18/2027",
+        "6/19/2028",
+        "7/3/1998",
+        "7/5/1999",
+        "7/4/2000",
+        "7/4/2001",
+        "7/4/2002",
+        "7/4/2003",
+        "7/5/2004",
+        "7/4/2005",
+        "7/4/2006",
+        "7/4/2007",
+        "7/4/2008",
+        "7/3/2009",
+        "7/5/2010",
+        "7/4/2011",
+        "7/4/2012",
+        "7/4/2013",
+        "7/4/2014",
+        "7/3/2015",
+        "7/4/2016",
+        "7/4/2017",
+        "7/4/2018",
+        "7/4/2019",
+        "7/3/2020",
+        "7/5/2021",
+        "7/4/2022",
+        "7/4/2023",
+        "7/4/2024",
+        "7/4/2025",
+        "7/3/2026",
+        "7/5/2027",
+        "7/4/2028",
+        "9/7/1998",
+        "9/6/1999",
+        "9/4/2000",
+        "9/3/2001",
+        "9/2/2002",
+        "9/1/2003",
+        "9/6/2004",
+        "9/5/2005",
+        "9/4/2006",
+        "9/3/2007",
+        "9/1/2008",
+        "9/7/2009",
+        "9/6/2010",
+        "9/5/2011",
+        "9/3/2012",
+        "9/2/2013",
+        "9/1/2014",
+        "9/7/2015",
+        "9/5/2016",
+        "9/4/2017",
+        "9/3/2018",
+        "9/2/2019",
+        "9/7/2020",
+        "9/6/2021",
+        "9/5/2022",
+        "9/4/2023",
+        "9/2/2024",
+        "9/1/2025",
+        "9/7/2026",
+        "9/6/2027",
+        "9/4/2028",
+        "9/11/2001",
+        "9/12/2001",
+        "9/13/2001",
+        "9/14/2001",
+        "10/29/2012",
+        "10/30/2012",
+        "11/26/1998",
+        "11/25/1999",
+        "11/23/2000",
+        "11/22/2001",
+        "11/28/2002",
+        "11/27/2003",
+        "11/25/2004",
+        "11/24/2005",
+        "11/23/2006",
+        "11/22/2007",
+        "11/27/2008",
+        "11/26/2009",
+        "11/25/2010",
+        "11/24/2011",
+        "11/22/2012",
+        "11/28/2013",
+        "11/27/2014",
+        "11/26/2015",
+        "11/24/2016",
+        "11/23/2017",
+        "11/22/2018",
+        "11/28/2019",
+        "11/26/2020",
+        "11/25/2021",
+        "11/24/2022",
+        "11/23/2023",
+        "11/28/2024",
+        "11/27/2025",
+        "11/26/2026",
+        "11/25/2027",
+        "11/23/2028",
+        "12/05/2018",
+        "12/25/1998",
+        "12/24/1999",
+        "12/25/2000",
+        "12/25/2001",
+        "12/25/2002",
+        "12/25/2003",
+        "12/24/2004",
+        "12/26/2005",
+        "12/25/2006",
+        "12/25/2007",
+        "12/25/2008",
+        "12/25/2009",
+        "12/24/2010",
+        "12/26/2011",
+        "12/25/2012",
+        "12/25/2013",
+        "12/25/2014",
+        "12/25/2015",
+        "12/26/2016",
+        "12/25/2017",
+        "12/25/2018",
+        "12/25/2019",
+        "12/25/2020",
+        "12/24/2021",
+        "12/26/2022",
+        "12/25/2023",
+        "12/25/2024",
+        "12/25/2025",
+        "12/25/2026",
+        "12/24/2027",
+        "12/25/2028"
+      ],
+      "earlyCloses": {
+        "7/3/2000": "13:00:00",
+        "7/3/2001": "13:00:00",
+        "7/5/2002": "13:00:00",
+        "7/3/2003": "13:00:00",
+        "7/3/2006": "13:00:00",
+        "7/3/2007": "13:00:00",
+        "7/3/2008": "13:00:00",
+        "7/3/2012": "13:00:00",
+        "7/3/2013": "13:00:00",
+        "7/3/2014": "13:00:00",
+        "7/3/2017": "13:00:00",
+        "7/3/2018": "13:00:00",
+        "7/3/2019": "13:00:00",
+        "7/3/2023": "13:00:00",
+        "7/3/2024": "13:00:00",
+        "7/3/2025": "13:00:00",
+        "7/3/2028": "13:00:00",
+        "11/26/1999": "13:00:00",
+        "11/24/2000": "13:00:00",
+        "11/23/2001": "13:00:00",
+        "11/29/2002": "13:00:00",
+        "11/28/2003": "13:00:00",
+        "11/26/2004": "13:00:00",
+        "11/25/2005": "13:00:00",
+        "11/24/2006": "13:00:00",
+        "11/23/2007": "13:00:00",
+        "11/28/2008": "13:00:00",
+        "11/27/2009": "13:00:00",
+        "11/26/2010": "13:00:00",
+        "11/25/2011": "13:00:00",
+        "11/23/2012": "13:00:00",
+        "11/29/2013": "13:00:00",
+        "11/28/2014": "13:00:00",
+        "11/27/2015": "13:00:00",
+        "11/25/2016": "13:00:00",
+        "11/24/2017": "13:00:00",
+        "11/23/2018": "13:00:00",
+        "11/29/2019": "13:00:00",
+        "11/27/2020": "13:00:00",
+        "11/26/2021": "13:00:00",
+        "11/25/2022": "13:00:00",
+        "11/24/2023": "13:00:00",
+        "11/29/2024": "13:00:00",
+        "11/28/2025": "13:00:00",
+        "11/27/2026": "13:00:00",
+        "11/26/2027": "13:00:00",
+        "11/24/2028": "13:00:00",
+        "12/24/2001": "13:00:00",
+        "12/24/2002": "13:00:00",
+        "12/24/2003": "13:00:00",
+        "12/26/2003": "13:00:00",
+        "12/24/2007": "13:00:00",
+        "12/24/2008": "13:00:00",
+        "12/24/2009": "13:00:00",
+        "12/24/2012": "13:00:00",
+        "12/24/2013": "13:00:00",
+        "12/24/2014": "13:00:00",
+        "12/24/2015": "13:00:00",
+        "12/24/2017": "13:00:00",
+        "12/24/2018": "13:00:00",
+        "12/24/2019": "13:00:00",
+        "12/24/2020": "13:00:00",
+        "12/24/2024": "13:00:00",
+        "12/24/2025": "13:00:00",
+        "12/24/2026": "13:00:00"
+      }
+    }
+  }
+}
diff --git a/validation/lean/support/data/symbol-properties/symbol-properties-database.csv b/validation/lean/support/data/symbol-properties/symbol-properties-database.csv
new file mode 100644
index 00000000..4a71a8a2
--- /dev/null
+++ b/validation/lean/support/data/symbol-properties/symbol-properties-database.csv
@@ -0,0 +1,2 @@
+market,symbol,type,description,quote_currency,contract_multiplier,minimum_price_variation,lot_size,market_ticker,minimum_order_size,price_magnifier,strike_multiplier
+usa,[*],equity,,USD,1,0.01,1
diff --git a/validation/lean/support/lean.json b/validation/lean/support/lean.json
new file mode 100644
index 00000000..a3569a2b
--- /dev/null
+++ b/validation/lean/support/lean.json
@@ -0,0 +1,6 @@
+{
+  "data-folder": "data",
+  "organization-id": "local",
+  "job-organization-id": "local",
+  "id": "Local"
+}
diff --git a/validation/lean/workspace/chapter16_etfs/ml4t_order_events.csv.xz b/validation/lean/workspace/chapter16_etfs/ml4t_order_events.csv.xz
index b4996e73..b84db06e 100644
Binary files a/validation/lean/workspace/chapter16_etfs/ml4t_order_events.csv.xz and b/validation/lean/workspace/chapter16_etfs/ml4t_order_events.csv.xz differ
diff --git a/validation/lean/workspace/chapter16_sp500_equity_option_analytics/ml4t_order_events.csv b/validation/lean/workspace/chapter16_sp500_equity_option_analytics/ml4t_order_events.csv
index 9866097e..a2a5fe98 100644
--- a/validation/lean/workspace/chapter16_sp500_equity_option_analytics/ml4t_order_events.csv
+++ b/validation/lean/workspace/chapter16_sp500_equity_option_analytics/ml4t_order_events.csv
@@ -1,3700 +1,3700 @@
-timestamp,symbol,status,direction,fill_quantity,fill_price,fee,message,order_id
-2019-01-04 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1
-2019-01-07 16:00:00,MCCZID,Filled,Buy,323.0,43.0,9.7223,,1
-2019-01-07 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,2
-2019-01-08 16:00:00,MCCZID,Filled,Sell,-2.0,43.53,0.060942,,2
-2019-01-08 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,3
-2019-01-09 16:00:00,MCCZID,Filled,Sell,-89.0,43.41,2.704443,,3
-2019-01-09 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,4
-2019-01-10 16:00:00,MCCZID,Filled,Buy,1.0,43.18,0.030226,,4
-2019-01-10 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,5
-2019-01-11 16:00:00,MCCZID,Filled,Buy,5.0,42.33,0.14815499999999998,,5
-2019-01-11 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,6
-2019-01-14 16:00:00,MCCZID,Filled,Sell,-238.0,42.55,7.08883,,6
-2019-01-14 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,7
-2019-01-14 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,8
-2019-01-14 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,9
-2019-01-14 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,10
-2019-01-15 16:00:00,OCHCAU,Filled,Buy,231.0,43.22,6.988674,,7
-2019-01-15 16:00:00,CEMOJE,Filled,Buy,9.0,1043.92,6.576696,,8
-2019-01-15 16:00:00,GTKILW,Filled,Buy,9.0,1052.01,6.627663,,9
-2019-01-15 16:00:00,MCCZID,Filled,Buy,235.0,42.61,7.009345000000001,,10
-2019-01-15 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,11
-2019-01-15 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,12
-2019-01-16 16:00:00,OCHCAU,Filled,Sell,-4.0,44.1,0.12348,,11
-2019-01-16 16:00:00,MCCZID,Filled,Sell,-1.0,42.63,0.029841000000000003,,12
-2019-01-16 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,13
-2019-01-16 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,14
-2019-01-16 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,15
-2019-01-17 16:00:00,CEMOJE,Filled,Sell,-9.0,1079.19,6.798897,,13
-2019-01-17 16:00:00,GTKILW,Filled,Sell,-9.0,1087.08,6.848604,,14
-2019-01-17 16:00:00,MCCZID,Filled,Buy,3.0,41.89,0.087969,,15
-2019-01-17 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,16
-2019-01-17 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,17
-2019-01-18 16:00:00,OCHCAU,Filled,Sell,-1.0,44.61,0.031227,,16
-2019-01-18 16:00:00,MCCZID,Filled,Sell,-2.0,42.62,0.059668,,17
-2019-01-18 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,18
-2019-01-22 16:00:00,OCHCAU,Filled,Sell,-226.0,44.88,7.100016000000001,,18
-2019-01-22 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,19
-2019-01-23 16:00:00,MCCZID,Filled,Buy,93.0,41.95,2.730945,,19
-2019-01-23 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,20
-2019-01-24 16:00:00,MCCZID,Filled,Sell,-3.0,41.74,0.087654,,20
-2019-01-24 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,21
-2019-01-25 16:00:00,MCCZID,Filled,Buy,9.0,41.14,0.25918199999999997,,21
-2019-01-25 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,22
-2019-01-28 16:00:00,MCCZID,Filled,Buy,3.0,40.5,0.08505,,22
-2019-01-28 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,23
-2019-01-29 16:00:00,MCCZID,Filled,Sell,-36.0,39.53,0.996156,,23
-2019-01-29 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,24
-2019-01-30 16:00:00,MCCZID,Filled,Buy,88.0,40.81,2.513896,,24
-2019-01-30 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,25
-2019-01-30 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,26
-2019-01-31 16:00:00,MCCZID,Filled,Sell,-8.0,41.41,0.231896,,25
-2019-01-31 16:00:00,ISIJLH,Filled,Buy,540.0,29.47,11.13966,,26
-2019-01-31 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,27
-2019-01-31 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,28
-2019-02-01 16:00:00,MCCZID,Filled,Sell,-7.0,42.84,0.209916,,27
-2019-02-01 16:00:00,ISIJLH,Filled,Sell,-540.0,30.25,11.4345,,28
-2019-02-01 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,29
-2019-02-01 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,30
-2019-02-01 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,31
-2019-02-04 16:00:00,LUZLYG,Filled,Buy,560.0,28.46,11.15632,,29
-2019-02-04 16:00:00,MCCZID,Filled,Sell,-374.0,42.8,11.20504,,30
-2019-02-04 16:00:00,RUKNMV,Filled,Buy,325.0,48.85,11.113375,,31
-2019-02-04 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,32
-2019-02-04 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,33
-2019-02-04 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,34
-2019-02-05 16:00:00,LUZLYG,Filled,Sell,-560.0,28.85,11.3092,,32
-2019-02-05 16:00:00,ISIJLH,Filled,Buy,536.0,29.64,11.120928,,33
-2019-02-05 16:00:00,RUKNMV,Filled,Sell,-1.0,49.22,0.034454,,34
-2019-02-05 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,35
-2019-02-05 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,36
-2019-02-05 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,37
-2019-02-06 16:00:00,LUZLYG,Filled,Buy,355.0,28.63,7.114554999999999,,35
-2019-02-06 16:00:00,ISIJLH,Filled,Sell,-192.0,29.74,3.997056,,36
-2019-02-06 16:00:00,RUKNMV,Filled,Sell,-117.0,49.15,4.025385,,37
-2019-02-06 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,38
-2019-02-06 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,39
-2019-02-06 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,40
-2019-02-06 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,41
-2019-02-07 16:00:00,LUZLYG,Filled,Sell,-355.0,28.59,7.104615000000001,,38
-2019-02-07 16:00:00,MCCZID,Filled,Buy,239.0,42.09,7.041657,,39
-2019-02-07 16:00:00,ISIJLH,Filled,Sell,-2.0,29.5,0.0413,,40
-2019-02-07 16:00:00,RUKNMV,Filled,Sell,-207.0,49.11,7.116039000000001,,41
-2019-02-07 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,42
-2019-02-07 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,43
-2019-02-07 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,44
-2019-02-08 16:00:00,CEMOJE,Filled,Buy,9.0,1097.14,6.911982,,42
-2019-02-08 16:00:00,MCCZID,Filled,Buy,3.0,41.6,0.08736000000000001,,43
-2019-02-08 16:00:00,ISIJLH,Filled,Buy,1.0,29.4,0.02058,,44
-2019-02-08 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,45
-2019-02-08 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,46
-2019-02-08 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,47
-2019-02-11 16:00:00,CEMOJE,Filled,Sell,-9.0,1088.34,6.856541999999999,,45
-2019-02-11 16:00:00,MCCZID,Filled,Sell,-5.0,42.29,0.14801499999999998,,46
-2019-02-11 16:00:00,ISIJLH,Filled,Sell,-5.0,29.6,0.1036,,47
-2019-02-11 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,48
-2019-02-11 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,49
-2019-02-11 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,50
-2019-02-12 16:00:00,FFNDVM,Filled,Buy,1202.0,8.38,7.050932,,48
-2019-02-12 16:00:00,MCCZID,Filled,Buy,3.0,41.71,0.087591,,49
-2019-02-12 16:00:00,ISIJLH,Filled,Sell,-1.0,29.85,0.020895,,50
-2019-02-12 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,51
-2019-02-12 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,52
-2019-02-12 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,53
-2019-02-12 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,54
-2019-02-13 16:00:00,FFNDVM,Filled,Sell,-18.0,8.44,0.106344,,51
-2019-02-13 16:00:00,LMRIBF,Filled,Buy,60.0,165.38,6.9459599999999995,,52
-2019-02-13 16:00:00,MCCZID,Filled,Sell,-1.0,41.95,0.029365,,53
-2019-02-13 16:00:00,ISIJLH,Filled,Sell,-1.0,29.79,0.020853,,54
-2019-02-13 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,55
-2019-02-13 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,56
-2019-02-13 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,57
-2019-02-13 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,58
-2019-02-13 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,59
-2019-02-13 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,60
-2019-02-13 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,61
-2019-02-14 16:00:00,FFNDVM,Filled,Buy,6.0,8.38,0.035196,,55
-2019-02-14 16:00:00,LMRIBF,Filled,Buy,1.0,163.19,0.114233,,56
-2019-02-14 16:00:00,CEMOJE,Filled,Buy,8.0,1123.96,6.294176,,57
-2019-02-14 16:00:00,GTKILW,Filled,Buy,8.0,1124.62,6.297871999999999,,58
-2019-02-14 16:00:00,BPSPGV,Filled,Buy,93.0,106.31,6.920781,,59
-2019-02-14 16:00:00,MCCZID,Filled,Buy,1.0,41.74,0.029218,,60
-2019-02-14 16:00:00,ISIJLH,Filled,Sell,-1.0,29.73,0.020811,,61
-2019-02-14 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,62
-2019-02-14 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,63
-2019-02-14 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,64
-2019-02-14 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,65
-2019-02-14 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,66
-2019-02-15 16:00:00,XUEHVZ,Filled,Buy,6.0,1619.82,6.803244,,62
-2019-02-15 16:00:00,LUZLYG,Filled,Buy,352.0,28.75,7.084,,63
-2019-02-15 16:00:00,FFNDVM,Filled,Sell,-1.0,8.5,0.00595,,64
-2019-02-15 16:00:00,MCCZID,Filled,Sell,-2.0,42.36,0.059304,,65
-2019-02-15 16:00:00,ISIJLH,Filled,Buy,1.0,30.0,0.021,,66
-2019-02-15 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,67
-2019-02-15 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,68
-2019-02-15 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,69
-2019-02-15 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,70
-2019-02-15 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,71
-2019-02-19 16:00:00,LUZLYG,Filled,Sell,-8.0,28.88,0.16172799999999998,,67
-2019-02-19 16:00:00,FFNDVM,Filled,Sell,-1189.0,8.54,7.107842,,68
-2019-02-19 16:00:00,BPSPGV,Filled,Sell,-1.0,107.79,0.075453,,69
-2019-02-19 16:00:00,MCCZID,Filled,Sell,-238.0,42.23,7.035518,,70
-2019-02-19 16:00:00,ISIJLH,Filled,Sell,-8.0,30.48,0.170688,,71
-2019-02-19 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,72
-2019-02-19 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,73
-2019-02-19 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,74
-2019-02-19 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,75
-2019-02-19 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,76
-2019-02-19 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,77
-2019-02-19 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,78
-2019-02-19 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,79
-2019-02-20 16:00:00,XUEHVZ,Filled,Buy,3.0,1627.11,3.416931,,72
-2019-02-20 16:00:00,LUZLYG,Filled,Buy,193.0,29.1,3.93141,,73
-2019-02-20 16:00:00,LMRIBF,Filled,Buy,35.0,162.02,3.96949,,74
-2019-02-20 16:00:00,CEMOJE,Filled,Buy,5.0,1114.2,3.8997,,75
-2019-02-20 16:00:00,GTKILW,Filled,Buy,5.0,1123.83,3.933405,,76
-2019-02-20 16:00:00,BPSPGV,Filled,Buy,52.0,107.84,3.925376,,77
-2019-02-20 16:00:00,MCCZID,Filled,Buy,367.0,42.49,10.915681,,78
-2019-02-20 16:00:00,ISIJLH,Filled,Sell,-328.0,30.63,7.032647999999999,,79
-2019-02-20 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,80
-2019-02-20 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,81
-2019-02-20 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,82
-2019-02-20 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,83
-2019-02-20 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,84
-2019-02-21 16:00:00,LUZLYG,Filled,Sell,-5.0,29.34,0.10269,,80
-2019-02-21 16:00:00,CEMOJE,Filled,Buy,1.0,1113.06,0.779142,,81
-2019-02-21 16:00:00,BPSPGV,Filled,Buy,2.0,106.93,0.149702,,82
-2019-02-21 16:00:00,MCCZID,Filled,Buy,4.0,42.0,0.1176,,83
-2019-02-21 16:00:00,ISIJLH,Filled,Buy,507.0,30.85,10.948665,,84
-2019-02-21 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,85
-2019-02-21 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,86
-2019-02-21 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,87
-2019-02-21 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,88
-2019-02-22 16:00:00,LUZLYG,Filled,Buy,2.0,29.04,0.040656,,85
-2019-02-22 16:00:00,LMRIBF,Filled,Buy,1.0,160.58,0.112406,,86
-2019-02-22 16:00:00,GTKILW,Filled,Buy,1.0,1103.12,0.7721839999999999,,87
-2019-02-22 16:00:00,BPSPGV,Filled,Sell,-146.0,110.0,11.242,,88
-2019-02-22 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,89
-2019-02-22 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,90
-2019-02-22 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,91
-2019-02-22 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,92
-2019-02-22 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,93
-2019-02-25 16:00:00,LUZLYG,Filled,Buy,4.0,29.16,0.081648,,89
-2019-02-25 16:00:00,LMRIBF,Filled,Sell,-1.0,163.0,0.1141,,90
-2019-02-25 16:00:00,BPSPGV,Filled,Buy,141.0,111.62,11.016894,,91
-2019-02-25 16:00:00,MCCZID,Filled,Sell,-7.0,43.06,0.210994,,92
-2019-02-25 16:00:00,ISIJLH,Filled,Sell,-5.0,31.25,0.109375,,93
-2019-02-25 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,94
-2019-02-25 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,95
-2019-02-25 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,96
-2019-02-25 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,97
-2019-02-25 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,98
-2019-02-25 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,99
-2019-02-26 16:00:00,LUZLYG,Filled,Sell,-3.0,29.07,0.061047,,94
-2019-02-26 16:00:00,OCHCAU,Filled,Buy,308.0,50.59,10.907204,,95
-2019-02-26 16:00:00,LMRIBF,Filled,Sell,-1.0,164.22,0.114954,,96
-2019-02-26 16:00:00,BPSPGV,Filled,Sell,-1.0,111.17,0.077819,,97
-2019-02-26 16:00:00,MCCZID,Filled,Sell,-364.0,42.95,10.94366,,98
-2019-02-26 16:00:00,ISIJLH,Filled,Buy,1.0,31.13,0.021791,,99
-2019-02-26 16:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,100
-2019-02-26 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,101
-2019-02-26 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,102
-2019-02-26 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,103
-2019-02-26 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,104
-2019-02-27 16:00:00,XUEHVZ,Filled,Sell,-9.0,1639.97,10.331811,,100
-2019-02-27 16:00:00,OCHCAU,Filled,Sell,-2.0,51.25,0.07175,,101
-2019-02-27 16:00:00,GTKILW,Filled,Sell,-1.0,1123.85,0.7866949999999999,,102
-2019-02-27 16:00:00,BPSPGV,Filled,Sell,-1.0,111.69,0.078183,,103
-2019-02-27 16:00:00,ISIJLH,Filled,Sell,-503.0,31.23,10.996083,,104
-2019-02-27 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,105
-2019-02-27 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,106
-2019-02-27 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,107
-2019-02-27 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,108
-2019-02-27 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,109
-2019-02-27 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,110
-2019-02-27 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,111
-2019-02-28 16:00:00,LUZLYG,Filled,Buy,131.0,29.55,2.709735,,105
-2019-02-28 16:00:00,OCHCAU,Filled,Sell,-306.0,51.55,11.04201,,106
-2019-02-28 16:00:00,LMRIBF,Filled,Buy,25.0,162.37,2.841475,,107
-2019-02-28 16:00:00,CEMOJE,Filled,Buy,3.0,1114.86,2.341206,,108
-2019-02-28 16:00:00,GTKILW,Filled,Buy,4.0,1126.92,3.155376,,109
-2019-02-28 16:00:00,BPSPGV,Filled,Sell,-139.0,112.04,10.901492,,110
-2019-02-28 16:00:00,ISIJLH,Filled,Buy,633.0,31.08,13.771548,,111
-2019-02-28 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,112
-2019-02-28 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,113
-2019-02-28 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,114
-2019-02-28 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,115
-2019-02-28 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,116
-2019-03-01 16:00:00,LUZLYG,Filled,Buy,10.0,29.33,0.20530999999999996,,112
-2019-03-01 16:00:00,LMRIBF,Filled,Sell,-120.0,162.58,13.656720000000002,,113
-2019-03-01 16:00:00,CEMOJE,Filled,Sell,-17.0,1117.75,13.301225,,114
-2019-03-01 16:00:00,GTKILW,Filled,Sell,-17.0,1128.61,13.430459,,115
-2019-03-01 16:00:00,ISIJLH,Filled,Sell,-1.0,31.2,0.02184,,116
-2019-03-01 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,117
-2019-03-01 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,118
-2019-03-01 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,119
-2019-03-01 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,120
-2019-03-01 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,121
-2019-03-01 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,122
-2019-03-04 16:00:00,LUZLYG,Filled,Sell,-676.0,29.3,13.86476,,117
-2019-03-04 16:00:00,OCHCAU,Filled,Buy,382.0,51.63,13.805862,,118
-2019-03-04 16:00:00,CEMOJE,Filled,Buy,17.0,1145.97,13.637043,,119
-2019-03-04 16:00:00,BPSPGV,Filled,Buy,174.0,112.87,13.747566,,120
-2019-03-04 16:00:00,MCCZID,Filled,Buy,453.0,43.56,13.812876,,121
-2019-03-04 16:00:00,ISIJLH,Filled,Buy,6.0,30.92,0.129864,,122
-2019-03-04 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,123
-2019-03-04 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,124
-2019-03-04 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,125
-2019-03-04 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,126
-2019-03-04 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,127
-2019-03-04 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,128
-2019-03-04 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,129
-2019-03-05 16:00:00,OCHCAU,Filled,Sell,-99.0,51.12,3.542616,,123
-2019-03-05 16:00:00,LMRIBF,Filled,Buy,86.0,167.35,10.07447,,124
-2019-03-05 16:00:00,CEMOJE,Filled,Sell,-17.0,1145.87,13.635852999999996,,125
-2019-03-05 16:00:00,GTKILW,Filled,Buy,12.0,1150.68,9.665712,,126
-2019-03-05 16:00:00,BPSPGV,Filled,Sell,-174.0,112.19,13.664742,,127
-2019-03-05 16:00:00,MCCZID,Filled,Sell,-116.0,43.19,3.507028,,128
-2019-03-05 16:00:00,ISIJLH,Filled,Sell,-154.0,29.98,3.231844,,129
-2019-03-05 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,130
-2019-03-05 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,131
-2019-03-05 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,132
-2019-03-05 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,133
-2019-03-05 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,134
-2019-03-06 16:00:00,OCHCAU,Filled,Sell,-86.0,51.19,3.081638,,130
-2019-03-06 16:00:00,LMRIBF,Filled,Sell,-27.0,172.6,3.26214,,131
-2019-03-06 16:00:00,GTKILW,Filled,Sell,-12.0,1174.18,9.863112,,132
-2019-03-06 16:00:00,MCCZID,Filled,Sell,-337.0,42.84,10.105956,,133
-2019-03-06 16:00:00,ISIJLH,Filled,Sell,-146.0,30.0,3.066,,134
-2019-03-06 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,135
-2019-03-06 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,136
-2019-03-06 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,137
-2019-03-06 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,138
-2019-03-07 16:00:00,OCHCAU,Filled,Sell,-1.0,51.52,0.036064,,135
-2019-03-07 16:00:00,LMRIBF,Filled,Sell,-59.0,171.48,7.082123999999999,,136
-2019-03-07 16:00:00,BGDRAI,Filled,Buy,1111.0,9.09,7.069293,,137
-2019-03-07 16:00:00,ISIJLH,Filled,Sell,-338.0,29.9,7.074339999999999,,138
-2019-03-07 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,139
-2019-03-07 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,140
-2019-03-08 16:00:00,OCHCAU,Filled,Sell,-196.0,50.71,6.957412,,139
-2019-03-08 16:00:00,BGDRAI,Filled,Sell,-1111.0,9.33,7.255940999999999,,140
-2019-03-08 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,141
-2019-03-08 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,142
-2019-03-11 16:00:00,CEMOJE,Filled,Buy,8.0,1137.85,6.37196,,141
-2019-03-11 16:00:00,MCCZID,Filled,Buy,250.0,41.0,7.175,,142
-2019-03-11 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,143
-2019-03-11 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,144
-2019-03-11 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,145
-2019-03-12 16:00:00,LUZLYG,Filled,Buy,502.0,29.0,10.1906,,143
-2019-03-12 16:00:00,CEMOJE,Filled,Buy,4.0,1174.87,3.289636,,144
-2019-03-12 16:00:00,MCCZID,Filled,Sell,-250.0,41.65,7.28875,,145
-2019-03-12 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,146
-2019-03-12 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,147
-2019-03-13 16:00:00,LMRIBF,Filled,Buy,84.0,172.35,10.13418,,146
-2019-03-13 16:00:00,CEMOJE,Filled,Sell,-12.0,1192.37,10.015908,,147
-2019-03-13 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,148
-2019-03-13 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,149
-2019-03-13 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,150
-2019-03-14 16:00:00,LUZLYG,Filled,Sell,-6.0,29.31,0.123102,,148
-2019-03-14 16:00:00,LMRIBF,Filled,Sell,-1.0,169.18,0.118426,,149
-2019-03-14 16:00:00,CEMOJE,Filled,Buy,12.0,1191.55,10.00902,,150
-2019-03-14 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,151
-2019-03-14 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,152
-2019-03-14 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,153
-2019-03-15 16:00:00,LUZLYG,Filled,Sell,-156.0,29.45,3.21594,,151
-2019-03-15 16:00:00,LMRIBF,Filled,Sell,-25.0,167.15,2.925125,,152
-2019-03-15 16:00:00,CEMOJE,Filled,Sell,-4.0,1185.11,3.3183079999999996,,153
-2019-03-15 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,154
-2019-03-15 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,155
-2019-03-15 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,156
-2019-03-18 16:00:00,LUZLYG,Filled,Buy,2.0,29.38,0.041131999999999995,,154
-2019-03-18 16:00:00,LMRIBF,Filled,Sell,-58.0,163.4,6.634040000000001,,155
-2019-03-18 16:00:00,CEMOJE,Filled,Sell,-8.0,1184.54,6.633424,,156
-2019-03-18 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,157
-2019-03-18 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,158
-2019-03-18 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,159
-2019-03-19 16:00:00,LUZLYG,Filled,Sell,-6.0,30.0,0.126,,157
-2019-03-19 16:00:00,CEMOJE,Filled,Buy,8.0,1180.91,6.6130960000000005,,158
-2019-03-19 16:00:00,BPSPGV,Filled,Buy,85.0,118.0,7.021,,159
-2019-03-19 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,160
-2019-03-19 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,161
-2019-03-19 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,162
-2019-03-20 16:00:00,LUZLYG,Filled,Buy,2.0,29.62,0.041468,,160
-2019-03-20 16:00:00,CEMOJE,Filled,Sell,-8.0,1199.02,6.714512,,161
-2019-03-20 16:00:00,BPSPGV,Filled,Sell,-85.0,117.28,6.978159999999999,,162
-2019-03-20 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,163
-2019-03-21 16:00:00,LUZLYG,Filled,Buy,12.0,28.4,0.23855999999999997,,163
-2019-03-21 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,164
-2019-03-22 16:00:00,LUZLYG,Filled,Buy,5.0,27.85,0.097475,,164
-2019-03-22 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,165
-2019-03-22 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,166
-2019-03-25 16:00:00,LUZLYG,Filled,Buy,15.0,26.94,0.28287,,165
-2019-03-25 16:00:00,HECLON,Filled,Buy,164.0,61.1,7.014279999999999,,166
-2019-03-25 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,167
-2019-03-25 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,168
-2019-03-26 16:00:00,LUZLYG,Filled,Buy,170.0,27.15,3.23085,,167
-2019-03-26 16:00:00,HECLON,Filled,Buy,76.0,61.0,3.2452,,168
-2019-03-26 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,169
-2019-03-26 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,170
-2019-03-27 16:00:00,LUZLYG,Filled,Sell,-540.0,27.12,10.25136,,169
-2019-03-27 16:00:00,HECLON,Filled,Sell,-3.0,61.35,0.128835,,170
-2019-03-27 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,171
-2019-03-28 16:00:00,HECLON,Filled,Sell,-237.0,60.86,10.096674,,171
-2019-03-28 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,172
-2019-03-29 16:00:00,FFNDVM,Filled,Buy,1655.0,8.78,10.17163,,172
-2019-03-29 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,173
-2019-04-01 16:00:00,FFNDVM,Filled,Sell,-1655.0,8.88,10.28748,,173
-2019-04-01 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,174
-2019-04-02 16:00:00,OCHCAU,Filled,Buy,204.0,55.0,7.854,,174
-2019-04-02 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,175
-2019-04-03 16:00:00,OCHCAU,Filled,Sell,-204.0,55.46,7.919688,,175
-2019-04-09 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,176
-2019-04-10 16:00:00,OCHCAU,Filled,Buy,183.0,55.27,7.080087,,176
-2019-04-11 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,177
-2019-04-12 16:00:00,OCHCAU,Filled,Sell,-1.0,55.93,0.039151,,177
-2019-04-12 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,178
-2019-04-15 16:00:00,OCHCAU,Filled,Sell,-4.0,56.4,0.15792,,178
-2019-04-15 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,179
-2019-04-16 16:00:00,OCHCAU,Filled,Sell,-1.0,56.63,0.039641,,179
-2019-04-16 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,180
-2019-04-17 16:00:00,OCHCAU,Filled,Sell,-1.0,57.22,0.040054,,180
-2019-04-17 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,181
-2019-04-18 16:00:00,OCHCAU,Filled,Buy,2.0,56.63,0.079282,,181
-2019-04-18 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,182
-2019-04-22 16:00:00,OCHCAU,Filled,Sell,-178.0,56.16,6.997535999999999,,182
-2019-04-23 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,183
-2019-04-23 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,184
-2019-04-24 16:00:00,OCHCAU,Filled,Buy,242.0,56.62,9.591428,,183
-2019-04-24 16:00:00,MCCZID,Filled,Buy,348.0,39.45,9.61002,,184
-2019-04-24 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,185
-2019-04-24 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,186
-2019-04-25 16:00:00,OCHCAU,Filled,Sell,-1.0,56.46,0.039522,,185
-2019-04-25 16:00:00,MCCZID,Filled,Sell,-348.0,39.28,9.568608,,186
-2019-04-25 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,187
-2019-04-26 16:00:00,OCHCAU,Filled,Sell,-241.0,56.02,9.450574,,187
-2019-05-01 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,188
-2019-05-02 16:00:00,BPSPGV,Filled,Buy,120.0,127.98,10.75032,,188
-2019-05-02 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,189
-2019-05-02 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,190
-2019-05-03 16:00:00,BPSPGV,Filled,Buy,2.0,127.42,0.178388,,189
-2019-05-03 16:00:00,ISIJLH,Filled,Buy,503.0,30.63,10.784823,,190
-2019-05-03 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,191
-2019-05-03 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,192
-2019-05-06 16:00:00,BPSPGV,Filled,Sell,-3.0,126.33,0.265293,,191
-2019-05-06 16:00:00,ISIJLH,Filled,Sell,-503.0,30.49,10.735529,,192
-2019-05-06 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,193
-2019-05-06 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,194
-2019-05-06 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,195
-2019-05-06 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,196
-2019-05-07 16:00:00,XUEHVZ,Filled,Buy,8.0,1957.03,10.959368,,193
-2019-05-07 16:00:00,GTKILW,Filled,Buy,13.0,1194.82,10.872862,,194
-2019-05-07 16:00:00,BPSPGV,Filled,Buy,3.0,126.5,0.26565,,195
-2019-05-07 16:00:00,ISIJLH,Filled,Buy,511.0,30.47,10.899119,,196
-2019-05-07 16:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,197
-2019-05-07 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,198
-2019-05-07 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,199
-2019-05-07 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,200
-2019-05-08 16:00:00,XUEHVZ,Filled,Sell,-3.0,1920.48,4.033008000000001,,197
-2019-05-08 16:00:00,GTKILW,Filled,Sell,-13.0,1175.65,10.698415,,198
-2019-05-08 16:00:00,BPSPGV,Filled,Sell,-43.0,125.44,3.775744,,199
-2019-05-08 16:00:00,ISIJLH,Filled,Sell,-511.0,30.4,10.87408,,200
-2019-05-08 16:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,201
-2019-05-08 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,202
-2019-05-08 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,203
-2019-05-09 16:00:00,XUEHVZ,Filled,Sell,-5.0,1925.62,6.7396699999999985,,201
-2019-05-09 16:00:00,BPSPGV,Filled,Buy,1.0,124.26,0.086982,,202
-2019-05-09 16:00:00,ISIJLH,Filled,Buy,333.0,30.17,7.032627000000001,,203
-2019-05-09 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,204
-2019-05-09 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,205
-2019-05-09 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,206
-2019-05-09 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,207
-2019-05-09 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,208
-2019-05-09 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,209
-2019-05-10 16:00:00,SMDIFE,Filled,Buy,50.0,197.47,6.91145,,204
-2019-05-10 16:00:00,XUEHVZ,Filled,Buy,5.0,1903.74,6.66309,,205
-2019-05-10 16:00:00,FFNDVM,Filled,Buy,991.0,10.32,7.158984,,206
-2019-05-10 16:00:00,ZIJVRO,Filled,Buy,216.0,46.48,7.0277759999999985,,207
-2019-05-10 16:00:00,BPSPGV,Filled,Sell,-80.0,125.23,7.01288,,208
-2019-05-10 16:00:00,ISIJLH,Filled,Sell,-333.0,30.25,7.0512749999999995,,209
-2019-05-10 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,210
-2019-05-10 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,211
-2019-05-10 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,212
-2019-05-13 16:00:00,SMDIFE,Filled,Buy,1.0,187.48,0.131236,,210
-2019-05-13 16:00:00,FFNDVM,Filled,Sell,-18.0,10.15,0.12789,,211
-2019-05-13 16:00:00,ZIJVRO,Filled,Buy,2.0,45.2,0.06328,,212
-2019-05-13 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,213
-2019-05-13 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,214
-2019-05-13 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,215
-2019-05-13 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,216
-2019-05-13 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,217
-2019-05-13 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,218
-2019-05-13 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,219
-2019-05-13 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,220
-2019-05-14 16:00:00,SMDIFE,Filled,Buy,31.0,186.33,4.043361,,213
-2019-05-14 16:00:00,XUEHVZ,Filled,Buy,3.0,1833.7,3.85077,,214
-2019-05-14 16:00:00,FFNDVM,Filled,Buy,552.0,10.15,3.92196,,215
-2019-05-14 16:00:00,LMRIBF,Filled,Buy,84.0,182.72,10.743936,,216
-2019-05-14 16:00:00,CEMOJE,Filled,Buy,13.0,1128.99,10.273809,,217
-2019-05-14 16:00:00,GTKILW,Filled,Buy,13.0,1132.11,10.302200999999998,,218
-2019-05-14 16:00:00,ZIJVRO,Filled,Buy,125.0,45.26,3.96025,,219
-2019-05-14 16:00:00,BPSPGV,Filled,Buy,124.0,123.89,10.753652,,220
-2019-05-14 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,221
-2019-05-14 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,222
-2019-05-14 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,223
-2019-05-14 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,224
-2019-05-14 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,225
-2019-05-14 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,226
-2019-05-15 16:00:00,SMDIFE,Filled,Sell,-1.0,186.27,0.130389,,221
-2019-05-15 16:00:00,FFNDVM,Filled,Sell,-24.0,10.2,0.17135999999999998,,222
-2019-05-15 16:00:00,LMRIBF,Filled,Buy,1.0,180.08,0.126056,,223
-2019-05-15 16:00:00,CEMOJE,Filled,Sell,-13.0,1117.25,10.166975,,224
-2019-05-15 16:00:00,ZIJVRO,Filled,Sell,-3.0,44.83,0.094143,,225
-2019-05-15 16:00:00,BPSPGV,Filled,Sell,-124.0,124.06,10.768408,,226
-2019-05-15 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,227
-2019-05-15 16:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,228
-2019-05-15 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,229
-2019-05-15 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,230
-2019-05-15 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,231
-2019-05-15 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,232
-2019-05-16 16:00:00,SMDIFE,Filled,Sell,-1.0,189.88,0.132916,,227
-2019-05-16 16:00:00,XUEHVZ,Filled,Sell,-8.0,1882.36,10.541216,,228
-2019-05-16 16:00:00,FFNDVM,Filled,Sell,-1501.0,10.31,10.832717,,229
-2019-05-16 16:00:00,LMRIBF,Filled,Sell,-85.0,185.18,11.01821,,230
-2019-05-16 16:00:00,GTKILW,Filled,Sell,-13.0,1164.5,10.59695,,231
-2019-05-16 16:00:00,ZIJVRO,Filled,Sell,-3.0,45.58,0.095718,,232
-2019-05-16 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,233
-2019-05-16 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,234
-2019-05-17 16:00:00,SMDIFE,Filled,Buy,1.0,187.04,0.130928,,233
-2019-05-17 16:00:00,ZIJVRO,Filled,Buy,1.0,45.14,0.031598,,234
-2019-05-17 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,235
-2019-05-17 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,236
-2019-05-17 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,237
-2019-05-17 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,238
-2019-05-20 16:00:00,SMDIFE,Filled,Sell,-81.0,183.5,10.40445,,235
-2019-05-20 16:00:00,CEMOJE,Filled,Buy,8.0,1161.99,6.507144,,236
-2019-05-20 16:00:00,GTKILW,Filled,Buy,8.0,1163.32,6.5145919999999995,,237
-2019-05-20 16:00:00,ZIJVRO,Filled,Sell,-116.0,44.0,3.5728,,238
-2019-05-20 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,239
-2019-05-20 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,240
-2019-05-21 16:00:00,GTKILW,Filled,Sell,-8.0,1143.45,6.40332,,239
-2019-05-21 16:00:00,ZIJVRO,Filled,Buy,7.0,44.32,0.217168,,240
-2019-05-21 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,241
-2019-05-21 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,242
-2019-05-21 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,243
-2019-05-22 16:00:00,FFNDVM,Filled,Buy,976.0,10.17,6.948144,,241
-2019-05-22 16:00:00,CEMOJE,Filled,Sell,-8.0,1148.39,6.4309840000000005,,242
-2019-05-22 16:00:00,ZIJVRO,Filled,Sell,-5.0,44.15,0.154525,,243
-2019-05-22 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,244
-2019-05-22 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,245
-2019-05-22 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,246
-2019-05-22 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,247
-2019-05-22 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,248
-2019-05-22 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,249
-2019-05-23 16:00:00,SMDIFE,Filled,Buy,54.0,179.72,6.793416,,244
-2019-05-23 16:00:00,FFNDVM,Filled,Buy,26.0,9.85,0.17926999999999998,,245
-2019-05-23 16:00:00,LMRIBF,Filled,Buy,53.0,182.42,6.767782,,246
-2019-05-23 16:00:00,CEMOJE,Filled,Buy,8.0,1150.2,6.441120000000001,,247
-2019-05-23 16:00:00,GTKILW,Filled,Buy,8.0,1150.78,6.444368,,248
-2019-05-23 16:00:00,ZIJVRO,Filled,Buy,3.0,43.33,0.090993,,249
-2019-05-23 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,250
-2019-05-23 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,251
-2019-05-23 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,252
-2019-05-23 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,253
-2019-05-23 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,254
-2019-05-24 16:00:00,SMDIFE,Filled,Buy,1.0,180.2,0.12614,,250
-2019-05-24 16:00:00,XUEHVZ,Filled,Buy,5.0,1818.85,6.365975,,251
-2019-05-24 16:00:00,FFNDVM,Filled,Buy,12.0,9.92,0.083328,,252
-2019-05-24 16:00:00,LMRIBF,Filled,Buy,2.0,182.32,0.255248,,253
-2019-05-24 16:00:00,ZIJVRO,Filled,Sell,-3.0,44.59,0.093639,,254
-2019-05-24 16:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,255
-2019-05-24 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,256
-2019-05-24 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,257
-2019-05-28 16:00:00,XUEHVZ,Filled,Sell,-5.0,1819.7,6.36895,,255
-2019-05-28 16:00:00,FFNDVM,Filled,Buy,2.0,9.87,0.013818,,256
-2019-05-28 16:00:00,LMRIBF,Filled,Sell,-55.0,181.54,6.98929,,257
-2019-05-28 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,258
-2019-05-28 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,259
-2019-05-28 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,260
-2019-05-28 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,261
-2019-05-28 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,262
-2019-05-29 16:00:00,SMDIFE,Filled,Sell,-55.0,176.44,6.792940000000001,,258
-2019-05-29 16:00:00,FFNDVM,Filled,Buy,531.0,9.7,3.60549,,259
-2019-05-29 16:00:00,CEMOJE,Filled,Buy,5.0,1135.26,3.97341,,260
-2019-05-29 16:00:00,GTKILW,Filled,Sell,-8.0,1140.99,6.389544,,261
-2019-05-29 16:00:00,ZIJVRO,Filled,Sell,-224.0,43.36,6.798848,,262
-2019-05-29 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,263
-2019-05-29 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,264
-2019-05-29 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,265
-2019-05-29 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,266
-2019-05-30 16:00:00,OCHCAU,Filled,Buy,361.0,53.44,13.504288,,263
-2019-05-30 16:00:00,FFNDVM,Filled,Buy,430.0,9.74,2.93174,,264
-2019-05-30 16:00:00,LMRIBF,Filled,Buy,105.0,183.08,13.45638,,265
-2019-05-30 16:00:00,CEMOJE,Filled,Buy,4.0,1115.74,3.124072,,266
-2019-05-30 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,267
-2019-05-30 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,268
-2019-05-30 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,269
-2019-05-30 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,270
-2019-05-31 16:00:00,OCHCAU,Filled,Sell,-361.0,52.79,13.340032999999998,,267
-2019-05-31 16:00:00,FFNDVM,Filled,Sell,-6.0,9.5,0.0399,,268
-2019-05-31 16:00:00,LMRIBF,Filled,Sell,-1.0,180.28,0.126196,,269
-2019-05-31 16:00:00,CEMOJE,Filled,Sell,-17.0,1114.66,13.264454,,270
-2019-05-31 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,271
-2019-05-31 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,272
-2019-05-31 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,273
-2019-06-03 16:00:00,OCHCAU,Filled,Buy,368.0,52.05,13.408079999999998,,271
-2019-06-03 16:00:00,FFNDVM,Filled,Buy,43.0,9.61,0.289261,,272
-2019-06-03 16:00:00,LMRIBF,Filled,Buy,4.0,175.0,0.49,,273
-2019-06-03 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,274
-2019-06-03 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,275
-2019-06-03 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,276
-2019-06-04 16:00:00,OCHCAU,Filled,Sell,-90.0,52.48,3.30624,,274
-2019-06-04 16:00:00,FFNDVM,Filled,Sell,-513.0,9.73,3.494043,,275
-2019-06-04 16:00:00,LMRIBF,Filled,Sell,-21.0,163.81,2.408007,,276
-2019-06-04 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,277
-2019-06-04 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,278
-2019-06-04 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,279
-2019-06-05 16:00:00,OCHCAU,Filled,Sell,-278.0,53.85,10.47921,,277
-2019-06-05 16:00:00,FFNDVM,Filled,Sell,-45.0,9.87,0.310905,,278
-2019-06-05 16:00:00,LMRIBF,Filled,Sell,-1.0,167.49,0.117243,,279
-2019-06-05 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,280
-2019-06-05 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,281
-2019-06-05 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,282
-2019-06-05 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,283
-2019-06-05 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,284
-2019-06-06 16:00:00,FFNDVM,Filled,Buy,21.0,9.71,0.142737,,280
-2019-06-06 16:00:00,LMRIBF,Filled,Sell,-1.0,168.3,0.11781,,281
-2019-06-06 16:00:00,CEMOJE,Filled,Buy,13.0,1042.05,9.482655,,282
-2019-06-06 16:00:00,GTKILW,Filled,Buy,13.0,1041.12,9.474192,,283
-2019-06-06 16:00:00,MCCZID,Filled,Buy,340.0,42.67,10.15546,,284
-2019-06-06 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,285
-2019-06-06 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,286
-2019-06-06 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,287
-2019-06-06 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,288
-2019-06-07 16:00:00,FFNDVM,Filled,Buy,5.0,9.76,0.034159999999999996,,285
-2019-06-07 16:00:00,CEMOJE,Filled,Sell,-13.0,1043.4,9.49494,,286
-2019-06-07 16:00:00,GTKILW,Filled,Sell,-13.0,1041.84,9.480743999999998,,287
-2019-06-07 16:00:00,MCCZID,Filled,Sell,-2.0,43.02,0.060228,,288
-2019-06-07 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,289
-2019-06-07 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,290
-2019-06-07 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,291
-2019-06-10 16:00:00,FFNDVM,Filled,Sell,-1.0,9.89,0.006923,,289
-2019-06-10 16:00:00,LMRIBF,Filled,Sell,-85.0,174.54,10.38513,,290
-2019-06-10 16:00:00,MCCZID,Filled,Sell,-2.0,43.2,0.060480000000000006,,291
-2019-06-10 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,292
-2019-06-10 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,293
-2019-06-11 16:00:00,FFNDVM,Filled,Sell,-1481.0,9.87,10.232229,,292
-2019-06-11 16:00:00,MCCZID,Filled,Sell,-1.0,43.15,0.030205,,293
-2019-06-11 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,294
-2019-06-12 16:00:00,MCCZID,Filled,Sell,-335.0,42.51,9.968595,,294
-2019-06-13 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,295
-2019-06-14 16:00:00,MCCZID,Filled,Buy,237.0,42.57,7.062363,,295
-2019-06-14 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,296
-2019-06-17 16:00:00,MCCZID,Filled,Sell,-237.0,42.73,7.088906999999999,,296
-2019-06-19 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,297
-2019-06-20 16:00:00,FFNDVM,Filled,Buy,1003.0,10.13,7.112273000000001,,297
-2019-06-20 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,298
-2019-06-21 16:00:00,FFNDVM,Filled,Sell,-10.0,10.05,0.07035,,298
-2019-06-21 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,299
-2019-06-24 16:00:00,FFNDVM,Filled,Sell,-993.0,9.95,6.916244999999999,,299
-2019-06-24 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,300
-2019-06-25 16:00:00,FFNDVM,Filled,Buy,1002.0,9.97,6.992958000000001,,300
-2019-06-25 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,301
-2019-06-25 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,302
-2019-06-26 16:00:00,YIVYGH,Filled,Buy,338.0,42.66,10.093355999999998,,301
-2019-06-26 16:00:00,FFNDVM,Filled,Buy,466.0,9.87,3.219594,,302
-2019-06-26 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,303
-2019-06-26 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,304
-2019-06-27 16:00:00,YIVYGH,Filled,Sell,-338.0,42.29,10.005814,,303
-2019-06-27 16:00:00,FFNDVM,Filled,Sell,-10.0,10.04,0.07028,,304
-2019-06-27 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,305
-2019-06-28 16:00:00,FFNDVM,Filled,Sell,-1458.0,10.2,10.41012,,305
-2019-07-03 13:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,306
-2019-07-05 16:00:00,FFNDVM,Filled,Buy,1358.0,10.17,9.667602,,306
-2019-07-05 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,307
-2019-07-08 16:00:00,FFNDVM,Filled,Sell,-1358.0,10.2,9.69612,,307
-2019-07-10 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,308
-2019-07-11 16:00:00,HECLON,Filled,Buy,141.0,71.4,7.047180000000001,,308
-2019-07-11 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,309
-2019-07-12 16:00:00,HECLON,Filled,Sell,-141.0,71.83,7.089621,,309
-2019-07-23 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,310
-2019-07-24 16:00:00,BPSPGV,Filled,Buy,98.0,139.0,9.5354,,310
-2019-07-24 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,311
-2019-07-25 16:00:00,BPSPGV,Filled,Sell,-1.0,140.28,0.098196,,311
-2019-07-25 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,312
-2019-07-25 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,313
-2019-07-26 16:00:00,BPSPGV,Filled,Sell,-97.0,140.36,9.530444,,312
-2019-07-26 16:00:00,ISIJLH,Filled,Buy,404.0,33.7,9.53036,,313
-2019-07-26 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,314
-2019-07-26 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,315
-2019-07-29 16:00:00,FFNDVM,Filled,Buy,1428.0,9.58,9.576168,,314
-2019-07-29 16:00:00,ISIJLH,Filled,Sell,-4.0,34.15,0.09562,,315
-2019-07-29 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,316
-2019-07-29 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,317
-2019-07-29 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,318
-2019-07-30 16:00:00,FFNDVM,Filled,Sell,-191.0,9.53,1.274161,,316
-2019-07-30 16:00:00,BPSPGV,Filled,Buy,84.0,140.0,8.232,,317
-2019-07-30 16:00:00,ISIJLH,Filled,Sell,-400.0,34.44,9.6432,,318
-2019-07-30 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,319
-2019-07-31 16:00:00,FFNDVM,Filled,Sell,-1237.0,9.55,8.269345,,319
-2019-07-31 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,320
-2019-07-31 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,321
-2019-07-31 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,322
-2019-07-31 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,323
-2019-08-01 16:00:00,LUZLYG,Filled,Buy,500.0,30.57,10.6995,,320
-2019-08-01 16:00:00,HECLON,Filled,Buy,215.0,70.76,10.64938,,321
-2019-08-01 16:00:00,FFNDVM,Filled,Buy,1610.0,9.55,10.762850000000002,,322
-2019-08-01 16:00:00,BPSPGV,Filled,Buy,28.0,137.0,2.6852,,323
-2019-08-01 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,324
-2019-08-01 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,325
-2019-08-01 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,326
-2019-08-01 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,327
-2019-08-01 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,328
-2019-08-02 16:00:00,LUZLYG,Filled,Sell,-500.0,29.36,10.276,,324
-2019-08-02 16:00:00,HECLON,Filled,Sell,-215.0,67.56,10.16778,,325
-2019-08-02 16:00:00,FFNDVM,Filled,Sell,-1610.0,9.26,10.43602,,326
-2019-08-02 16:00:00,BPSPGV,Filled,Sell,-1.0,138.05,0.096635,,327
-2019-08-02 16:00:00,ISIJLH,Filled,Buy,449.0,33.83,10.632769,,328
-2019-08-02 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,329
-2019-08-05 16:00:00,ISIJLH,Filled,Sell,-1.0,33.76,0.023631999999999997,,329
-2019-08-05 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,330
-2019-08-05 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,331
-2019-08-05 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,332
-2019-08-05 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,333
-2019-08-06 16:00:00,CEMOJE,Filled,Buy,13.0,1148.14,10.448074,,330
-2019-08-06 16:00:00,GTKILW,Filled,Buy,13.0,1149.24,10.458084,,331
-2019-08-06 16:00:00,BPSPGV,Filled,Buy,4.0,133.91,0.374948,,332
-2019-08-06 16:00:00,ISIJLH,Filled,Buy,9.0,33.5,0.21105,,333
-2019-08-06 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,334
-2019-08-06 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,335
-2019-08-06 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,336
-2019-08-06 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,337
-2019-08-07 16:00:00,CEMOJE,Filled,Sell,-13.0,1172.06,10.665746,,334
-2019-08-07 16:00:00,GTKILW,Filled,Sell,-13.0,1175.74,10.699234,,335
-2019-08-07 16:00:00,BPSPGV,Filled,Sell,-115.0,133.59,10.753995,,336
-2019-08-07 16:00:00,ISIJLH,Filled,Sell,-457.0,33.62,10.755038,,337
-2019-08-07 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,338
-2019-08-07 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,339
-2019-08-07 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,340
-2019-08-08 16:00:00,HECLON,Filled,Buy,154.0,65.9,7.10402,,338
-2019-08-08 16:00:00,CEMOJE,Filled,Buy,8.0,1172.39,6.565384000000001,,339
-2019-08-08 16:00:00,GTKILW,Filled,Buy,8.0,1177.82,6.595791999999999,,340
-2019-08-08 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,341
-2019-08-08 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,342
-2019-08-08 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,343
-2019-08-09 16:00:00,HECLON,Filled,Sell,-154.0,66.26,7.142828000000001,,341
-2019-08-09 16:00:00,GTKILW,Filled,Sell,-8.0,1206.67,6.757352,,342
-2019-08-09 16:00:00,ISIJLH,Filled,Buy,291.0,34.38,7.003206,,343
-2019-08-09 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,344
-2019-08-09 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,345
-2019-08-12 16:00:00,GTKILW,Filled,Buy,8.0,1185.6,6.639359999999999,,344
-2019-08-12 16:00:00,ISIJLH,Filled,Buy,3.0,34.42,0.072282,,345
-2019-08-12 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,346
-2019-08-12 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,347
-2019-08-12 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,348
-2019-08-12 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,349
-2019-08-13 16:00:00,CEMOJE,Filled,Buy,5.0,1171.29,4.099515,,346
-2019-08-13 16:00:00,GTKILW,Filled,Buy,5.0,1169.01,4.091535,,347
-2019-08-13 16:00:00,ZIJVRO,Filled,Buy,336.0,45.49,10.699248,,348
-2019-08-13 16:00:00,ISIJLH,Filled,Buy,150.0,34.46,3.6183,,349
-2019-08-13 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,350
-2019-08-13 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,351
-2019-08-13 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,352
-2019-08-13 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,353
-2019-08-13 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,354
-2019-08-14 16:00:00,FFNDVM,Filled,Buy,1657.0,9.11,10.566688999999998,,350
-2019-08-14 16:00:00,CEMOJE,Filled,Sell,-1.0,1199.86,0.8399019999999999,,351
-2019-08-14 16:00:00,GTKILW,Filled,Sell,-13.0,1194.47,10.869677,,352
-2019-08-14 16:00:00,ZIJVRO,Filled,Sell,-336.0,46.1,10.84272,,353
-2019-08-14 16:00:00,ISIJLH,Filled,Sell,-4.0,34.6,0.09688,,354
-2019-08-14 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,355
-2019-08-14 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,356
-2019-08-14 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,357
-2019-08-14 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,358
-2019-08-14 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,359
-2019-08-15 16:00:00,FFNDVM,Filled,Buy,45.0,9.04,0.28475999999999996,,355
-2019-08-15 16:00:00,CEMOJE,Filled,Buy,1.0,1163.43,0.814401,,356
-2019-08-15 16:00:00,GTKILW,Filled,Buy,13.0,1157.66,10.534706000000002,,357
-2019-08-15 16:00:00,MCCZID,Filled,Buy,447.0,34.29,10.729341,,358
-2019-08-15 16:00:00,ISIJLH,Filled,Buy,9.0,34.16,0.21520799999999995,,359
-2019-08-15 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,360
-2019-08-15 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,361
-2019-08-15 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,362
-2019-08-15 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,363
-2019-08-16 16:00:00,FFNDVM,Filled,Sell,-1702.0,8.94,10.651116,,360
-2019-08-16 16:00:00,GTKILW,Filled,Sell,-13.0,1168.24,10.630984,,361
-2019-08-16 16:00:00,MCCZID,Filled,Sell,-3.0,34.74,0.072954,,362
-2019-08-16 16:00:00,ISIJLH,Filled,Sell,-449.0,34.51,10.846493,,363
-2019-08-16 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,364
-2019-08-16 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,365
-2019-08-16 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,366
-2019-08-19 16:00:00,OCHCAU,Filled,Buy,212.0,47.92,7.111328,,364
-2019-08-19 16:00:00,CEMOJE,Filled,Sell,-13.0,1173.48,10.678668,,365
-2019-08-19 16:00:00,MCCZID,Filled,Sell,-157.0,34.86,3.831113999999999,,366
-2019-08-19 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,367
-2019-08-19 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,368
-2019-08-19 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,369
-2019-08-19 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,370
-2019-08-20 16:00:00,OCHCAU,Filled,Sell,-212.0,48.53,7.201852000000001,,367
-2019-08-20 16:00:00,CEMOJE,Filled,Buy,8.0,1194.18,6.6874080000000005,,368
-2019-08-20 16:00:00,GTKILW,Filled,Buy,8.0,1204.73,6.746488,,369
-2019-08-20 16:00:00,MCCZID,Filled,Sell,-287.0,35.12,7.055607999999999,,370
-2019-08-21 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,371
-2019-08-21 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,372
-2019-08-22 16:00:00,FFNDVM,Filled,Buy,1102.0,9.07,6.996598,,371
-2019-08-22 16:00:00,ZIJVRO,Filled,Buy,211.0,47.28,6.983256,,372
-2019-08-22 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,373
-2019-08-22 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,374
-2019-08-22 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,375
-2019-08-23 16:00:00,FFNDVM,Filled,Sell,-1102.0,8.9,6.865460000000001,,373
-2019-08-23 16:00:00,GTKILW,Filled,Sell,-8.0,1193.08,6.681247999999999,,374
-2019-08-23 16:00:00,ZIJVRO,Filled,Sell,-211.0,46.37,6.8488489999999995,,375
-2019-08-23 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,376
-2019-08-26 16:00:00,CEMOJE,Filled,Sell,-8.0,1151.74,6.449744,,376
-2019-08-27 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,377
-2019-08-27 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,378
-2019-08-28 16:00:00,CEMOJE,Filled,Buy,12.0,1168.45,9.81498,,377
-2019-08-28 16:00:00,GTKILW,Filled,Buy,12.0,1167.17,9.804228,,378
-2019-08-28 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,379
-2019-08-28 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,380
-2019-08-28 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,381
-2019-08-29 16:00:00,OCHCAU,Filled,Buy,408.0,47.59,13.591704,,379
-2019-08-29 16:00:00,CEMOJE,Filled,Buy,4.0,1172.85,3.2839799999999997,,380
-2019-08-29 16:00:00,GTKILW,Filled,Buy,4.0,1178.91,3.300948,,381
-2019-08-29 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,382
-2019-08-29 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,383
-2019-08-30 16:00:00,OCHCAU,Filled,Sell,-3.0,47.52,0.099792,,382
-2019-08-30 16:00:00,ISIJLH,Filled,Buy,545.0,35.17,13.417355,,383
-2019-08-30 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,384
-2019-08-30 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,385
-2019-09-03 16:00:00,OCHCAU,Filled,Buy,4.0,46.63,0.130564,,384
-2019-09-03 16:00:00,ISIJLH,Filled,Sell,-2.0,35.1,0.04914,,385
-2019-09-03 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,386
-2019-09-03 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,387
-2019-09-03 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,388
-2019-09-03 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,389
-2019-09-04 16:00:00,OCHCAU,Filled,Sell,-409.0,47.02,13.461826,,386
-2019-09-04 16:00:00,CEMOJE,Filled,Sell,-5.0,1164.1,4.07435,,387
-2019-09-04 16:00:00,GTKILW,Filled,Sell,-5.0,1171.63,4.1007050000000005,,388
-2019-09-04 16:00:00,ISIJLH,Filled,Sell,-543.0,35.55,13.512555,,389
-2019-09-04 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,390
-2019-09-05 16:00:00,ISIJLH,Filled,Buy,376.0,35.9,9.44888,,390
-2019-09-05 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,391
-2019-09-06 16:00:00,ISIJLH,Filled,Sell,-1.0,35.95,0.025165000000000003,,391
-2019-09-06 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,392
-2019-09-09 16:00:00,ISIJLH,Filled,Sell,-4.0,37.75,0.1057,,392
-2019-09-09 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,393
-2019-09-10 16:00:00,ISIJLH,Filled,Sell,-371.0,37.19,9.658243,,393
-2019-09-10 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,394
-2019-09-10 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,395
-2019-09-11 16:00:00,CEMOJE,Filled,Sell,-3.0,1203.75,2.527875,,394
-2019-09-11 16:00:00,GTKILW,Filled,Sell,-3.0,1203.16,2.5266360000000003,,395
-2019-09-17 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,396
-2019-09-18 16:00:00,ISIJLH,Filled,Buy,268.0,36.75,6.8943,,396
-2019-09-18 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,397
-2019-09-19 16:00:00,ISIJLH,Filled,Buy,3.0,37.0,0.0777,,397
-2019-09-19 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,398
-2019-09-19 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,399
-2019-09-20 16:00:00,SMDIFE,Filled,Buy,45.0,221.5,6.97725,,398
-2019-09-20 16:00:00,ISIJLH,Filled,Sell,-3.0,37.31,0.078351,,399
-2019-09-20 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,400
-2019-09-20 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,401
-2019-09-23 16:00:00,YIVYGH,Filled,Buy,215.0,46.17,6.9485850000000005,,400
-2019-09-23 16:00:00,ISIJLH,Filled,Sell,-268.0,37.63,7.059388,,401
-2019-09-23 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,402
-2019-09-23 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,403
-2019-09-24 16:00:00,SMDIFE,Filled,Sell,-45.0,221.08,6.9640200000000005,,402
-2019-09-24 16:00:00,YIVYGH,Filled,Sell,-215.0,46.62,7.01631,,403
-2019-09-24 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,404
-2019-09-24 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,405
-2019-09-25 16:00:00,CEMOJE,Filled,Buy,3.0,1219.79,2.561559,,404
-2019-09-25 16:00:00,GTKILW,Filled,Buy,3.0,1211.09,2.5432889999999997,,405
-2019-09-25 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,406
-2019-09-25 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,407
-2019-09-26 16:00:00,CEMOJE,Filled,Sell,-1.0,1244.48,0.871136,,406
-2019-09-26 16:00:00,GTKILW,Filled,Sell,-1.0,1246.61,0.8726269999999999,,407
-2019-09-27 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,408
-2019-09-27 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,409
-2019-09-30 16:00:00,FFNDVM,Filled,Buy,1485.0,9.14,9.50103,,408
-2019-09-30 16:00:00,CEMOJE,Filled,Buy,1.0,1224.57,0.8571989999999999,,409
-2019-09-30 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,410
-2019-09-30 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,411
-2019-09-30 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,412
-2019-10-01 16:00:00,FFNDVM,Filled,Sell,-1485.0,9.19,9.553005,,410
-2019-10-01 16:00:00,CEMOJE,Filled,Sell,-11.0,1220.7,9.39939,,411
-2019-10-01 16:00:00,GTKILW,Filled,Sell,-10.0,1210.63,8.47441,,412
-2019-10-04 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,413
-2019-10-07 16:00:00,RUKNMV,Filled,Buy,235.0,48.91,8.045694999999998,,413
-2019-10-07 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,414
-2019-10-08 16:00:00,RUKNMV,Filled,Buy,2.0,48.25,0.06755,,414
-2019-10-08 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,415
-2019-10-08 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,416
-2019-10-09 16:00:00,ISIJLH,Filled,Buy,266.0,37.08,6.9042959999999995,,415
-2019-10-09 16:00:00,RUKNMV,Filled,Sell,-29.0,48.18,0.978054,,416
-2019-10-09 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,417
-2019-10-09 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,418
-2019-10-10 16:00:00,ISIJLH,Filled,Buy,3.0,37.0,0.0777,,417
-2019-10-10 16:00:00,RUKNMV,Filled,Sell,-1.0,48.32,0.033824,,418
-2019-10-11 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,419
-2019-10-11 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,420
-2019-10-14 16:00:00,ISIJLH,Filled,Sell,-4.0,37.58,0.105224,,419
-2019-10-14 16:00:00,RUKNMV,Filled,Sell,-5.0,49.15,0.172025,,420
-2019-10-14 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,421
-2019-10-15 16:00:00,ISIJLH,Filled,Buy,1.0,37.46,0.026222,,421
-2019-10-15 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,422
-2019-10-15 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,423
-2019-10-15 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,424
-2019-10-16 16:00:00,HECLON,Filled,Buy,140.0,71.11,6.96878,,422
-2019-10-16 16:00:00,ISIJLH,Filled,Sell,-3.0,37.9,0.07959,,423
-2019-10-16 16:00:00,RUKNMV,Filled,Sell,-3.0,50.14,0.105294,,424
-2019-10-16 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,425
-2019-10-16 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,426
-2019-10-16 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,427
-2019-10-17 16:00:00,HECLON,Filled,Sell,-140.0,70.08,6.867839999999999,,425
-2019-10-17 16:00:00,ISIJLH,Filled,Buy,1.0,37.8,0.026459999999999997,,426
-2019-10-17 16:00:00,RUKNMV,Filled,Sell,-199.0,49.9,6.9510700000000005,,427
-2019-10-17 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,428
-2019-10-18 16:00:00,ISIJLH,Filled,Sell,-1.0,37.81,0.026467,,428
-2019-10-18 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,429
-2019-10-21 16:00:00,ISIJLH,Filled,Sell,-4.0,38.42,0.107576,,429
-2019-10-21 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,430
-2019-10-21 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,431
-2019-10-22 16:00:00,ISIJLH,Filled,Buy,2.0,37.83,0.052961999999999995,,430
-2019-10-22 16:00:00,RUKNMV,Filled,Buy,197.0,50.46,6.9584340000000005,,431
-2019-10-22 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,432
-2019-10-22 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,433
-2019-10-23 16:00:00,ISIJLH,Filled,Buy,43.0,38.0,1.1438,,432
-2019-10-23 16:00:00,RUKNMV,Filled,Buy,32.0,50.76,1.137024,,433
-2019-10-23 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,434
-2019-10-23 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,435
-2019-10-24 16:00:00,ISIJLH,Filled,Sell,-304.0,37.74,8.031072,,434
-2019-10-24 16:00:00,RUKNMV,Filled,Sell,-2.0,50.98,0.07137199999999999,,435
-2019-10-25 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,436
-2019-10-28 16:00:00,RUKNMV,Filled,Sell,-2.0,51.98,0.07277199999999999,,436
-2019-10-28 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,437
-2019-10-28 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,438
-2019-10-29 16:00:00,YIVYGH,Filled,Buy,255.0,45.19,8.066415,,437
-2019-10-29 16:00:00,RUKNMV,Filled,Sell,-1.0,51.53,0.036071,,438
-2019-10-29 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,439
-2019-10-29 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,440
-2019-10-30 16:00:00,YIVYGH,Filled,Sell,-255.0,45.35,8.094975,,439
-2019-10-30 16:00:00,RUKNMV,Filled,Sell,-2.0,51.88,0.072632,,440
-2019-10-30 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,441
-2019-10-30 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,442
-2019-10-30 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,443
-2019-10-31 16:00:00,YIVYGH,Filled,Buy,429.0,44.75,13.438425,,441
-2019-10-31 16:00:00,MCCZID,Filled,Buy,498.0,38.39,13.382754,,442
-2019-10-31 16:00:00,RUKNMV,Filled,Buy,146.0,51.73,5.286806,,443
-2019-10-31 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,444
-2019-10-31 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,445
-2019-10-31 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,446
-2019-11-01 16:00:00,YIVYGH,Filled,Sell,-429.0,45.19,13.570557,,444
-2019-11-01 16:00:00,MCCZID,Filled,Buy,2.0,38.67,0.054138,,445
-2019-11-01 16:00:00,RUKNMV,Filled,Buy,3.0,52.18,0.109578,,446
-2019-11-01 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,447
-2019-11-01 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,448
-2019-11-01 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,449
-2019-11-04 16:00:00,YIVYGH,Filled,Buy,429.0,45.17,13.564551,,447
-2019-11-04 16:00:00,BPSPGV,Filled,Buy,133.0,144.96,13.495776,,448
-2019-11-04 16:00:00,RUKNMV,Filled,Sell,-4.0,52.52,0.14705600000000002,,449
-2019-11-04 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,450
-2019-11-04 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,451
-2019-11-04 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,452
-2019-11-04 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,453
-2019-11-05 16:00:00,YIVYGH,Filled,Sell,-74.0,43.89,2.273502,,450
-2019-11-05 16:00:00,BPSPGV,Filled,Sell,-26.0,145.0,2.639,,451
-2019-11-05 16:00:00,MCCZID,Filled,Sell,-500.0,38.05,13.3175,,452
-2019-11-05 16:00:00,RUKNMV,Filled,Sell,-72.0,52.83,2.662632,,453
-2019-11-05 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,454
-2019-11-05 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,455
-2019-11-05 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,456
-2019-11-05 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,457
-2019-11-06 16:00:00,YIVYGH,Filled,Sell,-128.0,44.32,3.971072,,454
-2019-11-06 16:00:00,BPSPGV,Filled,Sell,-107.0,144.17,10.798333,,455
-2019-11-06 16:00:00,MCCZID,Filled,Buy,269.0,37.62,7.083845999999999,,456
-2019-11-06 16:00:00,RUKNMV,Filled,Sell,-295.0,53.29,11.004385,,457
-2019-11-06 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,458
-2019-11-07 16:00:00,MCCZID,Filled,Sell,-1.0,37.36,0.026152,,458
-2019-11-07 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,459
-2019-11-07 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,460
-2019-11-08 16:00:00,YIVYGH,Filled,Sell,-227.0,44.68,7.099652000000001,,459
-2019-11-08 16:00:00,MCCZID,Filled,Buy,5.0,36.86,0.12901,,460
-2019-11-08 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,461
-2019-11-11 16:00:00,MCCZID,Filled,Buy,1.0,36.91,0.025837,,461
-2019-11-11 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,462
-2019-11-11 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,463
-2019-11-11 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,464
-2019-11-12 16:00:00,BPSPGV,Filled,Buy,106.0,146.2,10.84804,,462
-2019-11-12 16:00:00,MCCZID,Filled,Buy,148.0,36.88,3.8207680000000006,,463
-2019-11-12 16:00:00,ISIJLH,Filled,Buy,396.0,39.4,10.92168,,464
-2019-11-12 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,465
-2019-11-12 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,466
-2019-11-12 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,467
-2019-11-13 16:00:00,HECLON,Filled,Buy,207.0,74.3,10.76607,,465
-2019-11-13 16:00:00,MCCZID,Filled,Sell,-1.0,36.91,0.025837,,466
-2019-11-13 16:00:00,ISIJLH,Filled,Buy,2.0,39.17,0.054838000000000005,,467
-2019-11-13 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,468
-2019-11-13 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,469
-2019-11-13 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,470
-2019-11-13 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,471
-2019-11-14 16:00:00,BPSPGV,Filled,Sell,-2.0,147.11,0.20595400000000005,,468
-2019-11-14 16:00:00,MCCZID,Filled,Sell,-2.0,36.6,0.05124,,469
-2019-11-14 16:00:00,ISIJLH,Filled,Sell,-7.0,38.95,0.190855,,470
-2019-11-14 16:00:00,RUKNMV,Filled,Buy,288.0,53.27,10.739232,,471
-2019-11-14 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,472
-2019-11-14 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,473
-2019-11-14 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,474
-2019-11-14 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,475
-2019-11-15 16:00:00,ZIJVRO,Filled,Buy,265.0,58.17,10.790535,,472
-2019-11-15 16:00:00,BPSPGV,Filled,Sell,-104.0,149.0,10.8472,,473
-2019-11-15 16:00:00,ISIJLH,Filled,Buy,3.0,39.17,0.082257,,474
-2019-11-15 16:00:00,RUKNMV,Filled,Sell,-2.0,53.75,0.07525,,475
-2019-11-15 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,476
-2019-11-15 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,477
-2019-11-15 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,478
-2019-11-15 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,479
-2019-11-15 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,480
-2019-11-15 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,481
-2019-11-18 16:00:00,HECLON,Filled,Sell,-73.0,74.37,3.800307,,476
-2019-11-18 16:00:00,ZIJVRO,Filled,Sell,-265.0,57.71,10.705205,,477
-2019-11-18 16:00:00,BPSPGV,Filled,Buy,66.0,150.0,6.93,,478
-2019-11-18 16:00:00,MCCZID,Filled,Sell,-152.0,37.4,3.97936,,479
-2019-11-18 16:00:00,ISIJLH,Filled,Sell,-142.0,39.25,3.90145,,480
-2019-11-18 16:00:00,RUKNMV,Filled,Sell,-101.0,53.84,3.806488,,481
-2019-11-18 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,482
-2019-11-18 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,483
-2019-11-18 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,484
-2019-11-18 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,485
-2019-11-19 16:00:00,BPSPGV,Filled,Sell,-66.0,150.85,6.96927,,482
-2019-11-19 16:00:00,MCCZID,Filled,Buy,1.0,37.45,0.026215,,483
-2019-11-19 16:00:00,ISIJLH,Filled,Sell,-1.0,38.92,0.027244,,484
-2019-11-19 16:00:00,RUKNMV,Filled,Sell,-185.0,54.15,7.012425,,485
-2019-11-19 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,486
-2019-11-19 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,487
-2019-11-19 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,488
-2019-11-19 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,489
-2019-11-19 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,490
-2019-11-20 16:00:00,LUZLYG,Filled,Buy,303.0,32.8,6.95688,,486
-2019-11-20 16:00:00,HECLON,Filled,Sell,-1.0,74.7,0.05229,,487
-2019-11-20 16:00:00,MCCZID,Filled,Sell,-268.0,37.59,7.051884,,488
-2019-11-20 16:00:00,ISIJLH,Filled,Buy,11.0,37.24,0.286748,,489
-2019-11-20 16:00:00,RUKNMV,Filled,Buy,184.0,53.71,6.917847999999999,,490
-2019-11-20 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,491
-2019-11-20 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,492
-2019-11-20 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,493
-2019-11-20 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,494
-2019-11-21 16:00:00,LUZLYG,Filled,Buy,2.0,32.82,0.045948,,491
-2019-11-21 16:00:00,HECLON,Filled,Buy,2.0,74.01,0.103614,,492
-2019-11-21 16:00:00,ISIJLH,Filled,Buy,6.0,37.06,0.155652,,493
-2019-11-21 16:00:00,RUKNMV,Filled,Buy,2.0,53.84,0.075376,,494
-2019-11-21 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,495
-2019-11-21 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,496
-2019-11-22 16:00:00,LUZLYG,Filled,Sell,-305.0,32.96,7.0369600000000005,,495
-2019-11-22 16:00:00,ISIJLH,Filled,Sell,-3.0,37.76,0.079296,,496
-2019-11-22 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,497
-2019-11-22 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,498
-2019-11-22 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,499
-2019-11-25 16:00:00,HECLON,Filled,Sell,-2.0,74.9,0.10486,,497
-2019-11-25 16:00:00,ISIJLH,Filled,Sell,-1.0,37.87,0.026509,,498
-2019-11-25 16:00:00,RUKNMV,Filled,Sell,-3.0,54.4,0.11424,,499
-2019-11-25 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,500
-2019-11-25 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,501
-2019-11-26 16:00:00,ISIJLH,Filled,Buy,6.0,37.21,0.156282,,500
-2019-11-26 16:00:00,RUKNMV,Filled,Buy,3.0,53.98,0.113358,,501
-2019-11-26 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,502
-2019-11-26 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,503
-2019-11-26 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,504
-2019-11-26 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,505
-2019-11-26 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,506
-2019-11-26 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,507
-2019-11-27 16:00:00,LUZLYG,Filled,Buy,460.0,33.49,10.78378,,502
-2019-11-27 16:00:00,HECLON,Filled,Buy,70.0,75.84,3.71616,,503
-2019-11-27 16:00:00,ZIJVRO,Filled,Buy,260.0,58.53,10.65246,,504
-2019-11-27 16:00:00,BPSPGV,Filled,Buy,101.0,152.33,10.769731000000002,,505
-2019-11-27 16:00:00,ISIJLH,Filled,Buy,140.0,37.42,3.66716,,506
-2019-11-27 16:00:00,RUKNMV,Filled,Buy,99.0,54.14,3.751902,,507
-2019-11-27 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,508
-2019-11-27 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,509
-2019-11-27 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,510
-2019-11-27 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,511
-2019-11-27 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,512
-2019-11-27 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,513
-2019-11-27 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,514
-2019-11-29 13:00:00,SMDIFE,Filled,Buy,57.0,266.2,10.62138,,508
-2019-11-29 13:00:00,LUZLYG,Filled,Sell,-1.0,33.37,0.023359,,509
-2019-11-29 13:00:00,HECLON,Filled,Sell,-1.0,75.49,0.052842999999999994,,510
-2019-11-29 13:00:00,ZIJVRO,Filled,Buy,2.0,58.15,0.08141,,511
-2019-11-29 13:00:00,BPSPGV,Filled,Sell,-101.0,152.0,10.7464,,512
-2019-11-29 13:00:00,ISIJLH,Filled,Sell,-410.0,37.74,10.83138,,513
-2019-11-29 13:00:00,RUKNMV,Filled,Sell,-3.0,54.29,0.114009,,514
-2019-11-29 13:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,515
-2019-11-29 13:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,516
-2019-11-29 13:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,517
-2019-11-29 13:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,518
-2019-11-29 13:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,519
-2019-12-02 16:00:00,SMDIFE,Filled,Sell,-57.0,267.33,10.666467,,515
-2019-12-02 16:00:00,LUZLYG,Filled,Buy,1.0,33.45,0.023415,,516
-2019-12-02 16:00:00,HECLON,Filled,Buy,2.0,75.44,0.105616,,517
-2019-12-02 16:00:00,ZIJVRO,Filled,Buy,2.0,58.55,0.08197,,518
-2019-12-02 16:00:00,RUKNMV,Filled,Sell,-1.0,54.3,0.038009999999999995,,519
-2019-12-02 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,520
-2019-12-02 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,521
-2019-12-02 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,522
-2019-12-02 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,523
-2019-12-03 16:00:00,LUZLYG,Filled,Sell,-92.0,32.84,2.1148960000000003,,520
-2019-12-03 16:00:00,HECLON,Filled,Sell,-39.0,73.2,1.99836,,521
-2019-12-03 16:00:00,ZIJVRO,Filled,Sell,-51.0,56.83,2.028831,,522
-2019-12-03 16:00:00,RUKNMV,Filled,Sell,-52.0,52.99,1.928836,,523
-2019-12-03 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,524
-2019-12-03 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,525
-2019-12-03 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,526
-2019-12-03 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,527
-2019-12-03 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,528
-2019-12-03 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,529
-2019-12-04 16:00:00,SMDIFE,Filled,Buy,47.0,261.0,8.5869,,524
-2019-12-04 16:00:00,LUZLYG,Filled,Buy,6.0,33.08,0.138936,,525
-2019-12-04 16:00:00,HECLON,Filled,Buy,2.0,73.56,0.102984,,526
-2019-12-04 16:00:00,ZIJVRO,Filled,Buy,6.0,56.61,0.23776199999999997,,527
-2019-12-04 16:00:00,MCCZID,Filled,Buy,323.0,38.16,8.627975999999999,,528
-2019-12-04 16:00:00,RUKNMV,Filled,Buy,5.0,52.58,0.18402999999999997,,529
-2019-12-04 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,530
-2019-12-04 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,531
-2019-12-04 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,532
-2019-12-04 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,533
-2019-12-04 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,534
-2019-12-04 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,535
-2019-12-04 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,536
-2019-12-05 16:00:00,SMDIFE,Filled,Buy,8.0,263.8,1.47728,,530
-2019-12-05 16:00:00,LUZLYG,Filled,Buy,61.0,33.16,1.4159319999999995,,531
-2019-12-05 16:00:00,HECLON,Filled,Buy,27.0,74.51,1.4082390000000002,,532
-2019-12-05 16:00:00,OCHCAU,Filled,Buy,329.0,44.05,10.144715,,533
-2019-12-05 16:00:00,ZIJVRO,Filled,Sell,-219.0,56.41,8.647653,,534
-2019-12-05 16:00:00,MCCZID,Filled,Buy,55.0,38.35,1.476475,,535
-2019-12-05 16:00:00,RUKNMV,Filled,Buy,37.0,53.31,1.380729,,536
-2019-12-05 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,537
-2019-12-05 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,538
-2019-12-05 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,539
-2019-12-05 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,540
-2019-12-05 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,541
-2019-12-05 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,542
-2019-12-05 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,543
-2019-12-06 16:00:00,SMDIFE,Filled,Sell,-55.0,267.58,10.30183,,537
-2019-12-06 16:00:00,LUZLYG,Filled,Buy,1.0,33.69,0.023583,,538
-2019-12-06 16:00:00,HECLON,Filled,Sell,-1.0,75.91,0.053137,,539
-2019-12-06 16:00:00,OCHCAU,Filled,Buy,3.0,43.89,0.092169,,540
-2019-12-06 16:00:00,ZIJVRO,Filled,Buy,257.0,56.67,10.194933,,541
-2019-12-06 16:00:00,BPSPGV,Filled,Buy,96.0,151.0,10.1472,,542
-2019-12-06 16:00:00,MCCZID,Filled,Buy,1.0,38.24,0.026768,,543
-2019-12-06 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,544
-2019-12-06 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,545
-2019-12-06 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,546
-2019-12-06 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,547
-2019-12-06 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,548
-2019-12-06 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,549
-2019-12-06 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,550
-2019-12-09 16:00:00,LUZLYG,Filled,Sell,-7.0,33.49,0.164101,,544
-2019-12-09 16:00:00,HECLON,Filled,Sell,-3.0,75.25,0.158025,,545
-2019-12-09 16:00:00,OCHCAU,Filled,Sell,-2.0,43.89,0.061446,,546
-2019-12-09 16:00:00,ZIJVRO,Filled,Sell,-257.0,56.5,10.16435,,547
-2019-12-09 16:00:00,BPSPGV,Filled,Sell,-96.0,151.05,10.15056,,548
-2019-12-09 16:00:00,MCCZID,Filled,Sell,-2.0,38.2,0.05348000000000001,,549
-2019-12-09 16:00:00,RUKNMV,Filled,Sell,-5.0,54.18,0.18963,,550
-2019-12-09 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,551
-2019-12-09 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,552
-2019-12-09 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,553
-2019-12-09 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,554
-2019-12-09 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,555
-2019-12-09 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,556
-2019-12-10 16:00:00,SMDIFE,Filled,Buy,54.0,268.67,10.155726,,551
-2019-12-10 16:00:00,LUZLYG,Filled,Buy,2.0,33.4,0.04676,,552
-2019-12-10 16:00:00,HECLON,Filled,Sell,-190.0,75.1,9.9883,,553
-2019-12-10 16:00:00,OCHCAU,Filled,Sell,-1.0,43.84,0.030688000000000003,,554
-2019-12-10 16:00:00,ZIJVRO,Filled,Buy,255.0,56.73,10.126305,,555
-2019-12-10 16:00:00,RUKNMV,Filled,Buy,2.0,53.46,0.074844,,556
-2019-12-10 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,557
-2019-12-10 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,558
-2019-12-10 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,559
-2019-12-10 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,560
-2019-12-10 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,561
-2019-12-10 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,562
-2019-12-10 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,563
-2019-12-11 16:00:00,SMDIFE,Filled,Sell,-54.0,268.73,10.157994,,557
-2019-12-11 16:00:00,LUZLYG,Filled,Sell,-431.0,33.55,10.122035,,558
-2019-12-11 16:00:00,OCHCAU,Filled,Sell,-101.0,44.3,3.1320099999999993,,559
-2019-12-11 16:00:00,CEMOJE,Filled,Buy,7.0,1351.52,6.6224479999999994,,560
-2019-12-11 16:00:00,ZIJVRO,Filled,Sell,-255.0,56.91,10.158435,,561
-2019-12-11 16:00:00,MCCZID,Filled,Sell,-116.0,38.36,3.1148320000000003,,562
-2019-12-11 16:00:00,RUKNMV,Filled,Sell,-81.0,53.74,3.0470580000000003,,563
-2019-12-11 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,564
-2019-12-11 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,565
-2019-12-11 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,566
-2019-12-11 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,567
-2019-12-12 16:00:00,OCHCAU,Filled,Sell,-228.0,44.52,7.105392000000001,,564
-2019-12-12 16:00:00,MCCZID,Filled,Sell,-261.0,38.21,6.980967,,565
-2019-12-12 16:00:00,ISIJLH,Filled,Buy,264.0,38.2,7.059360000000001,,566
-2019-12-12 16:00:00,RUKNMV,Filled,Buy,2.0,53.37,0.07471799999999999,,567
-2019-12-12 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,568
-2019-12-12 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,569
-2019-12-12 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,570
-2019-12-12 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,571
-2019-12-13 16:00:00,BPSPGV,Filled,Buy,65.0,153.23,6.971964999999999,,568
-2019-12-13 16:00:00,MCCZID,Filled,Buy,261.0,38.52,7.037604000000001,,569
-2019-12-13 16:00:00,ISIJLH,Filled,Sell,-264.0,38.2,7.059360000000001,,570
-2019-12-13 16:00:00,RUKNMV,Filled,Sell,-4.0,53.99,0.151172,,571
-2019-12-13 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,572
-2019-12-13 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,573
-2019-12-13 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,574
-2019-12-13 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,575
-2019-12-16 16:00:00,GTKILW,Filled,Buy,7.0,1349.45,6.612305,,572
-2019-12-16 16:00:00,BPSPGV,Filled,Sell,-65.0,155.11,7.057505000000001,,573
-2019-12-16 16:00:00,MCCZID,Filled,Sell,-1.0,38.7,0.027090000000000003,,574
-2019-12-16 16:00:00,ISIJLH,Filled,Buy,260.0,38.38,6.9851600000000005,,575
-2019-12-16 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,576
-2019-12-16 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,577
-2019-12-16 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,578
-2019-12-16 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,579
-2019-12-17 16:00:00,GTKILW,Filled,Sell,-7.0,1360.62,6.667038,,576
-2019-12-17 16:00:00,MCCZID,Filled,Sell,-260.0,39.33,7.158059999999999,,577
-2019-12-17 16:00:00,ISIJLH,Filled,Sell,-260.0,38.6,7.0252,,578
-2019-12-17 16:00:00,RUKNMV,Filled,Sell,-1.0,54.11,0.037877,,579
-2019-12-17 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,580
-2019-12-17 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,581
-2019-12-17 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,582
-2019-12-18 16:00:00,CEMOJE,Filled,Sell,-7.0,1353.28,6.631072,,580
-2019-12-18 16:00:00,MCCZID,Filled,Buy,256.0,39.0,6.9888,,581
-2019-12-18 16:00:00,RUKNMV,Filled,Sell,-1.0,54.35,0.038045,,582
-2019-12-18 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,583
-2019-12-18 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,584
-2019-12-18 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,585
-2019-12-19 16:00:00,CEMOJE,Filled,Buy,7.0,1349.94,6.614706,,583
-2019-12-19 16:00:00,MCCZID,Filled,Sell,-256.0,39.0,6.9888,,584
-2019-12-19 16:00:00,RUKNMV,Filled,Sell,-183.0,53.74,6.884094,,585
-2019-12-19 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,586
-2019-12-19 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,587
-2019-12-19 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,588
-2019-12-20 16:00:00,LUZLYG,Filled,Buy,288.0,35.15,7.086239999999999,,586
-2019-12-20 16:00:00,CEMOJE,Filled,Sell,-7.0,1356.32,6.645968,,587
-2019-12-20 16:00:00,MCCZID,Filled,Buy,258.0,39.13,7.066878000000001,,588
-2019-12-20 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,589
-2019-12-20 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,590
-2019-12-20 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,591
-2019-12-23 16:00:00,LUZLYG,Filled,Sell,-3.0,35.02,0.073542,,589
-2019-12-23 16:00:00,MCCZID,Filled,Sell,-4.0,39.32,0.110096,,590
-2019-12-23 16:00:00,RUKNMV,Filled,Buy,187.0,53.3,6.976970000000001,,591
-2019-12-23 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,592
-2019-12-23 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,593
-2019-12-23 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,594
-2019-12-23 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,595
-2019-12-23 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,596
-2019-12-23 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,597
-2019-12-23 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,598
-2019-12-24 13:00:00,LUZLYG,Filled,Buy,1.0,35.19,0.024633,,592
-2019-12-24 13:00:00,CEMOJE,Filled,Buy,7.0,1343.69,6.584081,,593
-2019-12-24 13:00:00,GTKILW,Filled,Buy,7.0,1355.01,6.639549,,594
-2019-12-24 13:00:00,ZIJVRO,Filled,Buy,170.0,59.25,7.05075,,595
-2019-12-24 13:00:00,BPSPGV,Filled,Buy,64.0,157.41,7.051968,,596
-2019-12-24 13:00:00,MCCZID,Filled,Buy,2.0,39.33,0.055062,,597
-2019-12-24 13:00:00,ISIJLH,Filled,Buy,258.0,39.12,7.065071999999999,,598
-2019-12-24 13:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,599
-2019-12-24 13:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,600
-2019-12-24 13:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,601
-2019-12-24 13:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,602
-2019-12-24 13:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,603
-2019-12-24 13:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,604
-2019-12-24 13:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,605
-2019-12-24 13:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,606
-2019-12-26 16:00:00,LUZLYG,Filled,Sell,-286.0,35.32,7.071064,,599
-2019-12-26 16:00:00,CEMOJE,Filled,Buy,3.0,1344.92,2.824332,,600
-2019-12-26 16:00:00,GTKILW,Filled,Buy,3.0,1343.5,2.82135,,601
-2019-12-26 16:00:00,ZIJVRO,Filled,Sell,-170.0,59.41,7.069789999999999,,602
-2019-12-26 16:00:00,BPSPGV,Filled,Sell,-64.0,157.56,7.058688,,603
-2019-12-26 16:00:00,MCCZID,Filled,Buy,117.0,39.3,3.2186699999999995,,604
-2019-12-26 16:00:00,ISIJLH,Filled,Sell,-258.0,39.0,7.0434,,605
-2019-12-26 16:00:00,RUKNMV,Filled,Buy,85.0,54.05,3.215975,,606
-2019-12-26 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,607
-2019-12-26 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,608
-2019-12-27 16:00:00,MCCZID,Filled,Sell,-1.0,39.45,0.027615,,607
-2019-12-27 16:00:00,RUKNMV,Filled,Sell,-272.0,54.27,10.333008,,608
-2019-12-27 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,609
-2019-12-30 16:00:00,MCCZID,Filled,Buy,1.0,39.3,0.027509999999999996,,609
-2019-12-30 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,610
-2019-12-30 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,611
-2019-12-30 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,612
-2019-12-30 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,613
-2019-12-30 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,614
-2019-12-31 16:00:00,LUZLYG,Filled,Buy,322.0,35.04,7.898015999999999,,610
-2019-12-31 16:00:00,CEMOJE,Filled,Sell,-2.0,1332.4,1.86536,,611
-2019-12-31 16:00:00,GTKILW,Filled,Sell,-2.0,1337.35,1.87229,,612
-2019-12-31 16:00:00,BPSPGV,Filled,Buy,71.0,156.83,7.794451,,613
-2019-12-31 16:00:00,MCCZID,Filled,Sell,-82.0,38.78,2.225972,,614
-2019-12-31 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,615
-2019-12-31 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,616
-2020-01-02 16:00:00,BPSPGV,Filled,Sell,-71.0,158.65,7.884905,,615
-2020-01-02 16:00:00,MCCZID,Filled,Sell,-2.0,39.3,0.05501999999999999,,616
-2020-01-02 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,617
-2020-01-02 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,618
-2020-01-02 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,619
-2020-01-02 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,620
-2020-01-03 16:00:00,LUZLYG,Filled,Buy,61.0,34.99,1.4940730000000002,,617
-2020-01-03 16:00:00,CEMOJE,Filled,Buy,2.0,1370.23,1.918322,,618
-2020-01-03 16:00:00,GTKILW,Filled,Buy,2.0,1371.68,1.920352,,619
-2020-01-03 16:00:00,MCCZID,Filled,Buy,60.0,38.7,1.6254,,620
-2020-01-03 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,621
-2020-01-03 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,622
-2020-01-03 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,623
-2020-01-03 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,624
-2020-01-03 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,625
-2020-01-03 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,626
-2020-01-03 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,627
-2020-01-03 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,628
-2020-01-03 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,629
-2020-01-06 16:00:00,COMNHQ,Filled,Buy,494.0,27.19,9.402302,,621
-2020-01-06 16:00:00,LUZLYG,Filled,Sell,-383.0,34.41,9.225321,,622
-2020-01-06 16:00:00,HECLON,Filled,Buy,171.0,78.85,9.438344999999998,,623
-2020-01-06 16:00:00,FFNDVM,Filled,Buy,1485.0,9.1,9.45945,,624
-2020-01-06 16:00:00,BGDRAI,Filled,Buy,1142.0,11.86,9.480884,,625
-2020-01-06 16:00:00,CEMOJE,Filled,Sell,-10.0,1355.66,9.48962,,626
-2020-01-06 16:00:00,GTKILW,Filled,Sell,-10.0,1359.69,9.517830000000002,,627
-2020-01-06 16:00:00,BPSPGV,Filled,Buy,86.0,156.98,9.450195999999998,,628
-2020-01-06 16:00:00,MCCZID,Filled,Sell,-349.0,38.82,9.483726,,629
-2020-01-06 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,630
-2020-01-06 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,631
-2020-01-06 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,632
-2020-01-06 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,633
-2020-01-06 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,634
-2020-01-06 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,635
-2020-01-07 16:00:00,COMNHQ,Filled,Sell,-494.0,27.56,9.530248,,630
-2020-01-07 16:00:00,HECLON,Filled,Sell,-171.0,79.19,9.479043,,631
-2020-01-07 16:00:00,FFNDVM,Filled,Sell,-1485.0,9.15,9.511425,,632
-2020-01-07 16:00:00,CEMOJE,Filled,Buy,9.0,1386.25,8.733375,,633
-2020-01-07 16:00:00,GTKILW,Filled,Buy,9.0,1400.57,8.823590999999999,,634
-2020-01-07 16:00:00,BPSPGV,Filled,Sell,-86.0,159.35,9.59287,,635
-2020-01-07 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,636
-2020-01-07 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,637
-2020-01-07 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,638
-2020-01-07 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,639
-2020-01-08 16:00:00,FFNDVM,Filled,Buy,1079.0,9.23,6.971419,,636
-2020-01-08 16:00:00,BGDRAI,Filled,Sell,-314.0,11.98,2.633204,,637
-2020-01-08 16:00:00,CEMOJE,Filled,Sell,-9.0,1391.64,8.767332,,638
-2020-01-08 16:00:00,GTKILW,Filled,Sell,-9.0,1390.61,8.760843,,639
-2020-01-08 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,640
-2020-01-08 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,641
-2020-01-08 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,642
-2020-01-09 16:00:00,FFNDVM,Filled,Sell,-1079.0,9.29,7.016737,,640
-2020-01-09 16:00:00,BGDRAI,Filled,Buy,16.0,12.05,0.13496,,641
-2020-01-09 16:00:00,MCCZID,Filled,Buy,258.0,39.2,7.0795200000000005,,642
-2020-01-09 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,643
-2020-01-09 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,644
-2020-01-09 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,645
-2020-01-10 16:00:00,ZIXTLG,Filled,Buy,786.0,12.9,7.09758,,643
-2020-01-10 16:00:00,BGDRAI,Filled,Sell,-844.0,11.85,7.000979999999999,,644
-2020-01-10 16:00:00,MCCZID,Filled,Sell,-258.0,38.98,7.039787999999999,,645
-2020-01-10 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,646
-2020-01-10 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,647
-2020-01-10 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,648
-2020-01-13 16:00:00,ZIXTLG,Filled,Sell,-786.0,13.05,7.180110000000001,,646
-2020-01-13 16:00:00,BGDRAI,Filled,Buy,873.0,11.71,7.155981,,647
-2020-01-13 16:00:00,MCCZID,Filled,Buy,258.0,39.53,7.139118,,648
-2020-01-13 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,649
-2020-01-13 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,650
-2020-01-13 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,651
-2020-01-13 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,652
-2020-01-14 16:00:00,OCHCAU,Filled,Buy,289.0,47.96,9.702308,,649
-2020-01-14 16:00:00,ZIXTLG,Filled,Buy,1025.0,13.33,9.564275,,650
-2020-01-14 16:00:00,BGDRAI,Filled,Buy,271.0,12.12,2.299164,,651
-2020-01-14 16:00:00,MCCZID,Filled,Sell,-258.0,39.31,7.099386000000001,,652
-2020-01-14 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,653
-2020-01-14 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,654
-2020-01-14 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,655
-2020-01-14 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,656
-2020-01-15 16:00:00,OCHCAU,Filled,Sell,-289.0,47.92,9.694216,,653
-2020-01-15 16:00:00,ZIXTLG,Filled,Sell,-1025.0,13.06,9.37055,,654
-2020-01-15 16:00:00,BGDRAI,Filled,Buy,8.0,12.0,0.0672,,655
-2020-01-15 16:00:00,MCCZID,Filled,Buy,346.0,40.25,9.74855,,656
-2020-01-15 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,657
-2020-01-15 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,658
-2020-01-15 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,659
-2020-01-15 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,660
-2020-01-16 16:00:00,HECLON,Filled,Buy,170.0,81.94,9.75086,,657
-2020-01-16 16:00:00,OCHCAU,Filled,Buy,288.0,48.37,9.751392,,658
-2020-01-16 16:00:00,BGDRAI,Filled,Buy,16.0,11.92,0.133504,,659
-2020-01-16 16:00:00,MCCZID,Filled,Sell,-6.0,40.79,0.171318,,660
-2020-01-16 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,661
-2020-01-16 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,662
-2020-01-16 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,663
-2020-01-16 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,664
-2020-01-16 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,665
-2020-01-17 16:00:00,HECLON,Filled,Sell,-170.0,81.11,9.65209,,661
-2020-01-17 16:00:00,OCHCAU,Filled,Sell,-6.0,49.32,0.207144,,662
-2020-01-17 16:00:00,BGDRAI,Filled,Sell,-1168.0,11.84,9.680383999999998,,663
-2020-01-17 16:00:00,BPSPGV,Filled,Buy,83.0,167.41,9.726521,,664
-2020-01-17 16:00:00,MCCZID,Filled,Sell,-340.0,40.65,9.6747,,665
-2020-01-17 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,666
-2020-01-17 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,667
-2020-01-17 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,668
-2020-01-21 16:00:00,OCHCAU,Filled,Sell,-282.0,48.93,9.658782,,666
-2020-01-21 16:00:00,ZIJVRO,Filled,Buy,167.0,59.81,6.991789,,667
-2020-01-21 16:00:00,BPSPGV,Filled,Sell,-83.0,166.78,9.689918,,668
-2020-01-21 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,669
-2020-01-21 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,670
-2020-01-21 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,671
-2020-01-21 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,672
-2020-01-22 16:00:00,HECLON,Filled,Buy,124.0,80.09,6.951811999999999,,669
-2020-01-22 16:00:00,BGDRAI,Filled,Buy,856.0,11.71,7.016632,,670
-2020-01-22 16:00:00,ZIJVRO,Filled,Sell,-167.0,61.04,7.135576,,671
-2020-01-22 16:00:00,MCCZID,Filled,Buy,247.0,40.33,6.973057,,672
-2020-01-22 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,673
-2020-01-22 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,674
-2020-01-22 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,675
-2020-01-22 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,676
-2020-01-23 16:00:00,HECLON,Filled,Sell,-124.0,79.51,6.9014679999999995,,673
-2020-01-23 16:00:00,OCHCAU,Filled,Buy,203.0,49.0,6.9629,,674
-2020-01-23 16:00:00,BGDRAI,Filled,Buy,21.0,11.75,0.172725,,675
-2020-01-23 16:00:00,MCCZID,Filled,Sell,-247.0,40.17,6.945393,,676
-2020-01-23 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,677
-2020-01-23 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,678
-2020-01-23 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,679
-2020-01-23 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,680
-2020-01-23 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,681
-2020-01-23 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,682
-2020-01-24 16:00:00,COMNHQ,Filled,Buy,346.0,28.85,6.98747,,677
-2020-01-24 16:00:00,YIVYGH,Filled,Buy,218.0,44.9,6.8517399999999995,,678
-2020-01-24 16:00:00,OCHCAU,Filled,Sell,-203.0,49.22,6.994162,,679
-2020-01-24 16:00:00,ZIXTLG,Filled,Buy,834.0,11.8,6.88884,,680
-2020-01-24 16:00:00,BGDRAI,Filled,Sell,-29.0,11.84,0.240352,,681
-2020-01-24 16:00:00,MCCZID,Filled,Buy,245.0,40.93,7.019495,,682
-2020-01-24 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,683
-2020-01-24 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,684
-2020-01-24 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,685
-2020-01-24 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,686
-2020-01-24 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,687
-2020-01-24 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,688
-2020-01-27 16:00:00,COMNHQ,Filled,Sell,-346.0,26.57,6.435254,,683
-2020-01-27 16:00:00,YIVYGH,Filled,Sell,-218.0,43.92,6.702191999999999,,684
-2020-01-27 16:00:00,ZIXTLG,Filled,Sell,-834.0,11.32,6.6086160000000005,,685
-2020-01-27 16:00:00,BGDRAI,Filled,Sell,-848.0,11.45,6.796719999999999,,686
-2020-01-27 16:00:00,ZIJVRO,Filled,Buy,145.0,66.72,6.77208,,687
-2020-01-27 16:00:00,MCCZID,Filled,Buy,5.0,39.4,0.1379,,688
-2020-01-27 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,689
-2020-01-27 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,690
-2020-01-27 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,691
-2020-01-27 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,692
-2020-01-27 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,693
-2020-01-27 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,694
-2020-01-28 16:00:00,OCHCAU,Filled,Buy,209.0,47.68,6.9755840000000005,,689
-2020-01-28 16:00:00,ZIXTLG,Filled,Buy,914.0,11.11,7.108178,,690
-2020-01-28 16:00:00,GTKILW,Filled,Buy,6.0,1430.73,6.009066000000001,,691
-2020-01-28 16:00:00,ZIJVRO,Filled,Sell,-145.0,66.5,6.74975,,692
-2020-01-28 16:00:00,HCDUCB,Filled,Buy,179.0,56.25,7.048125,,693
-2020-01-28 16:00:00,MCCZID,Filled,Sell,-250.0,39.32,6.881,,694
-2020-01-28 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,695
-2020-01-28 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,696
-2020-01-28 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,697
-2020-01-28 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,698
-2020-01-28 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,699
-2020-01-29 16:00:00,OCHCAU,Filled,Sell,-209.0,47.97,7.018011,,695
-2020-01-29 16:00:00,ZIXTLG,Filled,Buy,123.0,11.42,0.983262,,696
-2020-01-29 16:00:00,BGDRAI,Filled,Buy,999.0,12.55,8.776215,,697
-2020-01-29 16:00:00,GTKILW,Filled,Sell,-6.0,1450.49,6.092058000000001,,698
-2020-01-29 16:00:00,HCDUCB,Filled,Sell,-179.0,56.16,7.036847999999999,,699
-2020-01-29 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,700
-2020-01-29 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,701
-2020-01-29 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,702
-2020-01-29 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,703
-2020-01-30 16:00:00,OCHCAU,Filled,Buy,325.0,46.54,10.58785,,700
-2020-01-30 16:00:00,ZIXTLG,Filled,Sell,-1037.0,11.1,8.05749,,701
-2020-01-30 16:00:00,BGDRAI,Filled,Buy,186.0,12.93,1.683486,,702
-2020-01-30 16:00:00,ISIJLH,Filled,Buy,413.0,36.47,10.543477,,703
-2020-01-30 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,704
-2020-01-30 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,705
-2020-01-30 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,706
-2020-01-31 16:00:00,OCHCAU,Filled,Sell,-325.0,46.91,10.672024999999998,,704
-2020-01-31 16:00:00,BGDRAI,Filled,Sell,-1185.0,12.65,10.493175,,705
-2020-01-31 16:00:00,ISIJLH,Filled,Sell,-413.0,37.3,10.78343,,706
-2020-01-31 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,707
-2020-01-31 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,708
-2020-02-03 16:00:00,XUEHVZ,Filled,Buy,7.0,2013.51,9.866199,,707
-2020-02-03 16:00:00,ZIXTLG,Filled,Buy,1381.0,11.19,10.817373,,708
-2020-02-03 16:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,709
-2020-02-03 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,710
-2020-02-04 16:00:00,XUEHVZ,Filled,Sell,-7.0,2009.98,9.848902,,709
-2020-02-04 16:00:00,ZIXTLG,Filled,Sell,-41.0,11.88,0.34095600000000004,,710
-2020-02-04 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,711
-2020-02-04 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,712
-2020-02-04 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,713
-2020-02-05 16:00:00,YIVYGH,Filled,Buy,346.0,44.74,10.836028,,711
-2020-02-05 16:00:00,OCHCAU,Filled,Buy,322.0,48.33,10.893582,,712
-2020-02-05 16:00:00,ZIXTLG,Filled,Sell,-65.0,12.42,0.56511,,713
-2020-02-05 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,714
-2020-02-05 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,715
-2020-02-05 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,716
-2020-02-05 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,717
-2020-02-06 16:00:00,YIVYGH,Filled,Sell,-346.0,44.76,10.840872,,714
-2020-02-06 16:00:00,OCHCAU,Filled,Sell,-322.0,48.71,10.979234,,715
-2020-02-06 16:00:00,ZIXTLG,Filled,Sell,-1275.0,12.4,11.067,,716
-2020-02-06 16:00:00,RUKNMV,Filled,Buy,317.0,48.36,10.731084,,717
-2020-02-06 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,718
-2020-02-06 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,719
-2020-02-06 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,720
-2020-02-06 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,721
-2020-02-07 16:00:00,CEMOJE,Filled,Buy,10.0,1477.66,10.34362,,718
-2020-02-07 16:00:00,GTKILW,Filled,Buy,10.0,1473.15,10.31205,,719
-2020-02-07 16:00:00,HCDUCB,Filled,Buy,257.0,57.97,10.428802999999998,,720
-2020-02-07 16:00:00,RUKNMV,Filled,Sell,-317.0,47.77,10.600163,,721
-2020-02-07 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,722
-2020-02-07 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,723
-2020-02-07 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,724
-2020-02-07 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,725
-2020-02-10 16:00:00,ZIXTLG,Filled,Buy,1301.0,11.67,10.627869,,722
-2020-02-10 16:00:00,CEMOJE,Filled,Sell,-10.0,1479.31,10.35517,,723
-2020-02-10 16:00:00,GTKILW,Filled,Sell,-10.0,1479.84,10.35888,,724
-2020-02-10 16:00:00,HCDUCB,Filled,Buy,12.0,56.4,0.47376,,725
-2020-02-10 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,726
-2020-02-10 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,727
-2020-02-10 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,728
-2020-02-10 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,729
-2020-02-11 16:00:00,RLSRXX,Filled,Buy,289.0,53.19,10.760337,,726
-2020-02-11 16:00:00,XUEHVZ,Filled,Buy,7.0,2149.23,10.531227,,727
-2020-02-11 16:00:00,ZIXTLG,Filled,Sell,-1301.0,12.44,11.329108,,728
-2020-02-11 16:00:00,HCDUCB,Filled,Sell,-269.0,57.93,10.908219,,729
-2020-02-11 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,730
-2020-02-11 16:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,731
-2020-02-12 16:00:00,RLSRXX,Filled,Sell,-289.0,54.52,11.029396,,730
-2020-02-12 16:00:00,XUEHVZ,Filled,Sell,-7.0,2158.24,10.575376,,731
-2020-02-12 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,732
-2020-02-12 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,733
-2020-02-13 16:00:00,YIVYGH,Filled,Buy,221.0,45.9,7.1007299999999995,,732
-2020-02-13 16:00:00,HCDUCB,Filled,Buy,172.0,59.09,7.114436000000001,,733
-2020-02-13 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,734
-2020-02-13 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,735
-2020-02-13 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,736
-2020-02-14 16:00:00,YIVYGH,Filled,Sell,-221.0,46.08,7.128576,,734
-2020-02-14 16:00:00,HCDUCB,Filled,Sell,-172.0,60.15,7.24206,,735
-2020-02-14 16:00:00,MCCZID,Filled,Buy,276.0,36.96,7.140672,,736
-2020-02-14 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,737
-2020-02-18 16:00:00,MCCZID,Filled,Sell,-276.0,36.51,7.053732,,737
-2020-02-18 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,738
-2020-02-19 16:00:00,RUKNMV,Filled,Buy,212.0,47.28,7.016352,,738
-2020-02-19 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,739
-2020-02-19 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,740
-2020-02-20 16:00:00,HCDUCB,Filled,Buy,166.0,59.99,6.970838,,739
-2020-02-20 16:00:00,RUKNMV,Filled,Sell,-212.0,47.01,6.976283999999999,,740
-2020-02-20 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,741
-2020-02-20 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,742
-2020-02-21 16:00:00,HCDUCB,Filled,Sell,-166.0,58.63,6.812806,,741
-2020-02-21 16:00:00,MCCZID,Filled,Buy,278.0,35.75,6.95695,,742
-2020-02-21 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,743
-2020-02-21 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,744
-2020-02-21 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,745
-2020-02-21 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,746
-2020-02-21 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,747
-2020-02-24 16:00:00,RLSRXX,Filled,Buy,187.0,48.09,6.294981,,743
-2020-02-24 16:00:00,CEMOJE,Filled,Buy,6.0,1482.62,6.227003999999999,,744
-2020-02-24 16:00:00,GTKILW,Filled,Buy,6.0,1479.45,6.213690000000001,,745
-2020-02-24 16:00:00,HCDUCB,Filled,Buy,175.0,53.06,6.49985,,746
-2020-02-24 16:00:00,MCCZID,Filled,Sell,-278.0,35.25,6.85965,,747
-2020-02-24 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,748
-2020-02-24 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,749
-2020-02-24 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,750
-2020-02-24 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,751
-2020-02-24 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,752
-2020-02-24 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,753
-2020-02-25 16:00:00,RLSRXX,Filled,Buy,16.0,51.15,0.57288,,748
-2020-02-25 16:00:00,YIVYGH,Filled,Buy,223.0,44.69,6.976108999999999,,749
-2020-02-25 16:00:00,CEMOJE,Filled,Buy,1.0,1421.28,0.994896,,750
-2020-02-25 16:00:00,GTKILW,Filled,Buy,1.0,1428.36,0.999852,,751
-2020-02-25 16:00:00,HCDUCB,Filled,Sell,-175.0,54.75,6.706875,,752
-2020-02-25 16:00:00,MCCZID,Filled,Buy,288.0,34.7,6.99552,,753
-2020-02-25 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,754
-2020-02-25 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,755
-2020-02-25 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,756
-2020-02-25 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,757
-2020-02-25 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,758
-2020-02-25 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,759
-2020-02-25 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,760
-2020-02-26 16:00:00,COMNHQ,Filled,Buy,653.0,23.57,10.773847,,754
-2020-02-26 16:00:00,RLSRXX,Filled,Sell,-203.0,47.63,6.768223000000001,,755
-2020-02-26 16:00:00,YIVYGH,Filled,Buy,127.0,44.06,3.916934,,756
-2020-02-26 16:00:00,CEMOJE,Filled,Sell,-7.0,1389.4,6.808060000000001,,757
-2020-02-26 16:00:00,GTKILW,Filled,Sell,-7.0,1385.45,6.788704999999999,,758
-2020-02-26 16:00:00,HCDUCB,Filled,Buy,290.0,52.77,10.71231,,759
-2020-02-26 16:00:00,MCCZID,Filled,Sell,-288.0,34.26,6.906815999999999,,760
-2020-02-26 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,761
-2020-02-26 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,762
-2020-02-26 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,763
-2020-02-26 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,764
-2020-02-27 16:00:00,COMNHQ,Filled,Buy,222.0,20.82,3.2354279999999997,,761
-2020-02-27 16:00:00,YIVYGH,Filled,Buy,112.0,41.86,3.281824,,762
-2020-02-27 16:00:00,HCDUCB,Filled,Sell,-290.0,50.64,10.27992,,763
-2020-02-27 16:00:00,MCCZID,Filled,Buy,562.0,34.5,13.5723,,764
-2020-02-27 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,765
-2020-02-27 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,766
-2020-02-27 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,767
-2020-02-27 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,768
-2020-02-27 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,769
-2020-02-27 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,770
-2020-02-27 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,771
-2020-02-28 16:00:00,COMNHQ,Filled,Buy,52.0,19.8,0.7207200000000001,,765
-2020-02-28 16:00:00,YIVYGH,Filled,Buy,3.0,40.0,0.084,,766
-2020-02-28 16:00:00,CEMOJE,Filled,Buy,14.0,1325.64,12.991272000000002,,767
-2020-02-28 16:00:00,GTKILW,Filled,Buy,14.0,1315.22,12.889156000000002,,768
-2020-02-28 16:00:00,ZIJVRO,Filled,Buy,342.0,54.3,12.99942,,769
-2020-02-28 16:00:00,MCCZID,Filled,Sell,-562.0,33.42,13.147428,,770
-2020-02-28 16:00:00,ISIJLH,Filled,Buy,534.0,34.05,12.72789,,771
-2020-02-28 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,772
-2020-02-28 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,773
-2020-02-28 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,774
-2020-02-28 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,775
-2020-02-28 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,776
-2020-02-28 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,777
-2020-02-28 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,778
-2020-02-28 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,779
-2020-03-02 16:00:00,COMNHQ,Filled,Buy,75.0,19.02,0.99855,,772
-2020-03-02 16:00:00,LUZLYG,Filled,Buy,670.0,28.38,13.31022,,773
-2020-03-02 16:00:00,YIVYGH,Filled,Buy,7.0,40.34,0.197666,,774
-2020-03-02 16:00:00,CEMOJE,Filled,Sell,-14.0,1347.29,13.203442,,775
-2020-03-02 16:00:00,GTKILW,Filled,Sell,-14.0,1345.94,13.190212,,776
-2020-03-02 16:00:00,ZIJVRO,Filled,Sell,-342.0,55.87,13.375278,,777
-2020-03-02 16:00:00,HCDUCB,Filled,Buy,363.0,53.27,13.535907000000002,,778
-2020-03-02 16:00:00,ISIJLH,Filled,Sell,-534.0,35.39,13.228782,,779
-2020-03-02 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,780
-2020-03-02 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,781
-2020-03-02 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,782
-2020-03-02 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,783
-2020-03-02 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,784
-2020-03-02 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,785
-2020-03-02 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,786
-2020-03-02 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,787
-2020-03-02 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,788
-2020-03-03 16:00:00,COMNHQ,Filled,Sell,-226.0,19.66,3.110212,,780
-2020-03-03 16:00:00,SMDIFE,Filled,Buy,48.0,303.75,10.206,,781
-2020-03-03 16:00:00,LUZLYG,Filled,Sell,-172.0,29.39,3.538556,,782
-2020-03-03 16:00:00,YIVYGH,Filled,Sell,-128.0,42.07,3.769472,,783
-2020-03-03 16:00:00,ZIXTLG,Filled,Buy,1394.0,10.4,10.14832,,784
-2020-03-03 16:00:00,ZIJVRO,Filled,Buy,251.0,58.08,10.204656,,785
-2020-03-03 16:00:00,HCDUCB,Filled,Sell,-363.0,54.64,13.884024,,786
-2020-03-03 16:00:00,MCCZID,Filled,Buy,419.0,34.93,10.244969,,787
-2020-03-03 16:00:00,ISIJLH,Filled,Buy,393.0,37.15,10.219964999999998,,788
-2020-03-03 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,789
-2020-03-03 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,790
-2020-03-03 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,791
-2020-03-03 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,792
-2020-03-03 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,793
-2020-03-03 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,794
-2020-03-03 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,795
-2020-03-03 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,796
-2020-03-03 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,797
-2020-03-03 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,798
-2020-03-04 16:00:00,COMNHQ,Filled,Buy,40.0,18.36,0.51408,,789
-2020-03-04 16:00:00,SMDIFE,Filled,Sell,-48.0,296.8,9.97248,,790
-2020-03-04 16:00:00,LUZLYG,Filled,Sell,-498.0,28.11,9.799146,,791
-2020-03-04 16:00:00,YIVYGH,Filled,Sell,-344.0,41.97,10.106376,,792
-2020-03-04 16:00:00,LMRIBF,Filled,Buy,78.0,189.17,10.328682,,793
-2020-03-04 16:00:00,ZIXTLG,Filled,Sell,-1394.0,10.31,10.060498,,794
-2020-03-04 16:00:00,ZIJVRO,Filled,Sell,-251.0,57.01,10.016657,,795
-2020-03-04 16:00:00,HCDUCB,Filled,Buy,281.0,53.04,10.432968,,796
-2020-03-04 16:00:00,MCCZID,Filled,Sell,-419.0,35.06,10.283098,,797
-2020-03-04 16:00:00,ISIJLH,Filled,Sell,-393.0,36.97,10.170447,,798
-2020-03-04 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,799
-2020-03-04 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,800
-2020-03-04 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,801
-2020-03-04 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,802
-2020-03-04 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,803
-2020-03-05 16:00:00,COMNHQ,Filled,Sell,-27.0,17.54,0.33150599999999997,,799
-2020-03-05 16:00:00,YIVYGH,Filled,Buy,344.0,41.27,9.937816,,800
-2020-03-05 16:00:00,LMRIBF,Filled,Sell,-78.0,186.97,10.208562,,801
-2020-03-05 16:00:00,HCDUCB,Filled,Sell,-17.0,53.45,0.636055,,802
-2020-03-05 16:00:00,MCCZID,Filled,Buy,401.0,35.64,10.004148,,803
-2020-03-05 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,804
-2020-03-05 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,805
-2020-03-05 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,806
-2020-03-05 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,807
-2020-03-05 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,808
-2020-03-06 16:00:00,COMNHQ,Filled,Buy,119.0,15.0,1.2495,,804
-2020-03-06 16:00:00,YIVYGH,Filled,Buy,13.0,38.91,0.3540809999999999,,805
-2020-03-06 16:00:00,FFNDVM,Filled,Buy,2163.0,6.57,9.947637,,806
-2020-03-06 16:00:00,HCDUCB,Filled,Sell,-264.0,52.2,9.64656,,807
-2020-03-06 16:00:00,MCCZID,Filled,Sell,-401.0,34.73,9.748711,,808
-2020-03-06 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,809
-2020-03-06 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,810
-2020-03-06 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,811
-2020-03-06 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,812
-2020-03-06 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,813
-2020-03-09 16:00:00,COMNHQ,Filled,Buy,4.0,14.92,0.041776,,809
-2020-03-09 16:00:00,YIVYGH,Filled,Sell,-357.0,38.17,9.538683,,810
-2020-03-09 16:00:00,FFNDVM,Filled,Sell,-2163.0,5.99,9.069459,,811
-2020-03-09 16:00:00,ZIXTLG,Filled,Buy,1544.0,8.16,8.819328,,812
-2020-03-09 16:00:00,BGDRAI,Filled,Buy,1549.0,8.34,9.043062,,813
-2020-03-09 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,814
-2020-03-09 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,815
-2020-03-09 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,816
-2020-03-09 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,817
-2020-03-09 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,818
-2020-03-09 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,819
-2020-03-10 16:00:00,COMNHQ,Filled,Buy,72.0,15.82,0.7973279999999999,,814
-2020-03-10 16:00:00,YIVYGH,Filled,Buy,383.0,38.64,10.359384,,815
-2020-03-10 16:00:00,ZIXTLG,Filled,Buy,220.0,8.97,1.38138,,816
-2020-03-10 16:00:00,BGDRAI,Filled,Buy,219.0,8.78,1.345974,,817
-2020-03-10 16:00:00,ZIJVRO,Filled,Buy,285.0,52.76,10.525619999999998,,818
-2020-03-10 16:00:00,HCDUCB,Filled,Buy,315.0,48.18,10.62369,,819
-2020-03-10 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,820
-2020-03-10 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,821
-2020-03-10 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,822
-2020-03-10 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,823
-2020-03-10 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,824
-2020-03-10 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,825
-2020-03-10 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,826
-2020-03-10 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,827
-2020-03-10 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,828
-2020-03-10 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,829
-2020-03-10 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,830
-2020-03-11 16:00:00,COMNHQ,Filled,Sell,-401.0,16.29,4.572603,,820
-2020-03-11 16:00:00,LUZLYG,Filled,Buy,420.0,22.84,6.71496,,821
-2020-03-11 16:00:00,HECLON,Filled,Buy,178.0,53.61,6.679806,,822
-2020-03-11 16:00:00,YIVYGH,Filled,Sell,-130.0,37.77,3.4370700000000003,,823
-2020-03-11 16:00:00,OCHCAU,Filled,Buy,247.0,39.02,6.746558,,824
-2020-03-11 16:00:00,FFNDVM,Filled,Buy,1584.0,6.05,6.708239999999999,,825
-2020-03-11 16:00:00,LMRIBF,Filled,Buy,55.0,174.01,6.6993849999999995,,826
-2020-03-11 16:00:00,ZIXTLG,Filled,Sell,-662.0,8.66,4.013044,,827
-2020-03-11 16:00:00,BGDRAI,Filled,Sell,-648.0,8.63,3.914568000000001,,828
-2020-03-11 16:00:00,ZIJVRO,Filled,Sell,-102.0,52.39,3.740646,,829
-2020-03-11 16:00:00,HCDUCB,Filled,Sell,-108.0,46.14,3.488184,,830
-2020-03-11 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,831
-2020-03-11 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,832
-2020-03-11 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,833
-2020-03-11 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,834
-2020-03-11 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,835
-2020-03-11 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,836
-2020-03-11 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,837
-2020-03-11 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,838
-2020-03-11 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,839
-2020-03-11 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,840
-2020-03-11 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,841
-2020-03-12 16:00:00,COMNHQ,Filled,Buy,23.0,14.19,0.228459,,831
-2020-03-12 16:00:00,LUZLYG,Filled,Buy,14.0,20.73,0.20315400000000003,,832
-2020-03-12 16:00:00,HECLON,Filled,Buy,16.0,45.29,0.507248,,833
-2020-03-12 16:00:00,YIVYGH,Filled,Buy,6.0,35.58,0.149436,,834
-2020-03-12 16:00:00,OCHCAU,Filled,Buy,19.0,34.61,0.460313,,835
-2020-03-12 16:00:00,FFNDVM,Filled,Buy,86.0,5.37,0.323274,,836
-2020-03-12 16:00:00,LMRIBF,Filled,Sell,-55.0,159.95,6.158075,,837
-2020-03-12 16:00:00,ZIXTLG,Filled,Buy,111.0,7.15,0.555555,,838
-2020-03-12 16:00:00,BGDRAI,Filled,Buy,80.0,7.35,0.4116,,839
-2020-03-12 16:00:00,ZIJVRO,Filled,Buy,7.0,47.99,0.235151,,840
-2020-03-12 16:00:00,HCDUCB,Filled,Buy,18.0,39.26,0.4946759999999999,,841
-2020-03-12 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,842
-2020-03-12 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,843
-2020-03-12 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,844
-2020-03-12 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,845
-2020-03-12 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,846
-2020-03-12 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,847
-2020-03-12 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,848
-2020-03-12 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,849
-2020-03-12 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,850
-2020-03-12 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,851
-2020-03-12 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,852
-2020-03-12 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,853
-2020-03-13 16:00:00,COMNHQ,Filled,Buy,133.0,15.3,1.42443,,842
-2020-03-13 16:00:00,LUZLYG,Filled,Buy,50.0,22.5,0.7875,,843
-2020-03-13 16:00:00,HECLON,Filled,Buy,35.0,47.74,1.16963,,844
-2020-03-13 16:00:00,YIVYGH,Filled,Buy,25.0,36.3,0.6352499999999999,,845
-2020-03-13 16:00:00,OCHCAU,Filled,Sell,-266.0,35.18,6.550515999999999,,846
-2020-03-13 16:00:00,FFNDVM,Filled,Sell,-1670.0,5.85,6.83865,,847
-2020-03-13 16:00:00,LMRIBF,Filled,Buy,64.0,163.12,7.307776,,848
-2020-03-13 16:00:00,ZIXTLG,Filled,Buy,173.0,7.8,0.94458,,849
-2020-03-13 16:00:00,BGDRAI,Filled,Buy,174.0,7.81,0.9512579999999998,,850
-2020-03-13 16:00:00,ZIJVRO,Filled,Buy,28.0,47.79,0.936684,,851
-2020-03-13 16:00:00,HCDUCB,Filled,Buy,31.0,41.44,0.8992479999999999,,852
-2020-03-13 16:00:00,MCCZID,Filled,Buy,331.0,31.0,7.1827,,853
-2020-03-13 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,854
-2020-03-13 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,855
-2020-03-13 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,856
-2020-03-13 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,857
-2020-03-13 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,858
-2020-03-13 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,859
-2020-03-13 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,860
-2020-03-13 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,861
-2020-03-13 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,862
-2020-03-13 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,863
-2020-03-13 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,864
-2020-03-13 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,865
-2020-03-16 16:00:00,COMNHQ,Filled,Sell,-51.0,12.8,0.45696,,854
-2020-03-16 16:00:00,LUZLYG,Filled,Sell,-77.0,20.0,1.078,,855
-2020-03-16 16:00:00,HECLON,Filled,Sell,-36.0,43.27,1.090404,,856
-2020-03-16 16:00:00,YIVYGH,Filled,Sell,-34.0,34.64,0.8244319999999999,,857
-2020-03-16 16:00:00,LMRIBF,Filled,Sell,-7.0,149.0,0.7301,,858
-2020-03-16 16:00:00,ZIXTLG,Filled,Sell,-78.0,6.44,0.35162400000000005,,859
-2020-03-16 16:00:00,BGDRAI,Filled,Sell,-119.0,7.0,0.5831,,860
-2020-03-16 16:00:00,ZIJVRO,Filled,Sell,-37.0,47.48,1.229732,,861
-2020-03-16 16:00:00,HCDUCB,Filled,Sell,-27.0,37.35,0.7059150000000001,,862
-2020-03-16 16:00:00,MCCZID,Filled,Sell,-331.0,30.0,6.951,,863
-2020-03-16 16:00:00,ISIJLH,Filled,Buy,285.0,31.0,6.1845,,864
-2020-03-16 16:00:00,RUKNMV,Filled,Buy,319.0,26.87,6.000071,,865
-2020-03-16 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,866
-2020-03-16 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,867
-2020-03-16 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,868
-2020-03-16 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,869
-2020-03-16 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,870
-2020-03-16 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,871
-2020-03-16 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,872
-2020-03-16 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,873
-2020-03-16 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,874
-2020-03-16 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,875
-2020-03-16 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,876
-2020-03-16 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,877
-2020-03-17 16:00:00,COMNHQ,Filled,Sell,-78.0,15.83,0.864318,,866
-2020-03-17 16:00:00,LUZLYG,Filled,Sell,-407.0,21.06,5.999994,,867
-2020-03-17 16:00:00,HECLON,Filled,Sell,-193.0,42.14,5.6931140000000005,,868
-2020-03-17 16:00:00,YIVYGH,Filled,Sell,-250.0,36.55,6.39625,,869
-2020-03-17 16:00:00,FFNDVM,Filled,Buy,1939.0,5.08,6.895084000000001,,870
-2020-03-17 16:00:00,LMRIBF,Filled,Sell,-57.0,150.8,6.01692,,871
-2020-03-17 16:00:00,ZIXTLG,Filled,Sell,-1308.0,6.38,5.841527999999999,,872
-2020-03-17 16:00:00,BGDRAI,Filled,Buy,203.0,6.91,0.981911,,873
-2020-03-17 16:00:00,ZIJVRO,Filled,Sell,-181.0,45.74,5.7952580000000005,,874
-2020-03-17 16:00:00,HCDUCB,Filled,Sell,-229.0,35.49,5.689047,,875
-2020-03-17 16:00:00,ISIJLH,Filled,Sell,-285.0,32.36,6.45582,,876
-2020-03-17 16:00:00,RUKNMV,Filled,Sell,-319.0,27.5,6.14075,,877
-2020-03-17 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,878
-2020-03-17 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,879
-2020-03-17 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,880
-2020-03-17 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,881
-2020-03-17 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,882
-2020-03-18 16:00:00,COMNHQ,Filled,Buy,14.0,14.24,0.139552,,878
-2020-03-18 16:00:00,RLSRXX,Filled,Buy,232.0,39.67,6.442408,,879
-2020-03-18 16:00:00,FFNDVM,Filled,Buy,4.0,4.74,0.013272,,880
-2020-03-18 16:00:00,ZIXTLG,Filled,Buy,1502.0,5.86,6.161204000000001,,881
-2020-03-18 16:00:00,BGDRAI,Filled,Sell,-83.0,6.55,0.380555,,882
-2020-03-18 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,883
-2020-03-18 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,884
-2020-03-18 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,885
-2020-03-18 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,886
-2020-03-18 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,887
-2020-03-18 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,888
-2020-03-19 16:00:00,COMNHQ,Filled,Buy,207.0,11.61,1.682289,,883
-2020-03-19 16:00:00,RLSRXX,Filled,Sell,-232.0,39.56,6.424544,,884
-2020-03-19 16:00:00,YIVYGH,Filled,Buy,271.0,35.64,6.760908000000001,,885
-2020-03-19 16:00:00,FFNDVM,Filled,Sell,-1943.0,4.3,5.84843,,886
-2020-03-19 16:00:00,ZIXTLG,Filled,Buy,322.0,5.14,1.158556,,887
-2020-03-19 16:00:00,BGDRAI,Filled,Buy,92.0,6.39,0.411516,,888
-2020-03-19 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,889
-2020-03-19 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,890
-2020-03-19 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,891
-2020-03-19 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,892
-2020-03-19 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,893
-2020-03-20 16:00:00,COMNHQ,Filled,Buy,119.0,10.66,0.8879779999999999,,889
-2020-03-20 16:00:00,YIVYGH,Filled,Buy,1.0,36.09,0.025263,,890
-2020-03-20 16:00:00,FFNDVM,Filled,Buy,2187.0,4.54,6.950285999999999,,891
-2020-03-20 16:00:00,ZIXTLG,Filled,Sell,-121.0,6.02,0.509894,,892
-2020-03-20 16:00:00,BGDRAI,Filled,Buy,41.0,7.0,0.2009,,893
-2020-03-20 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,894
-2020-03-20 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,895
-2020-03-20 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,896
-2020-03-20 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,897
-2020-03-20 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,898
-2020-03-23 16:00:00,COMNHQ,Filled,Sell,-10.0,10.92,0.07644000000000001,,894
-2020-03-23 16:00:00,YIVYGH,Filled,Sell,-272.0,32.93,6.2698719999999994,,895
-2020-03-23 16:00:00,FFNDVM,Filled,Buy,67.0,4.25,0.199325,,896
-2020-03-23 16:00:00,ZIXTLG,Filled,Buy,65.0,5.46,0.24843,,897
-2020-03-23 16:00:00,BGDRAI,Filled,Sell,-1508.0,6.44,6.798064,,898
-2020-03-23 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,899
-2020-03-23 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,900
-2020-03-23 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,901
-2020-03-23 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,902
-2020-03-24 16:00:00,COMNHQ,Filled,Buy,1.0,11.99,0.008393,,899
-2020-03-24 16:00:00,LUZLYG,Filled,Buy,533.0,19.42,7.245602000000001,,900
-2020-03-24 16:00:00,FFNDVM,Filled,Buy,153.0,4.51,0.483021,,901
-2020-03-24 16:00:00,ZIXTLG,Filled,Buy,22.0,6.13,0.094402,,902
-2020-03-24 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,903
-2020-03-24 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,904
-2020-03-24 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,905
-2020-03-24 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,906
-2020-03-25 16:00:00,COMNHQ,Filled,Buy,88.0,16.81,1.035496,,903
-2020-03-25 16:00:00,LUZLYG,Filled,Sell,-533.0,21.6,8.05896,,904
-2020-03-25 16:00:00,FFNDVM,Filled,Sell,-2407.0,5.73,9.654477,,905
-2020-03-25 16:00:00,ZIXTLG,Filled,Buy,260.0,6.96,1.2667199999999998,,906
-2020-03-25 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,907
-2020-03-25 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,908
-2020-03-25 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,909
-2020-03-26 16:00:00,COMNHQ,Filled,Sell,-94.0,16.11,1.060038,,907
-2020-03-26 16:00:00,YIVYGH,Filled,Buy,428.0,33.19,9.943724,,908
-2020-03-26 16:00:00,ZIXTLG,Filled,Sell,-66.0,7.37,0.340494,,909
-2020-03-26 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,910
-2020-03-26 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,911
-2020-03-26 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,912
-2020-03-27 16:00:00,COMNHQ,Filled,Sell,-15.0,14.98,0.15729,,910
-2020-03-27 16:00:00,YIVYGH,Filled,Sell,-428.0,35.59,10.662764,,911
-2020-03-27 16:00:00,ZIXTLG,Filled,Sell,-1984.0,6.63,9.207744,,912
-2020-03-27 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,913
-2020-03-27 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,914
-2020-03-30 16:00:00,COMNHQ,Filled,Buy,103.0,13.15,0.948115,,913
-2020-03-30 16:00:00,ZIXTLG,Filled,Buy,2317.0,6.27,10.169313,,914
-2020-03-30 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,915
-2020-03-30 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,916
-2020-03-31 16:00:00,COMNHQ,Filled,Sell,-119.0,12.9,1.07457,,915
-2020-03-31 16:00:00,ZIXTLG,Filled,Sell,-2317.0,6.32,10.250408,,916
-2020-03-31 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,917
-2020-03-31 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,918
-2020-04-01 16:00:00,COMNHQ,Filled,Sell,-904.0,11.48,7.264544,,917
-2020-04-01 16:00:00,ZIXTLG,Filled,Buy,1642.0,6.35,7.298689999999999,,918
-2020-04-01 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,919
-2020-04-02 16:00:00,ZIXTLG,Filled,Buy,474.0,6.54,2.169972,,919
-2020-04-02 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,920
-2020-04-02 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,921
-2020-04-03 16:00:00,COMNHQ,Filled,Buy,1327.0,10.35,9.614115,,920
-2020-04-03 16:00:00,ZIXTLG,Filled,Sell,-2116.0,6.36,9.420432,,921
-2020-04-03 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,922
-2020-04-06 16:00:00,COMNHQ,Filled,Buy,112.0,9.72,0.7620480000000001,,922
-2020-04-06 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,923
-2020-04-06 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,924
-2020-04-07 16:00:00,COMNHQ,Filled,Sell,-16.0,11.08,0.124096,,923
-2020-04-07 16:00:00,ZIXTLG,Filled,Buy,1880.0,7.86,10.34376,,924
-2020-04-07 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,925
-2020-04-07 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,926
-2020-04-08 16:00:00,COMNHQ,Filled,Sell,-461.0,10.9,3.5174300000000005,,925
-2020-04-08 16:00:00,ZIXTLG,Filled,Sell,-1880.0,7.64,10.054239999999998,,926
-2020-04-08 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,927
-2020-04-08 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,928
-2020-04-08 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,929
-2020-04-08 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,930
-2020-04-09 16:00:00,COMNHQ,Filled,Sell,-93.0,12.62,0.8215619999999999,,927
-2020-04-09 16:00:00,LUZLYG,Filled,Buy,420.0,24.05,7.0706999999999995,,928
-2020-04-09 16:00:00,YIVYGH,Filled,Buy,261.0,37.41,6.834806999999999,,929
-2020-04-09 16:00:00,ZIXTLG,Filled,Buy,1227.0,8.31,7.137459000000001,,930
-2020-04-09 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,931
-2020-04-09 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,932
-2020-04-09 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,933
-2020-04-09 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,934
-2020-04-09 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,935
-2020-04-09 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,936
-2020-04-09 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,937
-2020-04-09 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,938
-2020-04-09 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,939
-2020-04-13 16:00:00,COMNHQ,Filled,Sell,-81.0,12.94,0.7336979999999999,,931
-2020-04-13 16:00:00,LUZLYG,Filled,Sell,-24.0,24.85,0.4174800000000001,,932
-2020-04-13 16:00:00,HECLON,Filled,Buy,208.0,47.5,6.916,,933
-2020-04-13 16:00:00,YIVYGH,Filled,Sell,-261.0,37.48,6.847595999999999,,934
-2020-04-13 16:00:00,ZIXTLG,Filled,Sell,-1227.0,8.28,7.111692,,935
-2020-04-13 16:00:00,BGDRAI,Filled,Buy,1382.0,7.1,6.868539999999999,,936
-2020-04-13 16:00:00,MCCZID,Filled,Buy,278.0,35.94,6.993924,,937
-2020-04-13 16:00:00,ISIJLH,Filled,Buy,321.0,30.52,6.857844,,938
-2020-04-13 16:00:00,RUKNMV,Filled,Buy,297.0,33.22,6.906438,,939
-2020-04-13 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,940
-2020-04-13 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,941
-2020-04-13 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,942
-2020-04-13 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,943
-2020-04-13 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,944
-2020-04-13 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,945
-2020-04-13 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,946
-2020-04-14 16:00:00,COMNHQ,Filled,Buy,63.0,12.22,0.538902,,940
-2020-04-14 16:00:00,LUZLYG,Filled,Sell,-396.0,24.55,6.8052600000000005,,941
-2020-04-14 16:00:00,HECLON,Filled,Buy,2.0,47.66,0.06672399999999999,,942
-2020-04-14 16:00:00,BGDRAI,Filled,Sell,-1382.0,7.12,6.887888,,943
-2020-04-14 16:00:00,MCCZID,Filled,Sell,-278.0,36.0,7.0056,,944
-2020-04-14 16:00:00,ISIJLH,Filled,Buy,5.0,30.69,0.107415,,945
-2020-04-14 16:00:00,RUKNMV,Filled,Buy,16.0,32.11,0.359632,,946
-2020-04-14 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,947
-2020-04-14 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,948
-2020-04-14 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,949
-2020-04-14 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,950
-2020-04-14 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,951
-2020-04-14 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,952
-2020-04-14 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,953
-2020-04-14 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,954
-2020-04-15 16:00:00,COMNHQ,Filled,Sell,-27.0,12.53,0.236817,,947
-2020-04-15 16:00:00,SMDIFE,Filled,Buy,34.0,282.62,6.726356,,948
-2020-04-15 16:00:00,HECLON,Filled,Buy,6.0,43.25,0.18165,,949
-2020-04-15 16:00:00,FFNDVM,Filled,Buy,1862.0,5.04,6.569135999999999,,950
-2020-04-15 16:00:00,BGDRAI,Filled,Buy,1421.0,6.69,6.654542999999999,,951
-2020-04-15 16:00:00,BPSPGV,Filled,Buy,56.0,171.01,6.703592,,952
-2020-04-15 16:00:00,ISIJLH,Filled,Sell,-10.0,30.63,0.21441,,953
-2020-04-15 16:00:00,RUKNMV,Filled,Buy,13.0,28.68,0.260988,,954
-2020-04-15 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,955
-2020-04-15 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,956
-2020-04-15 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,957
-2020-04-15 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,958
-2020-04-15 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,959
-2020-04-15 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,960
-2020-04-15 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,961
-2020-04-15 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,962
-2020-04-15 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,963
-2020-04-16 16:00:00,COMNHQ,Filled,Sell,-32.0,11.91,0.266784,,955
-2020-04-16 16:00:00,SMDIFE,Filled,Sell,-34.0,287.25,6.83655,,956
-2020-04-16 16:00:00,HECLON,Filled,Buy,11.0,42.8,0.32955999999999996,,957
-2020-04-16 16:00:00,YIVYGH,Filled,Buy,262.0,37.53,6.883002,,958
-2020-04-16 16:00:00,FFNDVM,Filled,Sell,-1862.0,5.01,6.530033999999999,,959
-2020-04-16 16:00:00,BGDRAI,Filled,Buy,77.0,6.45,0.34765500000000005,,960
-2020-04-16 16:00:00,BPSPGV,Filled,Sell,-56.0,174.36,6.834912,,961
-2020-04-16 16:00:00,ISIJLH,Filled,Buy,7.0,30.27,0.14832299999999998,,962
-2020-04-16 16:00:00,RUKNMV,Filled,Sell,-326.0,28.18,6.430676,,963
-2020-04-16 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,964
-2020-04-16 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,965
-2020-04-16 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,966
-2020-04-16 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,967
-2020-04-16 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,968
-2020-04-16 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,969
-2020-04-16 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,970
-2020-04-16 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,971
-2020-04-17 16:00:00,COMNHQ,Filled,Buy,86.0,11.87,0.7145739999999999,,964
-2020-04-17 16:00:00,LUZLYG,Filled,Buy,453.0,22.33,7.080843,,965
-2020-04-17 16:00:00,HECLON,Filled,Buy,12.0,43.0,0.3612,,966
-2020-04-17 16:00:00,YIVYGH,Filled,Sell,-5.0,38.55,0.134925,,967
-2020-04-17 16:00:00,BGDRAI,Filled,Buy,60.0,6.42,0.26964,,968
-2020-04-17 16:00:00,BPSPGV,Filled,Buy,54.0,179.56,6.787368,,969
-2020-04-17 16:00:00,ISIJLH,Filled,Sell,-1.0,30.8,0.02156,,970
-2020-04-17 16:00:00,RUKNMV,Filled,Buy,361.0,28.15,7.113505,,971
-2020-04-17 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,972
-2020-04-17 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,973
-2020-04-17 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,974
-2020-04-17 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,975
-2020-04-17 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,976
-2020-04-17 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,977
-2020-04-17 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,978
-2020-04-17 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,979
-2020-04-17 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,980
-2020-04-20 16:00:00,COMNHQ,Filled,Sell,-35.0,11.13,0.272685,,972
-2020-04-20 16:00:00,LUZLYG,Filled,Sell,-34.0,22.57,0.537166,,973
-2020-04-20 16:00:00,HECLON,Filled,Sell,-25.0,43.4,0.7595,,974
-2020-04-20 16:00:00,YIVYGH,Filled,Sell,-1.0,37.68,0.026376,,975
-2020-04-20 16:00:00,OCHCAU,Filled,Buy,229.0,41.92,6.719776,,976
-2020-04-20 16:00:00,BGDRAI,Filled,Sell,-132.0,6.61,0.6107640000000001,,977
-2020-04-20 16:00:00,BPSPGV,Filled,Sell,-54.0,176.6,6.675479999999999,,978
-2020-04-20 16:00:00,ISIJLH,Filled,Sell,-10.0,30.85,0.21595,,979
-2020-04-20 16:00:00,RUKNMV,Filled,Sell,-18.0,27.29,0.343854,,980
-2020-04-20 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,981
-2020-04-20 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,982
-2020-04-20 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,983
-2020-04-20 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,984
-2020-04-20 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,985
-2020-04-20 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,986
-2020-04-20 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,987
-2020-04-20 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,988
-2020-04-20 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,989
-2020-04-20 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,990
-2020-04-21 16:00:00,COMNHQ,Filled,Buy,37.0,10.75,0.278425,,981
-2020-04-21 16:00:00,LUZLYG,Filled,Buy,13.0,21.88,0.199108,,982
-2020-04-21 16:00:00,HECLON,Filled,Buy,7.0,42.35,0.207515,,983
-2020-04-21 16:00:00,YIVYGH,Filled,Buy,5.0,36.75,0.128625,,984
-2020-04-21 16:00:00,OCHCAU,Filled,Sell,-229.0,41.81,6.7021429999999995,,985
-2020-04-21 16:00:00,FFNDVM,Filled,Buy,1954.0,4.82,6.592796000000001,,986
-2020-04-21 16:00:00,ZIXTLG,Filled,Buy,1213.0,7.5,6.36825,,987
-2020-04-21 16:00:00,BGDRAI,Filled,Buy,69.0,6.34,0.306222,,988
-2020-04-21 16:00:00,ISIJLH,Filled,Buy,2.0,30.5,0.0427,,989
-2020-04-21 16:00:00,RUKNMV,Filled,Buy,8.0,26.89,0.150584,,990
-2020-04-21 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,991
-2020-04-21 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,992
-2020-04-21 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,993
-2020-04-21 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,994
-2020-04-21 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,995
-2020-04-21 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,996
-2020-04-21 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,997
-2020-04-21 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,998
-2020-04-21 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,999
-2020-04-22 16:00:00,COMNHQ,Filled,Buy,345.0,11.09,2.678235,,991
-2020-04-22 16:00:00,LUZLYG,Filled,Sell,-432.0,22.16,6.7011840000000005,,992
-2020-04-22 16:00:00,HECLON,Filled,Sell,-221.0,42.99,6.650553,,993
-2020-04-22 16:00:00,YIVYGH,Filled,Sell,-261.0,36.23,6.619220999999999,,994
-2020-04-22 16:00:00,FFNDVM,Filled,Sell,-1954.0,4.87,6.661186,,995
-2020-04-22 16:00:00,ZIXTLG,Filled,Buy,606.0,7.55,3.20271,,996
-2020-04-22 16:00:00,BGDRAI,Filled,Buy,586.0,6.59,2.7032179999999997,,997
-2020-04-22 16:00:00,ISIJLH,Filled,Sell,-314.0,30.9,6.79182,,998
-2020-04-22 16:00:00,RUKNMV,Filled,Sell,-351.0,27.5,6.75675,,999
-2020-04-22 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1000
-2020-04-22 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1001
-2020-04-22 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1002
-2020-04-22 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1003
-2020-04-23 16:00:00,COMNHQ,Filled,Buy,88.0,10.38,0.639408,,1000
-2020-04-23 16:00:00,ZIXTLG,Filled,Sell,-53.0,7.87,0.291977,,1001
-2020-04-23 16:00:00,BGDRAI,Filled,Sell,-2081.0,6.46,9.410282,,1002
-2020-04-23 16:00:00,ISIJLH,Filled,Buy,457.0,29.41,9.408259,,1003
-2020-04-23 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1004
-2020-04-23 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1005
-2020-04-23 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1006
-2020-04-23 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1007
-2020-04-24 16:00:00,COMNHQ,Filled,Buy,3.0,10.4,0.02184,,1004
-2020-04-24 16:00:00,ZIXTLG,Filled,Sell,-1766.0,8.22,10.161564,,1005
-2020-04-24 16:00:00,ISIJLH,Filled,Sell,-457.0,29.49,9.433851,,1006
-2020-04-24 16:00:00,RUKNMV,Filled,Buy,508.0,26.8,9.53008,,1007
-2020-04-24 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1008
-2020-04-24 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1009
-2020-04-24 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1010
-2020-04-27 16:00:00,COMNHQ,Filled,Sell,-6.0,10.52,0.044184,,1008
-2020-04-27 16:00:00,BGDRAI,Filled,Buy,2158.0,6.37,9.622522,,1009
-2020-04-27 16:00:00,RUKNMV,Filled,Sell,-508.0,27.28,9.700768,,1010
-2020-04-27 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1011
-2020-04-27 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1012
-2020-04-27 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1013
-2020-04-28 16:00:00,COMNHQ,Filled,Buy,38.0,10.28,0.27344799999999997,,1011
-2020-04-28 16:00:00,BGDRAI,Filled,Sell,-2158.0,6.6,9.96996,,1012
-2020-04-28 16:00:00,RUKNMV,Filled,Buy,475.0,29.6,9.842,,1013
-2020-04-28 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1014
-2020-04-28 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1015
-2020-04-29 16:00:00,COMNHQ,Filled,Sell,-147.0,12.11,1.246119,,1014
-2020-04-29 16:00:00,RUKNMV,Filled,Sell,-7.0,30.1,0.14749,,1015
-2020-04-29 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1016
-2020-04-29 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1017
-2020-04-29 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,1018
-2020-04-29 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1019
-2020-04-30 16:00:00,COMNHQ,Filled,Buy,315.0,11.92,2.6283600000000003,,1016
-2020-04-30 16:00:00,BGDRAI,Filled,Buy,2910.0,6.54,13.321980000000002,,1017
-2020-04-30 16:00:00,HCDUCB,Filled,Buy,384.0,49.5,13.3056,,1018
-2020-04-30 16:00:00,RUKNMV,Filled,Buy,170.0,29.27,3.4831299999999996,,1019
-2020-04-30 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1020
-2020-04-30 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1021
-2020-04-30 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,1022
-2020-04-30 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1023
-2020-04-30 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1024
-2020-05-01 16:00:00,COMNHQ,Filled,Buy,76.0,11.38,0.6054160000000001,,1020
-2020-05-01 16:00:00,BGDRAI,Filled,Sell,-97.0,6.65,0.451535,,1021
-2020-05-01 16:00:00,HCDUCB,Filled,Sell,-384.0,46.36,12.461567999999998,,1022
-2020-05-01 16:00:00,ISIJLH,Filled,Buy,627.0,30.77,13.504953,,1023
-2020-05-01 16:00:00,RUKNMV,Filled,Buy,20.0,28.5,0.399,,1024
-2020-05-01 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1025
-2020-05-01 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1026
-2020-05-01 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1027
-2020-05-01 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1028
-2020-05-04 16:00:00,COMNHQ,Filled,Buy,196.0,9.42,1.292424,,1025
-2020-05-04 16:00:00,BGDRAI,Filled,Buy,114.0,6.3,0.50274,,1026
-2020-05-04 16:00:00,ISIJLH,Filled,Sell,-627.0,29.63,13.004606999999998,,1027
-2020-05-04 16:00:00,RUKNMV,Filled,Buy,31.0,26.91,0.583947,,1028
-2020-05-04 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1029
-2020-05-04 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1030
-2020-05-04 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1031
-2020-05-04 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1032
-2020-05-04 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1033
-2020-05-05 16:00:00,COMNHQ,Filled,Sell,-272.0,10.27,1.955408,,1029
-2020-05-05 16:00:00,OCHCAU,Filled,Buy,360.0,41.63,10.49076,,1030
-2020-05-05 16:00:00,BGDRAI,Filled,Sell,-529.0,6.3,2.33289,,1031
-2020-05-05 16:00:00,ISIJLH,Filled,Buy,503.0,29.74,10.471454,,1032
-2020-05-05 16:00:00,RUKNMV,Filled,Sell,-145.0,27.52,2.79328,,1033
-2020-05-05 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1034
-2020-05-05 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1035
-2020-05-05 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1036
-2020-05-05 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1037
-2020-05-05 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1038
-2020-05-05 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1039
-2020-05-06 16:00:00,COMNHQ,Filled,Sell,-500.0,9.56,3.346,,1034
-2020-05-06 16:00:00,OCHCAU,Filled,Sell,-360.0,41.53,10.46556,,1035
-2020-05-06 16:00:00,BGDRAI,Filled,Sell,-839.0,6.2,3.64126,,1036
-2020-05-06 16:00:00,MCCZID,Filled,Buy,251.0,38.8,6.817159999999999,,1037
-2020-05-06 16:00:00,ISIJLH,Filled,Sell,-503.0,29.74,10.471454,,1038
-2020-05-06 16:00:00,RUKNMV,Filled,Sell,-177.0,26.5,3.28335,,1039
-2020-05-06 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1040
-2020-05-06 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1041
-2020-05-06 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1042
-2020-05-06 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,1043
-2020-05-06 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1044
-2020-05-06 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1045
-2020-05-07 16:00:00,COMNHQ,Filled,Buy,28.0,9.33,0.182868,,1040
-2020-05-07 16:00:00,HECLON,Filled,Buy,224.0,43.52,6.823936000000001,,1041
-2020-05-07 16:00:00,BGDRAI,Filled,Buy,56.0,6.06,0.23755199999999996,,1042
-2020-05-07 16:00:00,MCCZID,Filled,Sell,-251.0,38.32,6.732824,,1043
-2020-05-07 16:00:00,ISIJLH,Filled,Buy,335.0,29.13,6.830984999999999,,1044
-2020-05-07 16:00:00,RUKNMV,Filled,Buy,10.0,25.53,0.17871,,1045
-2020-05-07 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1046
-2020-05-07 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1047
-2020-05-07 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1048
-2020-05-07 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1049
-2020-05-07 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1050
-2020-05-07 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1051
-2020-05-08 16:00:00,COMNHQ,Filled,Sell,-21.0,9.79,0.143913,,1046
-2020-05-08 16:00:00,HECLON,Filled,Sell,-224.0,45.32,7.1061760000000005,,1047
-2020-05-08 16:00:00,BGDRAI,Filled,Sell,-17.0,6.21,0.07389899999999999,,1048
-2020-05-08 16:00:00,MCCZID,Filled,Buy,264.0,37.23,6.880103999999999,,1049
-2020-05-08 16:00:00,ISIJLH,Filled,Sell,-335.0,29.31,6.873195,,1050
-2020-05-08 16:00:00,RUKNMV,Filled,Buy,10.0,25.64,0.17947999999999997,,1051
-2020-05-08 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1052
-2020-05-08 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1053
-2020-05-08 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1054
-2020-05-08 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,1055
-2020-05-08 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1056
-2020-05-11 16:00:00,COMNHQ,Filled,Sell,-59.0,9.92,0.4096959999999999,,1052
-2020-05-11 16:00:00,OCHCAU,Filled,Buy,227.0,42.78,6.7977419999999995,,1053
-2020-05-11 16:00:00,BGDRAI,Filled,Sell,-44.0,6.24,0.192192,,1054
-2020-05-11 16:00:00,MCCZID,Filled,Sell,-264.0,37.25,6.8838,,1055
-2020-05-11 16:00:00,RUKNMV,Filled,Sell,-3.0,25.11,0.052731,,1056
-2020-05-11 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1057
-2020-05-11 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1058
-2020-05-11 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1059
-2020-05-11 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1060
-2020-05-11 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1061
-2020-05-11 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1062
-2020-05-12 16:00:00,COMNHQ,Filled,Buy,532.0,10.01,3.727724,,1057
-2020-05-12 16:00:00,HECLON,Filled,Buy,343.0,44.39,10.658039,,1058
-2020-05-12 16:00:00,OCHCAU,Filled,Sell,-227.0,43.9,6.975709999999999,,1059
-2020-05-12 16:00:00,BGDRAI,Filled,Sell,-1554.0,6.21,6.755238,,1060
-2020-05-12 16:00:00,MCCZID,Filled,Buy,396.0,38.12,10.566864,,1061
-2020-05-12 16:00:00,RUKNMV,Filled,Buy,226.0,24.96,3.948672,,1062
-2020-05-12 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1063
-2020-05-12 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1064
-2020-05-12 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1065
-2020-05-12 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,1066
-2020-05-12 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1067
-2020-05-13 16:00:00,COMNHQ,Filled,Buy,67.0,9.5,0.44555,,1063
-2020-05-13 16:00:00,HECLON,Filled,Buy,13.0,42.03,0.382473,,1064
-2020-05-13 16:00:00,BGDRAI,Filled,Buy,2514.0,6.0,10.5588,,1065
-2020-05-13 16:00:00,MCCZID,Filled,Sell,-396.0,37.31,10.342332,,1066
-2020-05-13 16:00:00,RUKNMV,Filled,Buy,17.0,23.92,0.284648,,1067
-2020-05-13 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1068
-2020-05-13 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1069
-2020-05-13 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1070
-2020-05-13 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1071
-2020-05-13 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1072
-2020-05-13 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1073
-2020-05-14 16:00:00,COMNHQ,Filled,Buy,88.0,8.75,0.539,,1068
-2020-05-14 16:00:00,HECLON,Filled,Buy,14.0,39.87,0.390726,,1069
-2020-05-14 16:00:00,FFNDVM,Filled,Buy,3186.0,4.63,10.325826,,1070
-2020-05-14 16:00:00,BGDRAI,Filled,Sell,-2514.0,5.62,9.890076,,1071
-2020-05-14 16:00:00,ISIJLH,Filled,Buy,535.0,28.0,10.486,,1072
-2020-05-14 16:00:00,RUKNMV,Filled,Buy,40.0,22.14,0.61992,,1073
-2020-05-14 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1074
-2020-05-14 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1075
-2020-05-14 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1076
-2020-05-14 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1077
-2020-05-14 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,1078
-2020-05-14 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1079
-2020-05-14 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1080
-2020-05-14 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1081
-2020-05-15 16:00:00,COMNHQ,Filled,Sell,-29.0,8.92,0.181076,,1074
-2020-05-15 16:00:00,HECLON,Filled,Sell,-18.0,41.53,0.523278,,1075
-2020-05-15 16:00:00,FFNDVM,Filled,Sell,-3186.0,4.8,10.70496,,1076
-2020-05-15 16:00:00,ZIJVRO,Filled,Buy,251.0,57.47,10.097479,,1077
-2020-05-15 16:00:00,HCDUCB,Filled,Buy,324.0,43.4,9.84312,,1078
-2020-05-15 16:00:00,MCCZID,Filled,Buy,391.0,37.96,10.389652,,1079
-2020-05-15 16:00:00,ISIJLH,Filled,Sell,-535.0,28.28,10.59086,,1080
-2020-05-15 16:00:00,RUKNMV,Filled,Sell,-50.0,23.69,0.8291499999999999,,1081
-2020-05-15 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1082
-2020-05-15 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1083
-2020-05-15 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1084
-2020-05-15 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1085
-2020-05-15 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,1086
-2020-05-15 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,1087
-2020-05-15 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1088
-2020-05-18 16:00:00,COMNHQ,Filled,Sell,-545.0,9.6,3.6624,,1082
-2020-05-18 16:00:00,HECLON,Filled,Sell,-352.0,44.05,10.85392,,1083
-2020-05-18 16:00:00,BGDRAI,Filled,Buy,1774.0,5.78,7.1776040000000005,,1084
-2020-05-18 16:00:00,ZIJVRO,Filled,Sell,-84.0,59.75,3.5133,,1085
-2020-05-18 16:00:00,HCDUCB,Filled,Sell,-324.0,45.86,10.401048,,1086
-2020-05-18 16:00:00,MCCZID,Filled,Sell,-391.0,38.34,10.493658,,1087
-2020-05-18 16:00:00,RUKNMV,Filled,Sell,-201.0,24.56,3.455592,,1088
-2020-05-18 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1089
-2020-05-18 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1090
-2020-05-18 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1091
-2020-05-18 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1092
-2020-05-19 16:00:00,COMNHQ,Filled,Sell,-96.0,10.12,0.680064,,1089
-2020-05-19 16:00:00,BGDRAI,Filled,Sell,-229.0,6.27,1.005081,,1090
-2020-05-19 16:00:00,ZIJVRO,Filled,Sell,-167.0,60.1,7.025690000000001,,1091
-2020-05-19 16:00:00,RUKNMV,Filled,Sell,-35.0,25.0,0.6125,,1092
-2020-05-19 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1093
-2020-05-19 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1094
-2020-05-19 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1095
-2020-05-20 16:00:00,COMNHQ,Filled,Buy,23.0,9.9,0.15939,,1093
-2020-05-20 16:00:00,BGDRAI,Filled,Sell,-1545.0,6.34,6.85671,,1094
-2020-05-20 16:00:00,RUKNMV,Filled,Buy,23.0,24.45,0.393645,,1095
-2020-05-20 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1096
-2020-05-20 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1097
-2020-05-21 16:00:00,COMNHQ,Filled,Sell,-1004.0,9.87,6.936636,,1096
-2020-05-21 16:00:00,RUKNMV,Filled,Sell,-9.0,24.39,0.153657,,1097
-2020-05-21 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1098
-2020-05-22 16:00:00,RUKNMV,Filled,Sell,-395.0,24.47,6.765955,,1098
-2020-05-22 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1099
-2020-05-22 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1100
-2020-05-26 16:00:00,COMNHQ,Filled,Buy,998.0,10.25,7.1606499999999995,,1099
-2020-05-26 16:00:00,RUKNMV,Filled,Buy,400.0,25.1,7.028,,1100
-2020-05-26 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1101
-2020-05-26 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1102
-2020-05-26 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1103
-2020-05-26 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1104
-2020-05-27 16:00:00,COMNHQ,Filled,Buy,342.0,12.5,2.9925,,1101
-2020-05-27 16:00:00,LUZLYG,Filled,Buy,614.0,26.15,11.23927,,1102
-2020-05-27 16:00:00,HECLON,Filled,Buy,309.0,51.75,11.193525,,1103
-2020-05-27 16:00:00,RUKNMV,Filled,Buy,168.0,27.86,3.2763359999999997,,1104
-2020-05-27 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1105
-2020-05-27 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1106
-2020-05-27 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1107
-2020-05-27 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1108
-2020-05-28 16:00:00,COMNHQ,Filled,Sell,-93.0,11.83,0.7701330000000001,,1105
-2020-05-28 16:00:00,LUZLYG,Filled,Sell,-39.0,26.06,0.7114379999999999,,1106
-2020-05-28 16:00:00,HECLON,Filled,Sell,-23.0,52.85,0.850885,,1107
-2020-05-28 16:00:00,RUKNMV,Filled,Sell,-34.0,28.32,0.674016,,1108
-2020-05-28 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1109
-2020-05-28 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1110
-2020-05-28 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1111
-2020-05-28 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,1112
-2020-05-28 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1113
-2020-05-29 16:00:00,COMNHQ,Filled,Buy,110.0,10.43,0.80311,,1109
-2020-05-29 16:00:00,LUZLYG,Filled,Buy,24.0,24.42,0.410256,,1110
-2020-05-29 16:00:00,HECLON,Filled,Buy,17.0,48.0,0.5712,,1111
-2020-05-29 16:00:00,HCDUCB,Filled,Buy,320.0,46.61,10.44064,,1112
-2020-05-29 16:00:00,RUKNMV,Filled,Buy,13.0,26.5,0.24115,,1113
-2020-05-29 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1114
-2020-05-29 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1115
-2020-05-29 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1116
-2020-05-29 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1117
-2020-05-29 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,1118
-2020-05-29 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1119
-2020-06-01 16:00:00,COMNHQ,Filled,Buy,60.0,10.81,0.45402,,1114
-2020-06-01 16:00:00,LUZLYG,Filled,Buy,17.0,24.28,0.28893199999999997,,1115
-2020-06-01 16:00:00,HECLON,Filled,Buy,7.0,48.14,0.235886,,1116
-2020-06-01 16:00:00,OCHCAU,Filled,Buy,311.0,47.14,10.262378,,1117
-2020-06-01 16:00:00,HCDUCB,Filled,Sell,-10.0,47.44,0.33208,,1118
-2020-06-01 16:00:00,RUKNMV,Filled,Buy,15.0,26.61,0.27940499999999996,,1119
-2020-06-01 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1120
-2020-06-01 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1121
-2020-06-01 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1122
-2020-06-01 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1123
-2020-06-01 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,1124
-2020-06-01 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1125
-2020-06-02 16:00:00,COMNHQ,Filled,Sell,-328.0,11.4,2.61744,,1120
-2020-06-02 16:00:00,LUZLYG,Filled,Sell,-616.0,24.99,10.775688,,1121
-2020-06-02 16:00:00,HECLON,Filled,Sell,-66.0,50.71,2.3428020000000003,,1122
-2020-06-02 16:00:00,OCHCAU,Filled,Sell,-50.0,46.35,1.62225,,1123
-2020-06-02 16:00:00,HCDUCB,Filled,Sell,-49.0,46.49,1.594607,,1124
-2020-06-02 16:00:00,RUKNMV,Filled,Sell,-116.0,27.58,2.239496,,1125
-2020-06-02 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1126
-2020-06-02 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1127
-2020-06-02 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1128
-2020-06-02 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,1129
-2020-06-02 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1130
-2020-06-03 16:00:00,COMNHQ,Filled,Sell,-9.0,11.57,0.072891,,1126
-2020-06-03 16:00:00,HECLON,Filled,Sell,-244.0,52.5,8.967,,1127
-2020-06-03 16:00:00,OCHCAU,Filled,Sell,-261.0,47.0,8.5869,,1128
-2020-06-03 16:00:00,HCDUCB,Filled,Sell,-261.0,48.1,8.78787,,1129
-2020-06-03 16:00:00,RUKNMV,Filled,Sell,-446.0,28.39,8.863358,,1130
-2020-06-03 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1131
-2020-06-03 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1132
-2020-06-03 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1133
-2020-06-03 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1134
-2020-06-04 16:00:00,COMNHQ,Filled,Buy,143.0,12.85,1.286285,,1131
-2020-06-04 16:00:00,LUZLYG,Filled,Buy,557.0,25.75,10.039925,,1132
-2020-06-04 16:00:00,HECLON,Filled,Buy,271.0,53.3,10.11101,,1133
-2020-06-04 16:00:00,RUKNMV,Filled,Buy,502.0,29.4,10.33116,,1134
-2020-06-04 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1135
-2020-06-04 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1136
-2020-06-04 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1137
-2020-06-04 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,1138
-2020-06-04 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1139
-2020-06-05 16:00:00,COMNHQ,Filled,Sell,-350.0,21.24,5.203799999999999,,1135
-2020-06-05 16:00:00,LUZLYG,Filled,Sell,-12.0,29.0,0.2436,,1136
-2020-06-05 16:00:00,HECLON,Filled,Sell,-9.0,61.54,0.387702,,1137
-2020-06-05 16:00:00,HCDUCB,Filled,Buy,285.0,52.69,10.511655,,1138
-2020-06-05 16:00:00,RUKNMV,Filled,Sell,-19.0,33.8,0.44953999999999994,,1139
-2020-06-05 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1140
-2020-06-05 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1141
-2020-06-05 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1142
-2020-06-05 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1143
-2020-06-05 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,1144
-2020-06-05 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1145
-2020-06-08 16:00:00,COMNHQ,Filled,Sell,-873.0,19.9,12.160889999999998,,1140
-2020-06-08 16:00:00,LUZLYG,Filled,Sell,-23.0,28.6,0.46046,,1141
-2020-06-08 16:00:00,HECLON,Filled,Sell,-262.0,60.7,11.13238,,1142
-2020-06-08 16:00:00,ZIXTLG,Filled,Buy,1353.0,11.17,10.579107,,1143
-2020-06-08 16:00:00,HCDUCB,Filled,Sell,-285.0,54.5,10.87275,,1144
-2020-06-08 16:00:00,RUKNMV,Filled,Sell,-19.0,32.79,0.436107,,1145
-2020-06-08 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1146
-2020-06-08 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1147
-2020-06-08 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1148
-2020-06-09 16:00:00,LUZLYG,Filled,Sell,-522.0,27.65,10.10331,,1146
-2020-06-09 16:00:00,ZIXTLG,Filled,Sell,-23.0,11.0,0.1771,,1147
-2020-06-09 16:00:00,RUKNMV,Filled,Sell,-15.0,32.4,0.3402,,1148
-2020-06-09 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1149
-2020-06-09 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1150
-2020-06-09 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1151
-2020-06-09 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1152
-2020-06-09 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1153
-2020-06-10 16:00:00,COMNHQ,Filled,Buy,532.0,17.69,6.587756,,1149
-2020-06-10 16:00:00,SMDIFE,Filled,Buy,28.0,347.97,6.820212,,1150
-2020-06-10 16:00:00,LUZLYG,Filled,Buy,349.0,27.97,6.8330709999999995,,1151
-2020-06-10 16:00:00,ZIXTLG,Filled,Sell,-1330.0,11.32,10.53892,,1152
-2020-06-10 16:00:00,RUKNMV,Filled,Sell,-449.0,32.3,10.15189,,1153
-2020-06-10 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1154
-2020-06-10 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1155
-2020-06-10 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1156
-2020-06-10 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1157
-2020-06-10 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1158
-2020-06-11 16:00:00,COMNHQ,Filled,Buy,47.0,14.52,0.477708,,1154
-2020-06-11 16:00:00,SMDIFE,Filled,Sell,-1.0,349.3,0.24451,,1155
-2020-06-11 16:00:00,LUZLYG,Filled,Buy,21.0,25.0,0.3675,,1156
-2020-06-11 16:00:00,HECLON,Filled,Buy,176.0,51.67,6.365744,,1157
-2020-06-11 16:00:00,BPSPGV,Filled,Buy,50.0,193.13,6.75955,,1158
-2020-06-11 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1159
-2020-06-11 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1160
-2020-06-11 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1161
-2020-06-11 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1162
-2020-06-11 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1163
-2020-06-11 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1164
-2020-06-12 16:00:00,COMNHQ,Filled,Sell,-579.0,16.82,6.817146,,1159
-2020-06-12 16:00:00,SMDIFE,Filled,Sell,-27.0,344.9,6.51861,,1160
-2020-06-12 16:00:00,LUZLYG,Filled,Sell,-370.0,25.05,6.48795,,1161
-2020-06-12 16:00:00,HECLON,Filled,Buy,29.0,51.42,1.043826,,1162
-2020-06-12 16:00:00,ZIXTLG,Filled,Buy,1001.0,10.48,7.343336,,1163
-2020-06-12 16:00:00,BPSPGV,Filled,Sell,-50.0,190.55,6.66925,,1164
-2020-06-12 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1165
-2020-06-12 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1166
-2020-06-15 16:00:00,HECLON,Filled,Sell,-205.0,50.0,7.175,,1165
-2020-06-15 16:00:00,ZIXTLG,Filled,Sell,-62.0,10.0,0.434,,1166
-2020-06-15 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1167
-2020-06-16 16:00:00,ZIXTLG,Filled,Sell,-939.0,11.13,7.315749000000001,,1167
-2020-06-16 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1168
-2020-06-17 16:00:00,HECLON,Filled,Buy,180.0,54.56,6.874560000000001,,1168
-2020-06-17 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1169
-2020-06-18 16:00:00,HECLON,Filled,Buy,5.0,52.67,0.184345,,1169
-2020-06-18 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1170
-2020-06-18 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1171
-2020-06-19 16:00:00,HECLON,Filled,Sell,-185.0,54.02,6.995590000000001,,1170
-2020-06-19 16:00:00,ZIXTLG,Filled,Buy,932.0,10.83,7.065492,,1171
-2020-06-19 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1172
-2020-06-22 16:00:00,ZIXTLG,Filled,Buy,6.0,10.57,0.044394,,1172
-2020-06-22 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1173
-2020-06-22 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1174
-2020-06-23 16:00:00,HECLON,Filled,Buy,189.0,52.95,7.005285000000001,,1173
-2020-06-23 16:00:00,ZIXTLG,Filled,Sell,-25.0,11.09,0.194075,,1174
-2020-06-23 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1175
-2020-06-23 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1176
-2020-06-24 16:00:00,HECLON,Filled,Sell,-189.0,51.7,6.839910000000001,,1175
-2020-06-24 16:00:00,ZIXTLG,Filled,Buy,414.0,10.92,3.164616,,1176
-2020-06-24 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1177
-2020-06-25 16:00:00,ZIXTLG,Filled,Sell,-1327.0,10.56,9.809184,,1177
-2020-06-25 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1178
-2020-06-25 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1179
-2020-06-25 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1180
-2020-06-26 16:00:00,HECLON,Filled,Buy,283.0,51.9,10.281389999999998,,1178
-2020-06-26 16:00:00,ZIXTLG,Filled,Buy,1346.0,11.0,10.3642,,1179
-2020-06-26 16:00:00,RUKNMV,Filled,Buy,545.0,26.2,9.9953,,1180
-2020-06-26 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1181
-2020-06-26 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1182
-2020-06-26 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1183
-2020-06-26 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1184
-2020-06-29 16:00:00,COMNHQ,Filled,Buy,1185.0,12.55,10.410225,,1181
-2020-06-29 16:00:00,HECLON,Filled,Buy,12.0,50.28,0.422352,,1182
-2020-06-29 16:00:00,ZIXTLG,Filled,Buy,14.0,10.94,0.107212,,1183
-2020-06-29 16:00:00,RUKNMV,Filled,Sell,-545.0,25.64,9.78166,,1184
-2020-06-29 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1185
-2020-06-29 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1186
-2020-06-29 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1187
-2020-06-30 16:00:00,COMNHQ,Filled,Sell,-345.0,13.11,3.1660649999999997,,1185
-2020-06-30 16:00:00,HECLON,Filled,Sell,-295.0,49.7,10.26305,,1186
-2020-06-30 16:00:00,ZIXTLG,Filled,Sell,-1360.0,11.07,10.53864,,1187
-2020-06-30 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1188
-2020-06-30 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1189
-2020-07-01 16:00:00,COMNHQ,Filled,Buy,15.0,13.46,0.14133,,1188
-2020-07-01 16:00:00,ZIXTLG,Filled,Buy,966.0,11.64,7.870968,,1189
-2020-07-01 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1190
-2020-07-01 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1191
-2020-07-01 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1192
-2020-07-02 16:00:00,COMNHQ,Filled,Buy,211.0,13.36,1.973272,,1190
-2020-07-02 16:00:00,FFNDVM,Filled,Buy,2285.0,6.1,9.75695,,1191
-2020-07-02 16:00:00,ZIXTLG,Filled,Sell,-966.0,11.65,7.87773,,1192
-2020-07-02 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1193
-2020-07-02 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1194
-2020-07-06 16:00:00,COMNHQ,Filled,Buy,26.0,12.82,0.233324,,1193
-2020-07-06 16:00:00,FFNDVM,Filled,Sell,-27.0,6.15,0.116235,,1194
-2020-07-06 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1195
-2020-07-06 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1196
-2020-07-06 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1197
-2020-07-06 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1198
-2020-07-07 16:00:00,COMNHQ,Filled,Sell,-25.0,12.51,0.218925,,1195
-2020-07-07 16:00:00,HECLON,Filled,Buy,263.0,51.25,9.435125,,1196
-2020-07-07 16:00:00,FFNDVM,Filled,Sell,-50.0,6.13,0.21455,,1197
-2020-07-07 16:00:00,ZIXTLG,Filled,Buy,1072.0,12.7,9.53008,,1198
-2020-07-07 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1199
-2020-07-07 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1200
-2020-07-07 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1201
-2020-07-07 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1202
-2020-07-07 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1203
-2020-07-07 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1204
-2020-07-08 16:00:00,COMNHQ,Filled,Sell,-242.0,11.59,1.963346,,1199
-2020-07-08 16:00:00,LUZLYG,Filled,Buy,427.0,22.98,6.868722000000001,,1200
-2020-07-08 16:00:00,HECLON,Filled,Sell,-68.0,50.2,2.38952,,1201
-2020-07-08 16:00:00,FFNDVM,Filled,Sell,-602.0,6.12,2.578968,,1202
-2020-07-08 16:00:00,ZIXTLG,Filled,Sell,-1072.0,12.93,9.702672,,1203
-2020-07-08 16:00:00,RUKNMV,Filled,Buy,401.0,24.44,6.860308,,1204
-2020-07-08 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1205
-2020-07-08 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1206
-2020-07-08 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1207
-2020-07-08 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1208
-2020-07-08 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1209
-2020-07-08 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1210
-2020-07-09 16:00:00,COMNHQ,Filled,Sell,-5.0,11.92,0.04172,,1205
-2020-07-09 16:00:00,LUZLYG,Filled,Sell,-2.0,22.92,0.032088000000000005,,1206
-2020-07-09 16:00:00,HECLON,Filled,Sell,-2.0,50.73,0.071022,,1207
-2020-07-09 16:00:00,FFNDVM,Filled,Buy,8.0,6.09,0.034103999999999995,,1208
-2020-07-09 16:00:00,BGDRAI,Filled,Buy,1433.0,6.79,6.811049,,1209
-2020-07-09 16:00:00,RUKNMV,Filled,Sell,-1.0,24.45,0.017115,,1210
-2020-07-09 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1211
-2020-07-09 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1212
-2020-07-09 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1213
-2020-07-09 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1214
-2020-07-09 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1215
-2020-07-09 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1216
-2020-07-09 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1217
-2020-07-10 16:00:00,COMNHQ,Filled,Buy,57.0,11.0,0.4389,,1211
-2020-07-10 16:00:00,LUZLYG,Filled,Buy,5.0,22.71,0.07948500000000001,,1212
-2020-07-10 16:00:00,HECLON,Filled,Buy,5.0,49.52,0.17332,,1213
-2020-07-10 16:00:00,FFNDVM,Filled,Buy,66.0,5.77,0.266574,,1214
-2020-07-10 16:00:00,BGDRAI,Filled,Buy,58.0,6.55,0.26593,,1215
-2020-07-10 16:00:00,ISIJLH,Filled,Buy,332.0,29.47,6.848827999999999,,1216
-2020-07-10 16:00:00,RUKNMV,Filled,Buy,8.0,24.15,0.13524,,1217
-2020-07-10 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1218
-2020-07-10 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1219
-2020-07-10 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1220
-2020-07-10 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1221
-2020-07-10 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1222
-2020-07-10 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1223
-2020-07-10 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1224
-2020-07-10 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1225
-2020-07-13 16:00:00,COMNHQ,Filled,Sell,-53.0,12.17,0.451507,,1218
-2020-07-13 16:00:00,RLSRXX,Filled,Buy,176.0,56.71,6.986672,,1219
-2020-07-13 16:00:00,LUZLYG,Filled,Sell,-21.0,24.39,0.35853300000000005,,1220
-2020-07-13 16:00:00,HECLON,Filled,Sell,-12.0,53.31,0.447804,,1221
-2020-07-13 16:00:00,FFNDVM,Filled,Sell,-67.0,6.17,0.289373,,1222
-2020-07-13 16:00:00,BGDRAI,Filled,Sell,-20.0,6.77,0.09478,,1223
-2020-07-13 16:00:00,ISIJLH,Filled,Sell,-332.0,30.14,7.004536,,1224
-2020-07-13 16:00:00,RUKNMV,Filled,Sell,-22.0,25.8,0.39732,,1225
-2020-07-13 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1226
-2020-07-13 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1227
-2020-07-13 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1228
-2020-07-13 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1229
-2020-07-13 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1230
-2020-07-13 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1231
-2020-07-13 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1232
-2020-07-13 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1233
-2020-07-14 16:00:00,COMNHQ,Filled,Buy,334.0,11.33,2.648954,,1226
-2020-07-14 16:00:00,RLSRXX,Filled,Sell,-176.0,53.65,6.60968,,1227
-2020-07-14 16:00:00,LUZLYG,Filled,Sell,-409.0,23.96,6.859748000000001,,1228
-2020-07-14 16:00:00,HECLON,Filled,Sell,-186.0,51.34,6.684468,,1229
-2020-07-14 16:00:00,FFNDVM,Filled,Sell,-1613.0,6.15,6.943965,,1230
-2020-07-14 16:00:00,BGDRAI,Filled,Sell,-1471.0,6.65,6.847505,,1231
-2020-07-14 16:00:00,MCCZID,Filled,Buy,382.0,35.34,9.449916,,1232
-2020-07-14 16:00:00,RUKNMV,Filled,Sell,-386.0,23.99,6.482098,,1233
-2020-07-14 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1234
-2020-07-14 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1235
-2020-07-14 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1236
-2020-07-14 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1237
-2020-07-14 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,1238
-2020-07-14 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1239
-2020-07-15 16:00:00,COMNHQ,Filled,Buy,5.0,12.47,0.043645,,1234
-2020-07-15 16:00:00,HECLON,Filled,Buy,268.0,51.85,9.72706,,1235
-2020-07-15 16:00:00,FFNDVM,Filled,Buy,2116.0,6.53,9.672236000000002,,1236
-2020-07-15 16:00:00,BGDRAI,Filled,Buy,1956.0,7.09,9.707628,,1237
-2020-07-15 16:00:00,MCCZID,Filled,Sell,-382.0,35.92,9.605008,,1238
-2020-07-15 16:00:00,RUKNMV,Filled,Buy,555.0,25.04,9.72804,,1239
-2020-07-15 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1240
-2020-07-15 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1241
-2020-07-15 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1242
-2020-07-15 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1243
-2020-07-15 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1244
-2020-07-16 16:00:00,COMNHQ,Filled,Sell,-145.0,12.71,1.290065,,1240
-2020-07-16 16:00:00,HECLON,Filled,Sell,-4.0,51.44,0.144032,,1241
-2020-07-16 16:00:00,FFNDVM,Filled,Sell,-2116.0,6.65,9.84998,,1242
-2020-07-16 16:00:00,BGDRAI,Filled,Sell,-39.0,7.06,0.192738,,1243
-2020-07-16 16:00:00,RUKNMV,Filled,Sell,-15.0,24.9,0.26145,,1244
-2020-07-16 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1245
-2020-07-16 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1246
-2020-07-16 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1247
-2020-07-16 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1248
-2020-07-16 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1249
-2020-07-17 16:00:00,COMNHQ,Filled,Buy,65.0,12.47,0.567385,,1245
-2020-07-17 16:00:00,HECLON,Filled,Sell,-2.0,51.14,0.071596,,1246
-2020-07-17 16:00:00,FFNDVM,Filled,Buy,1965.0,6.9,9.49095,,1247
-2020-07-17 16:00:00,BGDRAI,Filled,Sell,-5.0,7.07,0.024745,,1248
-2020-07-17 16:00:00,RUKNMV,Filled,Sell,-540.0,25.43,9.61254,,1249
-2020-07-17 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1250
-2020-07-17 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1251
-2020-07-17 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1252
-2020-07-17 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1253
-2020-07-17 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1254
-2020-07-17 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1255
-2020-07-17 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1256
-2020-07-20 16:00:00,COMNHQ,Filled,Sell,-258.0,11.92,2.152752,,1250
-2020-07-20 16:00:00,LUZLYG,Filled,Buy,423.0,23.19,6.8665590000000005,,1251
-2020-07-20 16:00:00,HECLON,Filled,Sell,-67.0,49.88,2.339372,,1252
-2020-07-20 16:00:00,OCHCAU,Filled,Buy,210.0,46.63,6.854610000000001,,1253
-2020-07-20 16:00:00,FFNDVM,Filled,Sell,-1965.0,6.76,9.29838,,1254
-2020-07-20 16:00:00,BGDRAI,Filled,Sell,-1912.0,7.01,9.382184,,1255
-2020-07-20 16:00:00,RUKNMV,Filled,Buy,394.0,24.75,6.8260499999999995,,1256
-2020-07-20 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1257
-2020-07-20 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1258
-2020-07-20 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1259
-2020-07-20 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1260
-2020-07-20 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1261
-2020-07-20 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1262
-2020-07-21 16:00:00,COMNHQ,Filled,Buy,31.0,11.54,0.250418,,1257
-2020-07-21 16:00:00,LUZLYG,Filled,Sell,-423.0,23.72,7.023491999999999,,1258
-2020-07-21 16:00:00,HECLON,Filled,Sell,-195.0,50.85,6.941025,,1259
-2020-07-21 16:00:00,OCHCAU,Filled,Sell,-210.0,47.29,6.95163,,1260
-2020-07-21 16:00:00,BGDRAI,Filled,Buy,1430.0,6.92,6.92692,,1261
-2020-07-21 16:00:00,RUKNMV,Filled,Sell,-394.0,24.71,6.815017999999999,,1262
-2020-07-21 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1263
-2020-07-21 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1264
-2020-07-21 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1265
-2020-07-21 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1266
-2020-07-21 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1267
-2020-07-22 16:00:00,COMNHQ,Filled,Buy,1.0,11.39,0.007973000000000001,,1263
-2020-07-22 16:00:00,LUZLYG,Filled,Buy,402.0,24.27,6.829578,,1264
-2020-07-22 16:00:00,HECLON,Filled,Buy,190.0,51.54,6.85482,,1265
-2020-07-22 16:00:00,BGDRAI,Filled,Sell,-1430.0,6.97,6.976970000000001,,1266
-2020-07-22 16:00:00,RUKNMV,Filled,Buy,375.0,26.13,6.859125,,1267
-2020-07-22 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1268
-2020-07-22 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1269
-2020-07-22 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1270
-2020-07-22 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1271
-2020-07-23 16:00:00,COMNHQ,Filled,Buy,8.0,11.27,0.063112,,1268
-2020-07-23 16:00:00,LUZLYG,Filled,Sell,-402.0,24.5,6.8943,,1269
-2020-07-23 16:00:00,HECLON,Filled,Sell,-190.0,51.45,6.84285,,1270
-2020-07-23 16:00:00,RUKNMV,Filled,Sell,-375.0,26.19,6.874875,,1271
-2020-07-23 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1272
-2020-07-23 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1273
-2020-07-23 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1274
-2020-07-24 16:00:00,COMNHQ,Filled,Sell,-30.0,11.66,0.24486,,1272
-2020-07-24 16:00:00,LUZLYG,Filled,Buy,400.0,24.56,6.8768,,1273
-2020-07-24 16:00:00,HECLON,Filled,Buy,188.0,52.1,6.8563600000000005,,1274
-2020-07-24 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1275
-2020-07-24 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1276
-2020-07-24 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1277
-2020-07-24 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1278
-2020-07-24 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,1279
-2020-07-27 16:00:00,COMNHQ,Filled,Buy,28.0,11.5,0.2254,,1275
-2020-07-27 16:00:00,LUZLYG,Filled,Buy,3.0,24.21,0.050841,,1276
-2020-07-27 16:00:00,HECLON,Filled,Buy,2.0,51.16,0.071624,,1277
-2020-07-27 16:00:00,ZIJVRO,Filled,Buy,194.0,51.05,6.932589999999999,,1278
-2020-07-27 16:00:00,HCDUCB,Filled,Buy,196.0,50.59,6.940948000000001,,1279
-2020-07-27 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1280
-2020-07-27 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1281
-2020-07-27 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1282
-2020-07-27 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1283
-2020-07-27 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1284
-2020-07-27 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,1285
-2020-07-27 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1286
-2020-07-28 16:00:00,COMNHQ,Filled,Sell,-1.0,11.37,0.007958999999999999,,1280
-2020-07-28 16:00:00,LUZLYG,Filled,Buy,4.0,24.13,0.067564,,1281
-2020-07-28 16:00:00,HECLON,Filled,Buy,1.0,51.02,0.035714,,1282
-2020-07-28 16:00:00,ZIXTLG,Filled,Buy,724.0,13.35,6.7657799999999995,,1283
-2020-07-28 16:00:00,ZIJVRO,Filled,Sell,-194.0,49.5,6.7221,,1284
-2020-07-28 16:00:00,HCDUCB,Filled,Sell,-196.0,51.25,7.0315,,1285
-2020-07-28 16:00:00,RUKNMV,Filled,Buy,385.0,25.5,6.87225,,1286
-2020-07-28 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1287
-2020-07-28 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1288
-2020-07-28 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1289
-2020-07-28 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1290
-2020-07-28 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1291
-2020-07-29 16:00:00,COMNHQ,Filled,Buy,282.0,11.79,2.327346,,1287
-2020-07-29 16:00:00,LUZLYG,Filled,Buy,145.0,24.33,2.469495,,1288
-2020-07-29 16:00:00,HECLON,Filled,Sell,-191.0,51.17,6.841429000000001,,1289
-2020-07-29 16:00:00,ZIXTLG,Filled,Sell,-724.0,13.32,6.750576000000001,,1290
-2020-07-29 16:00:00,RUKNMV,Filled,Sell,-385.0,25.5,6.87225,,1291
-2020-07-29 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1292
-2020-07-29 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1293
-2020-07-29 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1294
-2020-07-30 16:00:00,COMNHQ,Filled,Buy,580.0,11.22,4.55532,,1292
-2020-07-30 16:00:00,LUZLYG,Filled,Buy,226.0,24.64,3.898048,,1293
-2020-07-30 16:00:00,HECLON,Filled,Buy,374.0,51.07,13.370126,,1294
-2020-07-30 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1295
-2020-07-30 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1296
-2020-07-30 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1297
-2020-07-30 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1298
-2020-07-30 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1299
-2020-07-31 16:00:00,COMNHQ,Filled,Buy,33.0,11.12,0.256872,,1295
-2020-07-31 16:00:00,LUZLYG,Filled,Sell,-778.0,24.9,13.560539999999998,,1296
-2020-07-31 16:00:00,HECLON,Filled,Buy,12.0,50.24,0.422016,,1297
-2020-07-31 16:00:00,ZIXTLG,Filled,Buy,1518.0,12.99,13.803174,,1298
-2020-07-31 16:00:00,RUKNMV,Filled,Buy,797.0,24.5,13.66855,,1299
-2020-07-31 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1300
-2020-07-31 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1301
-2020-07-31 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1302
-2020-07-31 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1303
-2020-07-31 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1304
-2020-08-03 16:00:00,COMNHQ,Filled,Buy,8.0,11.06,0.061936000000000005,,1300
-2020-08-03 16:00:00,SMDIFE,Filled,Buy,46.0,433.0,13.9426,,1301
-2020-08-03 16:00:00,HECLON,Filled,Buy,6.0,50.4,0.21168,,1302
-2020-08-03 16:00:00,ZIXTLG,Filled,Sell,-1518.0,13.15,13.97319,,1303
-2020-08-03 16:00:00,RUKNMV,Filled,Sell,-797.0,24.15,13.473285,,1304
-2020-08-03 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1305
-2020-08-03 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1306
-2020-08-03 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1307
-2020-08-03 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1308
-2020-08-03 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1309
-2020-08-04 16:00:00,COMNHQ,Filled,Sell,-380.0,11.24,2.98984,,1305
-2020-08-04 16:00:00,SMDIFE,Filled,Sell,-46.0,436.55,14.056909999999998,,1306
-2020-08-04 16:00:00,HECLON,Filled,Sell,-392.0,50.28,13.796832000000002,,1307
-2020-08-04 16:00:00,FFNDVM,Filled,Buy,2293.0,6.88,11.043088,,1308
-2020-08-04 16:00:00,BPSPGV,Filled,Buy,70.0,214.29,10.50021,,1309
-2020-08-04 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1310
-2020-08-04 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1311
-2020-08-04 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1312
-2020-08-05 16:00:00,COMNHQ,Filled,Sell,-47.0,11.85,0.389865,,1310
-2020-08-05 16:00:00,FFNDVM,Filled,Sell,-55.0,6.86,0.26411,,1311
-2020-08-05 16:00:00,BPSPGV,Filled,Sell,-70.0,214.97,10.53353,,1312
-2020-08-05 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1313
-2020-08-05 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1314
-2020-08-05 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1315
-2020-08-05 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1316
-2020-08-06 16:00:00,COMNHQ,Filled,Sell,-114.0,13.02,1.038996,,1313
-2020-08-06 16:00:00,HECLON,Filled,Buy,301.0,50.75,10.693025,,1314
-2020-08-06 16:00:00,FFNDVM,Filled,Sell,-29.0,6.93,0.140679,,1315
-2020-08-06 16:00:00,ZIXTLG,Filled,Buy,1101.0,14.0,10.7898,,1316
-2020-08-06 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1317
-2020-08-06 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1318
-2020-08-06 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1319
-2020-08-06 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1320
-2020-08-06 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1321
-2020-08-07 16:00:00,COMNHQ,Filled,Sell,-44.0,12.79,0.393932,,1317
-2020-08-07 16:00:00,HECLON,Filled,Buy,1.0,50.52,0.035364,,1318
-2020-08-07 16:00:00,FFNDVM,Filled,Sell,-2209.0,6.88,10.638544,,1319
-2020-08-07 16:00:00,ZIXTLG,Filled,Sell,-44.0,14.12,0.4348959999999999,,1320
-2020-08-07 16:00:00,BGDRAI,Filled,Buy,2432.0,6.3,10.72512,,1321
-2020-08-07 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1322
-2020-08-07 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1323
-2020-08-07 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1324
-2020-08-07 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,1325
-2020-08-07 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1326
-2020-08-07 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1327
-2020-08-07 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1328
-2020-08-10 16:00:00,COMNHQ,Filled,Buy,1.0,13.27,0.009289,,1322
-2020-08-10 16:00:00,LUZLYG,Filled,Buy,589.0,26.27,10.831121,,1323
-2020-08-10 16:00:00,HECLON,Filled,Sell,-7.0,52.29,0.256221,,1324
-2020-08-10 16:00:00,YIVYGH,Filled,Buy,359.0,42.56,10.695328,,1325
-2020-08-10 16:00:00,ZIXTLG,Filled,Sell,-1057.0,14.15,10.469585,,1326
-2020-08-10 16:00:00,BGDRAI,Filled,Sell,-27.0,6.4,0.12096,,1327
-2020-08-10 16:00:00,RUKNMV,Filled,Buy,614.0,25.25,10.85245,,1328
-2020-08-10 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1329
-2020-08-10 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1330
-2020-08-10 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1331
-2020-08-10 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,1332
-2020-08-10 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1333
-2020-08-10 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1334
-2020-08-10 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1335
-2020-08-11 16:00:00,COMNHQ,Filled,Sell,-79.0,15.03,0.8311589999999999,,1329
-2020-08-11 16:00:00,LUZLYG,Filled,Sell,-9.0,27.25,0.171675,,1330
-2020-08-11 16:00:00,HECLON,Filled,Sell,-4.0,54.5,0.1526,,1331
-2020-08-11 16:00:00,YIVYGH,Filled,Sell,-359.0,43.25,10.868725,,1332
-2020-08-11 16:00:00,FFNDVM,Filled,Buy,2176.0,7.24,11.027968,,1333
-2020-08-11 16:00:00,BGDRAI,Filled,Sell,-92.0,6.86,0.441784,,1334
-2020-08-11 16:00:00,RUKNMV,Filled,Buy,10.0,25.34,0.17738,,1335
-2020-08-11 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1336
-2020-08-11 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1337
-2020-08-11 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1338
-2020-08-11 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1339
-2020-08-11 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1340
-2020-08-11 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1341
-2020-08-11 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1342
-2020-08-12 16:00:00,COMNHQ,Filled,Sell,-383.0,14.04,3.764124,,1336
-2020-08-12 16:00:00,LUZLYG,Filled,Sell,-213.0,27.5,4.10025,,1337
-2020-08-12 16:00:00,HECLON,Filled,Sell,-108.0,54.86,4.147416,,1338
-2020-08-12 16:00:00,FFNDVM,Filled,Sell,-809.0,7.31,4.139653,,1339
-2020-08-12 16:00:00,ZIXTLG,Filled,Buy,708.0,14.2,7.03752,,1340
-2020-08-12 16:00:00,BGDRAI,Filled,Sell,-845.0,6.87,4.063605,,1341
-2020-08-12 16:00:00,RUKNMV,Filled,Sell,-234.0,25.98,4.255523999999999,,1342
-2020-08-12 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1343
-2020-08-12 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1344
-2020-08-12 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1345
-2020-08-12 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1346
-2020-08-12 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1347
-2020-08-12 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1348
-2020-08-12 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1349
-2020-08-13 16:00:00,COMNHQ,Filled,Buy,11.0,13.17,0.101409,,1343
-2020-08-13 16:00:00,LUZLYG,Filled,Buy,2.0,26.38,0.036932,,1344
-2020-08-13 16:00:00,HECLON,Filled,Buy,2.0,52.81,0.073934,,1345
-2020-08-13 16:00:00,FFNDVM,Filled,Buy,23.0,7.02,0.11302199999999998,,1346
-2020-08-13 16:00:00,ZIXTLG,Filled,Sell,-708.0,13.85,6.864059999999999,,1347
-2020-08-13 16:00:00,BGDRAI,Filled,Buy,2.0,6.59,0.009226,,1348
-2020-08-13 16:00:00,RUKNMV,Filled,Buy,2.0,24.93,0.034902,,1349
-2020-08-13 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1350
-2020-08-13 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1351
-2020-08-13 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1352
-2020-08-13 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1353
-2020-08-13 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1354
-2020-08-13 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1355
-2020-08-14 16:00:00,COMNHQ,Filled,Buy,12.0,13.11,0.110124,,1350
-2020-08-14 16:00:00,LUZLYG,Filled,Buy,5.0,26.06,0.09121,,1351
-2020-08-14 16:00:00,HECLON,Filled,Buy,1.0,52.45,0.036715000000000005,,1352
-2020-08-14 16:00:00,FFNDVM,Filled,Buy,14.0,6.98,0.06840399999999999,,1353
-2020-08-14 16:00:00,BGDRAI,Filled,Buy,26.0,6.52,0.118664,,1354
-2020-08-14 16:00:00,RUKNMV,Filled,Sell,-392.0,24.81,6.807863999999999,,1355
-2020-08-14 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1356
-2020-08-14 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1357
-2020-08-14 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1358
-2020-08-14 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1359
-2020-08-14 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1360
-2020-08-17 16:00:00,COMNHQ,Filled,Sell,-2.0,13.31,0.018634,,1356
-2020-08-17 16:00:00,LUZLYG,Filled,Sell,-374.0,26.31,6.887957999999999,,1357
-2020-08-17 16:00:00,FFNDVM,Filled,Sell,-2.0,7.02,0.009828,,1358
-2020-08-17 16:00:00,BGDRAI,Filled,Sell,-13.0,6.67,0.060696999999999994,,1359
-2020-08-17 16:00:00,RUKNMV,Filled,Buy,390.0,25.0,6.825,,1360
-2020-08-17 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1361
-2020-08-17 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1362
-2020-08-17 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1363
-2020-08-17 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,1364
-2020-08-17 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1365
-2020-08-17 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1366
-2020-08-17 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1367
-2020-08-17 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1368
-2020-08-18 16:00:00,COMNHQ,Filled,Buy,41.0,12.61,0.361907,,1361
-2020-08-18 16:00:00,LUZLYG,Filled,Buy,380.0,25.86,6.87876,,1362
-2020-08-18 16:00:00,HECLON,Filled,Buy,5.0,51.49,0.180215,,1363
-2020-08-18 16:00:00,YIVYGH,Filled,Buy,226.0,43.71,6.914922000000001,,1364
-2020-08-18 16:00:00,FFNDVM,Filled,Buy,10.0,7.0,0.049,,1365
-2020-08-18 16:00:00,ZIXTLG,Filled,Buy,699.0,14.3,6.99699,,1366
-2020-08-18 16:00:00,BGDRAI,Filled,Buy,41.0,6.5,0.18655,,1367
-2020-08-18 16:00:00,RUKNMV,Filled,Buy,13.0,24.42,0.22222200000000003,,1368
-2020-08-18 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1369
-2020-08-18 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1370
-2020-08-18 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1371
-2020-08-18 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,1372
-2020-08-18 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1373
-2020-08-18 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1374
-2020-08-18 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1375
-2020-08-18 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1376
-2020-08-18 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,1377
-2020-08-18 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1378
-2020-08-19 16:00:00,COMNHQ,Filled,Buy,1.0,12.65,0.008855,,1369
-2020-08-19 16:00:00,LUZLYG,Filled,Buy,6.0,25.64,0.107688,,1370
-2020-08-19 16:00:00,HECLON,Filled,Buy,4.0,50.68,0.141904,,1371
-2020-08-19 16:00:00,YIVYGH,Filled,Sell,-226.0,43.66,6.907012,,1372
-2020-08-19 16:00:00,FFNDVM,Filled,Buy,18.0,6.88,0.086688,,1373
-2020-08-19 16:00:00,ZIXTLG,Filled,Sell,-16.0,14.55,0.16296,,1374
-2020-08-19 16:00:00,BGDRAI,Filled,Buy,6.0,6.44,0.027048,,1375
-2020-08-19 16:00:00,ZIJVRO,Filled,Buy,202.0,48.8,6.900319999999999,,1376
-2020-08-19 16:00:00,HCDUCB,Filled,Buy,221.0,44.3,6.85321,,1377
-2020-08-19 16:00:00,RUKNMV,Filled,Buy,6.0,24.0,0.1008,,1378
-2020-08-19 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1379
-2020-08-19 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1380
-2020-08-19 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1381
-2020-08-19 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1382
-2020-08-19 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1383
-2020-08-19 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1384
-2020-08-19 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1385
-2020-08-19 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,1386
-2020-08-20 16:00:00,COMNHQ,Filled,Sell,-5.0,12.38,0.04333,,1379
-2020-08-20 16:00:00,LUZLYG,Filled,Sell,-386.0,25.15,6.795529999999999,,1380
-2020-08-20 16:00:00,HECLON,Filled,Buy,1.0,49.52,0.034664,,1381
-2020-08-20 16:00:00,FFNDVM,Filled,Sell,-1430.0,6.77,6.776769999999999,,1382
-2020-08-20 16:00:00,ZIXTLG,Filled,Sell,-24.0,14.6,0.24527999999999997,,1383
-2020-08-20 16:00:00,BGDRAI,Filled,Buy,14.0,6.33,0.062034000000000006,,1384
-2020-08-20 16:00:00,ZIJVRO,Filled,Buy,1.0,49.82,0.034874,,1385
-2020-08-20 16:00:00,HCDUCB,Filled,Sell,-221.0,42.68,6.602596,,1386
-2020-08-20 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1387
-2020-08-20 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1388
-2020-08-20 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1389
-2020-08-20 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1390
-2020-08-20 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1391
-2020-08-20 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1392
-2020-08-20 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,1393
-2020-08-20 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1394
-2020-08-20 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1395
-2020-08-21 16:00:00,COMNHQ,Filled,Buy,10.0,12.47,0.08729,,1387
-2020-08-21 16:00:00,LUZLYG,Filled,Buy,392.0,25.0,6.86,,1388
-2020-08-21 16:00:00,HECLON,Filled,Buy,2.0,49.45,0.06923,,1389
-2020-08-21 16:00:00,ZIXTLG,Filled,Sell,-659.0,14.44,6.661172,,1390
-2020-08-21 16:00:00,BGDRAI,Filled,Buy,26.0,6.25,0.11375,,1391
-2020-08-21 16:00:00,ZIJVRO,Filled,Sell,-3.0,49.07,0.103047,,1392
-2020-08-21 16:00:00,HCDUCB,Filled,Buy,229.0,42.92,6.880076,,1393
-2020-08-21 16:00:00,MCCZID,Filled,Buy,254.0,38.85,6.9075299999999995,,1394
-2020-08-21 16:00:00,RUKNMV,Filled,Buy,5.0,23.6,0.08259999999999999,,1395
-2020-08-21 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1396
-2020-08-21 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1397
-2020-08-21 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1398
-2020-08-21 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1399
-2020-08-21 16:00:00,ZIXTLG,Submitted,Buy,0.0,0.0,0.0,,1400
-2020-08-21 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1401
-2020-08-21 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1402
-2020-08-21 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,1403
-2020-08-21 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,1404
-2020-08-21 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1405
-2020-08-24 16:00:00,COMNHQ,Filled,Buy,22.0,12.44,0.191576,,1396
-2020-08-24 16:00:00,LUZLYG,Filled,Buy,1.0,25.22,0.017654,,1397
-2020-08-24 16:00:00,HECLON,Filled,Buy,1.0,49.9,0.034929999999999996,,1398
-2020-08-24 16:00:00,FFNDVM,Filled,Buy,1477.0,6.73,6.958147,,1399
-2020-08-24 16:00:00,ZIXTLG,Filled,Buy,685.0,14.6,7.0007,,1400
-2020-08-24 16:00:00,BGDRAI,Filled,Sell,-11.0,6.35,0.048894999999999994,,1401
-2020-08-24 16:00:00,ZIJVRO,Filled,Sell,-1.0,49.28,0.034496,,1402
-2020-08-24 16:00:00,HCDUCB,Filled,Buy,1.0,43.17,0.030219,,1403
-2020-08-24 16:00:00,MCCZID,Filled,Sell,-254.0,39.0,6.9342,,1404
-2020-08-24 16:00:00,RUKNMV,Filled,Buy,2.0,23.76,0.033264,,1405
-2020-08-24 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1406
-2020-08-24 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1407
-2020-08-24 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1408
-2020-08-24 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1409
-2020-08-24 16:00:00,ZIXTLG,Submitted,Sell,0.0,0.0,0.0,,1410
-2020-08-24 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1411
-2020-08-24 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1412
-2020-08-24 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,1413
-2020-08-24 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1414
-2020-08-25 16:00:00,COMNHQ,Filled,Sell,-75.0,13.7,0.71925,,1406
-2020-08-25 16:00:00,LUZLYG,Filled,Sell,-9.0,26.04,0.16405199999999998,,1407
-2020-08-25 16:00:00,HECLON,Filled,Sell,-6.0,51.8,0.21756,,1408
-2020-08-25 16:00:00,FFNDVM,Filled,Sell,-1477.0,7.01,7.247639,,1409
-2020-08-25 16:00:00,ZIXTLG,Filled,Sell,-685.0,14.54,6.9719299999999995,,1410
-2020-08-25 16:00:00,BGDRAI,Filled,Sell,-71.0,6.65,0.330505,,1411
-2020-08-25 16:00:00,ZIJVRO,Filled,Sell,-199.0,49.35,6.874454999999999,,1412
-2020-08-25 16:00:00,HCDUCB,Filled,Sell,-230.0,44.84,7.21924,,1413
-2020-08-25 16:00:00,RUKNMV,Filled,Sell,-13.0,24.74,0.225134,,1414
-2020-08-25 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1415
-2020-08-25 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1416
-2020-08-25 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1417
-2020-08-25 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1418
-2020-08-25 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,1419
-2020-08-25 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1420
-2020-08-26 16:00:00,COMNHQ,Filled,Buy,422.0,13.1,3.86974,,1415
-2020-08-26 16:00:00,LUZLYG,Filled,Sell,-384.0,25.94,6.972672,,1416
-2020-08-26 16:00:00,HECLON,Filled,Buy,101.0,51.66,3.652362,,1417
-2020-08-26 16:00:00,BGDRAI,Filled,Sell,-1488.0,6.6,6.87456,,1418
-2020-08-26 16:00:00,HCDUCB,Filled,Buy,336.0,45.65,10.73688,,1419
-2020-08-26 16:00:00,RUKNMV,Filled,Buy,214.0,24.49,3.668602,,1420
-2020-08-26 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1421
-2020-08-26 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1422
-2020-08-26 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1423
-2020-08-26 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,1424
-2020-08-26 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1425
-2020-08-27 16:00:00,COMNHQ,Filled,Buy,30.0,13.4,0.2814,,1421
-2020-08-27 16:00:00,HECLON,Filled,Buy,4.0,50.68,0.141904,,1422
-2020-08-27 16:00:00,BGDRAI,Filled,Buy,2341.0,6.5,10.65155,,1423
-2020-08-27 16:00:00,HCDUCB,Filled,Sell,-336.0,44.55,10.47816,,1424
-2020-08-27 16:00:00,RUKNMV,Filled,Buy,14.0,24.0,0.2352,,1425
-2020-08-27 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1426
-2020-08-27 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1427
-2020-08-27 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1428
-2020-08-27 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1429
-2020-08-27 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1430
-2020-08-28 16:00:00,COMNHQ,Filled,Sell,-43.0,13.58,0.408758,,1426
-2020-08-28 16:00:00,LUZLYG,Filled,Buy,582.0,26.45,10.77573,,1427
-2020-08-28 16:00:00,HECLON,Filled,Sell,-5.0,52.07,0.182245,,1428
-2020-08-28 16:00:00,BGDRAI,Filled,Sell,-2341.0,6.5,10.65155,,1429
-2020-08-28 16:00:00,RUKNMV,Filled,Sell,-14.0,24.72,0.242256,,1430
-2020-08-28 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1431
-2020-08-28 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1432
-2020-08-28 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1433
-2020-08-28 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,1434
-2020-08-28 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1435
-2020-08-31 16:00:00,COMNHQ,Filled,Sell,-25.0,13.59,0.237825,,1431
-2020-08-31 16:00:00,LUZLYG,Filled,Sell,-582.0,26.09,10.629066,,1432
-2020-08-31 16:00:00,HECLON,Filled,Sell,-3.0,51.91,0.109011,,1433
-2020-08-31 16:00:00,HCDUCB,Filled,Buy,332.0,45.33,10.534692,,1434
-2020-08-31 16:00:00,RUKNMV,Filled,Sell,-617.0,24.48,10.572912,,1435
-2020-08-31 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1436
-2020-08-31 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1437
-2020-08-31 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1438
-2020-08-31 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,1439
-2020-08-31 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1440
-2020-09-01 16:00:00,COMNHQ,Filled,Sell,-219.0,12.8,1.96224,,1436
-2020-09-01 16:00:00,SMDIFE,Filled,Buy,91.0,132.91,8.466367,,1437
-2020-09-01 16:00:00,HECLON,Filled,Sell,-61.0,50.88,2.1725760000000003,,1438
-2020-09-01 16:00:00,HCDUCB,Filled,Sell,-332.0,45.5,10.5742,,1439
-2020-09-01 16:00:00,RUKNMV,Filled,Buy,486.0,23.96,8.151192,,1440
-2020-09-01 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1441
-2020-09-01 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1442
-2020-09-01 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1443
-2020-09-01 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1444
-2020-09-01 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1445
-2020-09-02 16:00:00,COMNHQ,Filled,Sell,-3.0,12.92,0.027132,,1441
-2020-09-02 16:00:00,SMDIFE,Filled,Sell,-4.0,137.58,0.385224,,1442
-2020-09-02 16:00:00,HECLON,Filled,Sell,-229.0,51.01,8.176903,,1443
-2020-09-02 16:00:00,ISIJLH,Filled,Buy,398.0,29.35,8.176910000000001,,1444
-2020-09-02 16:00:00,RUKNMV,Filled,Sell,-486.0,23.98,8.157996,,1445
-2020-09-02 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1446
-2020-09-02 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1447
-2020-09-02 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1448
-2020-09-03 16:00:00,COMNHQ,Filled,Buy,139.0,13.4,1.30382,,1446
-2020-09-03 16:00:00,SMDIFE,Filled,Buy,17.0,126.97,1.510943,,1447
-2020-09-03 16:00:00,ISIJLH,Filled,Sell,-398.0,29.9,8.330139999999998,,1448
-2020-09-03 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1449
-2020-09-03 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1450
-2020-09-03 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1451
-2020-09-04 16:00:00,COMNHQ,Filled,Sell,-25.0,13.66,0.23905,,1449
-2020-09-04 16:00:00,SMDIFE,Filled,Buy,7.0,120.0,0.588,,1450
-2020-09-04 16:00:00,RLSRXX,Filled,Buy,163.0,81.4,9.28774,,1451
-2020-09-04 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1452
-2020-09-04 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1453
-2020-09-04 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1454
-2020-09-04 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1455
-2020-09-08 16:00:00,COMNHQ,Filled,Sell,-18.0,13.36,0.168336,,1452
-2020-09-08 16:00:00,RLSRXX,Filled,Sell,-163.0,78.0,8.899799999999999,,1453
-2020-09-08 16:00:00,LUZLYG,Filled,Buy,508.0,26.1,9.28116,,1454
-2020-09-08 16:00:00,HECLON,Filled,Buy,257.0,51.97,9.349403,,1455
-2020-09-08 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1456
-2020-09-08 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1457
-2020-09-08 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1458
-2020-09-08 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1459
-2020-09-08 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1460
-2020-09-09 16:00:00,COMNHQ,Filled,Sell,-271.0,13.49,2.559053,,1456
-2020-09-09 16:00:00,SMDIFE,Filled,Sell,-24.0,117.3,1.97064,,1457
-2020-09-09 16:00:00,LUZLYG,Filled,Sell,-508.0,25.65,9.12114,,1458
-2020-09-09 16:00:00,HECLON,Filled,Sell,-65.0,51.2,2.3296,,1459
-2020-09-09 16:00:00,RUKNMV,Filled,Buy,410.0,24.0,6.888,,1460
-2020-09-09 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1461
-2020-09-09 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1462
-2020-09-09 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1463
-2020-09-09 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1464
-2020-09-10 16:00:00,COMNHQ,Filled,Buy,33.0,13.2,0.30491999999999997,,1461
-2020-09-10 16:00:00,SMDIFE,Filled,Sell,-4.0,120.37,0.337036,,1462
-2020-09-10 16:00:00,HECLON,Filled,Sell,-192.0,51.72,6.951168,,1463
-2020-09-10 16:00:00,RUKNMV,Filled,Sell,-410.0,24.1,6.9167,,1464
-2020-09-10 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1465
-2020-09-10 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1466
-2020-09-10 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1467
-2020-09-10 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1468
-2020-09-11 16:00:00,COMNHQ,Filled,Buy,2.0,13.03,0.018242,,1465
-2020-09-11 16:00:00,SMDIFE,Filled,Buy,3.0,114.68,0.240828,,1466
-2020-09-11 16:00:00,BGDRAI,Filled,Buy,1639.0,6.02,6.906745999999999,,1467
-2020-09-11 16:00:00,ISIJLH,Filled,Buy,340.0,28.95,6.8901,,1468
-2020-09-11 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1469
-2020-09-11 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1470
-2020-09-11 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1471
-2020-09-11 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1472
-2020-09-11 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1473
-2020-09-11 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1474
-2020-09-14 16:00:00,COMNHQ,Filled,Sell,-756.0,13.02,6.890184,,1469
-2020-09-14 16:00:00,SMDIFE,Filled,Buy,1.0,114.78,0.080346,,1470
-2020-09-14 16:00:00,OCHCAU,Filled,Buy,246.0,40.26,6.932771999999999,,1471
-2020-09-14 16:00:00,FFNDVM,Filled,Buy,1405.0,7.01,6.894334999999999,,1472
-2020-09-14 16:00:00,BGDRAI,Filled,Sell,-1639.0,5.99,6.872327,,1473
-2020-09-14 16:00:00,ISIJLH,Filled,Sell,-1.0,29.11,0.020377,,1474
-2020-09-14 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1475
-2020-09-14 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1476
-2020-09-14 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1477
-2020-09-14 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1478
-2020-09-14 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1479
-2020-09-14 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1480
-2020-09-15 16:00:00,SMDIFE,Filled,Sell,-2.0,118.38,0.165732,,1475
-2020-09-15 16:00:00,HECLON,Filled,Buy,204.0,48.05,6.861539999999999,,1476
-2020-09-15 16:00:00,OCHCAU,Filled,Sell,-246.0,40.55,6.982709999999999,,1477
-2020-09-15 16:00:00,FFNDVM,Filled,Sell,-1405.0,7.15,7.032025,,1478
-2020-09-15 16:00:00,MCCZID,Filled,Buy,265.0,37.25,6.9098749999999995,,1479
-2020-09-15 16:00:00,ISIJLH,Filled,Sell,-2.0,29.17,0.040838,,1480
-2020-09-15 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1481
-2020-09-15 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,1482
-2020-09-15 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,1483
-2020-09-15 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1484
-2020-09-16 16:00:00,HECLON,Filled,Buy,15.0,45.17,0.47428500000000007,,1481
-2020-09-16 16:00:00,YIVYGH,Filled,Buy,211.0,47.05,6.949285,,1482
-2020-09-16 16:00:00,MCCZID,Filled,Sell,-265.0,37.19,6.898744999999999,,1483
-2020-09-16 16:00:00,ISIJLH,Filled,Sell,-337.0,29.13,6.871766999999999,,1484
-2020-09-16 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1485
-2020-09-16 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1486
-2020-09-16 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1487
-2020-09-16 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,1488
-2020-09-16 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1489
-2020-09-16 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1490
-2020-09-16 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1491
-2020-09-17 16:00:00,COMNHQ,Filled,Buy,712.0,13.54,6.748335999999999,,1485
-2020-09-17 16:00:00,SMDIFE,Filled,Buy,2.0,109.77,0.15367799999999998,,1486
-2020-09-17 16:00:00,HECLON,Filled,Sell,-219.0,45.44,6.965951999999999,,1487
-2020-09-17 16:00:00,YIVYGH,Filled,Sell,-211.0,46.02,6.797154000000001,,1488
-2020-09-17 16:00:00,BGDRAI,Filled,Buy,1457.0,6.75,6.884325,,1489
-2020-09-17 16:00:00,MCCZID,Filled,Buy,267.0,36.79,6.876051,,1490
-2020-09-17 16:00:00,RUKNMV,Filled,Buy,382.0,25.15,6.725109999999999,,1491
-2020-09-17 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1492
-2020-09-17 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1493
-2020-09-17 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,1494
-2020-09-17 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1495
-2020-09-17 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1496
-2020-09-18 16:00:00,COMNHQ,Filled,Sell,-712.0,13.5,6.7284,,1492
-2020-09-18 16:00:00,SMDIFE,Filled,Buy,2.0,110.41,0.154574,,1493
-2020-09-18 16:00:00,YIVYGH,Filled,Buy,215.0,45.48,6.844739999999999,,1494
-2020-09-18 16:00:00,BGDRAI,Filled,Sell,-1457.0,6.9,7.037310000000001,,1495
-2020-09-18 16:00:00,RUKNMV,Filled,Buy,9.0,24.92,0.15699600000000002,,1496
-2020-09-18 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1497
-2020-09-18 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,1498
-2020-09-18 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1499
-2020-09-18 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1500
-2020-09-21 16:00:00,SMDIFE,Filled,Buy,3.0,104.52,0.219492,,1497
-2020-09-21 16:00:00,YIVYGH,Filled,Sell,-215.0,44.82,6.74541,,1498
-2020-09-21 16:00:00,MCCZID,Filled,Buy,4.0,36.36,0.101808,,1499
-2020-09-21 16:00:00,RUKNMV,Filled,Sell,-391.0,24.46,6.694702,,1500
-2020-09-21 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1501
-2020-09-21 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1502
-2020-09-21 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1503
-2020-09-21 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1504
-2020-09-21 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1505
-2020-09-22 16:00:00,COMNHQ,Filled,Buy,804.0,12.26,6.899927999999999,,1501
-2020-09-22 16:00:00,SMDIFE,Filled,Sell,-3.0,112.67,0.236607,,1502
-2020-09-22 16:00:00,RLSRXX,Filled,Buy,126.0,78.3,6.906059999999999,,1503
-2020-09-22 16:00:00,OCHCAU,Filled,Buy,251.0,39.18,6.883926,,1504
-2020-09-22 16:00:00,MCCZID,Filled,Buy,1.0,35.77,0.025039,,1505
-2020-09-22 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1506
-2020-09-22 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1507
-2020-09-22 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1508
-2020-09-22 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,1509
-2020-09-22 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,1510
-2020-09-22 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1511
-2020-09-22 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1512
-2020-09-23 16:00:00,COMNHQ,Filled,Buy,287.0,12.52,2.515268,,1506
-2020-09-23 16:00:00,SMDIFE,Filled,Buy,31.0,111.63,2.4223709999999996,,1507
-2020-09-23 16:00:00,RLSRXX,Filled,Buy,47.0,77.42,2.547118,,1508
-2020-09-23 16:00:00,XUEHVZ,Filled,Buy,4.0,3119.42,8.734376,,1509
-2020-09-23 16:00:00,YIVYGH,Filled,Buy,291.0,46.19,9.408903,,1510
-2020-09-23 16:00:00,OCHCAU,Filled,Sell,-251.0,39.23,6.892710999999999,,1511
-2020-09-23 16:00:00,MCCZID,Filled,Buy,99.0,36.3,2.51559,,1512
-2020-09-23 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1513
-2020-09-23 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1514
-2020-09-23 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1515
-2020-09-23 16:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,1516
-2020-09-23 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,1517
-2020-09-23 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,1518
-2020-09-23 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1519
-2020-09-24 16:00:00,COMNHQ,Filled,Buy,34.0,11.72,0.278936,,1513
-2020-09-24 16:00:00,SMDIFE,Filled,Buy,5.0,105.18,0.36813000000000007,,1514
-2020-09-24 16:00:00,RLSRXX,Filled,Buy,6.0,74.35,0.31227,,1515
-2020-09-24 16:00:00,XUEHVZ,Filled,Sell,-4.0,2984.03,8.355284000000001,,1516
-2020-09-24 16:00:00,YIVYGH,Filled,Sell,-291.0,45.19,9.205203,,1517
-2020-09-24 16:00:00,MCCZID,Filled,Sell,-371.0,35.9,9.32323,,1518
-2020-09-24 16:00:00,ISIJLH,Filled,Buy,481.0,27.85,9.377095,,1519
-2020-09-24 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1520
-2020-09-24 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1521
-2020-09-24 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1522
-2020-09-24 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1523
-2020-09-25 16:00:00,COMNHQ,Filled,Buy,16.0,11.73,0.131376,,1520
-2020-09-25 16:00:00,SMDIFE,Filled,Sell,-1.0,108.49,0.075943,,1521
-2020-09-25 16:00:00,RLSRXX,Filled,Sell,-2.0,76.36,0.106904,,1522
-2020-09-25 16:00:00,ISIJLH,Filled,Sell,-481.0,27.89,9.390563,,1523
-2020-09-25 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1524
-2020-09-25 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1525
-2020-09-25 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1526
-2020-09-28 16:00:00,COMNHQ,Filled,Sell,-47.0,12.75,0.419475,,1524
-2020-09-28 16:00:00,SMDIFE,Filled,Sell,-5.0,114.91,0.402185,,1525
-2020-09-28 16:00:00,RLSRXX,Filled,Sell,-5.0,79.0,0.2765,,1526
-2020-09-28 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1527
-2020-09-28 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1528
-2020-09-28 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1529
-2020-09-29 16:00:00,COMNHQ,Filled,Sell,-292.0,12.57,2.569308,,1527
-2020-09-29 16:00:00,SMDIFE,Filled,Sell,-30.0,114.52,2.4049199999999997,,1528
-2020-09-29 16:00:00,RLSRXX,Filled,Sell,-44.0,79.3,2.44244,,1529
-2020-09-29 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1530
-2020-09-29 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1531
-2020-09-29 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1532
-2020-09-30 16:00:00,COMNHQ,Filled,Buy,33.0,12.35,0.285285,,1530
-2020-09-30 16:00:00,RLSRXX,Filled,Sell,-3.0,81.71,0.171591,,1531
-2020-09-30 16:00:00,MCCZID,Filled,Buy,283.0,36.28,7.187068,,1532
-2020-09-30 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1533
-2020-09-30 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1534
-2020-09-30 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1535
-2020-09-30 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1536
-2020-10-01 16:00:00,COMNHQ,Filled,Buy,105.0,12.44,0.91434,,1533
-2020-10-01 16:00:00,SMDIFE,Filled,Sell,-89.0,117.72,7.333956,,1534
-2020-10-01 16:00:00,RLSRXX,Filled,Buy,16.0,83.11,0.930832,,1535
-2020-10-01 16:00:00,MCCZID,Filled,Buy,32.0,36.75,0.8232,,1536
-2020-10-01 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1537
-2020-10-01 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1538
-2020-10-01 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,1539
-2020-10-02 16:00:00,COMNHQ,Filled,Sell,-21.0,12.02,0.176694,,1537
-2020-10-02 16:00:00,RLSRXX,Filled,Sell,-5.0,82.57,0.28899499999999995,,1538
-2020-10-02 16:00:00,MCCZID,Filled,Sell,-315.0,36.1,7.96005,,1539
-2020-10-02 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1540
-2020-10-02 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1541
-2020-10-05 16:00:00,COMNHQ,Filled,Sell,-29.0,13.1,0.26593,,1540
-2020-10-05 16:00:00,RLSRXX,Filled,Buy,5.0,82.55,0.288925,,1541
-2020-10-05 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1542
-2020-10-05 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1543
-2020-10-06 16:00:00,COMNHQ,Filled,Sell,-8.0,13.29,0.07442399999999999,,1542
-2020-10-06 16:00:00,RLSRXX,Filled,Sell,-7.0,86.19,0.422331,,1543
-2020-10-06 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1544
-2020-10-06 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1545
-2020-10-06 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1546
-2020-10-06 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1547
-2020-10-07 16:00:00,COMNHQ,Filled,Sell,-90.0,12.97,0.81711,,1544
-2020-10-07 16:00:00,RLSRXX,Filled,Sell,-17.0,86.11,1.024709,,1545
-2020-10-07 16:00:00,LUZLYG,Filled,Buy,407.0,24.61,7.011389,,1546
-2020-10-07 16:00:00,MCCZID,Filled,Buy,274.0,36.22,6.9469959999999995,,1547
-2020-10-07 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1548
-2020-10-07 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1549
-2020-10-07 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1550
-2020-10-07 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1551
-2020-10-07 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1552
-2020-10-07 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,1553
-2020-10-07 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1554
-2020-10-08 16:00:00,COMNHQ,Filled,Sell,-32.0,13.34,0.29881599999999997,,1548
-2020-10-08 16:00:00,RLSRXX,Filled,Sell,-3.0,88.01,0.184821,,1549
-2020-10-08 16:00:00,LUZLYG,Filled,Sell,-407.0,24.95,7.108255,,1550
-2020-10-08 16:00:00,OCHCAU,Filled,Buy,252.0,39.8,7.020719999999999,,1551
-2020-10-08 16:00:00,FFNDVM,Filled,Buy,1375.0,7.25,6.978125,,1552
-2020-10-08 16:00:00,MCCZID,Filled,Sell,-274.0,36.6,7.01988,,1553
-2020-10-08 16:00:00,RUKNMV,Filled,Buy,400.0,24.9,6.9719999999999995,,1554
-2020-10-08 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1555
-2020-10-08 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1556
-2020-10-08 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1557
-2020-10-08 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1558
-2020-10-09 16:00:00,COMNHQ,Filled,Sell,-5.0,13.24,0.04634,,1555
-2020-10-09 16:00:00,OCHCAU,Filled,Sell,-252.0,40.12,7.0771679999999995,,1556
-2020-10-09 16:00:00,FFNDVM,Filled,Sell,-1375.0,7.36,7.084,,1557
-2020-10-09 16:00:00,RUKNMV,Filled,Sell,-400.0,25.42,7.1176,,1558
-2020-10-09 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1559
-2020-10-09 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1560
-2020-10-09 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,1561
-2020-10-09 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1562
-2020-10-12 16:00:00,COMNHQ,Filled,Sell,-2.0,13.12,0.018368,,1559
-2020-10-12 16:00:00,RLSRXX,Filled,Buy,5.0,83.69,0.292915,,1560
-2020-10-12 16:00:00,XUEHVZ,Filled,Buy,3.0,3279.36,6.8866559999999994,,1561
-2020-10-12 16:00:00,BPSPGV,Filled,Buy,46.0,218.67,7.041174,,1562
-2020-10-12 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1563
-2020-10-12 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1564
-2020-10-12 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1565
-2020-10-12 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,1566
-2020-10-12 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,1567
-2020-10-12 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1568
-2020-10-12 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1569
-2020-10-13 16:00:00,COMNHQ,Filled,Buy,144.0,12.52,1.2620159999999998,,1563
-2020-10-13 16:00:00,RLSRXX,Filled,Buy,18.0,85.05,1.07163,,1564
-2020-10-13 16:00:00,OCHCAU,Filled,Buy,287.0,40.53,8.142477,,1565
-2020-10-13 16:00:00,CEMOJE,Filled,Buy,7.0,1569.27,7.689423,,1566
-2020-10-13 16:00:00,GTKILW,Filled,Buy,7.0,1575.35,7.719214999999999,,1567
-2020-10-13 16:00:00,ZIJVRO,Filled,Buy,215.0,54.27,8.167635,,1568
-2020-10-13 16:00:00,BPSPGV,Filled,Buy,6.0,222.47,0.934374,,1569
-2020-10-13 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1570
-2020-10-13 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1571
-2020-10-13 16:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,1572
-2020-10-13 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1573
-2020-10-13 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1574
-2020-10-13 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,1575
-2020-10-13 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,1576
-2020-10-13 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1577
-2020-10-13 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1578
-2020-10-14 16:00:00,COMNHQ,Filled,Buy,50.0,12.33,0.43155,,1570
-2020-10-14 16:00:00,RLSRXX,Filled,Sell,-2.0,85.86,0.120204,,1571
-2020-10-14 16:00:00,XUEHVZ,Filled,Sell,-3.0,3437.4,7.218540000000001,,1572
-2020-10-14 16:00:00,HECLON,Filled,Buy,265.0,43.6,8.0878,,1573
-2020-10-14 16:00:00,OCHCAU,Filled,Buy,3.0,39.85,0.08368500000000001,,1574
-2020-10-14 16:00:00,CEMOJE,Filled,Sell,-7.0,1580.02,7.742098,,1575
-2020-10-14 16:00:00,GTKILW,Filled,Sell,-7.0,1562.56,7.656544,,1576
-2020-10-14 16:00:00,ZIJVRO,Filled,Sell,-215.0,54.07,8.137535,,1577
-2020-10-14 16:00:00,BPSPGV,Filled,Sell,-52.0,222.96,8.115744,,1578
-2020-10-14 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1579
-2020-10-14 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1580
-2020-10-14 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,1581
-2020-10-14 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1582
-2020-10-14 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1583
-2020-10-15 16:00:00,COMNHQ,Filled,Sell,-11.0,12.22,0.094094,,1579
-2020-10-15 16:00:00,RLSRXX,Filled,Buy,2.0,83.48,0.116872,,1580
-2020-10-15 16:00:00,XUEHVZ,Filled,Buy,3.0,3339.1,7.01211,,1581
-2020-10-15 16:00:00,HECLON,Filled,Sell,-265.0,42.54,7.89117,,1582
-2020-10-15 16:00:00,BPSPGV,Filled,Buy,52.0,216.95,7.896979999999999,,1583
-2020-10-15 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1584
-2020-10-15 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1585
-2020-10-15 16:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,1586
-2020-10-15 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1587
-2020-10-15 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1588
-2020-10-15 16:00:00,HCDUCB,Submitted,Buy,0.0,0.0,0.0,,1589
-2020-10-16 16:00:00,COMNHQ,Filled,Buy,10.0,12.25,0.08574999999999999,,1584
-2020-10-16 16:00:00,RLSRXX,Filled,Buy,2.0,83.74,0.117236,,1585
-2020-10-16 16:00:00,XUEHVZ,Filled,Sell,-3.0,3330.58,6.994218,,1586
-2020-10-16 16:00:00,OCHCAU,Filled,Sell,-290.0,39.93,8.10579,,1587
-2020-10-16 16:00:00,BPSPGV,Filled,Sell,-52.0,220.42,8.023288,,1588
-2020-10-16 16:00:00,HCDUCB,Filled,Buy,222.0,52.19,8.110326,,1589
-2020-10-16 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1590
-2020-10-16 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1591
-2020-10-16 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1592
-2020-10-16 16:00:00,BGDRAI,Submitted,Buy,0.0,0.0,0.0,,1593
-2020-10-16 16:00:00,HCDUCB,Submitted,Sell,0.0,0.0,0.0,,1594
-2020-10-16 16:00:00,MCCZID,Submitted,Buy,0.0,0.0,0.0,,1595
-2020-10-19 16:00:00,COMNHQ,Filled,Sell,-157.0,12.64,1.389136,,1590
-2020-10-19 16:00:00,RLSRXX,Filled,Sell,-21.0,83.66,1.2298019999999998,,1591
-2020-10-19 16:00:00,OCHCAU,Filled,Buy,245.0,40.15,6.885725,,1592
-2020-10-19 16:00:00,BGDRAI,Filled,Buy,1349.0,7.39,6.978376999999999,,1593
-2020-10-19 16:00:00,HCDUCB,Filled,Sell,-222.0,51.97,8.076138,,1594
-2020-10-19 16:00:00,MCCZID,Filled,Buy,259.0,38.48,6.976424,,1595
-2020-10-19 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1596
-2020-10-19 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1597
-2020-10-19 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,1598
-2020-10-19 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1599
-2020-10-19 16:00:00,BGDRAI,Submitted,Sell,0.0,0.0,0.0,,1600
-2020-10-19 16:00:00,MCCZID,Submitted,Sell,0.0,0.0,0.0,,1601
-2020-10-20 16:00:00,COMNHQ,Filled,Sell,-6.0,12.75,0.05355,,1596
-2020-10-20 16:00:00,RLSRXX,Filled,Buy,1.0,82.17,0.057519,,1597
-2020-10-20 16:00:00,XUEHVZ,Filled,Buy,3.0,3195.54,6.710633999999999,,1598
-2020-10-20 16:00:00,OCHCAU,Filled,Buy,5.0,39.43,0.138005,,1599
-2020-10-20 16:00:00,BGDRAI,Filled,Sell,-1349.0,7.37,6.959491000000001,,1600
-2020-10-20 16:00:00,MCCZID,Filled,Sell,-259.0,37.79,6.851327,,1601
-2020-10-20 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1602
-2020-10-20 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1603
-2020-10-20 16:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,1604
-2020-10-20 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1605
-2020-10-21 16:00:00,COMNHQ,Filled,Sell,-15.0,12.65,0.132825,,1602
-2020-10-21 16:00:00,RLSRXX,Filled,Buy,1.0,81.78,0.057246,,1603
-2020-10-21 16:00:00,XUEHVZ,Filled,Sell,-3.0,3224.84,6.772164,,1604
-2020-10-21 16:00:00,OCHCAU,Filled,Sell,-250.0,39.31,6.87925,,1605
-2020-10-21 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1606
-2020-10-21 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1607
-2020-10-22 16:00:00,COMNHQ,Filled,Buy,3.0,12.62,0.026502,,1606
-2020-10-22 16:00:00,RLSRXX,Filled,Buy,4.0,79.61,0.222908,,1607
-2020-10-22 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1608
-2020-10-22 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1609
-2020-10-23 16:00:00,COMNHQ,Filled,Sell,-23.0,13.07,0.210427,,1608
-2020-10-23 16:00:00,RLSRXX,Filled,Sell,-124.0,80.86,7.018648,,1609
-2020-10-23 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1610
-2020-10-23 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1611
-2020-10-26 16:00:00,COMNHQ,Filled,Buy,32.0,12.4,0.27776,,1610
-2020-10-26 16:00:00,ZIJVRO,Filled,Buy,204.0,47.8,6.8258399999999995,,1611
-2020-10-26 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1612
-2020-10-26 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1613
-2020-10-26 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1614
-2020-10-27 16:00:00,COMNHQ,Filled,Buy,52.0,11.75,0.4277,,1612
-2020-10-27 16:00:00,ZIJVRO,Filled,Sell,-204.0,45.95,6.561660000000001,,1613
-2020-10-27 16:00:00,RUKNMV,Filled,Buy,432.0,22.55,6.81912,,1614
-2020-10-27 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1615
-2020-10-27 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1616
-2020-10-27 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1617
-2020-10-28 16:00:00,COMNHQ,Filled,Buy,184.0,10.94,1.409072,,1615
-2020-10-28 16:00:00,SMDIFE,Filled,Buy,97.0,114.89,7.801031,,1616
-2020-10-28 16:00:00,RUKNMV,Filled,Sell,-432.0,21.28,6.435072000000001,,1617
-2020-10-28 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1618
-2020-10-28 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1619
-2020-10-29 16:00:00,COMNHQ,Filled,Buy,775.0,10.98,5.95665,,1618
-2020-10-29 16:00:00,SMDIFE,Filled,Buy,79.0,112.42,6.216826,,1619
-2020-10-29 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1620
-2020-10-29 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1621
-2020-10-29 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,1622
-2020-10-30 16:00:00,COMNHQ,Filled,Sell,-32.0,11.07,0.247968,,1620
-2020-10-30 16:00:00,SMDIFE,Filled,Sell,-6.0,111.0,0.4662,,1621
-2020-10-30 16:00:00,YIVYGH,Filled,Buy,456.0,42.3,13.50216,,1622
-2020-10-30 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1623
-2020-10-30 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1624
-2020-10-30 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1625
-2020-10-30 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,1626
-2020-10-30 16:00:00,LMRIBF,Submitted,Buy,0.0,0.0,0.0,,1627
-2020-11-02 16:00:00,COMNHQ,Filled,Sell,-20.0,11.34,0.15876,,1623
-2020-11-02 16:00:00,SMDIFE,Filled,Buy,10.0,109.24,0.7646799999999999,,1624
-2020-11-02 16:00:00,RLSRXX,Filled,Buy,260.0,75.66,13.77012,,1625
-2020-11-02 16:00:00,YIVYGH,Filled,Buy,8.0,42.73,0.23928799999999997,,1626
-2020-11-02 16:00:00,LMRIBF,Filled,Buy,74.0,264.92,13.722856000000002,,1627
-2020-11-02 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1628
-2020-11-02 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1629
-2020-11-02 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1630
-2020-11-02 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,1631
-2020-11-02 16:00:00,LMRIBF,Submitted,Sell,0.0,0.0,0.0,,1632
-2020-11-03 16:00:00,COMNHQ,Filled,Sell,-327.0,11.34,2.595726,,1628
-2020-11-03 16:00:00,SMDIFE,Filled,Sell,-35.0,109.71,2.6878949999999997,,1629
-2020-11-03 16:00:00,RLSRXX,Filled,Sell,-260.0,74.88,13.62816,,1630
-2020-11-03 16:00:00,YIVYGH,Filled,Sell,-464.0,41.93,13.618864,,1631
-2020-11-03 16:00:00,LMRIBF,Filled,Sell,-74.0,263.18,13.632724,,1632
-2020-11-03 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1633
-2020-11-03 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1634
-2020-11-04 16:00:00,COMNHQ,Filled,Sell,-1412.0,11.21,11.079964,,1633
-2020-11-04 16:00:00,SMDIFE,Filled,Sell,-2.0,114.17,0.159838,,1634
-2020-11-04 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1635
-2020-11-04 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1636
-2020-11-04 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1637
-2020-11-05 16:00:00,COMNHQ,Filled,Buy,1437.0,11.11,11.175549,,1635
-2020-11-05 16:00:00,SMDIFE,Filled,Sell,-6.0,118.01,0.495642,,1636
-2020-11-05 16:00:00,BPSPGV,Filled,Buy,73.0,222.0,11.3442,,1637
-2020-11-05 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1638
-2020-11-05 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1639
-2020-11-05 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1640
-2020-11-06 16:00:00,COMNHQ,Filled,Sell,-71.0,11.46,0.569562,,1638
-2020-11-06 16:00:00,SMDIFE,Filled,Sell,-4.0,118.24,0.331072,,1639
-2020-11-06 16:00:00,BPSPGV,Filled,Sell,-3.0,222.13,0.466473,,1640
-2020-11-06 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1641
-2020-11-06 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1642
-2020-11-06 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1643
-2020-11-09 16:00:00,COMNHQ,Filled,Buy,16.0,14.36,0.160832,,1641
-2020-11-09 16:00:00,BPSPGV,Filled,Sell,-70.0,224.04,10.97796,,1642
-2020-11-09 16:00:00,RUKNMV,Filled,Buy,723.0,24.27,12.283047,,1643
-2020-11-09 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1644
-2020-11-09 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1645
-2020-11-09 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1646
-2020-11-09 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1647
-2020-11-09 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1648
-2020-11-10 16:00:00,COMNHQ,Filled,Sell,-180.0,12.87,1.6216199999999998,,1644
-2020-11-10 16:00:00,SMDIFE,Filled,Buy,3.0,115.54,0.242634,,1645
-2020-11-10 16:00:00,LUZLYG,Filled,Buy,571.0,27.56,11.015731999999998,,1646
-2020-11-10 16:00:00,HECLON,Filled,Buy,333.0,48.5,11.30535,,1647
-2020-11-10 16:00:00,RUKNMV,Filled,Sell,-68.0,24.26,1.154776,,1648
-2020-11-10 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1649
-2020-11-10 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1650
-2020-11-10 16:00:00,RLSRXX,Submitted,Buy,0.0,0.0,0.0,,1651
-2020-11-10 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1652
-2020-11-10 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1653
-2020-11-10 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1654
-2020-11-10 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1655
-2020-11-10 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1656
-2020-11-11 16:00:00,COMNHQ,Filled,Sell,-408.0,12.38,3.535728,,1649
-2020-11-11 16:00:00,SMDIFE,Filled,Sell,-52.0,117.15,4.26426,,1650
-2020-11-11 16:00:00,RLSRXX,Filled,Buy,126.0,79.41,7.003962,,1651
-2020-11-11 16:00:00,LUZLYG,Filled,Sell,-571.0,27.72,11.079684,,1652
-2020-11-11 16:00:00,HECLON,Filled,Sell,-333.0,47.82,11.146842,,1653
-2020-11-11 16:00:00,ZIJVRO,Filled,Buy,216.0,45.98,6.952175999999999,,1654
-2020-11-11 16:00:00,BPSPGV,Filled,Buy,46.0,212.54,6.843788,,1655
-2020-11-11 16:00:00,RUKNMV,Filled,Sell,-655.0,24.2,11.0957,,1656
-2020-11-11 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1657
-2020-11-11 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1658
-2020-11-11 16:00:00,RLSRXX,Submitted,Sell,0.0,0.0,0.0,,1659
-2020-11-11 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1660
-2020-11-11 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1661
-2020-11-12 16:00:00,COMNHQ,Filled,Buy,22.0,11.97,0.18433800000000003,,1657
-2020-11-12 16:00:00,SMDIFE,Filled,Sell,-2.0,119.62,0.167468,,1658
-2020-11-12 16:00:00,RLSRXX,Filled,Sell,-126.0,81.3,7.17066,,1659
-2020-11-12 16:00:00,ZIJVRO,Filled,Sell,-4.0,46.13,0.129164,,1660
-2020-11-12 16:00:00,BPSPGV,Filled,Sell,-1.0,217.14,0.151998,,1661
-2020-11-12 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1662
-2020-11-12 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1663
-2020-11-12 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1664
-2020-11-12 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1665
-2020-11-13 16:00:00,COMNHQ,Filled,Sell,-816.0,11.91,6.802992,,1662
-2020-11-13 16:00:00,SMDIFE,Filled,Buy,1.0,119.43,0.08360100000000001,,1663
-2020-11-13 16:00:00,ZIJVRO,Filled,Buy,8.0,44.99,0.251944,,1664
-2020-11-13 16:00:00,BPSPGV,Filled,Sell,-45.0,216.36,6.815340000000001,,1665
-2020-11-13 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1666
-2020-11-13 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1667
-2020-11-13 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1668
-2020-11-13 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1669
-2020-11-16 16:00:00,COMNHQ,Filled,Buy,803.0,12.91,7.256710999999999,,1666
-2020-11-16 16:00:00,SMDIFE,Filled,Sell,-1.0,118.88,0.083216,,1667
-2020-11-16 16:00:00,OCHCAU,Filled,Buy,237.0,41.74,6.924666,,1668
-2020-11-16 16:00:00,ZIJVRO,Filled,Sell,-4.0,46.01,0.128828,,1669
-2020-11-16 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1670
-2020-11-16 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1671
-2020-11-16 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1672
-2020-11-16 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1673
-2020-11-16 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1674
-2020-11-16 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1675
-2020-11-17 16:00:00,COMNHQ,Filled,Sell,-803.0,12.46,7.003766000000001,,1670
-2020-11-17 16:00:00,SMDIFE,Filled,Sell,-1.0,119.46,0.08362199999999999,,1671
-2020-11-17 16:00:00,OCHCAU,Filled,Sell,-6.0,41.92,0.176064,,1672
-2020-11-17 16:00:00,ZIJVRO,Filled,Sell,-4.0,45.75,0.1281,,1673
-2020-11-17 16:00:00,BPSPGV,Filled,Buy,45.0,216.1,6.80715,,1674
-2020-11-17 16:00:00,RUKNMV,Filled,Buy,395.0,24.62,6.80743,,1675
-2020-11-17 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1676
-2020-11-17 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1677
-2020-11-17 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1678
-2020-11-17 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1679
-2020-11-17 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1680
-2020-11-18 16:00:00,SMDIFE,Filled,Buy,2.0,118.61,0.166054,,1676
-2020-11-18 16:00:00,OCHCAU,Filled,Sell,-231.0,41.88,6.771996000000001,,1677
-2020-11-18 16:00:00,ZIJVRO,Filled,Buy,6.0,45.54,0.191268,,1678
-2020-11-18 16:00:00,BPSPGV,Filled,Buy,1.0,213.51,0.14945699999999998,,1679
-2020-11-18 16:00:00,RUKNMV,Filled,Sell,-395.0,25.16,6.956740000000001,,1680
-2020-11-18 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1681
-2020-11-19 16:00:00,ISIJLH,Filled,Buy,343.0,28.49,6.840449,,1681
-2020-11-19 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1682
-2020-11-19 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1683
-2020-11-19 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1684
-2020-11-19 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1685
-2020-11-19 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1686
-2020-11-20 16:00:00,COMNHQ,Filled,Buy,768.0,12.82,6.892032,,1682
-2020-11-20 16:00:00,SMDIFE,Filled,Sell,-1.0,118.63,0.08304099999999999,,1683
-2020-11-20 16:00:00,ZIJVRO,Filled,Sell,-3.0,45.65,0.095865,,1684
-2020-11-20 16:00:00,ISIJLH,Filled,Buy,4.0,28.21,0.078988,,1685
-2020-11-20 16:00:00,RUKNMV,Filled,Buy,375.0,26.04,6.8355,,1686
-2020-11-20 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1687
-2020-11-20 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1688
-2020-11-20 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,1689
-2020-11-20 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,1690
-2020-11-20 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1691
-2020-11-20 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1692
-2020-11-20 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1693
-2020-11-23 16:00:00,COMNHQ,Filled,Buy,15.0,12.75,0.133875,,1687
-2020-11-23 16:00:00,SMDIFE,Filled,Buy,1.0,117.13,0.081991,,1688
-2020-11-23 16:00:00,CEMOJE,Filled,Buy,5.0,1737.48,6.08118,,1689
-2020-11-23 16:00:00,GTKILW,Filled,Buy,5.0,1748.97,6.121395000000001,,1690
-2020-11-23 16:00:00,ZIJVRO,Filled,Buy,1.0,45.48,0.031835999999999996,,1691
-2020-11-23 16:00:00,ISIJLH,Filled,Sell,-1.0,28.39,0.019873,,1692
-2020-11-23 16:00:00,RUKNMV,Filled,Sell,-375.0,25.96,6.8145,,1693
-2020-11-23 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1694
-2020-11-23 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1695
-2020-11-23 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1696
-2020-11-23 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,1697
-2020-11-23 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,1698
-2020-11-23 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1699
-2020-11-23 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1700
-2020-11-23 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1701
-2020-11-24 16:00:00,COMNHQ,Filled,Sell,-59.0,14.38,0.593894,,1694
-2020-11-24 16:00:00,SMDIFE,Filled,Buy,3.0,113.89,0.239169,,1695
-2020-11-24 16:00:00,LUZLYG,Filled,Buy,358.0,27.92,6.996752000000001,,1696
-2020-11-24 16:00:00,CEMOJE,Filled,Sell,-5.0,1732.68,6.06438,,1697
-2020-11-24 16:00:00,GTKILW,Filled,Sell,-5.0,1736.4,6.0774,,1698
-2020-11-24 16:00:00,ZIJVRO,Filled,Sell,-3.0,46.27,0.097167,,1699
-2020-11-24 16:00:00,BPSPGV,Filled,Sell,-46.0,209.5,6.7459,,1700
-2020-11-24 16:00:00,ISIJLH,Filled,Sell,-3.0,28.93,0.060752999999999995,,1701
-2020-11-24 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1702
-2020-11-24 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1703
-2020-11-24 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1704
-2020-11-24 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1705
-2020-11-24 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1706
-2020-11-24 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1707
-2020-11-24 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1708
-2020-11-24 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1709
-2020-11-25 16:00:00,COMNHQ,Filled,Buy,347.0,14.78,3.5900619999999996,,1702
-2020-11-25 16:00:00,SMDIFE,Filled,Buy,51.0,115.62,4.127634,,1703
-2020-11-25 16:00:00,LUZLYG,Filled,Buy,190.0,28.71,3.81843,,1704
-2020-11-25 16:00:00,HECLON,Filled,Buy,278.0,56.13,10.922898,,1705
-2020-11-25 16:00:00,ZIJVRO,Filled,Buy,124.0,47.02,4.081336,,1706
-2020-11-25 16:00:00,BPSPGV,Filled,Buy,74.0,215.29,11.152022,,1707
-2020-11-25 16:00:00,ISIJLH,Filled,Buy,200.0,29.29,4.1006,,1708
-2020-11-25 16:00:00,RUKNMV,Filled,Buy,555.0,28.24,10.97124,,1709
-2020-11-25 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1710
-2020-11-25 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1711
-2020-11-25 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,1712
-2020-11-25 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1713
-2020-11-25 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1714
-2020-11-25 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1715
-2020-11-25 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1716
-2020-11-27 13:00:00,COMNHQ,Filled,Sell,-1071.0,15.13,11.342961,,1710
-2020-11-27 13:00:00,SMDIFE,Filled,Sell,-1.0,116.53,0.081571,,1711
-2020-11-27 13:00:00,XUEHVZ,Filled,Buy,4.0,3190.96,8.934688,,1712
-2020-11-27 13:00:00,LUZLYG,Filled,Sell,-548.0,28.97,11.112892,,1713
-2020-11-27 13:00:00,HECLON,Filled,Sell,-278.0,57.0,11.0922,,1714
-2020-11-27 13:00:00,ISIJLH,Filled,Buy,5.0,29.05,0.101675,,1715
-2020-11-27 13:00:00,RUKNMV,Filled,Sell,-555.0,28.56,11.09556,,1716
-2020-11-27 13:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,1717
-2020-11-27 13:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1718
-2020-11-27 13:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1719
-2020-11-27 13:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1720
-2020-11-30 16:00:00,XUEHVZ,Filled,Sell,-4.0,3205.78,8.976184,,1717
-2020-11-30 16:00:00,ZIJVRO,Filled,Sell,-2.0,47.44,0.066416,,1718
-2020-11-30 16:00:00,BPSPGV,Filled,Sell,-1.0,214.11,0.149877,,1719
-2020-11-30 16:00:00,ISIJLH,Filled,Sell,-548.0,28.85,11.06686,,1720
-2020-11-30 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1721
-2020-11-30 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,1722
-2020-11-30 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,1723
-2020-11-30 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1724
-2020-11-30 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1725
-2020-11-30 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1726
-2020-12-01 16:00:00,SMDIFE,Filled,Sell,-30.0,121.04,2.54184,,1721
-2020-12-01 16:00:00,CEMOJE,Filled,Buy,7.0,1765.61,8.651489,,1722
-2020-12-01 16:00:00,GTKILW,Filled,Buy,7.0,1750.15,8.575735,,1723
-2020-12-01 16:00:00,ZIJVRO,Filled,Sell,-335.0,48.78,11.43891,,1724
-2020-12-01 16:00:00,BPSPGV,Filled,Sell,-14.0,214.6,2.10308,,1725
-2020-12-01 16:00:00,ISIJLH,Filled,Buy,439.0,28.83,8.859459,,1726
-2020-12-01 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1727
-2020-12-01 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,1728
-2020-12-01 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1729
-2020-12-01 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1730
-2020-12-01 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1731
-2020-12-02 16:00:00,SMDIFE,Filled,Sell,-3.0,122.09,0.256389,,1727
-2020-12-02 16:00:00,YIVYGH,Filled,Buy,248.0,50.93,8.841448,,1728
-2020-12-02 16:00:00,ZIJVRO,Filled,Buy,255.0,49.18,8.77863,,1729
-2020-12-02 16:00:00,BPSPGV,Filled,Sell,-1.0,215.0,0.1505,,1730
-2020-12-02 16:00:00,ISIJLH,Filled,Sell,-1.0,28.84,0.020188,,1731
-2020-12-02 16:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1732
-2020-12-02 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1733
-2020-12-02 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,1734
-2020-12-02 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,1735
-2020-12-02 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,1736
-2020-12-02 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1737
-2020-12-02 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1738
-2020-12-02 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1739
-2020-12-03 16:00:00,COMNHQ,Filled,Buy,992.0,15.19,10.547936,,1732
-2020-12-03 16:00:00,SMDIFE,Filled,Buy,16.0,123.5,1.3832,,1733
-2020-12-03 16:00:00,YIVYGH,Filled,Sell,-248.0,50.82,8.822352,,1734
-2020-12-03 16:00:00,CEMOJE,Filled,Sell,-7.0,1826.6,8.950339999999999,,1735
-2020-12-03 16:00:00,GTKILW,Filled,Sell,-7.0,1827.41,8.954309,,1736
-2020-12-03 16:00:00,ZIJVRO,Filled,Sell,-255.0,49.92,8.91072,,1737
-2020-12-03 16:00:00,BPSPGV,Filled,Sell,-58.0,214.6,8.71276,,1738
-2020-12-03 16:00:00,ISIJLH,Filled,Buy,68.0,29.02,1.381352,,1739
-2020-12-03 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1740
-2020-12-03 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1741
-2020-12-03 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1742
-2020-12-04 16:00:00,COMNHQ,Filled,Sell,-992.0,16.4,11.38816,,1740
-2020-12-04 16:00:00,SMDIFE,Filled,Buy,2.0,122.54,0.171556,,1741
-2020-12-04 16:00:00,ISIJLH,Filled,Sell,-506.0,29.35,10.39577,,1742
-2020-12-04 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1743
-2020-12-04 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1744
-2020-12-07 16:00:00,SMDIFE,Filled,Sell,-1.0,122.35,0.085645,,1743
-2020-12-07 16:00:00,BPSPGV,Filled,Buy,68.0,214.39,10.204964,,1744
-2020-12-07 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1745
-2020-12-08 16:00:00,SMDIFE,Filled,Sell,-1.0,124.35,0.087045,,1745
-2020-12-08 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1746
-2020-12-08 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1747
-2020-12-08 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1748
-2020-12-09 16:00:00,SMDIFE,Filled,Sell,-40.0,124.45,3.4846,,1746
-2020-12-09 16:00:00,BPSPGV,Filled,Sell,-23.0,215.2,3.46472,,1747
-2020-12-09 16:00:00,ISIJLH,Filled,Buy,321.0,31.03,6.972441000000001,,1748
-2020-12-09 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1749
-2020-12-09 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,1750
-2020-12-09 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,1751
-2020-12-09 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1752
-2020-12-09 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1753
-2020-12-10 16:00:00,SMDIFE,Filled,Buy,2.0,120.53,0.168742,,1749
-2020-12-10 16:00:00,CEMOJE,Filled,Buy,5.0,1787.2,6.2552,,1750
-2020-12-10 16:00:00,GTKILW,Filled,Buy,5.0,1780.18,6.23063,,1751
-2020-12-10 16:00:00,BPSPGV,Filled,Buy,1.0,211.8,0.14826,,1752
-2020-12-10 16:00:00,ISIJLH,Filled,Sell,-7.0,31.05,0.152145,,1753
-2020-12-10 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1754
-2020-12-10 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,1755
-2020-12-10 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,1756
-2020-12-10 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1757
-2020-12-10 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1758
-2020-12-11 16:00:00,SMDIFE,Filled,Sell,-1.0,122.41,0.085687,,1754
-2020-12-11 16:00:00,CEMOJE,Filled,Sell,-5.0,1766.6,6.1831,,1755
-2020-12-11 16:00:00,GTKILW,Filled,Sell,-5.0,1766.07,6.1812450000000005,,1756
-2020-12-11 16:00:00,BPSPGV,Filled,Sell,-46.0,210.2,6.768439999999999,,1757
-2020-12-11 16:00:00,ISIJLH,Filled,Buy,8.0,30.47,0.17063199999999998,,1758
-2020-12-11 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,1759
-2020-12-11 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1760
-2020-12-11 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1761
-2020-12-14 16:00:00,CEMOJE,Filled,Buy,5.0,1779.66,6.228810000000001,,1759
-2020-12-14 16:00:00,BPSPGV,Filled,Buy,46.0,212.91,6.855702,,1760
-2020-12-14 16:00:00,ISIJLH,Filled,Sell,-322.0,31.2,7.03248,,1761
-2020-12-14 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1762
-2020-12-14 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,1763
-2020-12-14 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,1764
-2020-12-14 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1765
-2020-12-15 16:00:00,SMDIFE,Filled,Buy,1.0,124.32,0.08702399999999999,,1762
-2020-12-15 16:00:00,CEMOJE,Filled,Sell,-5.0,1755.72,6.145020000000001,,1763
-2020-12-15 16:00:00,GTKILW,Filled,Buy,5.0,1752.23,6.132804999999999,,1764
-2020-12-15 16:00:00,BPSPGV,Filled,Sell,-46.0,215.17,6.928474,,1765
-2020-12-15 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1766
-2020-12-15 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1767
-2020-12-15 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,1768
-2020-12-16 16:00:00,SMDIFE,Filled,Sell,-4.0,127.45,0.35686,,1766
-2020-12-16 16:00:00,OCHCAU,Filled,Buy,221.0,44.71,6.916637,,1767
-2020-12-16 16:00:00,GTKILW,Filled,Sell,-5.0,1770.0,6.195,,1768
-2020-12-16 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1769
-2020-12-16 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,1770
-2020-12-16 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1771
-2020-12-16 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,1772
-2020-12-16 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1773
-2020-12-17 16:00:00,SMDIFE,Filled,Buy,1.0,128.98,0.090286,,1769
-2020-12-17 16:00:00,XUEHVZ,Filled,Buy,3.0,3234.68,6.792827999999999,,1770
-2020-12-17 16:00:00,OCHCAU,Filled,Sell,-221.0,44.93,6.950671000000001,,1771
-2020-12-17 16:00:00,CEMOJE,Filled,Buy,5.0,1771.95,6.201825,,1772
-2020-12-17 16:00:00,BPSPGV,Filled,Buy,45.0,219.86,6.925590000000001,,1773
-2020-12-17 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1774
-2020-12-17 16:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,1775
-2020-12-17 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,1776
-2020-12-17 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1777
-2020-12-17 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1778
-2020-12-18 16:00:00,SMDIFE,Filled,Sell,-2.0,129.0,0.1806,,1774
-2020-12-18 16:00:00,XUEHVZ,Filled,Sell,-3.0,3231.35,6.785835,,1775
-2020-12-18 16:00:00,GTKILW,Filled,Buy,5.0,1737.88,6.082580000000001,,1776
-2020-12-18 16:00:00,BPSPGV,Filled,Sell,-45.0,218.92,6.89598,,1777
-2020-12-18 16:00:00,ISIJLH,Filled,Buy,334.0,29.54,6.906452000000001,,1778
-2020-12-18 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1779
-2020-12-18 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,1780
-2020-12-18 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1781
-2020-12-18 16:00:00,FFNDVM,Submitted,Buy,0.0,0.0,0.0,,1782
-2020-12-18 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1783
-2020-12-18 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1784
-2020-12-18 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1785
-2020-12-21 16:00:00,SMDIFE,Filled,Buy,2.0,125.1,0.17514,,1779
-2020-12-21 16:00:00,YIVYGH,Filled,Buy,194.0,50.48,6.8551839999999995,,1780
-2020-12-21 16:00:00,OCHCAU,Filled,Buy,217.0,44.47,6.754993,,1781
-2020-12-21 16:00:00,FFNDVM,Filled,Buy,1104.0,8.89,6.870192000000001,,1782
-2020-12-21 16:00:00,ZIJVRO,Filled,Buy,208.0,46.26,6.735456,,1783
-2020-12-21 16:00:00,BPSPGV,Filled,Buy,45.0,217.55,6.852825,,1784
-2020-12-21 16:00:00,ISIJLH,Filled,Sell,-334.0,29.0,6.7802,,1785
-2020-12-21 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1786
-2020-12-21 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1787
-2020-12-21 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1788
-2020-12-21 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,1789
-2020-12-21 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1790
-2020-12-21 16:00:00,FFNDVM,Submitted,Sell,0.0,0.0,0.0,,1791
-2020-12-21 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1792
-2020-12-21 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1793
-2020-12-21 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1794
-2020-12-21 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1795
-2020-12-22 16:00:00,SMDIFE,Filled,Sell,-1.0,131.61,0.092127,,1786
-2020-12-22 16:00:00,LUZLYG,Filled,Buy,332.0,29.75,6.9139,,1787
-2020-12-22 16:00:00,HECLON,Filled,Buy,161.0,61.0,6.8747,,1788
-2020-12-22 16:00:00,YIVYGH,Filled,Buy,2.0,50.02,0.070028,,1789
-2020-12-22 16:00:00,OCHCAU,Filled,Sell,-217.0,44.48,6.756512,,1790
-2020-12-22 16:00:00,FFNDVM,Filled,Sell,-1104.0,8.98,6.939744,,1791
-2020-12-22 16:00:00,ZIJVRO,Filled,Buy,5.0,46.27,0.161945,,1792
-2020-12-22 16:00:00,BPSPGV,Filled,Sell,-1.0,222.57,0.155799,,1793
-2020-12-22 16:00:00,ISIJLH,Filled,Buy,341.0,29.0,6.9223,,1794
-2020-12-22 16:00:00,RUKNMV,Filled,Buy,334.0,29.6,6.9204799999999995,,1795
-2020-12-22 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1796
-2020-12-22 16:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1797
-2020-12-22 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1798
-2020-12-22 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,1799
-2020-12-22 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,1800
-2020-12-22 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,1801
-2020-12-22 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1802
-2020-12-22 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1803
-2020-12-22 16:00:00,ISIJLH,Submitted,Buy,0.0,0.0,0.0,,1804
-2020-12-22 16:00:00,BPFUQM,Submitted,Buy,0.0,0.0,0.0,,1805
-2020-12-22 16:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1806
-2020-12-23 16:00:00,SMDIFE,Filled,Buy,34.0,132.17,3.1456459999999997,,1796
-2020-12-23 16:00:00,LUZLYG,Filled,Sell,-332.0,29.39,6.830235999999999,,1797
-2020-12-23 16:00:00,HECLON,Filled,Buy,87.0,60.0,3.654,,1798
-2020-12-23 16:00:00,YIVYGH,Filled,Sell,-196.0,50.15,6.880579999999999,,1799
-2020-12-23 16:00:00,CEMOJE,Filled,Sell,-5.0,1724.59,6.036064999999999,,1800
-2020-12-23 16:00:00,GTKILW,Filled,Sell,-5.0,1716.13,6.006455000000001,,1801
-2020-12-23 16:00:00,ZIJVRO,Filled,Sell,-213.0,46.21,6.889911,,1802
-2020-12-23 16:00:00,BPSPGV,Filled,Sell,-44.0,223.25,6.8761,,1803
-2020-12-23 16:00:00,ISIJLH,Filled,Buy,178.0,28.5,3.5511,,1804
-2020-12-23 16:00:00,BPFUQM,Filled,Buy,23.0,632.42,10.181962,,1805
-2020-12-23 16:00:00,RUKNMV,Filled,Buy,175.0,29.32,3.5917,,1806
-2020-12-23 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1807
-2020-12-23 16:00:00,LUZLYG,Submitted,Buy,0.0,0.0,0.0,,1808
-2020-12-23 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1809
-2020-12-23 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1810
-2020-12-23 16:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1811
-2020-12-23 16:00:00,BPFUQM,Submitted,Sell,0.0,0.0,0.0,,1812
-2020-12-23 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1813
-2020-12-24 13:00:00,SMDIFE,Filled,Buy,1.0,131.41,0.091987,,1807
-2020-12-24 13:00:00,LUZLYG,Filled,Buy,491.0,30.25,10.396925,,1808
-2020-12-24 13:00:00,HECLON,Filled,Sell,-248.0,60.87,10.567032,,1809
-2020-12-24 13:00:00,BPSPGV,Filled,Buy,66.0,221.4,10.22868,,1810
-2020-12-24 13:00:00,ISIJLH,Filled,Sell,-6.0,28.73,0.120666,,1811
-2020-12-24 13:00:00,BPFUQM,Filled,Sell,-1.0,643.01,0.450107,,1812
-2020-12-24 13:00:00,RUKNMV,Filled,Sell,-23.0,30.35,0.488635,,1813
-2020-12-24 13:00:00,COMNHQ,Submitted,Buy,0.0,0.0,0.0,,1814
-2020-12-24 13:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1815
-2020-12-24 13:00:00,LUZLYG,Submitted,Sell,0.0,0.0,0.0,,1816
-2020-12-24 13:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,1817
-2020-12-24 13:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,1818
-2020-12-24 13:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,1819
-2020-12-24 13:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1820
-2020-12-24 13:00:00,ISIJLH,Submitted,Sell,0.0,0.0,0.0,,1821
-2020-12-24 13:00:00,RUKNMV,Submitted,Buy,0.0,0.0,0.0,,1822
-2020-12-28 16:00:00,COMNHQ,Filled,Buy,943.0,16.0,10.5616,,1814
-2020-12-28 16:00:00,SMDIFE,Filled,Sell,-1.0,134.0,0.0938,,1815
-2020-12-28 16:00:00,LUZLYG,Filled,Sell,-491.0,30.24,10.393487999999998,,1816
-2020-12-28 16:00:00,YIVYGH,Filled,Buy,293.0,50.78,10.414978,,1817
-2020-12-28 16:00:00,CEMOJE,Filled,Buy,8.0,1737.17,9.728152,,1818
-2020-12-28 16:00:00,GTKILW,Filled,Buy,8.0,1742.04,9.755424,,1819
-2020-12-28 16:00:00,BPSPGV,Filled,Sell,-66.0,224.44,10.369128,,1820
-2020-12-28 16:00:00,ISIJLH,Filled,Sell,-513.0,28.9,10.37799,,1821
-2020-12-28 16:00:00,RUKNMV,Filled,Buy,9.0,30.05,0.189315,,1822
-2020-12-28 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1823
-2020-12-28 16:00:00,SMDIFE,Submitted,Sell,0.0,0.0,0.0,,1824
-2020-12-28 16:00:00,XUEHVZ,Submitted,Buy,0.0,0.0,0.0,,1825
-2020-12-28 16:00:00,HECLON,Submitted,Buy,0.0,0.0,0.0,,1826
-2020-12-28 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,1827
-2020-12-28 16:00:00,OCHCAU,Submitted,Buy,0.0,0.0,0.0,,1828
-2020-12-28 16:00:00,CEMOJE,Submitted,Sell,0.0,0.0,0.0,,1829
-2020-12-28 16:00:00,GTKILW,Submitted,Sell,0.0,0.0,0.0,,1830
-2020-12-28 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1831
-2020-12-28 16:00:00,BPFUQM,Submitted,Sell,0.0,0.0,0.0,,1832
-2020-12-28 16:00:00,RUKNMV,Submitted,Sell,0.0,0.0,0.0,,1833
-2020-12-29 16:00:00,COMNHQ,Filled,Sell,-250.0,16.32,2.856,,1823
-2020-12-29 16:00:00,SMDIFE,Filled,Sell,-30.0,138.05,2.89905,,1824
-2020-12-29 16:00:00,XUEHVZ,Filled,Buy,3.0,3293.73,6.9168330000000005,,1825
-2020-12-29 16:00:00,HECLON,Filled,Buy,182.0,61.1,7.784140000000001,,1826
-2020-12-29 16:00:00,YIVYGH,Filled,Sell,-293.0,51.16,10.492916,,1827
-2020-12-29 16:00:00,OCHCAU,Filled,Buy,248.0,44.99,7.810264,,1828
-2020-12-29 16:00:00,CEMOJE,Filled,Sell,-2.0,1775.96,2.486344,,1829
-2020-12-29 16:00:00,GTKILW,Filled,Sell,-2.0,1782.27,2.495178,,1830
-2020-12-29 16:00:00,BPSPGV,Filled,Buy,49.0,226.06,7.753858,,1831
-2020-12-29 16:00:00,BPFUQM,Filled,Sell,-6.0,660.86,2.7756119999999997,,1832
-2020-12-29 16:00:00,RUKNMV,Filled,Sell,-495.0,30.1,10.42965,,1833
-2020-12-29 16:00:00,COMNHQ,Submitted,Sell,0.0,0.0,0.0,,1834
-2020-12-29 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1835
-2020-12-29 16:00:00,XUEHVZ,Submitted,Sell,0.0,0.0,0.0,,1836
-2020-12-29 16:00:00,HECLON,Submitted,Sell,0.0,0.0,0.0,,1837
-2020-12-29 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,1838
-2020-12-29 16:00:00,OCHCAU,Submitted,Sell,0.0,0.0,0.0,,1839
-2020-12-29 16:00:00,ZIJVRO,Submitted,Buy,0.0,0.0,0.0,,1840
-2020-12-29 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1841
-2020-12-30 16:00:00,COMNHQ,Filled,Sell,-693.0,15.86,7.693686,,1834
-2020-12-30 16:00:00,SMDIFE,Filled,Buy,1.0,135.54,0.094878,,1835
-2020-12-30 16:00:00,XUEHVZ,Filled,Sell,-3.0,3318.85,6.9695849999999995,,1836
-2020-12-30 16:00:00,HECLON,Filled,Sell,-182.0,60.91,7.759933999999999,,1837
-2020-12-30 16:00:00,YIVYGH,Filled,Buy,216.0,51.69,7.815528,,1838
-2020-12-30 16:00:00,OCHCAU,Filled,Sell,-248.0,44.76,7.770336,,1839
-2020-12-30 16:00:00,ZIJVRO,Filled,Buy,225.0,49.1,7.73325,,1840
-2020-12-30 16:00:00,BPSPGV,Filled,Sell,-49.0,225.26,7.726418,,1841
-2020-12-30 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1842
-2020-12-30 16:00:00,YIVYGH,Submitted,Sell,0.0,0.0,0.0,,1843
-2020-12-30 16:00:00,CEMOJE,Submitted,Buy,0.0,0.0,0.0,,1844
-2020-12-30 16:00:00,GTKILW,Submitted,Buy,0.0,0.0,0.0,,1845
-2020-12-30 16:00:00,ZIJVRO,Submitted,Sell,0.0,0.0,0.0,,1846
-2020-12-30 16:00:00,BPSPGV,Submitted,Buy,0.0,0.0,0.0,,1847
-2020-12-30 16:00:00,BPFUQM,Submitted,Sell,0.0,0.0,0.0,,1848
-2020-12-31 16:00:00,SMDIFE,Filled,Buy,20.0,134.0,1.876,,1842
-2020-12-31 16:00:00,YIVYGH,Filled,Sell,-216.0,51.39,7.770168,,1843
-2020-12-31 16:00:00,CEMOJE,Filled,Buy,1.0,1745.45,1.221815,,1844
-2020-12-31 16:00:00,GTKILW,Filled,Buy,1.0,1735.28,1.214696,,1845
-2020-12-31 16:00:00,ZIJVRO,Filled,Sell,-225.0,48.75,7.678125,,1846
-2020-12-31 16:00:00,BPSPGV,Filled,Buy,62.0,221.82,9.626988,,1847
-2020-12-31 16:00:00,BPFUQM,Filled,Sell,-16.0,700.0,7.84,,1848
-2020-12-31 16:00:00,SMDIFE,Submitted,Buy,0.0,0.0,0.0,,1849
-2020-12-31 16:00:00,YIVYGH,Submitted,Buy,0.0,0.0,0.0,,1850
-2020-12-31 16:00:00,BPSPGV,Submitted,Sell,0.0,0.0,0.0,,1851
+timestamp,symbol,status,direction,fill_quantity,fill_price,fee,message,order_id
+2019-01-04 16:00:00,MCCZID,SUBMITTED,BUY,0.0,0.0,0.0,,1
+2019-01-07 16:00:00,MCCZID,FILLED,BUY,323.0,43.0,9.7223,,1
+2019-01-07 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,2
+2019-01-08 16:00:00,MCCZID,FILLED,SELL,-2.0,43.53,0.060942,,2
+2019-01-08 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,3
+2019-01-09 16:00:00,MCCZID,FILLED,SELL,-89.0,43.41,2.704443,,3
+2019-01-09 16:00:00,MCCZID,SUBMITTED,BUY,0.0,0.0,0.0,,4
+2019-01-10 16:00:00,MCCZID,FILLED,BUY,1.0,43.18,0.030226,,4
+2019-01-10 16:00:00,MCCZID,SUBMITTED,BUY,0.0,0.0,0.0,,5
+2019-01-11 16:00:00,MCCZID,FILLED,BUY,5.0,42.33,0.14815499999999998,,5
+2019-01-11 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,6
+2019-01-14 16:00:00,MCCZID,FILLED,SELL,-238.0,42.55,7.08883,,6
+2019-01-14 16:00:00,OCHCAU,SUBMITTED,BUY,0.0,0.0,0.0,,7
+2019-01-14 16:00:00,CEMOJE,SUBMITTED,BUY,0.0,0.0,0.0,,8
+2019-01-14 16:00:00,GTKILW,SUBMITTED,BUY,0.0,0.0,0.0,,9
+2019-01-14 16:00:00,MCCZID,SUBMITTED,BUY,0.0,0.0,0.0,,10
+2019-01-15 16:00:00,OCHCAU,FILLED,BUY,231.0,43.22,6.988674,,7
+2019-01-15 16:00:00,CEMOJE,FILLED,BUY,9.0,1043.92,6.576696,,8
+2019-01-15 16:00:00,GTKILW,FILLED,BUY,9.0,1052.01,6.627663,,9
+2019-01-15 16:00:00,MCCZID,FILLED,BUY,235.0,42.61,7.009345000000001,,10
+2019-01-15 16:00:00,OCHCAU,SUBMITTED,SELL,0.0,0.0,0.0,,11
+2019-01-15 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,12
+2019-01-16 16:00:00,OCHCAU,FILLED,SELL,-4.0,44.1,0.12348,,11
+2019-01-16 16:00:00,MCCZID,FILLED,SELL,-1.0,42.63,0.029841000000000003,,12
+2019-01-16 16:00:00,CEMOJE,SUBMITTED,SELL,0.0,0.0,0.0,,13
+2019-01-16 16:00:00,GTKILW,SUBMITTED,SELL,0.0,0.0,0.0,,14
+2019-01-16 16:00:00,MCCZID,SUBMITTED,BUY,0.0,0.0,0.0,,15
+2019-01-17 16:00:00,CEMOJE,FILLED,SELL,-9.0,1079.19,6.798897,,13
+2019-01-17 16:00:00,GTKILW,FILLED,SELL,-9.0,1087.08,6.848604,,14
+2019-01-17 16:00:00,MCCZID,FILLED,BUY,3.0,41.89,0.087969,,15
+2019-01-17 16:00:00,OCHCAU,SUBMITTED,SELL,0.0,0.0,0.0,,16
+2019-01-17 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,17
+2019-01-18 16:00:00,OCHCAU,FILLED,SELL,-1.0,44.61,0.031227,,16
+2019-01-18 16:00:00,MCCZID,FILLED,SELL,-2.0,42.62,0.059668,,17
+2019-01-18 16:00:00,OCHCAU,SUBMITTED,SELL,0.0,0.0,0.0,,18
+2019-01-22 16:00:00,OCHCAU,FILLED,SELL,-226.0,44.88,7.100016000000001,,18
+2019-01-22 16:00:00,MCCZID,SUBMITTED,BUY,0.0,0.0,0.0,,19
+2019-01-23 16:00:00,MCCZID,FILLED,BUY,93.0,41.95,2.730945,,19
+2019-01-23 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,20
+2019-01-24 16:00:00,MCCZID,FILLED,SELL,-3.0,41.74,0.087654,,20
+2019-01-24 16:00:00,MCCZID,SUBMITTED,BUY,0.0,0.0,0.0,,21
+2019-01-25 16:00:00,MCCZID,FILLED,BUY,9.0,41.14,0.25918199999999997,,21
+2019-01-25 16:00:00,MCCZID,SUBMITTED,BUY,0.0,0.0,0.0,,22
+2019-01-28 16:00:00,MCCZID,FILLED,BUY,3.0,40.5,0.08505,,22
+2019-01-28 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,23
+2019-01-29 16:00:00,MCCZID,FILLED,SELL,-36.0,39.53,0.996156,,23
+2019-01-29 16:00:00,MCCZID,SUBMITTED,BUY,0.0,0.0,0.0,,24
+2019-01-30 16:00:00,MCCZID,FILLED,BUY,88.0,40.81,2.513896,,24
+2019-01-30 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,25
+2019-01-30 16:00:00,ISIJLH,SUBMITTED,BUY,0.0,0.0,0.0,,26
+2019-01-31 16:00:00,MCCZID,FILLED,SELL,-8.0,41.41,0.231896,,25
+2019-01-31 16:00:00,ISIJLH,FILLED,BUY,540.0,29.47,11.13966,,26
+2019-01-31 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,27
+2019-01-31 16:00:00,ISIJLH,SUBMITTED,SELL,0.0,0.0,0.0,,28
+2019-02-01 16:00:00,MCCZID,FILLED,SELL,-7.0,42.84,0.209916,,27
+2019-02-01 16:00:00,ISIJLH,FILLED,SELL,-540.0,30.25,11.4345,,28
+2019-02-01 16:00:00,LUZLYG,SUBMITTED,BUY,0.0,0.0,0.0,,29
+2019-02-01 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,30
+2019-02-01 16:00:00,RUKNMV,SUBMITTED,BUY,0.0,0.0,0.0,,31
+2019-02-04 16:00:00,LUZLYG,FILLED,BUY,560.0,28.46,11.15632,,29
+2019-02-04 16:00:00,MCCZID,FILLED,SELL,-374.0,42.8,11.20504,,30
+2019-02-04 16:00:00,RUKNMV,FILLED,BUY,325.0,48.85,11.113375,,31
+2019-02-04 16:00:00,LUZLYG,SUBMITTED,SELL,0.0,0.0,0.0,,32
+2019-02-04 16:00:00,ISIJLH,SUBMITTED,BUY,0.0,0.0,0.0,,33
+2019-02-04 16:00:00,RUKNMV,SUBMITTED,SELL,0.0,0.0,0.0,,34
+2019-02-05 16:00:00,LUZLYG,FILLED,SELL,-560.0,28.85,11.3092,,32
+2019-02-05 16:00:00,ISIJLH,FILLED,BUY,536.0,29.64,11.120928,,33
+2019-02-05 16:00:00,RUKNMV,FILLED,SELL,-1.0,49.22,0.034454,,34
+2019-02-05 16:00:00,LUZLYG,SUBMITTED,BUY,0.0,0.0,0.0,,35
+2019-02-05 16:00:00,ISIJLH,SUBMITTED,SELL,0.0,0.0,0.0,,36
+2019-02-05 16:00:00,RUKNMV,SUBMITTED,SELL,0.0,0.0,0.0,,37
+2019-02-06 16:00:00,LUZLYG,FILLED,BUY,355.0,28.63,7.114554999999999,,35
+2019-02-06 16:00:00,ISIJLH,FILLED,SELL,-192.0,29.74,3.997056,,36
+2019-02-06 16:00:00,RUKNMV,FILLED,SELL,-117.0,49.15,4.025385,,37
+2019-02-06 16:00:00,LUZLYG,SUBMITTED,SELL,0.0,0.0,0.0,,38
+2019-02-06 16:00:00,MCCZID,SUBMITTED,BUY,0.0,0.0,0.0,,39
+2019-02-06 16:00:00,ISIJLH,SUBMITTED,SELL,0.0,0.0,0.0,,40
+2019-02-06 16:00:00,RUKNMV,SUBMITTED,SELL,0.0,0.0,0.0,,41
+2019-02-07 16:00:00,LUZLYG,FILLED,SELL,-355.0,28.59,7.104615000000001,,38
+2019-02-07 16:00:00,MCCZID,FILLED,BUY,239.0,42.09,7.041657,,39
+2019-02-07 16:00:00,ISIJLH,FILLED,SELL,-2.0,29.5,0.0413,,40
+2019-02-07 16:00:00,RUKNMV,FILLED,SELL,-207.0,49.11,7.116039000000001,,41
+2019-02-07 16:00:00,CEMOJE,SUBMITTED,BUY,0.0,0.0,0.0,,42
+2019-02-07 16:00:00,MCCZID,SUBMITTED,BUY,0.0,0.0,0.0,,43
+2019-02-07 16:00:00,ISIJLH,SUBMITTED,BUY,0.0,0.0,0.0,,44
+2019-02-08 16:00:00,CEMOJE,FILLED,BUY,9.0,1097.14,6.911982,,42
+2019-02-08 16:00:00,MCCZID,FILLED,BUY,3.0,41.6,0.08736000000000001,,43
+2019-02-08 16:00:00,ISIJLH,FILLED,BUY,1.0,29.4,0.02058,,44
+2019-02-08 16:00:00,CEMOJE,SUBMITTED,SELL,0.0,0.0,0.0,,45
+2019-02-08 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,46
+2019-02-08 16:00:00,ISIJLH,SUBMITTED,SELL,0.0,0.0,0.0,,47
+2019-02-11 16:00:00,CEMOJE,FILLED,SELL,-9.0,1088.34,6.856541999999999,,45
+2019-02-11 16:00:00,MCCZID,FILLED,SELL,-5.0,42.29,0.14801499999999998,,46
+2019-02-11 16:00:00,ISIJLH,FILLED,SELL,-5.0,29.6,0.1036,,47
+2019-02-11 16:00:00,FFNDVM,SUBMITTED,BUY,0.0,0.0,0.0,,48
+2019-02-11 16:00:00,MCCZID,SUBMITTED,BUY,0.0,0.0,0.0,,49
+2019-02-11 16:00:00,ISIJLH,SUBMITTED,SELL,0.0,0.0,0.0,,50
+2019-02-12 16:00:00,FFNDVM,FILLED,BUY,1202.0,8.38,7.050932,,48
+2019-02-12 16:00:00,MCCZID,FILLED,BUY,3.0,41.71,0.087591,,49
+2019-02-12 16:00:00,ISIJLH,FILLED,SELL,-1.0,29.85,0.020895,,50
+2019-02-12 16:00:00,FFNDVM,SUBMITTED,SELL,0.0,0.0,0.0,,51
+2019-02-12 16:00:00,LMRIBF,SUBMITTED,BUY,0.0,0.0,0.0,,52
+2019-02-12 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,53
+2019-02-12 16:00:00,ISIJLH,SUBMITTED,SELL,0.0,0.0,0.0,,54
+2019-02-13 16:00:00,FFNDVM,FILLED,SELL,-18.0,8.44,0.106344,,51
+2019-02-13 16:00:00,LMRIBF,FILLED,BUY,60.0,165.38,6.9459599999999995,,52
+2019-02-13 16:00:00,MCCZID,FILLED,SELL,-1.0,41.95,0.029365,,53
+2019-02-13 16:00:00,ISIJLH,FILLED,SELL,-1.0,29.79,0.020853,,54
+2019-02-13 16:00:00,FFNDVM,SUBMITTED,BUY,0.0,0.0,0.0,,55
+2019-02-13 16:00:00,LMRIBF,SUBMITTED,BUY,0.0,0.0,0.0,,56
+2019-02-13 16:00:00,CEMOJE,SUBMITTED,BUY,0.0,0.0,0.0,,57
+2019-02-13 16:00:00,GTKILW,SUBMITTED,BUY,0.0,0.0,0.0,,58
+2019-02-13 16:00:00,BPSPGV,SUBMITTED,BUY,0.0,0.0,0.0,,59
+2019-02-13 16:00:00,MCCZID,SUBMITTED,BUY,0.0,0.0,0.0,,60
+2019-02-13 16:00:00,ISIJLH,SUBMITTED,SELL,0.0,0.0,0.0,,61
+2019-02-14 16:00:00,FFNDVM,FILLED,BUY,6.0,8.38,0.035196,,55
+2019-02-14 16:00:00,LMRIBF,FILLED,BUY,1.0,163.19,0.114233,,56
+2019-02-14 16:00:00,CEMOJE,FILLED,BUY,8.0,1123.96,6.294176,,57
+2019-02-14 16:00:00,GTKILW,FILLED,BUY,8.0,1124.62,6.297871999999999,,58
+2019-02-14 16:00:00,BPSPGV,FILLED,BUY,93.0,106.31,6.920781,,59
+2019-02-14 16:00:00,MCCZID,FILLED,BUY,1.0,41.74,0.029218,,60
+2019-02-14 16:00:00,ISIJLH,FILLED,SELL,-1.0,29.73,0.020811,,61
+2019-02-14 16:00:00,XUEHVZ,SUBMITTED,BUY,0.0,0.0,0.0,,62
+2019-02-14 16:00:00,LUZLYG,SUBMITTED,BUY,0.0,0.0,0.0,,63
+2019-02-14 16:00:00,FFNDVM,SUBMITTED,SELL,0.0,0.0,0.0,,64
+2019-02-14 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,65
+2019-02-14 16:00:00,ISIJLH,SUBMITTED,BUY,0.0,0.0,0.0,,66
+2019-02-15 16:00:00,XUEHVZ,FILLED,BUY,6.0,1619.82,6.803244,,62
+2019-02-15 16:00:00,LUZLYG,FILLED,BUY,352.0,28.75,7.084,,63
+2019-02-15 16:00:00,FFNDVM,FILLED,SELL,-1.0,8.5,0.00595,,64
+2019-02-15 16:00:00,MCCZID,FILLED,SELL,-2.0,42.36,0.059304,,65
+2019-02-15 16:00:00,ISIJLH,FILLED,BUY,1.0,30.0,0.021,,66
+2019-02-15 16:00:00,LUZLYG,SUBMITTED,SELL,0.0,0.0,0.0,,67
+2019-02-15 16:00:00,FFNDVM,SUBMITTED,SELL,0.0,0.0,0.0,,68
+2019-02-15 16:00:00,BPSPGV,SUBMITTED,SELL,0.0,0.0,0.0,,69
+2019-02-15 16:00:00,MCCZID,SUBMITTED,SELL,0.0,0.0,0.0,,70
+2019-02-15 16:00:00,ISIJLH,SUBMITTED,SELL,0.0,0.0,0.0,,71
+2019-02-19 16:00:00,LUZLYG,FILLED,SELL,-8.0,28.88,0.16172799999999998,,67
+2019-02-19 16:00:00,FFNDVM,FILLED,SELL,-1189.0,8.54,7.107842,,68
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diff --git a/validation/lean/workspace/chapter16_us_equities_panel/ml4t_order_events.csv.part01.xz b/validation/lean/workspace/chapter16_us_equities_panel/ml4t_order_events.csv.part01.xz
index 41a4f4de..6d39a245 100644
Binary files a/validation/lean/workspace/chapter16_us_equities_panel/ml4t_order_events.csv.part01.xz and b/validation/lean/workspace/chapter16_us_equities_panel/ml4t_order_events.csv.part01.xz differ
diff --git a/validation/lean/workspace/chapter16_us_equities_panel/ml4t_order_events.csv.part02.xz b/validation/lean/workspace/chapter16_us_equities_panel/ml4t_order_events.csv.part02.xz
index 05eaf81f..45834cb4 100644
Binary files a/validation/lean/workspace/chapter16_us_equities_panel/ml4t_order_events.csv.part02.xz and b/validation/lean/workspace/chapter16_us_equities_panel/ml4t_order_events.csv.part02.xz differ
diff --git a/validation/native/backtrader_behavior.py b/validation/native/backtrader_behavior.py
new file mode 100644
index 00000000..b4bbba3d
--- /dev/null
+++ b/validation/native/backtrader_behavior.py
@@ -0,0 +1,779 @@
+#!/usr/bin/env python3
+"""Measure frozen Backtrader behavior without importing ML4T comparison code."""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import importlib
+import importlib.metadata
+import inspect
+import json
+import math
+import sys
+import warnings
+from pathlib import Path
+from typing import Any
+
+import pandas as pd
+
+with warnings.catch_warnings():
+    warnings.filterwarnings("ignore", message="invalid escape sequence.*", category=SyntaxWarning)
+    bt: Any = importlib.import_module("backtrader")
+
+VERSION = "1.9.78.123"
+ARTIFACT = "backtrader-1.9.78.123-py2.py3-none-any.whl"
+ARTIFACT_SHA256 = "9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd"
+SOURCE = "https://pypi.org/project/backtrader/1.9.78.123/"
+
+
+def _frame(
+    opens: list[float],
+    *,
+    closes: list[float] | None = None,
+    lows: list[float] | None = None,
+    highs: list[float] | None = None,
+    dates: list[str] | None = None,
+) -> pd.DataFrame:
+    closes = closes or opens
+    lows = lows or [min(open_, close) for open_, close in zip(opens, closes, strict=True)]
+    highs = highs or [max(open_, close) for open_, close in zip(opens, closes, strict=True)]
+    index = (
+        pd.to_datetime(dates)
+        if dates is not None
+        else pd.date_range("2024-01-01", periods=len(opens))
+    )
+    return pd.DataFrame(
+        {"open": opens, "high": highs, "low": lows, "close": closes, "volume": 1_000.0},
+        index=index,
+    )
+
+
+def _feed(frame: pd.DataFrame, name: str = "asset") -> Any:
+    return bt.feeds.PandasData(dataname=frame, name=name)
+
+
+def _run(
+    strategy: type,
+    *frames: tuple[str, pd.DataFrame],
+    cash: float = 1_000.0,
+    configure: Any = None,
+    **strategy_kwargs: Any,
+) -> tuple[Any, Any]:
+    cerebro = bt.Cerebro()
+    cerebro.broker.setcash(cash)
+    if configure is not None:
+        configure(cerebro.broker)
+    for name, frame in frames:
+        cerebro.adddata(_feed(frame, name))
+    cerebro.addstrategy(strategy, **strategy_kwargs)
+    instance = cerebro.run()[0]
+    return cerebro, instance
+
+
+def _terminal(order: Any) -> bool:
+    return order.status in {order.Completed, order.Margin, order.Rejected, order.Canceled}
+
+
+def _defaults() -> dict[str, Any]:
+    broker = bt.Cerebro().broker
+    commission = bt.CommInfoBase()
+    return {
+        "cash": broker.p.cash,
+        "checksubmit": broker.p.checksubmit,
+        "cheat_on_close": broker.p.coc,
+        "cheat_on_open": broker.p.coo,
+        "commission": commission.p.commission,
+        "leverage": commission.p.leverage,
+        "short_cash": broker.p.shortcash,
+        "slippage_fixed": broker.p.slip_fixed,
+        "slippage_percent": broker.p.slip_perc,
+    }
+
+
+def _timing(coc: bool = False) -> list[dict[str, Any]]:
+    class Strategy(bt.Strategy):
+        def __init__(self) -> None:
+            self.events: list[dict[str, Any]] = []
+
+        def next(self) -> None:
+            if len(self) == 1:
+                self.buy(size=1)
+
+        def notify_order(self, order: Any) -> None:
+            if order.status == order.Completed:
+                self.events.append(
+                    {
+                        "date": bt.num2date(order.executed.dt).date().isoformat(),
+                        "price": order.executed.price,
+                        "size": order.executed.size,
+                    }
+                )
+
+    def configure(broker: Any) -> None:
+        broker.set_coc(coc)
+
+    _, strategy = _run(
+        Strategy,
+        ("asset", _frame([100.0, 110.0, 120.0], closes=[100.0, 105.0, 120.0])),
+        configure=configure,
+    )
+    return strategy.events
+
+
+def _target_percent(target: float, commission: float = 0.0) -> list[dict[str, Any]]:
+    class Strategy(bt.Strategy):
+        def __init__(self) -> None:
+            self.events: list[dict[str, Any]] = []
+
+        def next(self) -> None:
+            if len(self) == 1:
+                self.order_target_percent(target=target)
+
+        def notify_order(self, order: Any) -> None:
+            if _terminal(order):
+                self.events.append(
+                    {
+                        "status": order.getstatusname(),
+                        "created_size": order.created.size,
+                        "executed_size": order.executed.size,
+                        "price": order.executed.price,
+                        "commission": order.executed.comm,
+                    }
+                )
+
+    def configure(broker: Any) -> None:
+        broker.setcommission(commission=commission)
+
+    _, strategy = _run(
+        Strategy,
+        ("asset", _frame([100.0, 100.0])),
+        configure=configure,
+    )
+    return strategy.events
+
+
+def _cash_and_margin(leverage: float) -> list[dict[str, Any]]:
+    class Strategy(bt.Strategy):
+        def __init__(self) -> None:
+            self.events: list[dict[str, Any]] = []
+
+        def next(self) -> None:
+            if len(self) == 1:
+                self.buy(size=20)
+
+        def notify_order(self, order: Any) -> None:
+            if _terminal(order):
+                self.events.append({"status": order.getstatusname(), "size": order.executed.size})
+
+    def configure(broker: Any) -> None:
+        broker.setcommission(leverage=leverage)
+
+    _, strategy = _run(
+        Strategy,
+        ("asset", _frame([100.0, 100.0])),
+        configure=configure,
+    )
+    return strategy.events
+
+
+def _submission_sequence(reverse: bool) -> list[dict[str, Any]]:
+    class Strategy(bt.Strategy):
+        def __init__(self) -> None:
+            self.events: list[dict[str, Any]] = []
+
+        def next(self) -> None:
+            if len(self) == 1:
+                data_sequence = list(reversed(self.datas)) if reverse else self.datas
+                for data in data_sequence:
+                    self.order_target_percent(data=data, target=0.6)
+
+        def notify_order(self, order: Any) -> None:
+            if _terminal(order):
+                self.events.append(
+                    {
+                        "asset": order.data._name,
+                        "created_size": order.created.size,
+                        "reference": order.ref,
+                        "status": order.getstatusname(),
+                    }
+                )
+
+    _, strategy = _run(
+        Strategy,
+        ("a", _frame([100.0, 100.0])),
+        ("b", _frame([100.0, 100.0])),
+        cash=1_000.0,
+    )
+    return [
+        {
+            "asset": event["asset"],
+            "created_size": event["created_size"],
+            "status": event["status"],
+        }
+        for event in sorted(strategy.events, key=lambda event: event["reference"])
+    ]
+
+
+def _losing_short_cover() -> dict[str, Any]:
+    class Strategy(bt.Strategy):
+        def __init__(self) -> None:
+            self.events: list[dict[str, Any]] = []
+
+        def next(self) -> None:
+            if len(self) == 1:
+                self.sell(size=1)
+            elif len(self) == 2:
+                self.buy(size=1)
+
+        def notify_order(self, order: Any) -> None:
+            if _terminal(order):
+                self.events.append(
+                    {
+                        "status": order.getstatusname(),
+                        "size": order.executed.size,
+                        "price": order.executed.price,
+                    }
+                )
+
+    cerebro, strategy = _run(
+        Strategy,
+        ("asset", _frame([100.0, 100.0, 250.0], closes=[100.0, 250.0, 250.0])),
+        cash=100.0,
+    )
+    return {
+        "events": strategy.events,
+        "cash": cerebro.broker.getcash(),
+        "position": strategy.getposition().size,
+    }
+
+
+def _gap_reversal() -> dict[str, Any]:
+    class Strategy(bt.Strategy):
+        def __init__(self) -> None:
+            self.events: list[dict[str, Any]] = []
+
+        def next(self) -> None:
+            if len(self) == 1:
+                self.sell(size=1)
+            elif len(self) == 2:
+                self.buy(size=2)
+
+        def notify_order(self, order: Any) -> None:
+            if _terminal(order):
+                self.events.append(
+                    {
+                        "status": order.getstatusname(),
+                        "created_size": order.created.size,
+                        "executed_size": order.executed.size,
+                        "price": order.executed.price,
+                    }
+                )
+
+    cerebro, strategy = _run(
+        Strategy,
+        ("asset", _frame([100.0, 100.0, 250.0], closes=[100.0, 90.0, 250.0])),
+        cash=100.0,
+    )
+    return {
+        "events": strategy.events,
+        "cash": cerebro.broker.getcash(),
+        "position": strategy.getposition().size,
+    }
+
+
+def _signal_price_stop() -> list[dict[str, Any]]:
+    class Strategy(bt.Strategy):
+        def __init__(self) -> None:
+            self.events: list[dict[str, Any]] = []
+
+        def next(self) -> None:
+            if len(self) == 1:
+                self.buy(size=1)
+                self.sell(size=1, exectype=bt.Order.Stop, price=self.data.close[0] * 0.9)
+
+        def notify_order(self, order: Any) -> None:
+            if order.status == order.Completed:
+                self.events.append(
+                    {
+                        "created_price": order.created.price,
+                        "executed_price": order.executed.price,
+                        "size": order.executed.size,
+                    }
+                )
+
+    _, strategy = _run(
+        Strategy,
+        (
+            "asset",
+            _frame(
+                [100.0, 110.0, 95.0],
+                closes=[100.0, 100.0, 95.0],
+                highs=[101.0, 111.0, 96.0],
+                lows=[99.0, 85.0, 94.0],
+            ),
+        ),
+    )
+    return strategy.events
+
+
+def _trailing_stop() -> list[dict[str, Any]]:
+    class Strategy(bt.Strategy):
+        def __init__(self) -> None:
+            self.events: list[dict[str, Any]] = []
+
+        def next(self) -> None:
+            if len(self) == 1:
+                self.buy(size=1)
+                self.sell(size=1, exectype=bt.Order.StopTrail, trailpercent=0.1)
+
+        def notify_order(self, order: Any) -> None:
+            if order.status == order.Completed:
+                self.events.append(
+                    {
+                        "date": bt.num2date(order.executed.dt).date().isoformat(),
+                        "executed_price": order.executed.price,
+                        "size": order.executed.size,
+                    }
+                )
+
+    _, strategy = _run(
+        Strategy,
+        (
+            "asset",
+            _frame(
+                [100.0, 110.0, 95.0, 100.0],
+                closes=[100.0, 95.0, 90.0, 100.0],
+                highs=[101.0, 111.0, 96.0, 101.0],
+                lows=[99.0, 94.0, 85.0, 99.0],
+            ),
+        ),
+    )
+    return strategy.events
+
+
+def _short_cash(short_cash: bool) -> dict[str, Any]:
+    class Strategy(bt.Strategy):
+        def __init__(self) -> None:
+            self.event: dict[str, Any] = {}
+
+        def next(self) -> None:
+            if len(self) == 1:
+                self.sell(size=1)
+
+        def notify_order(self, order: Any) -> None:
+            if order.status == order.Completed:
+                self.event = {
+                    "cash": self.broker.getcash(),
+                    "position": self.position.size,
+                    "price": order.executed.price,
+                }
+
+    def configure(broker: Any) -> None:
+        broker.set_shortcash(short_cash)
+
+    _, strategy = _run(
+        Strategy,
+        ("asset", _frame([100.0, 100.0, 100.0])),
+        configure=configure,
+    )
+    return strategy.event
+
+
+def _missing_and_late_bars() -> list[dict[str, Any]]:
+    class Strategy(bt.Strategy):
+        def __init__(self) -> None:
+            self.events: list[dict[str, Any]] = []
+
+        def prenext(self) -> None:
+            self._record("prenext")
+
+        def nextstart(self) -> None:
+            self._record("nextstart")
+
+        def next(self) -> None:
+            self._record("next")
+
+        def _record(self, callback: str) -> None:
+            self.events.append(
+                {
+                    "callback": callback,
+                    "date": self.datetime.date().isoformat(),
+                    "lengths": [len(data) for data in self.datas],
+                    "values": [float(data.close[0]) if len(data) else None for data in self.datas],
+                }
+            )
+
+    _, strategy = _run(
+        Strategy,
+        (
+            "a",
+            _frame(
+                [100.0, 120.0],
+                dates=["2024-01-01", "2024-01-03"],
+            ),
+        ),
+        (
+            "b",
+            _frame(
+                [200.0, 210.0, 220.0],
+                dates=["2024-01-01", "2024-01-02", "2024-01-03"],
+            ),
+        ),
+    )
+    return strategy.events
+
+
+def _late_start() -> list[dict[str, Any]]:
+    class Strategy(bt.Strategy):
+        def __init__(self) -> None:
+            self.events: list[dict[str, Any]] = []
+
+        def prenext(self) -> None:
+            self._record("prenext")
+
+        def nextstart(self) -> None:
+            self._record("nextstart")
+
+        def next(self) -> None:
+            self._record("next")
+
+        def _record(self, callback: str) -> None:
+            self.events.append(
+                {
+                    "callback": callback,
+                    "date": self.datetime.date().isoformat(),
+                    "lengths": [len(data) for data in self.datas],
+                }
+            )
+
+    _, strategy = _run(
+        Strategy,
+        ("a", _frame([100.0, 100.0, 100.0])),
+        (
+            "b",
+            _frame([100.0, 100.0], dates=["2024-01-02", "2024-01-03"]),
+        ),
+    )
+    return strategy.events
+
+
+def _final_bar_order() -> list[dict[str, Any]]:
+    class Strategy(bt.Strategy):
+        def __init__(self) -> None:
+            self.events: list[dict[str, Any]] = []
+
+        def next(self) -> None:
+            if len(self) == 2:
+                self.buy(size=1)
+
+        def notify_order(self, order: Any) -> None:
+            if order.status == order.Completed:
+                self.events.append({"price": order.executed.price})
+
+    _, strategy = _run(Strategy, ("asset", _frame([100.0, 110.0])))
+    return strategy.events
+
+
+def _trade_record() -> list[dict[str, Any]]:
+    class Strategy(bt.Strategy):
+        def __init__(self) -> None:
+            self.events: list[dict[str, Any]] = []
+
+        def next(self) -> None:
+            if len(self) == 1:
+                self.buy(size=2)
+            elif len(self) == 2:
+                self.close()
+
+        def notify_trade(self, trade: Any) -> None:
+            if trade.isclosed:
+                self.events.append(
+                    {
+                        "commission": trade.commission,
+                        "entry_price": trade.price,
+                        "is_long": trade.long,
+                        "pnl": trade.pnl,
+                        "pnl_after_commission": trade.pnlcomm,
+                    }
+                )
+
+    def configure(broker: Any) -> None:
+        broker.setcommission(commission=0.01)
+
+    _, strategy = _run(
+        Strategy,
+        ("asset", _frame([100.0, 110.0, 120.0, 130.0])),
+        configure=configure,
+    )
+    return strategy.events
+
+
+def _source_location(function: Any) -> dict[str, Any]:
+    source_file = inspect.getsourcefile(function)
+    if source_file is None:
+        raise RuntimeError(f"Could not locate source for {function}")
+    package_root = Path(bt.__file__).resolve().parent.parent
+    relative_path = Path(source_file).resolve().relative_to(package_root).as_posix()
+    return {
+        "artifact": ARTIFACT,
+        "artifact_sha256": ARTIFACT_SHA256,
+        "line": inspect.getsourcelines(function)[1],
+        "module": function.__module__,
+        "path": relative_path,
+        "qualname": function.__qualname__,
+        "source": SOURCE,
+    }
+
+
+def _equal(actual: Any, expected: Any) -> bool:
+    if isinstance(actual, float) and isinstance(expected, (float, int)):
+        return math.isclose(actual, float(expected), rel_tol=0.0, abs_tol=1e-12)
+    if isinstance(actual, list) and isinstance(expected, list) and len(actual) == len(expected):
+        return all(_equal(left, right) for left, right in zip(actual, expected, strict=True))
+    if isinstance(actual, dict) and isinstance(expected, dict) and actual.keys() == expected.keys():
+        return all(_equal(actual[key], expected[key]) for key in actual)
+    return bool(actual == expected)
+
+
+def run() -> dict[str, Any]:
+    """Execute Backtrader directly and return framework-native evidence."""
+    actual_version = importlib.metadata.version("backtrader")
+    if actual_version != VERSION:
+        raise RuntimeError(f"backtrader version differs: {actual_version} != {VERSION}")
+
+    measurements = [
+        (
+            "defaults",
+            _defaults(),
+            {
+                "cash": 10_000.0,
+                "checksubmit": True,
+                "cheat_on_close": False,
+                "cheat_on_open": False,
+                "commission": 0.0,
+                "leverage": 1.0,
+                "short_cash": True,
+                "slippage_fixed": 0.0,
+                "slippage_percent": 0.0,
+            },
+        ),
+        (
+            "next_bar_open_and_gap",
+            _timing(),
+            [{"date": "2024-01-02", "price": 110.0, "size": 1}],
+        ),
+        (
+            "cheat_on_close",
+            _timing(coc=True),
+            [{"date": "2024-01-01", "price": 100.0, "size": 1}],
+        ),
+        (
+            "integer_target_percent",
+            _target_percent(0.5),
+            [
+                {
+                    "status": "Completed",
+                    "created_size": 5,
+                    "executed_size": 5,
+                    "price": 100.0,
+                    "commission": 0.0,
+                }
+            ],
+        ),
+        (
+            "commission_headroom",
+            {"full": _target_percent(1.0, 0.001), "headroom": _target_percent(0.998, 0.001)},
+            {
+                "full": [
+                    {
+                        "status": "Margin",
+                        "created_size": 10,
+                        "executed_size": 0,
+                        "price": 0.0,
+                        "commission": 0.0,
+                    }
+                ],
+                "headroom": [
+                    {
+                        "status": "Completed",
+                        "created_size": 9,
+                        "executed_size": 9,
+                        "price": 100.0,
+                        "commission": 0.9000000000000001,
+                    }
+                ],
+            },
+        ),
+        (
+            "cash_rejection_and_configured_leverage",
+            {"default": _cash_and_margin(1.0), "leverage_2": _cash_and_margin(2.0)},
+            {
+                "default": [{"status": "Margin", "size": 0}],
+                "leverage_2": [{"status": "Completed", "size": 20}],
+            },
+        ),
+        (
+            "submission_sequence",
+            {"forward": _submission_sequence(False), "reverse": _submission_sequence(True)},
+            {
+                "forward": [
+                    {"asset": "a", "created_size": 6, "status": "Completed"},
+                    {"asset": "b", "created_size": 6, "status": "Margin"},
+                ],
+                "reverse": [
+                    {"asset": "b", "created_size": 6, "status": "Completed"},
+                    {"asset": "a", "created_size": 6, "status": "Margin"},
+                ],
+            },
+        ),
+        (
+            "losing_short_cover_submission_rejection",
+            _losing_short_cover(),
+            {
+                "events": [
+                    {"status": "Completed", "size": -1, "price": 100.0},
+                    {"status": "Margin", "size": 0, "price": 0.0},
+                ],
+                "cash": 200.0,
+                "position": -1,
+            },
+        ),
+        (
+            "gap_reversal_executes_close_leg_despite_margin",
+            _gap_reversal(),
+            {
+                "events": [
+                    {
+                        "status": "Completed",
+                        "created_size": -1,
+                        "executed_size": -1,
+                        "price": 100.0,
+                    },
+                    {
+                        "status": "Margin",
+                        "created_size": 2,
+                        "executed_size": 1,
+                        "price": 250.0,
+                    },
+                ],
+                "cash": -50.0,
+                "position": 0,
+            },
+        ),
+        (
+            "signal_price_stop_basis",
+            _signal_price_stop(),
+            [
+                {"created_price": 100.0, "executed_price": 110.0, "size": 1},
+                {"created_price": 90.0, "executed_price": 90.0, "size": -1},
+            ],
+        ),
+        (
+            "trailing_stop_signal_close_and_lagged",
+            _trailing_stop(),
+            [
+                {"date": "2024-01-02", "executed_price": 110.0, "size": 1},
+                {"date": "2024-01-03", "executed_price": 90.0, "size": -1},
+            ],
+        ),
+        (
+            "short_cash",
+            {"credit": _short_cash(True), "debit": _short_cash(False)},
+            {
+                "credit": {"cash": 1_100.0, "position": -1, "price": 100.0},
+                "debit": {"cash": 900.0, "position": -1, "price": 100.0},
+            },
+        ),
+        (
+            "missing_bar_uses_last_value",
+            _missing_and_late_bars(),
+            [
+                {
+                    "callback": "nextstart",
+                    "date": "2024-01-01",
+                    "lengths": [1, 1],
+                    "values": [100.0, 200.0],
+                },
+                {
+                    "callback": "nextstart",
+                    "date": "2024-01-02",
+                    "lengths": [1, 2],
+                    "values": [100.0, 210.0],
+                },
+                {
+                    "callback": "next",
+                    "date": "2024-01-03",
+                    "lengths": [2, 3],
+                    "values": [120.0, 220.0],
+                },
+            ],
+        ),
+        (
+            "late_feed_start",
+            _late_start(),
+            [
+                {"callback": "prenext", "date": "2024-01-01", "lengths": [1, 0]},
+                {"callback": "nextstart", "date": "2024-01-02", "lengths": [2, 1]},
+                {"callback": "next", "date": "2024-01-03", "lengths": [3, 2]},
+            ],
+        ),
+        ("final_bar_market_order", _final_bar_order(), []),
+        (
+            "trade_record",
+            _trade_record(),
+            [
+                {
+                    "commission": 4.6,
+                    "entry_price": 110.0,
+                    "is_long": True,
+                    "pnl": 20.0,
+                    "pnl_after_commission": 15.4,
+                }
+            ],
+        ),
+    ]
+    checks = [
+        {"id": check_id, "actual": actual, "expected": expected, "passed": _equal(actual, expected)}
+        for check_id, actual, expected in measurements
+    ]
+    return {
+        "schema_version": 1,
+        "framework": "backtrader",
+        "package": "backtrader",
+        "version": actual_version,
+        "artifact": ARTIFACT,
+        "artifact_sha256": ARTIFACT_SHA256,
+        "oracle_sha256": hashlib.sha256(Path(__file__).read_bytes()).hexdigest(),
+        "source_locations": {
+            "broker_next": _source_location(bt.brokers.BackBroker.next),
+            "order_execute": _source_location(bt.Order.execute),
+            "target_percent": _source_location(bt.Strategy.order_target_percent),
+            "target_size": _source_location(bt.CommInfoBase.getsize),
+        },
+        "checks": checks,
+        "passed": all(check["passed"] for check in checks),
+    }
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--output", type=Path, required=True)
+    args = parser.parse_args()
+    try:
+        evidence = run()
+    except (ImportError, OSError, RuntimeError, ValueError) as error:
+        print(f"Backtrader native behavior run failed: {error}", file=sys.stderr)
+        return 2
+    args.output.parent.mkdir(parents=True, exist_ok=True)
+    args.output.write_text(json.dumps(evidence, indent=2, sort_keys=True) + "\n", encoding="utf-8")
+    failed = [check["id"] for check in evidence["checks"] if not check["passed"]]
+    if failed:
+        print(f"Backtrader native behavior differs: {failed}", file=sys.stderr)
+        return 1
+    print(f"Backtrader native behavior passed: {len(evidence['checks'])} checks")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/native/evidence/backtrader-1.9.78.123.json b/validation/native/evidence/backtrader-1.9.78.123.json
new file mode 100644
index 00000000..fc28d7a1
--- /dev/null
+++ b/validation/native/evidence/backtrader-1.9.78.123.json
@@ -0,0 +1,590 @@
+{
+  "artifact": "backtrader-1.9.78.123-py2.py3-none-any.whl",
+  "artifact_sha256": "9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+  "checks": [
+    {
+      "actual": {
+        "cash": 10000.0,
+        "cheat_on_close": false,
+        "cheat_on_open": false,
+        "checksubmit": true,
+        "commission": 0.0,
+        "leverage": 1.0,
+        "short_cash": true,
+        "slippage_fixed": 0.0,
+        "slippage_percent": 0.0
+      },
+      "expected": {
+        "cash": 10000.0,
+        "cheat_on_close": false,
+        "cheat_on_open": false,
+        "checksubmit": true,
+        "commission": 0.0,
+        "leverage": 1.0,
+        "short_cash": true,
+        "slippage_fixed": 0.0,
+        "slippage_percent": 0.0
+      },
+      "id": "defaults",
+      "passed": true
+    },
+    {
+      "actual": [
+        {
+          "date": "2024-01-02",
+          "price": 110.0,
+          "size": 1
+        }
+      ],
+      "expected": [
+        {
+          "date": "2024-01-02",
+          "price": 110.0,
+          "size": 1
+        }
+      ],
+      "id": "next_bar_open_and_gap",
+      "passed": true
+    },
+    {
+      "actual": [
+        {
+          "date": "2024-01-01",
+          "price": 100.0,
+          "size": 1
+        }
+      ],
+      "expected": [
+        {
+          "date": "2024-01-01",
+          "price": 100.0,
+          "size": 1
+        }
+      ],
+      "id": "cheat_on_close",
+      "passed": true
+    },
+    {
+      "actual": [
+        {
+          "commission": 0.0,
+          "created_size": 5,
+          "executed_size": 5,
+          "price": 100.0,
+          "status": "Completed"
+        }
+      ],
+      "expected": [
+        {
+          "commission": 0.0,
+          "created_size": 5,
+          "executed_size": 5,
+          "price": 100.0,
+          "status": "Completed"
+        }
+      ],
+      "id": "integer_target_percent",
+      "passed": true
+    },
+    {
+      "actual": {
+        "full": [
+          {
+            "commission": 0.0,
+            "created_size": 10,
+            "executed_size": 0,
+            "price": 0.0,
+            "status": "Margin"
+          }
+        ],
+        "headroom": [
+          {
+            "commission": 0.9000000000000001,
+            "created_size": 9,
+            "executed_size": 9,
+            "price": 100.0,
+            "status": "Completed"
+          }
+        ]
+      },
+      "expected": {
+        "full": [
+          {
+            "commission": 0.0,
+            "created_size": 10,
+            "executed_size": 0,
+            "price": 0.0,
+            "status": "Margin"
+          }
+        ],
+        "headroom": [
+          {
+            "commission": 0.9000000000000001,
+            "created_size": 9,
+            "executed_size": 9,
+            "price": 100.0,
+            "status": "Completed"
+          }
+        ]
+      },
+      "id": "commission_headroom",
+      "passed": true
+    },
+    {
+      "actual": {
+        "default": [
+          {
+            "size": 0,
+            "status": "Margin"
+          }
+        ],
+        "leverage_2": [
+          {
+            "size": 20,
+            "status": "Completed"
+          }
+        ]
+      },
+      "expected": {
+        "default": [
+          {
+            "size": 0,
+            "status": "Margin"
+          }
+        ],
+        "leverage_2": [
+          {
+            "size": 20,
+            "status": "Completed"
+          }
+        ]
+      },
+      "id": "cash_rejection_and_configured_leverage",
+      "passed": true
+    },
+    {
+      "actual": {
+        "forward": [
+          {
+            "asset": "a",
+            "created_size": 6,
+            "status": "Completed"
+          },
+          {
+            "asset": "b",
+            "created_size": 6,
+            "status": "Margin"
+          }
+        ],
+        "reverse": [
+          {
+            "asset": "b",
+            "created_size": 6,
+            "status": "Completed"
+          },
+          {
+            "asset": "a",
+            "created_size": 6,
+            "status": "Margin"
+          }
+        ]
+      },
+      "expected": {
+        "forward": [
+          {
+            "asset": "a",
+            "created_size": 6,
+            "status": "Completed"
+          },
+          {
+            "asset": "b",
+            "created_size": 6,
+            "status": "Margin"
+          }
+        ],
+        "reverse": [
+          {
+            "asset": "b",
+            "created_size": 6,
+            "status": "Completed"
+          },
+          {
+            "asset": "a",
+            "created_size": 6,
+            "status": "Margin"
+          }
+        ]
+      },
+      "id": "submission_sequence",
+      "passed": true
+    },
+    {
+      "actual": {
+        "cash": 200.0,
+        "events": [
+          {
+            "price": 100.0,
+            "size": -1,
+            "status": "Completed"
+          },
+          {
+            "price": 0.0,
+            "size": 0,
+            "status": "Margin"
+          }
+        ],
+        "position": -1
+      },
+      "expected": {
+        "cash": 200.0,
+        "events": [
+          {
+            "price": 100.0,
+            "size": -1,
+            "status": "Completed"
+          },
+          {
+            "price": 0.0,
+            "size": 0,
+            "status": "Margin"
+          }
+        ],
+        "position": -1
+      },
+      "id": "losing_short_cover_submission_rejection",
+      "passed": true
+    },
+    {
+      "actual": {
+        "cash": -50.0,
+        "events": [
+          {
+            "created_size": -1,
+            "executed_size": -1,
+            "price": 100.0,
+            "status": "Completed"
+          },
+          {
+            "created_size": 2,
+            "executed_size": 1,
+            "price": 250.0,
+            "status": "Margin"
+          }
+        ],
+        "position": 0
+      },
+      "expected": {
+        "cash": -50.0,
+        "events": [
+          {
+            "created_size": -1,
+            "executed_size": -1,
+            "price": 100.0,
+            "status": "Completed"
+          },
+          {
+            "created_size": 2,
+            "executed_size": 1,
+            "price": 250.0,
+            "status": "Margin"
+          }
+        ],
+        "position": 0
+      },
+      "id": "gap_reversal_executes_close_leg_despite_margin",
+      "passed": true
+    },
+    {
+      "actual": [
+        {
+          "created_price": 100.0,
+          "executed_price": 110.0,
+          "size": 1
+        },
+        {
+          "created_price": 90.0,
+          "executed_price": 90.0,
+          "size": -1
+        }
+      ],
+      "expected": [
+        {
+          "created_price": 100.0,
+          "executed_price": 110.0,
+          "size": 1
+        },
+        {
+          "created_price": 90.0,
+          "executed_price": 90.0,
+          "size": -1
+        }
+      ],
+      "id": "signal_price_stop_basis",
+      "passed": true
+    },
+    {
+      "actual": [
+        {
+          "date": "2024-01-02",
+          "executed_price": 110.0,
+          "size": 1
+        },
+        {
+          "date": "2024-01-03",
+          "executed_price": 90.0,
+          "size": -1
+        }
+      ],
+      "expected": [
+        {
+          "date": "2024-01-02",
+          "executed_price": 110.0,
+          "size": 1
+        },
+        {
+          "date": "2024-01-03",
+          "executed_price": 90.0,
+          "size": -1
+        }
+      ],
+      "id": "trailing_stop_signal_close_and_lagged",
+      "passed": true
+    },
+    {
+      "actual": {
+        "credit": {
+          "cash": 1100.0,
+          "position": -1,
+          "price": 100.0
+        },
+        "debit": {
+          "cash": 900.0,
+          "position": -1,
+          "price": 100.0
+        }
+      },
+      "expected": {
+        "credit": {
+          "cash": 1100.0,
+          "position": -1,
+          "price": 100.0
+        },
+        "debit": {
+          "cash": 900.0,
+          "position": -1,
+          "price": 100.0
+        }
+      },
+      "id": "short_cash",
+      "passed": true
+    },
+    {
+      "actual": [
+        {
+          "callback": "nextstart",
+          "date": "2024-01-01",
+          "lengths": [
+            1,
+            1
+          ],
+          "values": [
+            100.0,
+            200.0
+          ]
+        },
+        {
+          "callback": "nextstart",
+          "date": "2024-01-02",
+          "lengths": [
+            1,
+            2
+          ],
+          "values": [
+            100.0,
+            210.0
+          ]
+        },
+        {
+          "callback": "next",
+          "date": "2024-01-03",
+          "lengths": [
+            2,
+            3
+          ],
+          "values": [
+            120.0,
+            220.0
+          ]
+        }
+      ],
+      "expected": [
+        {
+          "callback": "nextstart",
+          "date": "2024-01-01",
+          "lengths": [
+            1,
+            1
+          ],
+          "values": [
+            100.0,
+            200.0
+          ]
+        },
+        {
+          "callback": "nextstart",
+          "date": "2024-01-02",
+          "lengths": [
+            1,
+            2
+          ],
+          "values": [
+            100.0,
+            210.0
+          ]
+        },
+        {
+          "callback": "next",
+          "date": "2024-01-03",
+          "lengths": [
+            2,
+            3
+          ],
+          "values": [
+            120.0,
+            220.0
+          ]
+        }
+      ],
+      "id": "missing_bar_uses_last_value",
+      "passed": true
+    },
+    {
+      "actual": [
+        {
+          "callback": "prenext",
+          "date": "2024-01-01",
+          "lengths": [
+            1,
+            0
+          ]
+        },
+        {
+          "callback": "nextstart",
+          "date": "2024-01-02",
+          "lengths": [
+            2,
+            1
+          ]
+        },
+        {
+          "callback": "next",
+          "date": "2024-01-03",
+          "lengths": [
+            3,
+            2
+          ]
+        }
+      ],
+      "expected": [
+        {
+          "callback": "prenext",
+          "date": "2024-01-01",
+          "lengths": [
+            1,
+            0
+          ]
+        },
+        {
+          "callback": "nextstart",
+          "date": "2024-01-02",
+          "lengths": [
+            2,
+            1
+          ]
+        },
+        {
+          "callback": "next",
+          "date": "2024-01-03",
+          "lengths": [
+            3,
+            2
+          ]
+        }
+      ],
+      "id": "late_feed_start",
+      "passed": true
+    },
+    {
+      "actual": [],
+      "expected": [],
+      "id": "final_bar_market_order",
+      "passed": true
+    },
+    {
+      "actual": [
+        {
+          "commission": 4.6,
+          "entry_price": 110.0,
+          "is_long": true,
+          "pnl": 20.0,
+          "pnl_after_commission": 15.4
+        }
+      ],
+      "expected": [
+        {
+          "commission": 4.6,
+          "entry_price": 110.0,
+          "is_long": true,
+          "pnl": 20.0,
+          "pnl_after_commission": 15.4
+        }
+      ],
+      "id": "trade_record",
+      "passed": true
+    }
+  ],
+  "framework": "backtrader",
+  "oracle_sha256": "f516fb0bfb3b2cbebc076b092ce86f12cca502aec81735f240063512edbbf8df",
+  "package": "backtrader",
+  "passed": true,
+  "schema_version": 1,
+  "source_locations": {
+    "broker_next": {
+      "artifact": "backtrader-1.9.78.123-py2.py3-none-any.whl",
+      "artifact_sha256": "9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+      "line": 1176,
+      "module": "backtrader.brokers.bbroker",
+      "path": "backtrader/brokers/bbroker.py",
+      "qualname": "BackBroker.next",
+      "source": "https://pypi.org/project/backtrader/1.9.78.123/"
+    },
+    "order_execute": {
+      "artifact": "backtrader-1.9.78.123-py2.py3-none-any.whl",
+      "artifact_sha256": "9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+      "line": 566,
+      "module": "backtrader.order",
+      "path": "backtrader/order.py",
+      "qualname": "Order.execute",
+      "source": "https://pypi.org/project/backtrader/1.9.78.123/"
+    },
+    "target_percent": {
+      "artifact": "backtrader-1.9.78.123-py2.py3-none-any.whl",
+      "artifact_sha256": "9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+      "line": 1330,
+      "module": "backtrader.strategy",
+      "path": "backtrader/strategy.py",
+      "qualname": "Strategy.order_target_percent",
+      "source": "https://pypi.org/project/backtrader/1.9.78.123/"
+    },
+    "target_size": {
+      "artifact": "backtrader-1.9.78.123-py2.py3-none-any.whl",
+      "artifact_sha256": "9a07a516b0de9155539a35c56e9404d8711dd7020b3d37b30495e83e1b9d5dfd",
+      "line": 192,
+      "module": "backtrader.comminfo",
+      "path": "backtrader/comminfo.py",
+      "qualname": "CommInfoBase.getsize",
+      "source": "https://pypi.org/project/backtrader/1.9.78.123/"
+    }
+  },
+  "version": "1.9.78.123"
+}
diff --git a/validation/native/evidence/lean-18001.json b/validation/native/evidence/lean-18001.json
new file mode 100644
index 00000000..ee4640e7
--- /dev/null
+++ b/validation/native/evidence/lean-18001.json
@@ -0,0 +1,2276 @@
+{
+  "checks": [
+    {
+      "actual": {
+        "case": "timing",
+        "cash": 9889.0,
+        "events": [
+          {
+            "direction": "BUY",
+            "event_time_utc": "2024-01-02 21:00:00",
+            "fee": 0.0,
+            "fill_price": 0.0,
+            "fill_quantity": 0.0,
+            "message": "",
+            "order_id": 1,
+            "status": "SUBMITTED",
+            "time": "2024-01-02 16:00:00"
+          },
+          {
+            "direction": "BUY",
+            "event_time_utc": "2024-01-03 21:00:00",
+            "fee": 1.0,
+            "fill_price": 110.0,
+            "fill_quantity": 1.0,
+            "message": "",
+            "order_id": 1,
+            "status": "FILLED",
+            "time": "2024-01-03 16:00:00"
+          }
+        ],
+        "models": {
+          "brokerage": "DefaultBrokerageModel",
+          "buying_power": "SecurityMarginModel",
+          "fee": "InteractiveBrokersFeeModel",
+          "fill": "EquityFillModel",
+          "leverage": 2.0,
+          "slippage": "NullSlippageModel"
+        },
+        "observations": [
+          {
+            "close": 101.0,
+            "date": "2024-01-02",
+            "fill_forward": false,
+            "open": 100.0,
+            "volume": 100.0
+          },
+          {
+            "close": 111.0,
+            "date": "2024-01-03",
+            "fill_forward": false,
+            "open": 110.0,
+            "volume": 100.0
+          },
+          {
+            "close": 121.0,
+            "date": "2024-01-04",
+            "fill_forward": false,
+            "open": 120.0,
+            "volume": 100.0
+          },
+          {
+            "close": 131.0,
+            "date": "2024-01-05",
+            "fill_forward": false,
+            "open": 130.0,
+            "volume": 100.0
+          },
+          {
+            "close": 141.0,
+            "date": "2024-01-08",
+            "fill_forward": false,
+            "open": 140.0,
+            "volume": 100.0
+          },
+          {
+            "close": 151.0,
+            "date": "2024-01-09",
+            "fill_forward": false,
+            "open": 150.0,
+            "volume": 100.0
+          },
+          {
+            "close": 161.0,
+            "date": "2024-01-10",
+            "fill_forward": false,
+            "open": 160.0,
+            "volume": 100.0
+          },
+          {
+            "close": 171.0,
+            "date": "2024-01-11",
+            "fill_forward": false,
+            "open": 170.0,
+            "volume": 100.0
+          }
+        ],
+        "position": 1.0,
+        "submitted": [
+          {
+            "order_id": 1,
+            "quantity": 1.0,
+            "status": "SUBMITTED"
+          }
+        ],
+        "target_quantity": null,
+        "total_fees": 1.0,
+        "total_portfolio_value": 10060.0
+      },
+      "contract_actual": {
+        "events": [
+          [
+            "SUBMITTED",
+            "BUY",
+            0.0,
+            0.0,
+            0.0,
+            "2024-01-02 21:00:00"
+          ],
+          [
+            "FILLED",
+            "BUY",
+            1.0,
+            110.0,
+            1.0,
+            "2024-01-03 21:00:00"
+          ]
+        ],
+        "final": {
+          "cash": 9889.0,
+          "position": 1.0,
+          "total_fees": 1.0,
+          "total_portfolio_value": 10060.0
+        }
+      },
+      "expected": {
+        "events": [
+          [
+            "SUBMITTED",
+            "BUY",
+            0.0,
+            0.0,
+            0.0,
+            "2024-01-02 21:00:00"
+          ],
+          [
+            "FILLED",
+            "BUY",
+            1.0,
+            110.0,
+            1.0,
+            "2024-01-03 21:00:00"
+          ]
+        ],
+        "final": {
+          "cash": 9889.0,
+          "position": 1.0,
+          "total_fees": 1.0,
+          "total_portfolio_value": 10060.0
+        }
+      },
+      "id": "timing",
+      "passed": true
+    },
+    {
+      "actual": {
+        "case": "default_models",
+        "cash": 9889.0,
+        "events": [
+          {
+            "direction": "BUY",
+            "event_time_utc": "2024-01-02 21:00:00",
+            "fee": 0.0,
+            "fill_price": 0.0,
+            "fill_quantity": 0.0,
+            "message": "",
+            "order_id": 1,
+            "status": "SUBMITTED",
+            "time": "2024-01-02 16:00:00"
+          },
+          {
+            "direction": "BUY",
+            "event_time_utc": "2024-01-03 21:00:00",
+            "fee": 1.0,
+            "fill_price": 110.0,
+            "fill_quantity": 1.0,
+            "message": "",
+            "order_id": 1,
+            "status": "FILLED",
+            "time": "2024-01-03 16:00:00"
+          }
+        ],
+        "models": {
+          "brokerage": "DefaultBrokerageModel",
+          "buying_power": "SecurityMarginModel",
+          "fee": "InteractiveBrokersFeeModel",
+          "fill": "EquityFillModel",
+          "leverage": 2.0,
+          "slippage": "NullSlippageModel"
+        },
+        "observations": [
+          {
+            "close": 101.0,
+            "date": "2024-01-02",
+            "fill_forward": false,
+            "open": 100.0,
+            "volume": 100.0
+          },
+          {
+            "close": 111.0,
+            "date": "2024-01-03",
+            "fill_forward": false,
+            "open": 110.0,
+            "volume": 100.0
+          },
+          {
+            "close": 121.0,
+            "date": "2024-01-04",
+            "fill_forward": false,
+            "open": 120.0,
+            "volume": 100.0
+          },
+          {
+            "close": 131.0,
+            "date": "2024-01-05",
+            "fill_forward": false,
+            "open": 130.0,
+            "volume": 100.0
+          },
+          {
+            "close": 141.0,
+            "date": "2024-01-08",
+            "fill_forward": false,
+            "open": 140.0,
+            "volume": 100.0
+          },
+          {
+            "close": 151.0,
+            "date": "2024-01-09",
+            "fill_forward": false,
+            "open": 150.0,
+            "volume": 100.0
+          },
+          {
+            "close": 161.0,
+            "date": "2024-01-10",
+            "fill_forward": false,
+            "open": 160.0,
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+          "buying_power": "SecurityMarginModel",
+          "fee": "InteractiveBrokersFeeModel",
+          "fill": "EquityFillModel",
+          "leverage": 2.0,
+          "slippage": "NullSlippageModel"
+        },
+        "observations": [
+          {
+            "close": 101.0,
+            "date": "2024-01-02",
+            "fill_forward": false,
+            "open": 100.0,
+            "volume": 100.0
+          },
+          {
+            "close": 111.0,
+            "date": "2024-01-03",
+            "fill_forward": false,
+            "open": 110.0,
+            "volume": 100.0
+          },
+          {
+            "close": 121.0,
+            "date": "2024-01-04",
+            "fill_forward": false,
+            "open": 120.0,
+            "volume": 100.0
+          },
+          {
+            "close": 131.0,
+            "date": "2024-01-05",
+            "fill_forward": false,
+            "open": 130.0,
+            "volume": 100.0
+          },
+          {
+            "close": 141.0,
+            "date": "2024-01-08",
+            "fill_forward": false,
+            "open": 140.0,
+            "volume": 100.0
+          },
+          {
+            "close": 151.0,
+            "date": "2024-01-09",
+            "fill_forward": false,
+            "open": 150.0,
+            "volume": 100.0
+          },
+          {
+            "close": 161.0,
+            "date": "2024-01-10",
+            "fill_forward": false,
+            "open": 160.0,
+            "volume": 100.0
+          },
+          {
+            "close": 171.0,
+            "date": "2024-01-11",
+            "fill_forward": false,
+            "open": 170.0,
+            "volume": 100.0
+          }
+        ],
+        "position": 0.0,
+        "submitted": [
+          {
+            "order_id": 1,
+            "quantity": 1.0,
+            "status": "SUBMITTED"
+          }
+        ],
+        "target_quantity": null,
+        "total_fees": 0.0,
+        "total_portfolio_value": 10000.0
+      },
+      "contract_actual": {
+        "events": [
+          [
+            "SUBMITTED",
+            "BUY",
+            0.0,
+            0.0,
+            0.0,
+            "2024-01-11 21:00:00"
+          ]
+        ],
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+          "position": 0.0,
+          "total_fees": 0.0,
+          "total_portfolio_value": 10000.0
+        }
+      },
+      "expected": {
+        "events": [
+          [
+            "SUBMITTED",
+            "BUY",
+            0.0,
+            0.0,
+            0.0,
+            "2024-01-11 21:00:00"
+          ]
+        ],
+        "final": {
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+          "position": 0.0,
+          "total_fees": 0.0,
+          "total_portfolio_value": 10000.0
+        }
+      },
+      "id": "final_bar_order",
+      "passed": true
+    },
+    {
+      "actual": {
+        "case": "liquidation",
+        "cash": 10058.0,
+        "events": [
+          {
+            "direction": "BUY",
+            "event_time_utc": "2024-01-02 21:00:00",
+            "fee": 0.0,
+            "fill_price": 0.0,
+            "fill_quantity": 0.0,
+            "message": "",
+            "order_id": 1,
+            "status": "SUBMITTED",
+            "time": "2024-01-02 16:00:00"
+          },
+          {
+            "direction": "BUY",
+            "event_time_utc": "2024-01-03 21:00:00",
+            "fee": 1.0,
+            "fill_price": 110.0,
+            "fill_quantity": 1.0,
+            "message": "",
+            "order_id": 1,
+            "status": "FILLED",
+            "time": "2024-01-03 16:00:00"
+          },
+          {
+            "direction": "SELL",
+            "event_time_utc": "2024-01-10 21:00:00",
+            "fee": 0.0,
+            "fill_price": 0.0,
+            "fill_quantity": 0.0,
+            "message": "",
+            "order_id": 2,
+            "status": "SUBMITTED",
+            "time": "2024-01-10 16:00:00"
+          },
+          {
+            "direction": "SELL",
+            "event_time_utc": "2024-01-11 21:00:00",
+            "fee": 1.0,
+            "fill_price": 170.0,
+            "fill_quantity": -1.0,
+            "message": "",
+            "order_id": 2,
+            "status": "FILLED",
+            "time": "2024-01-11 16:00:00"
+          }
+        ],
+        "models": {
+          "brokerage": "DefaultBrokerageModel",
+          "buying_power": "SecurityMarginModel",
+          "fee": "InteractiveBrokersFeeModel",
+          "fill": "EquityFillModel",
+          "leverage": 2.0,
+          "slippage": "NullSlippageModel"
+        },
+        "observations": [
+          {
+            "close": 101.0,
+            "date": "2024-01-02",
+            "fill_forward": false,
+            "open": 100.0,
+            "volume": 100.0
+          },
+          {
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+            "date": "2024-01-03",
+            "fill_forward": false,
+            "open": 110.0,
+            "volume": 100.0
+          },
+          {
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+            "date": "2024-01-04",
+            "fill_forward": false,
+            "open": 120.0,
+            "volume": 100.0
+          },
+          {
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+            "date": "2024-01-05",
+            "fill_forward": false,
+            "open": 130.0,
+            "volume": 100.0
+          },
+          {
+            "close": 141.0,
+            "date": "2024-01-08",
+            "fill_forward": false,
+            "open": 140.0,
+            "volume": 100.0
+          },
+          {
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+            "date": "2024-01-09",
+            "fill_forward": false,
+            "open": 150.0,
+            "volume": 100.0
+          },
+          {
+            "close": 161.0,
+            "date": "2024-01-10",
+            "fill_forward": false,
+            "open": 160.0,
+            "volume": 100.0
+          },
+          {
+            "close": 171.0,
+            "date": "2024-01-11",
+            "fill_forward": false,
+            "open": 170.0,
+            "volume": 100.0
+          }
+        ],
+        "position": 0.0,
+        "submitted": [
+          {
+            "order_id": 1,
+            "quantity": 1.0,
+            "status": "SUBMITTED"
+          },
+          {
+            "order_id": 2,
+            "quantity": -1.0,
+            "status": "SUBMITTED"
+          }
+        ],
+        "target_quantity": null,
+        "total_fees": 2.0,
+        "total_portfolio_value": 10058.0
+      },
+      "contract_actual": {
+        "events": [
+          [
+            "SUBMITTED",
+            "BUY",
+            0.0,
+            0.0,
+            0.0,
+            "2024-01-02 21:00:00"
+          ],
+          [
+            "FILLED",
+            "BUY",
+            1.0,
+            110.0,
+            1.0,
+            "2024-01-03 21:00:00"
+          ],
+          [
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+            "SELL",
+            0.0,
+            0.0,
+            0.0,
+            "2024-01-10 21:00:00"
+          ],
+          [
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+            "SELL",
+            -1.0,
+            170.0,
+            1.0,
+            "2024-01-11 21:00:00"
+          ]
+        ],
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+          "position": 0.0,
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+          "total_portfolio_value": 10058.0
+        }
+      },
+      "expected": {
+        "events": [
+          [
+            "SUBMITTED",
+            "BUY",
+            0.0,
+            0.0,
+            0.0,
+            "2024-01-02 21:00:00"
+          ],
+          [
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+            110.0,
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+          ],
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+            0.0,
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+            170.0,
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+          ]
+        ],
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+          "position": 0.0,
+          "total_fees": 2.0,
+          "total_portfolio_value": 10058.0
+        }
+      },
+      "id": "liquidation",
+      "passed": true
+    }
+  ],
+  "cli": {
+    "immutable_id": "sha256:eaa4c08f16295b76f005e429d9ca0d0453784dc1a40c1f5cbe5e50c02a05bd7c",
+    "package": "lean",
+    "version": "1.0.228"
+  },
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+    "format": "LEAN local equity daily zip, raw prices scaled by 10000",
+    "payload_sha256": "b3f483a7d5cb3a2de611bde72b900f8bbb08c13cae86e08d5337edfd33c252fe",
+    "sessions": [
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+      "2024-01-03",
+      "2024-01-04",
+      "2024-01-05",
+      "2024-01-08",
+      "2024-01-09",
+      "2024-01-10",
+      "2024-01-11"
+    ]
+  },
+  "engine": {
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+    "image": "quantconnect/lean@sha256:ecd62b0e418d40d1d7c0cd95e90a94e397642a21d2c8810614830c8a4e9a8f70",
+    "image_id": "sha256:1ef05df55300c30a3e75f142b62e858e26b054f75445986e7599edde3c32fc20",
+    "platform_artifact": "linux/amd64@sha256:cbe3f26b3f16c57be836b2cf913253d434f58e010c84ed038360d26b9df88307",
+    "python_version": "3.11",
+    "source_commit": "278fcb3d1b815b63ccadba68d7ae54422e34b792",
+    "target_framework": "net10.0"
+  },
+  "framework": "lean",
+  "models": {
+    "account_type": "Margin",
+    "brokerage": "DefaultBrokerageModel",
+    "security": "Equity USA, daily, adjusted normalization, leverage 2"
+  },
+  "oracle_files": {
+    "config.json": "5b7ec7bf073127d026e6086ec18771dcb700375570ba51def97739d85009351c",
+    "main.py": "04aab940df029bf37e7aa1a9d3d8ab0996fce0bb3a10fa4dd4e15ca685e83e19"
+  },
+  "oracle_sha256": "1675f062ce54f29727d2bf7d17afc5c9db4e439e9f921e270feec49cde065d66",
+  "passed": true,
+  "schema_version": 1,
+  "source_references": {
+    "algorithm_settings": "https://github.com/QuantConnect/Lean/blob/278fcb3d1b815b63ccadba68d7ae54422e34b792/Common/AlgorithmSettings.cs",
+    "brokerage": "https://github.com/QuantConnect/Lean/blob/278fcb3d1b815b63ccadba68d7ae54422e34b792/Common/Brokerages/DefaultBrokerageModel.cs",
+    "fee": "https://github.com/QuantConnect/Lean/blob/278fcb3d1b815b63ccadba68d7ae54422e34b792/Common/Orders/Fees/InteractiveBrokersFeeModel.cs",
+    "fill": "https://github.com/QuantConnect/Lean/blob/278fcb3d1b815b63ccadba68d7ae54422e34b792/Common/Orders/Fills/EquityFillModel.cs",
+    "margin": "https://github.com/QuantConnect/Lean/blob/278fcb3d1b815b63ccadba68d7ae54422e34b792/Common/Securities/SecurityMarginModel.cs",
+    "slippage": "https://github.com/QuantConnect/Lean/blob/278fcb3d1b815b63ccadba68d7ae54422e34b792/Common/Orders/Slippage/ConstantSlippageModel.cs"
+  },
+  "support_files": {
+    "data/market-hours/market-hours-database.json": "935079bc33409373f37163eddb539f09e81a1efbd0e617cbc8fdb487c76dab2b",
+    "data/symbol-properties/symbol-properties-database.csv": "56b6dc80202bca88f212c78c4d4670c2e070e6f1e7386f7436232aafe5000e93",
+    "lean.json": "fa15d6d81f560fd1665b004c338b026458fa834a7645e015d16d861dd73540f4"
+  }
+}
diff --git a/validation/native/evidence/vectorbt_oss-1.1.0.json b/validation/native/evidence/vectorbt_oss-1.1.0.json
new file mode 100644
index 00000000..b45cca60
--- /dev/null
+++ b/validation/native/evidence/vectorbt_oss-1.1.0.json
@@ -0,0 +1,372 @@
+{
+  "checks": [
+    {
+      "actual": {
+        "accumulate": false,
+        "allow_partial": true,
+        "call_seq": "default",
+        "cash_sharing": false,
+        "fees": 0.0,
+        "ffill_val_price": true,
+        "fillna_close": true,
+        "fixed_fees": 0.0,
+        "raise_reject": false,
+        "slippage": 0.0,
+        "update_value": false,
+        "upon_dir_conflict": "ignore",
+        "upon_long_conflict": "ignore",
+        "upon_opposite_entry": "reversereduce",
+        "upon_short_conflict": "ignore"
+      },
+      "expected": {
+        "accumulate": false,
+        "allow_partial": true,
+        "call_seq": "default",
+        "cash_sharing": false,
+        "fees": 0.0,
+        "ffill_val_price": true,
+        "fillna_close": true,
+        "fixed_fees": 0.0,
+        "raise_reject": false,
+        "slippage": 0.0,
+        "update_value": false,
+        "upon_dir_conflict": "ignore",
+        "upon_long_conflict": "ignore",
+        "upon_opposite_entry": "reversereduce",
+        "upon_short_conflict": "ignore"
+      },
+      "id": "defaults",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
+      "actual": {
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+          110.0
+        ],
+        "timestamps": [
+          "2024-01-01 00:00:00",
+          "2024-01-02 00:00:00"
+        ]
+      },
+      "expected": {
+        "prices": [
+          100.0,
+          110.0
+        ],
+        "timestamps": [
+          "2024-01-01 00:00:00",
+          "2024-01-02 00:00:00"
+        ]
+      },
+      "id": "signal_timing_and_default_fill",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
+      "actual": [
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+        109.0
+      ],
+      "expected": [
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+        109.0
+      ],
+      "id": "explicit_fill_price",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
+      "actual": [
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+        5.0
+      ],
+      "expected": [
+        5.0,
+        5.0
+      ],
+      "id": "target_percent_sizing",
+      "passed": true,
+      "source": "from_orders"
+    },
+    {
+      "actual": {
+        "default": [
+          "a"
+        ],
+        "reversed": [
+          "b"
+        ]
+      },
+      "expected": {
+        "default": [
+          "a"
+        ],
+        "reversed": [
+          "b"
+        ]
+      },
+      "id": "cash_sharing_and_call_sequence",
+      "passed": true,
+      "source": "from_orders"
+    },
+    {
+      "actual": {
+        "cash": [
+          1500.0,
+          1000.0,
+          1000.0
+        ],
+        "orders": [
+          {
+            "column": "b",
+            "side": "Sell",
+            "size": 5.0
+          },
+          {
+            "column": "a",
+            "side": "Buy",
+            "size": 5.0
+          }
+        ]
+      },
+      "expected": {
+        "cash": [
+          1500.0,
+          1000.0,
+          1000.0
+        ],
+        "orders": [
+          {
+            "column": "b",
+            "side": "Sell",
+            "size": 5.0
+          },
+          {
+            "column": "a",
+            "side": "Buy",
+            "size": 5.0
+          }
+        ]
+      },
+      "id": "cash_sharing_short_collateral",
+      "passed": true,
+      "source": "from_orders"
+    },
+    {
+      "actual": 1035668.0954273955,
+      "expected": 1035668.0954273955,
+      "id": "lock_notional_update_arithmetic",
+      "passed": true,
+      "source": "from_orders"
+    },
+    {
+      "actual": {
+        "default_orders": 1,
+        "enabled_orders": 2
+      },
+      "expected": {
+        "default_orders": 1,
+        "enabled_orders": 2
+      },
+      "id": "accumulation",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
+      "actual": {
+        "default": [
+          "Buy"
+        ],
+        "entry": [
+          "Buy",
+          "Buy"
+        ],
+        "exit": [
+          "Buy",
+          "Sell"
+        ]
+      },
+      "expected": {
+        "default": [
+          "Buy"
+        ],
+        "entry": [
+          "Buy",
+          "Buy"
+        ],
+        "exit": [
+          "Buy",
+          "Sell"
+        ]
+      },
+      "id": "long_signal_conflict",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
+      "actual": {
+        "cash": [
+          1100.0,
+          990.0
+        ],
+        "sides": [
+          "Sell",
+          "Buy"
+        ]
+      },
+      "expected": {
+        "cash": [
+          1100.0,
+          990.0
+        ],
+        "sides": [
+          "Sell",
+          "Buy"
+        ]
+      },
+      "id": "short_cash",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
+      "actual": [
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+        90.0
+      ],
+      "expected": [
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+        90.0
+      ],
+      "id": "stop_fill",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
+      "actual": [
+        100.0,
+        108.0
+      ],
+      "expected": [
+        100.0,
+        108.0
+      ],
+      "id": "trailing_stop_extreme_and_intrabar_fill",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
+      "actual": {
+        "fees": [
+          3.01,
+          2.99
+        ],
+        "prices": [
+          101.0,
+          99.0
+        ]
+      },
+      "expected": {
+        "fees": [
+          3.01,
+          2.99
+        ],
+        "prices": [
+          101.0,
+          99.0
+        ]
+      },
+      "id": "fees_and_slippage",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
+      "actual": {
+        "cash": [
+          900.0,
+          900.0,
+          900.0
+        ],
+        "order_count": 1
+      },
+      "expected": {
+        "cash": [
+          900.0,
+          900.0,
+          900.0
+        ],
+        "order_count": 1
+      },
+      "id": "missing_order_price",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
+      "actual": [
+        1.0
+      ],
+      "expected": [
+        1.0
+      ],
+      "id": "insufficient_cash_partial_fill",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
+      "actual": {
+        "direction": "Long",
+        "order_ids": [
+          0,
+          1
+        ],
+        "pnl": 10.0,
+        "status": "Closed",
+        "trade_count": 1
+      },
+      "expected": {
+        "direction": "Long",
+        "order_ids": [
+          0,
+          1
+        ],
+        "pnl": 10.0,
+        "status": "Closed",
+        "trade_count": 1
+      },
+      "id": "record_construction",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
+      "actual": "accepted",
+      "expected": "accepted",
+      "id": "integer_signal_dtype",
+      "passed": true,
+      "source": "from_signals"
+    }
+  ],
+  "framework": "vectorbt_oss",
+  "oracle_sha256": "e3a002a1924a371cdf5b9f61eae13942ac371ad13d6f55125dd545c243a88bc8",
+  "package": "vectorbt",
+  "passed": true,
+  "schema_version": 1,
+  "source_commit": "259d2d89fe2e7638baf3ca76c394937cd32b656d",
+  "source_locations": {
+    "from_orders": {
+      "line": 1616,
+      "module": "vectorbt.portfolio.base",
+      "path": "vectorbt/portfolio/base.py",
+      "qualname": "Portfolio.from_orders",
+      "source_url": "https://github.com/polakowo/vectorbt/blob/259d2d89fe2e7638baf3ca76c394937cd32b656d/vectorbt/portfolio/base.py#L1616"
+    },
+    "from_signals": {
+      "line": 2047,
+      "module": "vectorbt.portfolio.base",
+      "path": "vectorbt/portfolio/base.py",
+      "qualname": "Portfolio.from_signals",
+      "source_url": "https://github.com/polakowo/vectorbt/blob/259d2d89fe2e7638baf3ca76c394937cd32b656d/vectorbt/portfolio/base.py#L2047"
+    }
+  },
+  "version": "1.1.0"
+}
diff --git a/validation/native/evidence/vectorbt_pro-2026.6.27.json b/validation/native/evidence/vectorbt_pro-2026.6.27.json
new file mode 100644
index 00000000..7e6d20f2
--- /dev/null
+++ b/validation/native/evidence/vectorbt_pro-2026.6.27.json
@@ -0,0 +1,372 @@
+{
+  "checks": [
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+        "allow_partial": true,
+        "call_seq": null,
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+        "upon_dir_conflict": "ignore",
+        "upon_long_conflict": "ignore",
+        "upon_opposite_entry": "reversereduce",
+        "upon_short_conflict": "ignore"
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+      "expected": {
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+        "allow_partial": true,
+        "call_seq": null,
+        "cash_sharing": false,
+        "fees": 0.0,
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+        "update_value": false,
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+      "source": "from_signals"
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+        "reversed": [
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+      "expected": {
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+      "id": "cash_sharing_and_call_sequence",
+      "passed": true,
+      "source": "from_orders"
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+          {
+            "column": "a",
+            "side": "Buy",
+            "size": 5.0
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+          1000.0,
+          1000.0
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+        "orders": [
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+            "side": "Sell",
+            "size": 5.0
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+          {
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+            "side": "Buy",
+            "size": 5.0
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+      "source": "from_orders"
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+        "enabled_orders": 2
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+      "passed": true,
+      "source": "from_signals"
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+        "entry": [
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+        "exit": [
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+          "Sell"
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+        "entry": [
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+        "exit": [
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+        "sides": [
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+        90.0
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+      "passed": true,
+      "source": "from_signals"
+    },
+    {
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+          2.99
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+          99.0
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+          2.99
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+          99.0
+        ]
+      },
+      "id": "fees_and_slippage",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
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+          900.0,
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+      "expected": {
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+          900.0,
+          900.0
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+      "id": "missing_order_price",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
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+        1.0
+      ],
+      "expected": [
+        1.0
+      ],
+      "id": "insufficient_cash_partial_fill",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
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+        "order_ids": [
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+          1
+        ],
+        "pnl": 10.0,
+        "status": "Closed",
+        "trade_count": 1
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+      "expected": {
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+          1
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+        "pnl": 10.0,
+        "status": "Closed",
+        "trade_count": 1
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+      "id": "record_construction",
+      "passed": true,
+      "source": "from_signals"
+    },
+    {
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+      "expected": "rejected",
+      "id": "integer_signal_dtype",
+      "passed": true,
+      "source": "from_signals"
+    }
+  ],
+  "framework": "vectorbt_pro",
+  "oracle_sha256": "e3a002a1924a371cdf5b9f61eae13942ac371ad13d6f55125dd545c243a88bc8",
+  "package": "vectorbtpro",
+  "passed": true,
+  "schema_version": 1,
+  "source_commit": "6e18cf0aa37849cfc20848f40f1d26ecfdc771b4",
+  "source_locations": {
+    "from_orders": {
+      "line": 4145,
+      "module": "vectorbtpro.portfolio.base",
+      "path": "vectorbtpro/portfolio/base.py",
+      "qualname": "Portfolio.from_orders",
+      "source_url": "https://github.com/polakowo/vectorbt.pro/blob/6e18cf0aa37849cfc20848f40f1d26ecfdc771b4/vectorbtpro/portfolio/base.py#L4145"
+    },
+    "from_signals": {
+      "line": 4646,
+      "module": "vectorbtpro.portfolio.base",
+      "path": "vectorbtpro/portfolio/base.py",
+      "qualname": "Portfolio.from_signals",
+      "source_url": "https://github.com/polakowo/vectorbt.pro/blob/6e18cf0aa37849cfc20848f40f1d26ecfdc771b4/vectorbtpro/portfolio/base.py#L4646"
+    }
+  },
+  "version": "2026.6.27"
+}
diff --git a/validation/native/evidence/zipline-3.1.1.json b/validation/native/evidence/zipline-3.1.1.json
new file mode 100644
index 00000000..32839bac
--- /dev/null
+++ b/validation/native/evidence/zipline-3.1.1.json
@@ -0,0 +1,608 @@
+{
+  "artifact": "zipline_reloaded-3.1.1.tar.gz",
+  "artifact_sha256": "4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+  "checks": [
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+        "commission_per_share": 0.001,
+        "slippage_basis_points": 5.0,
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+        "slippage_volume_limit": 0.1,
+        "volume_share_price_impact": 0.1,
+        "volume_share_volume_limit": 0.025
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+      "expected": {
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+        "commission_minimum": 0,
+        "commission_per_share": 0.001,
+        "slippage_basis_points": 5.0,
+        "slippage_class": "FixedBasisPointsSlippage",
+        "slippage_volume_limit": 0.1,
+        "volume_share_price_impact": 0.1,
+        "volume_share_volume_limit": 0.025
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+      "id": "defaults",
+      "passed": true
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+            "date": "2024-01-03",
+            "price": 120.06,
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+      "expected": {
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+            "price": 120.06,
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+      "id": "default_next_bar_close_fill",
+      "passed": true
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+          "date": "2024-01-03",
+          "price": 110.0,
+          "transaction_commission": 0.0
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+      "expected": [
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+          "date": "2024-01-03",
+          "price": 110.0,
+          "transaction_commission": 0.0
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+      ],
+      "id": "configured_next_bar_open_fill",
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+            "date": "2024-01-03",
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+        "transactions": [
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+            "date": "2024-01-03",
+            "price": 110.0,
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+      "id": "explicit_minimum_commission",
+      "passed": true
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+    {
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+            "date": "2024-01-02",
+            "filled": 0,
+            "status": 0
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+            "filled": 5,
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+            "date": "2024-01-03",
+            "price": 110.0,
+            "transaction_commission": 0.0
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+            "date": "2024-01-02",
+            "filled": 0,
+            "status": 0
+          },
+          {
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+            "filled": 5,
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+            "price": 110.0,
+            "transaction_commission": 0.0
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+        ]
+      },
+      "id": "integer_target_percent",
+      "passed": true
+    },
+    {
+      "actual": {
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+          5
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+        "transactions": [
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+            "price": 110.0,
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+            "date": "2024-01-03",
+            "price": 110.0,
+            "transaction_commission": 0.0
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+        ]
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+      "expected": {
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+        "transactions": [
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+            "date": "2024-01-03",
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+            "price": 110.0,
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+          }
+        ]
+      },
+      "id": "target_percent_snapshot",
+      "passed": true
+    },
+    {
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+          "price": 110.0,
+          "transaction_commission": 0.0
+        }
+      ],
+      "expected": [
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+          "price": 110.0,
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+        {
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+    },
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+          "position_after_fill": 20,
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+              "date": "2024-01-03",
+              "price": 110.0,
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+              "date": "2024-01-03",
+              "price": 110.0,
+              "transaction_commission": 0.0
+            }
+          ]
+        }
+      },
+      "expected": {
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+              "date": "2024-01-03",
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+              "price": 110.0,
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+          ]
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+      },
+      "id": "cash_and_short_proceeds",
+      "passed": true
+    },
+    {
+      "actual": [
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+          "amount": 2,
+          "date": "2024-01-03",
+          "price": 120.0048,
+          "transaction_commission": 0.0
+        },
+        {
+          "amount": 2,
+          "date": "2024-01-04",
+          "price": 130.0052,
+          "transaction_commission": 0.0
+        },
+        {
+          "amount": 1,
+          "date": "2024-01-05",
+          "price": 140.0014,
+          "transaction_commission": 0.0
+        }
+      ],
+      "expected": [
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+          "amount": 2,
+          "date": "2024-01-03",
+          "price": 120.0048,
+          "transaction_commission": 0.0
+        },
+        {
+          "amount": 2,
+          "date": "2024-01-04",
+          "price": 130.0052,
+          "transaction_commission": 0.0
+        },
+        {
+          "amount": 1,
+          "date": "2024-01-05",
+          "price": 140.0014,
+          "transaction_commission": 0.0
+        }
+      ],
+      "id": "volume_share_partial_fills",
+      "passed": true
+    },
+    {
+      "actual": {
+        "native_output_columns": [
+          "orders",
+          "positions",
+          "transactions"
+        ],
+        "native_trade_column": false,
+        "transactions": [
+          {
+            "amount": 2,
+            "date": "2024-01-03",
+            "price": 110.0,
+            "transaction_commission": 0.0
+          },
+          {
+            "amount": -2,
+            "date": "2024-01-05",
+            "price": 130.0,
+            "transaction_commission": 0.0
+          }
+        ]
+      },
+      "expected": {
+        "native_output_columns": [
+          "orders",
+          "positions",
+          "transactions"
+        ],
+        "native_trade_column": false,
+        "transactions": [
+          {
+            "amount": 2,
+            "date": "2024-01-03",
+            "price": 110.0,
+            "transaction_commission": 0.0
+          },
+          {
+            "amount": -2,
+            "date": "2024-01-05",
+            "price": 130.0,
+            "transaction_commission": 0.0
+          }
+        ]
+      },
+      "id": "transaction_records_not_native_trades",
+      "passed": true
+    },
+    {
+      "actual": [],
+      "expected": [],
+      "id": "final_bar_market_order",
+      "passed": true
+    },
+    {
+      "actual": [
+        "2024-01-02",
+        "2024-01-03",
+        "2024-01-04",
+        "2024-01-05",
+        "2024-01-08",
+        "2024-01-09",
+        "2024-01-10",
+        "2024-01-11"
+      ],
+      "expected": [
+        "2024-01-02",
+        "2024-01-03",
+        "2024-01-04",
+        "2024-01-05",
+        "2024-01-08",
+        "2024-01-09",
+        "2024-01-10",
+        "2024-01-11"
+      ],
+      "id": "session_calendar",
+      "passed": true
+    },
+    {
+      "actual": {
+        "observations": [
+          {
+            "close": 100.0,
+            "date": "2024-01-02",
+            "price": 100.0,
+            "stale": false,
+            "volume": 100.0
+          },
+          {
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+            "date": "2024-01-03",
+            "price": 120.0,
+            "stale": false,
+            "volume": 100.0
+          },
+          {
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+            "date": "2024-01-04",
+            "price": 120.0,
+            "stale": true,
+            "volume": 0.0
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+          {
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+            "date": "2024-01-05",
+            "price": 140.0,
+            "stale": false,
+            "volume": 100.0
+          },
+          {
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+            "date": "2024-01-08",
+            "price": 150.0,
+            "stale": false,
+            "volume": 100.0
+          },
+          {
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+            "date": "2024-01-09",
+            "price": 160.0,
+            "stale": false,
+            "volume": 100.0
+          },
+          {
+            "close": 170.0,
+            "date": "2024-01-10",
+            "price": 170.0,
+            "stale": false,
+            "volume": 100.0
+          },
+          {
+            "close": 180.0,
+            "date": "2024-01-11",
+            "price": 180.0,
+            "stale": false,
+            "volume": 100.0
+          }
+        ],
+        "transactions": [
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+            "date": "2024-01-05",
+            "price": 130.0,
+            "transaction_commission": 0.0
+          }
+        ]
+      },
+      "expected": {
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+            "date": "2024-01-02",
+            "price": 100.0,
+            "stale": false,
+            "volume": 100.0
+          },
+          {
+            "close": 120.0,
+            "date": "2024-01-03",
+            "price": 120.0,
+            "stale": false,
+            "volume": 100.0
+          },
+          {
+            "close": null,
+            "date": "2024-01-04",
+            "price": 120.0,
+            "stale": true,
+            "volume": 0.0
+          },
+          {
+            "close": 140.0,
+            "date": "2024-01-05",
+            "price": 140.0,
+            "stale": false,
+            "volume": 100.0
+          },
+          {
+            "close": 150.0,
+            "date": "2024-01-08",
+            "price": 150.0,
+            "stale": false,
+            "volume": 100.0
+          },
+          {
+            "close": 160.0,
+            "date": "2024-01-09",
+            "price": 160.0,
+            "stale": false,
+            "volume": 100.0
+          },
+          {
+            "close": 170.0,
+            "date": "2024-01-10",
+            "price": 170.0,
+            "stale": false,
+            "volume": 100.0
+          },
+          {
+            "close": 180.0,
+            "date": "2024-01-11",
+            "price": 180.0,
+            "stale": false,
+            "volume": 100.0
+          }
+        ],
+        "transactions": [
+          {
+            "amount": 1,
+            "date": "2024-01-05",
+            "price": 130.0,
+            "transaction_commission": 0.0
+          }
+        ]
+      },
+      "id": "missing_bar",
+      "passed": true
+    }
+  ],
+  "comparison_protocol": {
+    "commission": "NoCommission",
+    "execution": "next-session custom OpenPriceSlippage",
+    "risk_rules": "adapter-emulated from daily OHLC; not Zipline native trade records",
+    "slippage": "no volume cap unless a scenario explicitly configures slippage"
+  },
+  "framework": "zipline",
+  "oracle_sha256": "1804d3fae3a56ec930aba31fc832214d6be6f8a3f6d2e8043b4bd1f0a1040346",
+  "package": "zipline-reloaded",
+  "passed": true,
+  "schema_version": 1,
+  "source_commit": "09885a2ebc7567d40942c891b3879dc03c745070",
+  "source_locations": {
+    "algorithm_target_percent": {
+      "artifact": "zipline_reloaded-3.1.1.tar.gz",
+      "artifact_sha256": "4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+      "line": 1807,
+      "module": "zipline.algorithm",
+      "path": "zipline/utils/api_support.py",
+      "qualname": "TradingAlgorithm.order_target_percent",
+      "source_url": "https://github.com/stefan-jansen/zipline-reloaded/blob/09885a2ebc7567d40942c891b3879dc03c745070/zipline/utils/api_support.py#L1807"
+    },
+    "commission": {
+      "artifact": "zipline_reloaded-3.1.1.tar.gz",
+      "artifact_sha256": "4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+      "line": 163,
+      "module": "zipline.finance.commission",
+      "path": "zipline/finance/commission.py",
+      "qualname": "PerShare.__init__",
+      "source_url": "https://github.com/stefan-jansen/zipline-reloaded/blob/09885a2ebc7567d40942c891b3879dc03c745070/zipline/finance/commission.py#L163"
+    },
+    "default_blotter": {
+      "artifact": "zipline_reloaded-3.1.1.tar.gz",
+      "artifact_sha256": "4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+      "line": 42,
+      "module": "zipline.finance.blotter.simulation_blotter",
+      "path": "zipline/finance/blotter/simulation_blotter.py",
+      "qualname": "SimulationBlotter.__init__",
+      "source_url": "https://github.com/stefan-jansen/zipline-reloaded/blob/09885a2ebc7567d40942c891b3879dc03c745070/zipline/finance/blotter/simulation_blotter.py#L42"
+    },
+    "fixed_basis_points": {
+      "artifact": "zipline_reloaded-3.1.1.tar.gz",
+      "artifact_sha256": "4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+      "line": 663,
+      "module": "zipline.finance.slippage",
+      "path": "zipline/finance/slippage.py",
+      "qualname": "FixedBasisPointsSlippage.process_order",
+      "source_url": "https://github.com/stefan-jansen/zipline-reloaded/blob/09885a2ebc7567d40942c891b3879dc03c745070/zipline/finance/slippage.py#L663"
+    },
+    "volume_share": {
+      "artifact": "zipline_reloaded-3.1.1.tar.gz",
+      "artifact_sha256": "4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f",
+      "line": 288,
+      "module": "zipline.finance.slippage",
+      "path": "zipline/finance/slippage.py",
+      "qualname": "VolumeShareSlippage.process_order",
+      "source_url": "https://github.com/stefan-jansen/zipline-reloaded/blob/09885a2ebc7567d40942c891b3879dc03c745070/zipline/finance/slippage.py#L288"
+    }
+  },
+  "version": "3.1.1"
+}
diff --git a/validation/native/lean_behavior.py b/validation/native/lean_behavior.py
new file mode 100644
index 00000000..4db3ea71
--- /dev/null
+++ b/validation/native/lean_behavior.py
@@ -0,0 +1,517 @@
+#!/usr/bin/env python3
+"""Run framework-native behavior cases against the frozen LEAN engine image."""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+import math
+import shutil
+import subprocess
+import sys
+import tempfile
+import zipfile
+from pathlib import Path
+from typing import Any
+
+IMAGE = "quantconnect/lean@sha256:ecd62b0e418d40d1d7c0cd95e90a94e397642a21d2c8810614830c8a4e9a8f70"
+PLATFORM_ARTIFACT = (
+    "linux/amd64@sha256:cbe3f26b3f16c57be836b2cf913253d434f58e010c84ed038360d26b9df88307"
+)
+ENGINE_VERSION = "18001"
+ENGINE_COMMIT = "278fcb3d1b815b63ccadba68d7ae54422e34b792"
+CLI_VERSION = "1.0.228"
+CLI_SHA256 = "eaa4c08f16295b76f005e429d9ca0d0453784dc1a40c1f5cbe5e50c02a05bd7c"
+
+ROOT = Path(__file__).parents[2]
+PROJECT_SOURCE = Path(__file__).parent / "lean_project"
+SUPPORT_SOURCE = ROOT / "validation/lean/support"
+CASES = (
+    "timing",
+    "default_models",
+    "target_sizing",
+    "submission_sequence",
+    "buying_power_allowed",
+    "buying_power_rejected",
+    "buying_power_sequence",
+    "explicit_costs",
+    "default_full_fill",
+    "fill_forward",
+    "terminal_holding",
+    "final_bar_order",
+    "liquidation",
+)
+
+
+def _digest(path: Path) -> str:
+    return hashlib.sha256(path.read_bytes()).hexdigest()
+
+
+def _write_equity(data_root: Path, ticker: str, *, missing_second_bar: bool = False) -> None:
+    equity_root = data_root / "equity/usa"
+    daily = equity_root / "daily"
+    maps = equity_root / "map_files"
+    factors = equity_root / "factor_files"
+    for directory in (daily, maps, factors):
+        directory.mkdir(parents=True, exist_ok=True)
+
+    rows = [
+        ("20240102", 100.0, 102.0, 99.0, 101.0, 100),
+        ("20240103", 110.0, 112.0, 109.0, 111.0, 100),
+        ("20240104", 120.0, 122.0, 119.0, 121.0, 100),
+        ("20240105", 130.0, 132.0, 129.0, 131.0, 100),
+        ("20240108", 140.0, 142.0, 139.0, 141.0, 100),
+        ("20240109", 150.0, 152.0, 149.0, 151.0, 100),
+        ("20240110", 160.0, 162.0, 159.0, 161.0, 100),
+        ("20240111", 170.0, 172.0, 169.0, 171.0, 100),
+    ]
+    if missing_second_bar:
+        rows.pop(1)
+    lines = []
+    for date, open_, high, low, close, volume in rows:
+        prices = [int(round(value * 10_000)) for value in (open_, high, low, close)]
+        lines.append(f"{date} 00:00,{prices[0]},{prices[1]},{prices[2]},{prices[3]},{volume}")
+
+    ticker_lower = ticker.lower()
+    with zipfile.ZipFile(
+        daily / f"{ticker_lower}.zip", "w", compression=zipfile.ZIP_DEFLATED
+    ) as archive:
+        archive.writestr(f"{ticker_lower}.csv", "\n".join(lines))
+    (maps / f"{ticker_lower}.csv").write_text(
+        f"20240102,{ticker_lower}\n20501231,{ticker_lower}\n", encoding="utf-8"
+    )
+    (factors / f"{ticker_lower}.csv").write_text(
+        "20240102,1,1,1\n20501231,1,1,0\n", encoding="utf-8"
+    )
+
+
+def _prepare(root: Path) -> tuple[Path, Path]:
+    project = root / "lean_project"
+    shutil.copytree(PROJECT_SOURCE, project)
+    shutil.copy2(SUPPORT_SOURCE / "lean.json", root / "lean.json")
+    data = root / "data"
+    shutil.copytree(SUPPORT_SOURCE / "data", data)
+    _write_equity(data, "MLNATV")
+    _write_equity(data, "MLMISS", missing_second_bar=True)
+    return project, root / "lean.json"
+
+
+def _command_version(command: Path) -> str:
+    result = subprocess.run(
+        [str(command), "--version"], check=True, capture_output=True, text=True, timeout=60
+    )
+    return result.stdout.strip()
+
+
+def _image_identity() -> dict[str, Any]:
+    result = subprocess.run(
+        ["docker", "image", "inspect", IMAGE],
+        check=True,
+        capture_output=True,
+        text=True,
+        timeout=60,
+    )
+    payload = json.loads(result.stdout)[0]
+    labels = payload.get("Config", {}).get("Labels", {}) or {}
+    return {
+        "engine_version": labels.get("lean_version"),
+        "image": IMAGE,
+        "image_id": payload["Id"],
+        "platform_artifact": PLATFORM_ARTIFACT,
+        "python_version": labels.get("python_version"),
+        "target_framework": labels.get("target_framework"),
+    }
+
+
+def _run_case(
+    command: Path,
+    root: Path,
+    project: Path,
+    lean_config: Path,
+    case: str,
+) -> dict[str, Any]:
+    output = root / "outputs" / case
+    result = subprocess.run(
+        [
+            str(command),
+            "backtest",
+            str(project),
+            "--lean-config",
+            str(lean_config),
+            "--image",
+            IMAGE,
+            "--no-update",
+            "--output",
+            str(output),
+            "--parameter",
+            "case",
+            case,
+        ],
+        cwd=root,
+        capture_output=True,
+        text=True,
+        timeout=600,
+        check=False,
+    )
+    if result.returncode != 0:
+        error = f"STDOUT:\n{result.stdout}\nSTDERR:\n{result.stderr}".strip()
+        raise RuntimeError(f"LEAN case {case} failed: {error[-20_000:]}")
+    artifact = project / f"lean_native_{case}.json"
+    if not artifact.is_file():
+        raise RuntimeError(f"LEAN case {case} did not emit {artifact.name}")
+    return json.loads(artifact.read_text(encoding="utf-8"))
+
+
+def _equal(actual: Any, expected: Any) -> bool:
+    if isinstance(actual, float) and isinstance(expected, (float, int)):
+        return math.isclose(actual, float(expected), rel_tol=0.0, abs_tol=1e-8)
+    if isinstance(actual, list) and isinstance(expected, list) and len(actual) == len(expected):
+        return all(_equal(left, right) for left, right in zip(actual, expected, strict=True))
+    if isinstance(actual, dict) and isinstance(expected, dict) and actual.keys() == expected.keys():
+        return all(_equal(actual[key], expected[key]) for key in actual)
+    return bool(actual == expected)
+
+
+def _project_contract(case: str, payload: dict[str, Any]) -> dict[str, Any]:
+    events = [
+        [
+            event["status"],
+            event["direction"],
+            event["fill_quantity"],
+            event["fill_price"],
+            event["fee"],
+            event["event_time_utc"],
+        ]
+        for event in payload["events"]
+    ]
+    final = {
+        "cash": payload["cash"],
+        "position": payload["position"],
+        "total_fees": payload["total_fees"],
+        "total_portfolio_value": payload["total_portfolio_value"],
+    }
+    if case == "default_models":
+        return {"models": payload["models"]}
+    if case == "target_sizing":
+        return {"events": events, "final": final, "target_quantity": payload["target_quantity"]}
+    if case == "explicit_costs":
+        return {"events": events, "final": final, "models": payload["models"]}
+    if case == "default_full_fill":
+        return {
+            "events": events,
+            "final": final,
+            "source_volume": payload["observations"][0]["volume"],
+        }
+    if case == "fill_forward":
+        synthetic = next(row for row in payload["observations"] if row["date"] == "2024-01-03")
+        return {"events": events, "final": final, "synthetic_bar": synthetic}
+    return {"events": events, "final": final}
+
+
+EXPECTED = {
+    "timing": {
+        "events": [
+            ["SUBMITTED", "BUY", 0.0, 0.0, 0.0, "2024-01-02 21:00:00"],
+            ["FILLED", "BUY", 1.0, 110.0, 1.0, "2024-01-03 21:00:00"],
+        ],
+        "final": {
+            "cash": 9889.0,
+            "position": 1.0,
+            "total_fees": 1.0,
+            "total_portfolio_value": 10060.0,
+        },
+    },
+    "default_models": {
+        "models": {
+            "brokerage": "DefaultBrokerageModel",
+            "buying_power": "SecurityMarginModel",
+            "fee": "InteractiveBrokersFeeModel",
+            "fill": "EquityFillModel",
+            "leverage": 2.0,
+            "slippage": "NullSlippageModel",
+        }
+    },
+    "target_sizing": {
+        "events": [
+            ["SUBMITTED", "BUY", 0.0, 0.0, 0.0, "2024-01-02 21:00:00"],
+            ["FILLED", "BUY", 98.0, 110.0, 1.0, "2024-01-03 21:00:00"],
+        ],
+        "final": {
+            "cash": -781.0,
+            "position": 98.0,
+            "total_fees": 1.0,
+            "total_portfolio_value": 15977.0,
+        },
+        "target_quantity": 98.0,
+    },
+    "submission_sequence": {
+        "events": [
+            ["SUBMITTED", "BUY", 0.0, 0.0, 0.0, "2024-01-02 21:00:00"],
+            ["SUBMITTED", "SELL", 0.0, 0.0, 0.0, "2024-01-02 21:00:00"],
+            ["FILLED", "BUY", 1.0, 110.0, 1.0, "2024-01-03 21:00:00"],
+            ["FILLED", "SELL", -1.0, 110.0, 1.0, "2024-01-03 21:00:00"],
+        ],
+        "final": {
+            "cash": 9998.0,
+            "position": 0.0,
+            "total_fees": 2.0,
+            "total_portfolio_value": 9998.0,
+        },
+    },
+    "buying_power_allowed": {
+        "events": [
+            ["SUBMITTED", "BUY", 0.0, 0.0, 0.0, "2024-01-02 21:00:00"],
+            ["FILLED", "BUY", 150.0, 110.0, 1.0, "2024-01-03 21:00:00"],
+        ],
+        "final": {
+            "cash": -6501.0,
+            "position": 150.0,
+            "total_fees": 1.0,
+            "total_portfolio_value": 19149.0,
+        },
+    },
+    "buying_power_rejected": {
+        "events": [["INVALID", "BUY", 0.0, 0.0, 0.0, "2024-01-02 21:00:00"]],
+        "final": {
+            "cash": 10000.0,
+            "position": 0.0,
+            "total_fees": 0.0,
+            "total_portfolio_value": 10000.0,
+        },
+    },
+    "buying_power_sequence": {
+        "events": [
+            ["SUBMITTED", "BUY", 0.0, 0.0, 0.0, "2024-01-02 21:00:00"],
+            ["SUBMITTED", "BUY", 0.0, 0.0, 0.0, "2024-01-02 21:00:00"],
+            ["FILLED", "BUY", 150.0, 110.0, 1.0, "2024-01-03 21:00:00"],
+            ["INVALID", "BUY", 0.0, 0.0, 0.0, "2024-01-03 21:00:00"],
+        ],
+        "final": {
+            "cash": -6501.0,
+            "position": 150.0,
+            "total_fees": 1.0,
+            "total_portfolio_value": 19149.0,
+        },
+    },
+    "explicit_costs": {
+        "events": [
+            ["SUBMITTED", "BUY", 0.0, 0.0, 0.0, "2024-01-02 21:00:00"],
+            ["FILLED", "BUY", 1.0, 110.111, 1.0, "2024-01-03 21:00:00"],
+        ],
+        "final": {
+            "cash": 9888.889,
+            "position": 1.0,
+            "total_fees": 1.0,
+            "total_portfolio_value": 10059.889,
+        },
+        "models": {
+            "brokerage": "DefaultBrokerageModel",
+            "buying_power": "SecurityMarginModel",
+            "fee": "ConstantFeeModel",
+            "fill": "EquityFillModel",
+            "leverage": 2.0,
+            "slippage": "ConstantSlippageModel",
+        },
+    },
+    "default_full_fill": {
+        "events": [
+            ["SUBMITTED", "BUY", 0.0, 0.0, 0.0, "2024-01-02 21:00:00"],
+            ["FILLED", "BUY", 150.0, 110.0, 1.0, "2024-01-03 21:00:00"],
+        ],
+        "final": {
+            "cash": -6501.0,
+            "position": 150.0,
+            "total_fees": 1.0,
+            "total_portfolio_value": 19149.0,
+        },
+        "source_volume": 100.0,
+    },
+    "fill_forward": {
+        "events": [
+            ["SUBMITTED", "BUY", 0.0, 0.0, 0.0, "2024-01-03 21:00:00"],
+            ["FILLED", "BUY", 1.0, 120.0, 1.0, "2024-01-04 21:00:00"],
+        ],
+        "final": {
+            "cash": 9879.0,
+            "position": 1.0,
+            "total_fees": 1.0,
+            "total_portfolio_value": 10050.0,
+        },
+        "synthetic_bar": {
+            "close": 101.0,
+            "date": "2024-01-03",
+            "fill_forward": True,
+            "open": 100.0,
+            "volume": 0.0,
+        },
+    },
+    "terminal_holding": {
+        "events": [
+            ["SUBMITTED", "BUY", 0.0, 0.0, 0.0, "2024-01-02 21:00:00"],
+            ["FILLED", "BUY", 1.0, 110.0, 1.0, "2024-01-03 21:00:00"],
+        ],
+        "final": {
+            "cash": 9889.0,
+            "position": 1.0,
+            "total_fees": 1.0,
+            "total_portfolio_value": 10060.0,
+        },
+    },
+    "final_bar_order": {
+        "events": [["SUBMITTED", "BUY", 0.0, 0.0, 0.0, "2024-01-11 21:00:00"]],
+        "final": {
+            "cash": 10000.0,
+            "position": 0.0,
+            "total_fees": 0.0,
+            "total_portfolio_value": 10000.0,
+        },
+    },
+    "liquidation": {
+        "events": [
+            ["SUBMITTED", "BUY", 0.0, 0.0, 0.0, "2024-01-02 21:00:00"],
+            ["FILLED", "BUY", 1.0, 110.0, 1.0, "2024-01-03 21:00:00"],
+            ["SUBMITTED", "SELL", 0.0, 0.0, 0.0, "2024-01-10 21:00:00"],
+            ["FILLED", "SELL", -1.0, 170.0, 1.0, "2024-01-11 21:00:00"],
+        ],
+        "final": {
+            "cash": 10058.0,
+            "position": 0.0,
+            "total_fees": 2.0,
+            "total_portfolio_value": 10058.0,
+        },
+    },
+}
+
+
+def run(command: Path) -> dict[str, Any]:
+    command = command.resolve()
+    version = _command_version(command)
+    if version != f"lean {CLI_VERSION}":
+        raise RuntimeError(f"LEAN CLI differs: {version} != lean {CLI_VERSION}")
+    image = _image_identity()
+    if image["engine_version"] != ENGINE_VERSION:
+        raise RuntimeError(
+            f"LEAN engine version differs: {image['engine_version']} != {ENGINE_VERSION}"
+        )
+
+    with tempfile.TemporaryDirectory(prefix="ml4t-lean-native-") as temporary:
+        temporary_root = Path(temporary)
+        project, lean_config = _prepare(temporary_root)
+        actual = {
+            case: _run_case(command, temporary_root, project, lean_config, case) for case in CASES
+        }
+
+    checks = [
+        {
+            "id": case,
+            "actual": actual[case],
+            "contract_actual": _project_contract(case, actual[case]),
+            "expected": EXPECTED[case],
+            "passed": _equal(_project_contract(case, actual[case]), EXPECTED[case]),
+        }
+        for case in CASES
+    ]
+    project_files = {
+        path.relative_to(PROJECT_SOURCE).as_posix(): _digest(path)
+        for path in sorted(PROJECT_SOURCE.rglob("*"))
+        if path.is_file()
+    }
+    support_files = {
+        path.relative_to(SUPPORT_SOURCE).as_posix(): _digest(path)
+        for path in sorted(SUPPORT_SOURCE.rglob("*"))
+        if path.is_file()
+    }
+    data_payload = {
+        "full": [100.0, 101.0, 110.0, 111.0, 120.0, 121.0, 170.0, 171.0],
+        "missing_session": "MLMISS omits 2024-01-03 and enables fill_forward",
+    }
+    return {
+        "schema_version": 1,
+        "framework": "lean",
+        "engine": {
+            **image,
+            "source_commit": ENGINE_COMMIT,
+        },
+        "cli": {
+            "package": "lean",
+            "version": CLI_VERSION,
+            "immutable_id": f"sha256:{CLI_SHA256}",
+        },
+        "models": {
+            "account_type": "Margin",
+            "brokerage": "DefaultBrokerageModel",
+            "security": "Equity USA, daily, adjusted normalization, leverage 2",
+        },
+        "source_references": {
+            "algorithm_settings": (
+                "https://github.com/QuantConnect/Lean/blob/"
+                f"{ENGINE_COMMIT}/Common/AlgorithmSettings.cs"
+            ),
+            "brokerage": (
+                "https://github.com/QuantConnect/Lean/blob/"
+                f"{ENGINE_COMMIT}/Common/Brokerages/DefaultBrokerageModel.cs"
+            ),
+            "fee": (
+                "https://github.com/QuantConnect/Lean/blob/"
+                f"{ENGINE_COMMIT}/Common/Orders/Fees/InteractiveBrokersFeeModel.cs"
+            ),
+            "fill": (
+                "https://github.com/QuantConnect/Lean/blob/"
+                f"{ENGINE_COMMIT}/Common/Orders/Fills/EquityFillModel.cs"
+            ),
+            "margin": (
+                "https://github.com/QuantConnect/Lean/blob/"
+                f"{ENGINE_COMMIT}/Common/Securities/SecurityMarginModel.cs"
+            ),
+            "slippage": (
+                "https://github.com/QuantConnect/Lean/blob/"
+                f"{ENGINE_COMMIT}/Common/Orders/Slippage/ConstantSlippageModel.cs"
+            ),
+        },
+        "data": {
+            "format": "LEAN local equity daily zip, raw prices scaled by 10000",
+            "payload_sha256": hashlib.sha256(
+                json.dumps(data_payload, sort_keys=True).encode()
+            ).hexdigest(),
+            "sessions": [
+                "2024-01-02",
+                "2024-01-03",
+                "2024-01-04",
+                "2024-01-05",
+                "2024-01-08",
+                "2024-01-09",
+                "2024-01-10",
+                "2024-01-11",
+            ],
+        },
+        "oracle_files": project_files,
+        "support_files": support_files,
+        "oracle_sha256": hashlib.sha256(Path(__file__).read_bytes()).hexdigest(),
+        "checks": checks,
+        "passed": all(check["passed"] for check in checks),
+    }
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--lean-command", type=Path, default=ROOT / ".venv-lean/bin/lean")
+    parser.add_argument("--output", type=Path, required=True)
+    args = parser.parse_args()
+    try:
+        evidence = run(args.lean_command)
+    except (FileNotFoundError, json.JSONDecodeError, OSError, RuntimeError, ValueError) as error:
+        print(f"LEAN native behavior run failed: {error}", file=sys.stderr)
+        return 2
+    args.output.parent.mkdir(parents=True, exist_ok=True)
+    args.output.write_text(json.dumps(evidence, indent=2, sort_keys=True) + "\n", encoding="utf-8")
+    failed = [check["id"] for check in evidence["checks"] if not check["passed"]]
+    if failed:
+        print(f"LEAN native behavior differs: {failed}", file=sys.stderr)
+        return 1
+    print(f"LEAN native behavior passed: {len(evidence['checks'])} checks")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/native/lean_project/config.json b/validation/native/lean_project/config.json
new file mode 100644
index 00000000..82dc4517
--- /dev/null
+++ b/validation/native/lean_project/config.json
@@ -0,0 +1,6 @@
+{
+  "algorithm-language": "Python",
+  "description": "ML4T native LEAN behavior oracle",
+  "local-id": 771804201,
+  "parameters": {}
+}
diff --git a/validation/native/lean_project/main.py b/validation/native/lean_project/main.py
new file mode 100644
index 00000000..940ffd48
--- /dev/null
+++ b/validation/native/lean_project/main.py
@@ -0,0 +1,136 @@
+# ruff: noqa: F403, F405, I001, SIM114, SIM401
+# region imports
+from AlgorithmImports import *
+# endregion
+
+import json
+from pathlib import Path
+
+
+class LeanNativeBehavior(QCAlgorithm):
+    def initialize(self):
+        self.set_start_date(2024, 1, 2)
+        self.set_end_date(2024, 1, 11)
+        self.set_cash(10_000)
+        self.set_brokerage_model(BrokerageName.DEFAULT, AccountType.MARGIN)
+        self.case = self.get_parameter("case")
+        ticker = "MLMISS" if self.case == "fill_forward" else "MLNATV"
+        security = self.add_equity(ticker, Resolution.DAILY, fill_forward=True)
+        security.set_leverage(2.0)
+        self.symbol = security.symbol
+        self.security = security
+        self.events = []
+        self.observations = []
+        self.submitted = []
+        self.target_quantity = None
+
+        if self.case == "explicit_costs":
+            security.set_fee_model(ConstantFeeModel(1.0, "USD"))
+            security.set_slippage_model(ConstantSlippageModel(0.001))
+
+        self.models = {
+            "brokerage": type(self.brokerage_model).__name__,
+            "buying_power": type(security.buying_power_model).__name__,
+            "fee": type(security.fee_model).__name__,
+            "fill": type(security.fill_model).__name__,
+            "leverage": float(security.leverage),
+            "slippage": type(security.slippage_model).__name__,
+        }
+
+    def _submit(self, quantity):
+        ticket = self.market_order(self.symbol, quantity)
+        self.submitted.append(
+            {
+                "order_id": int(ticket.order_id),
+                "quantity": float(quantity),
+                "status": str(ticket.status),
+            }
+        )
+
+    def on_data(self, data: Slice):
+        bar = data.bars[self.symbol] if self.symbol in data.bars else None
+        self.observations.append(
+            {
+                "close": float(bar.close) if bar is not None else None,
+                "date": self.time.strftime("%Y-%m-%d"),
+                "fill_forward": bool(bar.is_fill_forward) if bar is not None else None,
+                "open": float(bar.open) if bar is not None else None,
+                "volume": float(bar.volume) if bar is not None else None,
+            }
+        )
+
+        first = self.time.strftime("%Y-%m-%d") == "2024-01-02"
+        final = self.time.strftime("%Y-%m-%d") == "2024-01-11"
+        if first:
+            if self.case in {"timing", "default_models", "explicit_costs"}:
+                self._submit(1)
+            elif self.case == "target_sizing":
+                self.target_quantity = float(self.calculate_order_quantity(self.symbol, 1.0))
+                self._submit(self.target_quantity)
+            elif self.case == "submission_sequence":
+                self._submit(1)
+                self._submit(-1)
+            elif self.case == "buying_power_allowed":
+                self._submit(150)
+            elif self.case == "buying_power_rejected":
+                self._submit(250)
+            elif self.case == "buying_power_sequence":
+                self._submit(150)
+                self._submit(150)
+            elif self.case == "default_full_fill":
+                self._submit(150)
+            elif self.case == "terminal_holding":
+                self._submit(1)
+            elif self.case == "liquidation":
+                self._submit(1)
+
+        if self.case == "fill_forward" and self.time.strftime("%Y-%m-%d") == "2024-01-03":
+            self._submit(1)
+
+        if self.case == "liquidation" and self.time.strftime("%Y-%m-%d") == "2024-01-10":
+            tickets = self.liquidate(self.symbol)
+            for ticket in tickets:
+                self.submitted.append(
+                    {
+                        "order_id": int(ticket.order_id),
+                        "quantity": float(ticket.quantity),
+                        "status": str(ticket.status),
+                    }
+                )
+
+        if final and self.case == "final_bar_order":
+            self._submit(1)
+
+    def on_order_event(self, order_event: OrderEvent):
+        fee = 0.0
+        if order_event.order_fee and order_event.order_fee.value is not None:
+            fee = float(order_event.order_fee.value.amount)
+        self.events.append(
+            {
+                "direction": str(order_event.direction),
+                "event_time_utc": order_event.utc_time.strftime("%Y-%m-%d %H:%M:%S"),
+                "fee": fee,
+                "fill_price": float(order_event.fill_price),
+                "fill_quantity": float(order_event.fill_quantity),
+                "message": str(order_event.message or ""),
+                "order_id": int(order_event.order_id),
+                "status": str(order_event.status),
+                "time": self.time.strftime("%Y-%m-%d %H:%M:%S"),
+            }
+        )
+
+    def on_end_of_algorithm(self):
+        payload = {
+            "case": self.case,
+            "cash": float(self.portfolio.cash),
+            "events": self.events,
+            "models": self.models,
+            "observations": self.observations,
+            "position": float(self.portfolio[self.symbol].quantity),
+            "submitted": self.submitted,
+            "target_quantity": self.target_quantity,
+            "total_fees": float(self.portfolio.total_fees),
+            "total_portfolio_value": float(self.portfolio.total_portfolio_value),
+        }
+        output = Path(__file__).resolve().parent / f"lean_native_{self.case}.json"
+        output.write_text(json.dumps(payload, indent=2, sort_keys=True), encoding="utf-8")
diff --git a/validation/native/vectorbt_behavior.py b/validation/native/vectorbt_behavior.py
new file mode 100644
index 00000000..918a27d2
--- /dev/null
+++ b/validation/native/vectorbt_behavior.py
@@ -0,0 +1,499 @@
+#!/usr/bin/env python3
+"""Measure current VectorBT behavior without importing ML4T comparison code."""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import importlib
+import importlib.metadata
+import inspect
+import json
+import math
+import sys
+from pathlib import Path
+from typing import Any
+
+import numpy as np
+import pandas as pd
+
+TARGETS = {
+    "vectorbt_oss": {
+        "package": "vectorbt",
+        "version": "1.1.0",
+        "commit": "259d2d89fe2e7638baf3ca76c394937cd32b656d",
+        "repository": "https://github.com/polakowo/vectorbt",
+    },
+    "vectorbt_pro": {
+        "package": "vectorbtpro",
+        "version": "2026.6.27",
+        "commit": "6e18cf0aa37849cfc20848f40f1d26ecfdc771b4",
+        "repository": "https://github.com/polakowo/vectorbt.pro",
+    },
+}
+
+
+def _bool(values: list[int]) -> np.ndarray:
+    return np.asarray(values, dtype=bool)
+
+
+def _orders(portfolio: Any) -> list[dict[str, Any]]:
+    return portfolio.orders.records_readable.to_dict("records")
+
+
+def _trades(portfolio: Any) -> list[dict[str, Any]]:
+    return portfolio.trades.records_readable.to_dict("records")
+
+
+def _cash(portfolio: Any) -> list[float]:
+    value = portfolio.cash() if callable(portfolio.cash) else portfolio.cash
+    return np.asarray(value, dtype=float).tolist()
+
+
+def _chronological_order_events(portfolio: Any) -> list[dict[str, Any]]:
+    orders = _orders(portfolio)
+    if not orders:
+        return []
+    time_key = next(key for key in ("Fill Index", "Timestamp", "Index") if key in orders[0])
+    ordered = sorted(orders, key=lambda order: (str(order[time_key]), str(order["Column"])))
+    return [
+        {"column": order["Column"], "side": order["Side"], "size": order["Size"]}
+        for order in ordered
+    ]
+
+
+def _source_location(package: Any, function: Any, target: dict[str, str]) -> dict:
+    source_file = inspect.getsourcefile(function)
+    if source_file is None:
+        raise RuntimeError(f"Could not locate source for {function}")
+    package_root = Path(package.__file__).resolve().parent.parent
+    relative_path = Path(source_file).resolve().relative_to(package_root).as_posix()
+    line = inspect.getsourcelines(function)[1]
+    return {
+        "module": function.__module__,
+        "qualname": function.__qualname__,
+        "path": relative_path,
+        "line": line,
+        "source_url": (f"{target['repository']}/blob/{target['commit']}/{relative_path}#L{line}"),
+    }
+
+
+def _defaults(framework: str, vbt: Any) -> dict[str, Any]:
+    portfolio = vbt.settings.portfolio
+    if framework == "vectorbt_pro":
+        signals = portfolio["from_signals"]
+        return {
+            "accumulate": signals["accumulate"],
+            "allow_partial": portfolio["allow_partial"],
+            "call_seq": portfolio["call_seq"],
+            "cash_sharing": portfolio["cash_sharing"],
+            "fees": portfolio["fees"],
+            "ffill_val_price": portfolio["ffill_val_price"],
+            "fillna_close": portfolio["fillna_close"],
+            "fixed_fees": portfolio["fixed_fees"],
+            "raise_reject": portfolio["raise_reject"],
+            "slippage": portfolio["slippage"],
+            "upon_dir_conflict": signals["upon_dir_conflict"],
+            "upon_long_conflict": signals["upon_long_conflict"],
+            "upon_opposite_entry": signals["upon_opposite_entry"],
+            "upon_short_conflict": signals["upon_short_conflict"],
+            "update_value": portfolio["update_value"],
+        }
+    return {
+        key: portfolio[key]
+        for key in (
+            "accumulate",
+            "allow_partial",
+            "call_seq",
+            "cash_sharing",
+            "fees",
+            "ffill_val_price",
+            "fillna_close",
+            "fixed_fees",
+            "raise_reject",
+            "slippage",
+            "upon_dir_conflict",
+            "upon_long_conflict",
+            "upon_opposite_entry",
+            "upon_short_conflict",
+            "update_value",
+        )
+    }
+
+
+def _expected_defaults(framework: str) -> dict[str, Any]:
+    return {
+        "accumulate": False,
+        "allow_partial": True,
+        "call_seq": None if framework == "vectorbt_pro" else "default",
+        "cash_sharing": False,
+        "fees": 0.0,
+        "ffill_val_price": True,
+        "fillna_close": True,
+        "fixed_fees": 0.0,
+        "raise_reject": False,
+        "slippage": 0.0,
+        "upon_dir_conflict": "ignore",
+        "upon_long_conflict": "ignore",
+        "upon_opposite_entry": "reversereduce",
+        "upon_short_conflict": "ignore",
+        "update_value": False,
+    }
+
+
+def _behavior_checks(framework: str, vbt: Any) -> list[tuple[str, Any, Any]]:
+    index = pd.date_range("2024-01-01", periods=3)
+    close = pd.Series([100.0, 110.0, 120.0], index=index)
+    entries = _bool([1, 0, 0])
+    exits = _bool([0, 1, 0])
+
+    signal_pf = vbt.Portfolio.from_signals(
+        close, entries=entries, exits=exits, size=1, init_cash=1_000
+    )
+    signal_orders = _orders(signal_pf)
+    time_key = "Fill Index" if framework == "vectorbt_pro" else "Timestamp"
+
+    explicit_pf = vbt.Portfolio.from_signals(
+        close,
+        entries=entries,
+        exits=exits,
+        price=pd.Series([99.0, 109.0, 119.0], index=index),
+        size=1,
+        init_cash=1_000,
+    )
+    target_pf = vbt.Portfolio.from_orders(
+        pd.Series([100.0, 200.0], index=index[:2]),
+        size=[0.5, 0.0],
+        size_type="targetpercent",
+        init_cash=1_000,
+    )
+    shared_close = pd.DataFrame([[100.0, 100.0]], index=index[:1], columns=pd.Index(["a", "b"]))
+    shared_default = vbt.Portfolio.from_orders(
+        shared_close,
+        size=1,
+        init_cash=100,
+        cash_sharing=True,
+        group_by=True,
+    )
+    shared_reversed = vbt.Portfolio.from_orders(
+        shared_close,
+        size=1,
+        init_cash=100,
+        cash_sharing=True,
+        group_by=True,
+        call_seq="reversed",
+    )
+    collateral_kwargs = {"lock_cash": True} if framework == "vectorbt_oss" else {}
+    collateral_pf = vbt.Portfolio.from_orders(
+        pd.DataFrame(100.0, index=index, columns=pd.Index(["a", "b"])),
+        size=pd.DataFrame(
+            [[0.0, -5.0], [5.0, -10.0], [5.0, -10.0]],
+            index=index,
+            columns=pd.Index(["a", "b"]),
+        ),
+        size_type="targetamount",
+        init_cash=1_000,
+        cash_sharing=True,
+        **collateral_kwargs,
+    )
+    arithmetic_pf = vbt.Portfolio.from_orders(
+        np.asarray([445.1764349947099, 98.35685542114634]),
+        size=np.asarray([-935.6511349828165, 822.3137995772428]),
+        size_type="amount",
+        init_cash=800_928.6801081297,
+        log=True,
+        **collateral_kwargs,
+    )
+    arithmetic_logs = arithmetic_pf.logs.records_readable.to_dict("records")
+    new_free_cash_key = "[ST1] Free Cash" if framework == "vectorbt_pro" else "New Free Cash"
+    accumulate_default = vbt.Portfolio.from_signals(
+        close, entries=_bool([1, 1, 0]), exits=False, size=1, init_cash=1_000
+    )
+    accumulate_true = vbt.Portfolio.from_signals(
+        close,
+        entries=_bool([1, 1, 0]),
+        exits=False,
+        size=1,
+        accumulate=True,
+        init_cash=1_000,
+    )
+    conflict_kwargs = {
+        "entries": _bool([1, 1, 0]),
+        "exits": _bool([0, 1, 0]),
+        "size": 1,
+        "accumulate": True,
+        "init_cash": 1_000,
+    }
+    conflict_default = vbt.Portfolio.from_signals(close, **conflict_kwargs)
+    conflict_entry = vbt.Portfolio.from_signals(
+        close, **conflict_kwargs, upon_long_conflict="entry"
+    )
+    conflict_exit = vbt.Portfolio.from_signals(close, **conflict_kwargs, upon_long_conflict="exit")
+    short_pf = vbt.Portfolio.from_signals(
+        close,
+        short_entries=entries,
+        short_exits=exits,
+        size=1,
+        init_cash=1_000,
+    )
+    stop_pf = vbt.Portfolio.from_signals(
+        pd.Series([100.0, 95.0, 100.0], index=index),
+        open=pd.Series([100.0, 100.0, 100.0], index=index),
+        high=pd.Series([101.0, 101.0, 101.0], index=index),
+        low=pd.Series([99.0, 85.0, 99.0], index=index),
+        entries=entries,
+        size=1,
+        sl_stop=0.1,
+        init_cash=1_000,
+    )
+    trailing_kwargs: dict[str, Any] = {
+        "close": pd.Series(
+            [100.0, 110.0, 107.0, 107.0], index=pd.date_range("2024-01-01", periods=4)
+        ),
+        "open": pd.Series(
+            [100.0, 110.0, 109.0, 107.0], index=pd.date_range("2024-01-01", periods=4)
+        ),
+        "high": pd.Series(
+            [101.0, 120.0, 110.0, 108.0], index=pd.date_range("2024-01-01", periods=4)
+        ),
+        "low": pd.Series([99.0, 109.0, 105.0, 106.0], index=pd.date_range("2024-01-01", periods=4)),
+        "entries": _bool([1, 0, 0, 0]),
+        "size": 1,
+        "init_cash": 1_000,
+    }
+    if framework == "vectorbt_pro":
+        trailing_kwargs["tsl_stop"] = 0.1
+    else:
+        trailing_kwargs["sl_stop"] = 0.1
+        trailing_kwargs["sl_trail"] = True
+    trailing_pf = vbt.Portfolio.from_signals(**trailing_kwargs)
+    cost_pf = vbt.Portfolio.from_signals(
+        pd.Series([100.0, 100.0], index=index[:2]),
+        entries=_bool([1, 0]),
+        exits=_bool([0, 1]),
+        size=1,
+        fees=0.01,
+        fixed_fees=2,
+        slippage=0.01,
+        init_cash=1_000,
+    )
+    missing_pf = vbt.Portfolio.from_signals(
+        pd.Series([100.0, np.nan, 110.0], index=index),
+        entries=entries,
+        exits=exits,
+        size=1,
+        init_cash=1_000,
+    )
+    partial_pf = vbt.Portfolio.from_signals(
+        pd.Series([100.0]),
+        entries=_bool([1]),
+        size=2,
+        init_cash=100,
+    )
+    trade = _trades(signal_pf)[0]
+    dtype_result: str
+    try:
+        vbt.Portfolio.from_signals(
+            close, entries=np.asarray([1, 0, 0]), exits=np.asarray([0, 1, 0]), size=1
+        )
+        dtype_result = "accepted"
+    except AssertionError:
+        dtype_result = "rejected"
+
+    return [
+        ("defaults", _defaults(framework, vbt), _expected_defaults(framework)),
+        (
+            "signal_timing_and_default_fill",
+            {
+                "timestamps": [str(order[time_key]) for order in signal_orders],
+                "prices": [order["Price"] for order in signal_orders],
+            },
+            {
+                "timestamps": ["2024-01-01 00:00:00", "2024-01-02 00:00:00"],
+                "prices": [100.0, 110.0],
+            },
+        ),
+        (
+            "explicit_fill_price",
+            [order["Price"] for order in _orders(explicit_pf)],
+            [99.0, 109.0],
+        ),
+        (
+            "target_percent_sizing",
+            [order["Size"] for order in _orders(target_pf)],
+            [5.0, 5.0],
+        ),
+        (
+            "cash_sharing_and_call_sequence",
+            {
+                "default": [_orders(shared_default)[0]["Column"]],
+                "reversed": [_orders(shared_reversed)[0]["Column"]],
+            },
+            {"default": ["a"], "reversed": ["b"]},
+        ),
+        (
+            "cash_sharing_short_collateral",
+            {
+                "cash": _cash(collateral_pf),
+                "orders": _chronological_order_events(collateral_pf),
+            },
+            {
+                "cash": [1_500.0, 1_000.0, 1_000.0],
+                "orders": [
+                    {"column": "b", "side": "Sell", "size": 5.0},
+                    {"column": "a", "side": "Buy", "size": 5.0},
+                ],
+            },
+        ),
+        (
+            "lock_notional_update_arithmetic",
+            arithmetic_logs[-1][new_free_cash_key],
+            1_035_668.0954273958 if framework == "vectorbt_pro" else 1_035_668.0954273955,
+        ),
+        (
+            "accumulation",
+            {
+                "default_orders": len(_orders(accumulate_default)),
+                "enabled_orders": len(_orders(accumulate_true)),
+            },
+            {"default_orders": 1, "enabled_orders": 2},
+        ),
+        (
+            "long_signal_conflict",
+            {
+                "default": [order["Side"] for order in _orders(conflict_default)],
+                "entry": [order["Side"] for order in _orders(conflict_entry)],
+                "exit": [order["Side"] for order in _orders(conflict_exit)],
+            },
+            {"default": ["Buy"], "entry": ["Buy", "Buy"], "exit": ["Buy", "Sell"]},
+        ),
+        (
+            "short_cash",
+            {"cash": _cash(short_pf)[:2], "sides": [order["Side"] for order in _orders(short_pf)]},
+            {"cash": [1_100.0, 990.0], "sides": ["Sell", "Buy"]},
+        ),
+        ("stop_fill", [order["Price"] for order in _orders(stop_pf)], [100.0, 90.0]),
+        (
+            "trailing_stop_extreme_and_intrabar_fill",
+            [order["Price"] for order in _orders(trailing_pf)],
+            [100.0, 108.0],
+        ),
+        (
+            "fees_and_slippage",
+            {
+                "fees": [order["Fees"] for order in _orders(cost_pf)],
+                "prices": [order["Price"] for order in _orders(cost_pf)],
+            },
+            {"fees": [3.01, 2.99], "prices": [101.0, 99.0]},
+        ),
+        (
+            "missing_order_price",
+            {"order_count": len(_orders(missing_pf)), "cash": _cash(missing_pf)},
+            {"order_count": 1, "cash": [900.0, 900.0, 900.0]},
+        ),
+        (
+            "insufficient_cash_partial_fill",
+            [order["Size"] for order in _orders(partial_pf)],
+            [1.0],
+        ),
+        (
+            "record_construction",
+            {
+                "direction": trade["Direction"],
+                "order_ids": [order["Order Id"] for order in signal_orders],
+                "pnl": trade["PnL"],
+                "status": trade["Status"],
+                "trade_count": len(_trades(signal_pf)),
+            },
+            {
+                "direction": "Long",
+                "order_ids": [0, 1],
+                "pnl": 10.0,
+                "status": "Closed",
+                "trade_count": 1,
+            },
+        ),
+        (
+            "integer_signal_dtype",
+            dtype_result,
+            "rejected" if framework == "vectorbt_pro" else "accepted",
+        ),
+    ]
+
+
+def _equal(actual: Any, expected: Any) -> bool:
+    if isinstance(actual, float) and isinstance(expected, (float, int)):
+        return math.isclose(actual, float(expected), rel_tol=0.0, abs_tol=1e-12)
+    if isinstance(actual, list) and isinstance(expected, list) and len(actual) == len(expected):
+        return all(_equal(left, right) for left, right in zip(actual, expected, strict=True))
+    if isinstance(actual, dict) and isinstance(expected, dict) and actual.keys() == expected.keys():
+        return all(_equal(actual[key], expected[key]) for key in actual)
+    return bool(actual == expected)
+
+
+def run(framework: str) -> dict[str, Any]:
+    """Execute the frozen framework directly and return native evidence."""
+    target = TARGETS[framework]
+    vbt = importlib.import_module(target["package"])
+    version = importlib.metadata.version(target["package"])
+    if version != target["version"]:
+        raise RuntimeError(f"{target['package']} version differs: {version} != {target['version']}")
+
+    source_locations = {
+        "from_orders": _source_location(vbt, vbt.Portfolio.from_orders, target),
+        "from_signals": _source_location(vbt, vbt.Portfolio.from_signals, target),
+    }
+    checks: list[dict[str, Any]] = []
+    for check_id, actual, expected in _behavior_checks(framework, vbt):
+        checks.append(
+            {
+                "id": check_id,
+                "actual": actual,
+                "expected": expected,
+                "passed": _equal(actual, expected),
+                "source": "from_orders"
+                if check_id
+                in {
+                    "target_percent_sizing",
+                    "cash_sharing_and_call_sequence",
+                    "cash_sharing_short_collateral",
+                    "lock_notional_update_arithmetic",
+                }
+                else "from_signals",
+            }
+        )
+    return {
+        "schema_version": 1,
+        "oracle_sha256": hashlib.sha256(Path(__file__).read_bytes()).hexdigest(),
+        "framework": framework,
+        "package": target["package"],
+        "version": version,
+        "source_commit": target["commit"],
+        "source_locations": source_locations,
+        "checks": checks,
+        "passed": all(check["passed"] for check in checks),
+    }
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--framework", choices=tuple(TARGETS), required=True)
+    parser.add_argument("--output", type=Path, required=True)
+    args = parser.parse_args()
+    try:
+        evidence = run(args.framework)
+    except (ImportError, OSError, RuntimeError, ValueError) as error:
+        print(f"VectorBT native behavior run failed: {error}", file=sys.stderr)
+        return 2
+    args.output.parent.mkdir(parents=True, exist_ok=True)
+    args.output.write_text(json.dumps(evidence, indent=2, sort_keys=True) + "\n", encoding="utf-8")
+    failed = [check["id"] for check in evidence["checks"] if not check["passed"]]
+    if failed:
+        print(f"VectorBT native behavior differs: {failed}", file=sys.stderr)
+        return 1
+    print(f"VectorBT native behavior passed: {len(evidence['checks'])} checks")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/native/zipline_behavior.py b/validation/native/zipline_behavior.py
new file mode 100644
index 00000000..d8fdcc3c
--- /dev/null
+++ b/validation/native/zipline_behavior.py
@@ -0,0 +1,712 @@
+#!/usr/bin/env python3
+"""Measure frozen Zipline Reloaded behavior without ML4T comparison code."""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import importlib
+import importlib.metadata
+import inspect
+import json
+import math
+import sys
+import warnings
+from pathlib import Path
+from typing import Any
+
+import pandas as pd
+
+VERSION = "3.1.1"
+COMMIT = "09885a2ebc7567d40942c891b3879dc03c745070"
+ARTIFACT = "zipline_reloaded-3.1.1.tar.gz"
+ARTIFACT_SHA256 = "4a305524616f7aad836f929e5a2ba5afc7db0e238757f47eb49487d9e2457a6f"
+REPOSITORY = "https://github.com/stefan-jansen/zipline-reloaded"
+
+zipline: Any = importlib.import_module("zipline")
+api: Any = importlib.import_module("zipline.api")
+commission: Any = importlib.import_module("zipline.finance.commission")
+slippage: Any = importlib.import_module("zipline.finance.slippage")
+blotter_module: Any = importlib.import_module("zipline.finance.blotter.simulation_blotter")
+algorithm_module: Any = importlib.import_module("zipline.algorithm")
+calendar_module: Any = importlib.import_module("exchange_calendars")
+bundles_module: Any = importlib.import_module("zipline.data.bundles")
+
+
+def _source_location(function: Any) -> dict[str, Any]:
+    source_file = inspect.getsourcefile(function)
+    if source_file is None:
+        raise RuntimeError(f"Could not locate source for {function}")
+    package_root = Path(zipline.__file__).resolve().parent.parent
+    relative_path = Path(source_file).resolve().relative_to(package_root).as_posix()
+    line = inspect.getsourcelines(function)[1]
+    return {
+        "artifact": ARTIFACT,
+        "artifact_sha256": ARTIFACT_SHA256,
+        "line": line,
+        "module": function.__module__,
+        "path": relative_path,
+        "qualname": function.__qualname__,
+        "source_url": f"{REPOSITORY}/blob/{COMMIT}/{relative_path}#L{line}",
+    }
+
+
+def _frame() -> pd.DataFrame:
+    calendar = calendar_module.get_calendar("XNYS")
+    sessions = calendar.sessions_in_range("2024-01-02", "2024-01-12")[:8]
+    return pd.DataFrame(
+        {
+            "open": [100.0, 110.0, 120.0, 130.0, 140.0, 150.0, 160.0, 170.0],
+            "high": [101.0, 121.0, 131.0, 141.0, 151.0, 161.0, 171.0, 181.0],
+            "low": [99.0, 109.0, 119.0, 129.0, 139.0, 149.0, 159.0, 169.0],
+            "close": [100.0, 120.0, 130.0, 140.0, 150.0, 160.0, 170.0, 180.0],
+            "volume": [100.0] * 8,
+        },
+        index=pd.DatetimeIndex(sessions).tz_localize(None),
+    )
+
+
+def _setup_bundle(frame: pd.DataFrame, name: str) -> str:
+    def ingest_function(
+        _environ: Any,
+        asset_db_writer: Any,
+        _minute_bar_writer: Any,
+        daily_bar_writer: Any,
+        adjustment_writer: Any,
+        calendar: Any,
+        start_session: Any,
+        end_session: Any,
+        _cache: Any,
+        show_progress: bool,
+        _output_dir: Any,
+    ) -> None:
+        sessions = calendar.sessions_in_range(start_session, end_session)
+        trading_frame = frame.loc[frame.index.isin(pd.DatetimeIndex(sessions).tz_localize(None))]
+        asset_db_writer.write(
+            equities=pd.DataFrame(
+                {
+                    "symbol": ["TEST"],
+                    "asset_name": ["Native behavior asset"],
+                    "exchange": ["NYSE"],
+                }
+            )
+        )
+        daily_bar_writer.write(
+            [(0, trading_frame[["open", "high", "low", "close", "volume"]])],
+            show_progress=show_progress,
+        )
+        adjustment_writer.write()
+
+    if name in bundles_module.bundles:
+        bundles_module.unregister(name)
+    bundles_module.register(
+        name,
+        ingest_function,
+        calendar_name="XNYS",
+        start_session=frame.index[0],
+        end_session=frame.index[-1],
+    )
+    bundles_module.ingest(name, show_progress=False)
+    return name
+
+
+def _run(
+    bundle: str,
+    frame: pd.DataFrame,
+    initialize_case: Any,
+    handle_case: Any,
+) -> pd.DataFrame:
+    def initialize(context: Any) -> None:
+        context.asset = api.symbol("TEST")
+        context.bar_number = 0
+        initialize_case(context)
+
+    def handle_data(context: Any, data: Any) -> None:
+        handle_case(context, data)
+        context.bar_number += 1
+
+    return zipline.run_algorithm(
+        start=frame.index[0],
+        end=frame.index[-1],
+        initialize=initialize,
+        handle_data=handle_data,
+        analyze=lambda _context, _performance: None,
+        capital_base=1_000.0,
+        bundle=bundle,
+        data_frequency="daily",
+    )
+
+
+class OpenPriceSlippage(slippage.SlippageModel):
+    """Explicit comparison protocol: next-session open with no volume cap."""
+
+    @staticmethod
+    def process_order(data: Any, order: Any) -> tuple[float, int]:
+        return data.current(order.asset, "open"), order.open_amount
+
+
+def _configure_open(_context: Any) -> None:
+    api.set_commission(commission.NoCommission())
+    api.set_slippage(OpenPriceSlippage())
+
+
+def _transactions(results: pd.DataFrame) -> list[dict[str, Any]]:
+    records: list[dict[str, Any]] = []
+    for transactions in results["transactions"]:
+        for transaction in transactions:
+            records.append(
+                {
+                    "amount": int(transaction["amount"]),
+                    "date": pd.Timestamp(transaction["dt"]).date().isoformat(),
+                    "price": float(transaction["price"]),
+                    "transaction_commission": float(transaction["commission"] or 0.0),
+                }
+            )
+    return records
+
+
+def _orders(results: pd.DataFrame) -> list[dict[str, Any]]:
+    records: list[dict[str, Any]] = []
+    for orders in results["orders"]:
+        for order in orders:
+            records.append(
+                {
+                    "amount": int(order["amount"]),
+                    "date": pd.Timestamp(order["dt"]).date().isoformat(),
+                    "filled": int(order["filled"]),
+                    "status": int(order["status"]),
+                }
+            )
+    return records
+
+
+def _submitted_amounts(results: pd.DataFrame) -> list[int]:
+    seen: set[str] = set()
+    amounts: list[int] = []
+    for orders in results["orders"]:
+        for order in orders:
+            order_id = str(order["id"])
+            if order_id not in seen:
+                seen.add(order_id)
+                amounts.append(int(order["amount"]))
+    return amounts
+
+
+def _default_models() -> dict[str, Any]:
+    broker = blotter_module.SimulationBlotter()
+    equity_type = importlib.import_module("zipline.assets").Equity
+    default_slippage = broker.slippage_models[equity_type]
+    default_commission = broker.commission_models[equity_type]
+    volume_share = slippage.VolumeShareSlippage()
+    return {
+        "commission_class": type(default_commission).__name__,
+        "commission_per_share": default_commission.cost_per_share,
+        "commission_minimum": default_commission.min_trade_cost,
+        "slippage_class": type(default_slippage).__name__,
+        "slippage_basis_points": default_slippage.basis_points,
+        "slippage_volume_limit": default_slippage.volume_limit,
+        "volume_share_price_impact": volume_share.price_impact,
+        "volume_share_volume_limit": volume_share.volume_limit,
+    }
+
+
+def _default_fill(bundle: str, frame: pd.DataFrame) -> dict[str, Any]:
+    results = _run(
+        bundle,
+        frame,
+        lambda _context: None,
+        lambda context, _data: api.order(context.asset, 1) if context.bar_number == 0 else None,
+    )
+    return {
+        "cash_after_fill": float(results["ending_cash"].iloc[1]),
+        "transactions": _transactions(results),
+    }
+
+
+def _explicit_minimum_commission(bundle: str, frame: pd.DataFrame) -> dict[str, Any]:
+    def configure(_context: Any) -> None:
+        api.set_commission(commission.PerShare(cost=0.005, min_trade_cost=1.0))
+        api.set_slippage(OpenPriceSlippage())
+
+    results = _run(
+        bundle,
+        frame,
+        configure,
+        lambda context, _data: api.order(context.asset, 1) if context.bar_number == 0 else None,
+    )
+    return {
+        "cash_after_fill": float(results["ending_cash"].iloc[1]),
+        "transactions": _transactions(results),
+    }
+
+
+def _open_fill(bundle: str, frame: pd.DataFrame) -> list[dict[str, Any]]:
+    results = _run(
+        bundle,
+        frame,
+        _configure_open,
+        lambda context, _data: api.order(context.asset, 1) if context.bar_number == 0 else None,
+    )
+    return _transactions(results)
+
+
+def _target_percent(bundle: str, frame: pd.DataFrame) -> dict[str, Any]:
+    results = _run(
+        bundle,
+        frame,
+        _configure_open,
+        lambda context, _data: api.order_target_percent(context.asset, 0.5)
+        if context.bar_number == 0
+        else None,
+    )
+    return {"orders": _orders(results), "transactions": _transactions(results)}
+
+
+def _target_percent_snapshot(bundle: str, frame: pd.DataFrame) -> dict[str, Any]:
+    def handle(context: Any, _data: Any) -> None:
+        if context.bar_number == 0:
+            api.order_target_percent(context.asset, 0.5)
+            api.order_target_percent(context.asset, 0.5)
+
+    results = _run(bundle, frame, _configure_open, handle)
+    return {
+        "submitted_amounts": _submitted_amounts(results),
+        "transactions": _transactions(results),
+    }
+
+
+def _submission_sequence(bundle: str, frame: pd.DataFrame) -> list[dict[str, Any]]:
+    def handle(context: Any, _data: Any) -> None:
+        if context.bar_number == 0:
+            api.order(context.asset, 1)
+            api.order(context.asset, -1)
+
+    return _transactions(_run(bundle, frame, _configure_open, handle))
+
+
+def _cash_and_short(bundle: str, frame: pd.DataFrame) -> dict[str, Any]:
+    long_results = _run(
+        bundle,
+        frame,
+        _configure_open,
+        lambda context, _data: api.order(context.asset, 20) if context.bar_number == 0 else None,
+    )
+    short_results = _run(
+        bundle,
+        frame,
+        _configure_open,
+        lambda context, _data: api.order(context.asset, -1) if context.bar_number == 0 else None,
+    )
+    return {
+        "long": {
+            "cash_after_fill": float(long_results["ending_cash"].iloc[1]),
+            "position_after_fill": int(long_results["positions"].iloc[1][0]["amount"]),
+            "transactions": _transactions(long_results),
+        },
+        "short": {
+            "cash_after_fill": float(short_results["ending_cash"].iloc[1]),
+            "position_after_fill": int(short_results["positions"].iloc[1][0]["amount"]),
+            "transactions": _transactions(short_results),
+        },
+    }
+
+
+def _volume_share_partial(bundle: str, frame: pd.DataFrame) -> list[dict[str, Any]]:
+    def configure(_context: Any) -> None:
+        api.set_commission(commission.NoCommission())
+        api.set_slippage(slippage.VolumeShareSlippage())
+
+    results = _run(
+        bundle,
+        frame,
+        configure,
+        lambda context, _data: api.order(context.asset, 5) if context.bar_number == 0 else None,
+    )
+    return _transactions(results)
+
+
+def _round_trip_records(bundle: str, frame: pd.DataFrame) -> dict[str, Any]:
+    def handle(context: Any, _data: Any) -> None:
+        if context.bar_number == 0:
+            api.order(context.asset, 2)
+        elif context.bar_number == 2:
+            api.order_target(context.asset, 0)
+
+    results = _run(bundle, frame, _configure_open, handle)
+    return {
+        "transactions": _transactions(results),
+        "native_output_columns": sorted(
+            column for column in ("orders", "positions", "transactions") if column in results
+        ),
+        "native_trade_column": "trades" in results,
+    }
+
+
+def _final_bar_order(bundle: str, frame: pd.DataFrame) -> list[dict[str, Any]]:
+    results = _run(
+        bundle,
+        frame,
+        _configure_open,
+        lambda context, _data: api.order(context.asset, 1)
+        if context.bar_number == len(frame) - 1
+        else None,
+    )
+    return _transactions(results)
+
+
+def _missing_bar(frame: pd.DataFrame) -> dict[str, Any]:
+    missing_frame = frame.copy()
+    missing_frame.loc[frame.index[2], ["open", "high", "low", "close"]] = float("nan")
+    missing_frame.loc[frame.index[2], "volume"] = 0.0
+    bundle = _setup_bundle(missing_frame, "ml4t_native_zipline_311_missing")
+
+    def handle(context: Any, data: Any) -> None:
+        api.record(
+            observed_close=data.current(context.asset, "close"),
+            observed_price=data.current(context.asset, "price"),
+            observed_stale=data.is_stale(context.asset),
+            observed_volume=data.current(context.asset, "volume"),
+        )
+        if context.bar_number == 1:
+            api.order(context.asset, 1)
+
+    results = _run(bundle, frame, _configure_open, handle)
+    observations = []
+    for date, row in results.iterrows():
+        observations.append(
+            {
+                "close": None if pd.isna(row["observed_close"]) else float(row["observed_close"]),
+                "date": pd.Timestamp(str(date)).date().isoformat(),
+                "price": None if pd.isna(row["observed_price"]) else float(row["observed_price"]),
+                "stale": bool(row["observed_stale"]),
+                "volume": float(row["observed_volume"]),
+            }
+        )
+    return {"observations": observations, "transactions": _transactions(results)}
+
+
+def _expected_missing_bar(frame: pd.DataFrame) -> dict[str, Any]:
+    observations = []
+    closes = [100.0, 120.0, None, 140.0, 150.0, 160.0, 170.0, 180.0]
+    prices = [100.0, 120.0, 120.0, 140.0, 150.0, 160.0, 170.0, 180.0]
+    for index, date in enumerate(frame.index):
+        observations.append(
+            {
+                "close": closes[index],
+                "date": date.date().isoformat(),
+                "price": prices[index],
+                "stale": index == 2,
+                "volume": 0.0 if index == 2 else 100.0,
+            }
+        )
+    return {
+        "observations": observations,
+        "transactions": [
+            {
+                "amount": 1,
+                "date": frame.index[3].date().isoformat(),
+                "price": 130.0,
+                "transaction_commission": 0.0,
+            }
+        ],
+    }
+
+
+def _equal(actual: Any, expected: Any) -> bool:
+    if isinstance(actual, float) and isinstance(expected, (float, int)):
+        return math.isclose(actual, float(expected), rel_tol=0.0, abs_tol=1e-10)
+    if isinstance(actual, list) and isinstance(expected, list) and len(actual) == len(expected):
+        return all(_equal(left, right) for left, right in zip(actual, expected, strict=True))
+    if isinstance(actual, dict) and isinstance(expected, dict) and actual.keys() == expected.keys():
+        return all(_equal(actual[key], expected[key]) for key in actual)
+    return bool(actual == expected)
+
+
+def run() -> dict[str, Any]:
+    actual_version = importlib.metadata.version("zipline-reloaded")
+    if actual_version != VERSION:
+        raise RuntimeError(f"zipline-reloaded version differs: {actual_version} != {VERSION}")
+
+    frame = _frame()
+    bundle = _setup_bundle(frame, "ml4t_native_zipline_311")
+    measurements = [
+        (
+            "defaults",
+            _default_models(),
+            {
+                "commission_class": "PerShare",
+                "commission_per_share": 0.001,
+                "commission_minimum": 0,
+                "slippage_class": "FixedBasisPointsSlippage",
+                "slippage_basis_points": 5.0,
+                "slippage_volume_limit": 0.1,
+                "volume_share_price_impact": 0.1,
+                "volume_share_volume_limit": 0.025,
+            },
+        ),
+        (
+            "default_next_bar_close_fill",
+            _default_fill(bundle, frame),
+            {
+                "cash_after_fill": 879.9390000000001,
+                "transactions": [
+                    {
+                        "amount": 1,
+                        "date": frame.index[1].date().isoformat(),
+                        "price": 120.06,
+                        "transaction_commission": 0.0,
+                    }
+                ],
+            },
+        ),
+        (
+            "configured_next_bar_open_fill",
+            _open_fill(bundle, frame),
+            [
+                {
+                    "amount": 1,
+                    "date": frame.index[1].date().isoformat(),
+                    "price": 110.0,
+                    "transaction_commission": 0.0,
+                }
+            ],
+        ),
+        (
+            "explicit_minimum_commission",
+            _explicit_minimum_commission(bundle, frame),
+            {
+                "cash_after_fill": 889.0,
+                "transactions": [
+                    {
+                        "amount": 1,
+                        "date": frame.index[1].date().isoformat(),
+                        "price": 110.0,
+                        "transaction_commission": 0.0,
+                    }
+                ],
+            },
+        ),
+        (
+            "integer_target_percent",
+            _target_percent(bundle, frame),
+            {
+                "orders": [
+                    {
+                        "amount": 5,
+                        "date": frame.index[0].date().isoformat(),
+                        "filled": 0,
+                        "status": 0,
+                    },
+                    {
+                        "amount": 5,
+                        "date": frame.index[1].date().isoformat(),
+                        "filled": 5,
+                        "status": 1,
+                    },
+                ],
+                "transactions": [
+                    {
+                        "amount": 5,
+                        "date": frame.index[1].date().isoformat(),
+                        "price": 110.0,
+                        "transaction_commission": 0.0,
+                    }
+                ],
+            },
+        ),
+        (
+            "target_percent_snapshot",
+            _target_percent_snapshot(bundle, frame),
+            {
+                "submitted_amounts": [5, 5],
+                "transactions": [
+                    {
+                        "amount": 5,
+                        "date": frame.index[1].date().isoformat(),
+                        "price": 110.0,
+                        "transaction_commission": 0.0,
+                    },
+                    {
+                        "amount": 5,
+                        "date": frame.index[1].date().isoformat(),
+                        "price": 110.0,
+                        "transaction_commission": 0.0,
+                    },
+                ],
+            },
+        ),
+        (
+            "submission_sequence",
+            _submission_sequence(bundle, frame),
+            [
+                {
+                    "amount": 1,
+                    "date": frame.index[1].date().isoformat(),
+                    "price": 110.0,
+                    "transaction_commission": 0.0,
+                },
+                {
+                    "amount": -1,
+                    "date": frame.index[1].date().isoformat(),
+                    "price": 110.0,
+                    "transaction_commission": 0.0,
+                },
+            ],
+        ),
+        (
+            "cash_and_short_proceeds",
+            _cash_and_short(bundle, frame),
+            {
+                "long": {
+                    "cash_after_fill": -1_200.0,
+                    "position_after_fill": 20,
+                    "transactions": [
+                        {
+                            "amount": 20,
+                            "date": frame.index[1].date().isoformat(),
+                            "price": 110.0,
+                            "transaction_commission": 0.0,
+                        }
+                    ],
+                },
+                "short": {
+                    "cash_after_fill": 1_110.0,
+                    "position_after_fill": -1,
+                    "transactions": [
+                        {
+                            "amount": -1,
+                            "date": frame.index[1].date().isoformat(),
+                            "price": 110.0,
+                            "transaction_commission": 0.0,
+                        }
+                    ],
+                },
+            },
+        ),
+        (
+            "volume_share_partial_fills",
+            _volume_share_partial(bundle, frame),
+            [
+                {
+                    "amount": 2,
+                    "date": frame.index[1].date().isoformat(),
+                    "price": 120.0048,
+                    "transaction_commission": 0.0,
+                },
+                {
+                    "amount": 2,
+                    "date": frame.index[2].date().isoformat(),
+                    "price": 130.0052,
+                    "transaction_commission": 0.0,
+                },
+                {
+                    "amount": 1,
+                    "date": frame.index[3].date().isoformat(),
+                    "price": 140.0014,
+                    "transaction_commission": 0.0,
+                },
+            ],
+        ),
+        (
+            "transaction_records_not_native_trades",
+            _round_trip_records(bundle, frame),
+            {
+                "transactions": [
+                    {
+                        "amount": 2,
+                        "date": frame.index[1].date().isoformat(),
+                        "price": 110.0,
+                        "transaction_commission": 0.0,
+                    },
+                    {
+                        "amount": -2,
+                        "date": frame.index[3].date().isoformat(),
+                        "price": 130.0,
+                        "transaction_commission": 0.0,
+                    },
+                ],
+                "native_output_columns": ["orders", "positions", "transactions"],
+                "native_trade_column": False,
+            },
+        ),
+        ("final_bar_market_order", _final_bar_order(bundle, frame), []),
+        (
+            "session_calendar",
+            [date.date().isoformat() for date in frame.index],
+            [
+                "2024-01-02",
+                "2024-01-03",
+                "2024-01-04",
+                "2024-01-05",
+                "2024-01-08",
+                "2024-01-09",
+                "2024-01-10",
+                "2024-01-11",
+            ],
+        ),
+        ("missing_bar", _missing_bar(frame), _expected_missing_bar(frame)),
+    ]
+    checks = [
+        {"id": check_id, "actual": actual, "expected": expected, "passed": _equal(actual, expected)}
+        for check_id, actual, expected in measurements
+    ]
+    return {
+        "schema_version": 1,
+        "framework": "zipline",
+        "package": "zipline-reloaded",
+        "version": actual_version,
+        "source_commit": COMMIT,
+        "artifact": ARTIFACT,
+        "artifact_sha256": ARTIFACT_SHA256,
+        "oracle_sha256": hashlib.sha256(Path(__file__).read_bytes()).hexdigest(),
+        "comparison_protocol": {
+            "commission": "NoCommission",
+            "execution": "next-session custom OpenPriceSlippage",
+            "risk_rules": "adapter-emulated from daily OHLC; not Zipline native trade records",
+            "slippage": "no volume cap unless a scenario explicitly configures slippage",
+        },
+        "source_locations": {
+            "algorithm_target_percent": _source_location(
+                algorithm_module.TradingAlgorithm.order_target_percent
+            ),
+            "commission": _source_location(commission.PerShare.__init__),
+            "default_blotter": _source_location(blotter_module.SimulationBlotter.__init__),
+            "fixed_basis_points": _source_location(slippage.FixedBasisPointsSlippage.process_order),
+            "volume_share": _source_location(slippage.VolumeShareSlippage.process_order),
+        },
+        "checks": checks,
+        "passed": all(check["passed"] for check in checks),
+    }
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--output", type=Path, required=True)
+    args = parser.parse_args()
+    warnings.filterwarnings(
+        "ignore",
+        message="DataFrameGroupBy.apply operated on the grouping columns.*",
+        category=FutureWarning,
+    )
+    warnings.filterwarnings(
+        "ignore",
+        message="Ignoring 4 values because they are out of bounds for uint32.*",
+        category=UserWarning,
+    )
+    try:
+        evidence = run()
+    except (ImportError, OSError, RuntimeError, TypeError, ValueError) as error:
+        print(f"Zipline native behavior run failed: {error}", file=sys.stderr)
+        return 2
+    args.output.parent.mkdir(parents=True, exist_ok=True)
+    args.output.write_text(json.dumps(evidence, indent=2, sort_keys=True) + "\n", encoding="utf-8")
+    failed = [check["id"] for check in evidence["checks"] if not check["passed"]]
+    if failed:
+        print(f"Zipline native behavior differs: {failed}", file=sys.stderr)
+        return 1
+    print(f"Zipline native behavior passed: {len(evidence['checks'])} checks")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/real_strategy_applicability.toml b/validation/real_strategy_applicability.toml
new file mode 100644
index 00000000..70d8ce80
--- /dev/null
+++ b/validation/real_strategy_applicability.toml
@@ -0,0 +1,109 @@
+[metadata]
+schema_version = 1
+frameworks = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline", "lean"]
+case_studies = ["etfs", "cme_futures", "crypto_perps_funding"]
+
+[[pair]]
+case_study = "etfs"
+framework = "vectorbt_pro"
+status = "required"
+native_contract = "multi-asset target allocation and cash sharing"
+source = "https://vectorbt.pro/features/portfolio/"
+
+[[pair]]
+case_study = "etfs"
+framework = "vectorbt_oss"
+status = "required"
+native_contract = "multi-asset target allocation and cash sharing"
+source = "https://vectorbt.dev/api/portfolio/base/"
+
+[[pair]]
+case_study = "etfs"
+framework = "backtrader"
+status = "required"
+native_contract = "multi-data target-percent orders"
+source = "https://www.backtrader.com/docu/order_target/order_target/"
+
+[[pair]]
+case_study = "etfs"
+framework = "zipline"
+status = "required"
+native_contract = "equity assets and target-percent orders"
+source = "https://zipline.ml4trading.io/api-reference.html"
+
+[[pair]]
+case_study = "etfs"
+framework = "lean"
+status = "required"
+native_contract = "equity margin accounts and market-on-open orders"
+source = "https://www.quantconnect.com/docs/v2/writing-algorithms/trading-and-orders/position-sizing"
+
+[[pair]]
+case_study = "cme_futures"
+framework = "vectorbt_pro"
+status = "required"
+native_contract = "contract multipliers and eager leverage on target-percent orders"
+source = "https://vectorbt.pro/features/portfolio/"
+
+[[pair]]
+case_study = "cme_futures"
+framework = "vectorbt_oss"
+status = "unsupported"
+native_contract = "no native futures contract multiplier and margin-account model"
+source = "https://vectorbt.dev/api/portfolio/base/"
+
+[[pair]]
+case_study = "cme_futures"
+framework = "backtrader"
+status = "required"
+native_contract = "futures-like commission scheme with margin and contract multiplier"
+source = "https://www.backtrader.com/docu/commission-schemes/commission-schemes/"
+
+[[pair]]
+case_study = "cme_futures"
+framework = "zipline"
+status = "unsupported"
+native_contract = "the frozen workload has continuous root series but no dated contract chain or roll map"
+source = "https://zipline.ml4trading.io/api-reference.html"
+
+[[pair]]
+case_study = "cme_futures"
+framework = "lean"
+status = "unsupported"
+native_contract = "the frozen workload has continuous root series but no dated contract chain or roll map"
+source = "https://www.quantconnect.com/docs/v2/writing-algorithms/securities/asset-classes/futures"
+
+[[pair]]
+case_study = "crypto_perps_funding"
+framework = "vectorbt_pro"
+status = "unsupported"
+native_contract = "no native perpetual-futures funding and margin-account model"
+source = "https://vectorbt.pro/features/portfolio/"
+
+[[pair]]
+case_study = "crypto_perps_funding"
+framework = "vectorbt_oss"
+status = "unsupported"
+native_contract = "no native perpetual-futures funding and margin-account model"
+source = "https://vectorbt.dev/api/portfolio/base/"
+
+[[pair]]
+case_study = "crypto_perps_funding"
+framework = "backtrader"
+status = "unsupported"
+native_contract = "no native perpetual-futures funding model"
+source = "https://www.backtrader.com/docu/commission-schemes/commission-schemes/"
+
+[[pair]]
+case_study = "crypto_perps_funding"
+framework = "zipline"
+status = "unsupported"
+native_contract = "no crypto perpetual-futures asset and funding model"
+source = "https://zipline.ml4trading.io/api-reference.html"
+
+[[pair]]
+case_study = "crypto_perps_funding"
+framework = "lean"
+status = "required"
+native_contract = "CryptoFuture securities with scheduled funding debits and credits"
+source = "https://www.quantconnect.com/docs/v2/writing-algorithms/reality-modeling/margin-interest-rate/supported-models"
diff --git a/validation/real_strategy_backtrader.py b/validation/real_strategy_backtrader.py
new file mode 100644
index 00000000..2b6d3ae3
--- /dev/null
+++ b/validation/real_strategy_backtrader.py
@@ -0,0 +1,246 @@
+#!/usr/bin/env python3
+"""Run a frozen real target-allocation workload with Backtrader."""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+import os
+import tempfile
+import time
+from pathlib import Path
+from typing import Any
+
+import backtrader as bt
+import pandas as pd
+import polars as pl
+
+
+def _sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as stream:
+        for chunk in iter(lambda: stream.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def _target_map(targets: pl.DataFrame) -> dict[pd.Timestamp, dict[str, float]]:
+    result: dict[pd.Timestamp, dict[str, float]] = {}
+    for row in targets.sort("timestamp", "symbol").iter_rows(named=True):
+        result.setdefault(pd.Timestamp(row["timestamp"]), {})[str(row["symbol"])] = float(
+            row["weight"]
+        )
+    return result
+
+
+class FrozenTargetStrategy(bt.Strategy):
+    params = (("targets", None), ("contracts", None))
+
+    def __init__(self) -> None:
+        self.fills: list[dict[str, Any]] = []
+        self.equity: list[dict[str, Any]] = []
+        self.rejections: list[dict[str, Any]] = []
+
+    def prenext(self) -> None:
+        self.next()
+
+    def nextstart(self) -> None:
+        self.next()
+
+    def next(self) -> None:
+        timestamp = pd.Timestamp(self.datetime.datetime(0))
+        self.equity.append(
+            {"timestamp": timestamp.to_pydatetime(), "equity": self.broker.getvalue()}
+        )
+        requested = self.p.targets.get(timestamp)
+        if requested is None:
+            return
+        available = {
+            data._name: weight
+            for data in self.datas
+            if data._name in requested and pd.Timestamp(data.datetime.datetime(0)) == timestamp
+            for weight in (requested[data._name],)
+        }
+        if not available:
+            return
+        value = self.broker.getvalue()
+        current = {
+            data._name: (
+                self.getposition(data).size
+                * float(data.close[0])
+                * float(self.p.contracts.get(data._name, {}).get("multiplier", 1.0))
+                / value
+            )
+            for data in self.datas
+            if self.getposition(data).size != 0
+        }
+        reductions = sorted(
+            symbol for symbol, weight in available.items() if weight < current.get(symbol, 0.0)
+        )
+        omitted = sorted(symbol for symbol in current if symbol not in available)
+        increases = sorted(symbol for symbol in available if symbol not in reductions)
+        by_name = {data._name: data for data in self.datas}
+        for symbol in reductions:
+            self._submit_target(by_name[symbol], available[symbol], current, value)
+        for symbol in omitted:
+            self.order_target_size(data=by_name[symbol], target=0)
+        for symbol in increases:
+            self._submit_target(by_name[symbol], available[symbol], current, value)
+
+    def _submit_target(
+        self, data, target_weight: float, current_weights: dict[str, float], value: float
+    ) -> None:
+        contract = self.p.contracts.get(data._name)
+        if contract is None:
+            self.order_target_percent(data=data, target=target_weight)
+            return
+        price = float(data.close[0])
+        multiplier = float(contract["multiplier"])
+        delta = int(
+            (target_weight - current_weights.get(data._name, 0.0)) * value / (price * multiplier)
+        )
+        target_size = self.getposition(data).size + delta
+        self.order_target_size(data=data, target=target_size)
+
+    def notify_order(self, order) -> None:
+        if order.status == order.Completed:
+            self.fills.append(
+                {
+                    "timestamp": bt.num2date(order.executed.dt).replace(tzinfo=None),
+                    "asset": order.data._name,
+                    "side": "buy" if order.isbuy() else "sell",
+                    "quantity": abs(float(order.executed.size)),
+                    "price": float(order.executed.price),
+                    "commission": abs(float(order.executed.comm)),
+                }
+            )
+        elif order.status in {order.Canceled, order.Margin, order.Rejected}:
+            self.rejections.append(
+                {
+                    "timestamp": bt.num2date(order.created.dt).replace(tzinfo=None),
+                    "asset": order.data._name,
+                    "status": order.getstatusname(),
+                    "requested_quantity": abs(float(order.created.size)),
+                }
+            )
+
+
+def run(bundle: Path) -> tuple[dict[str, Any], pl.DataFrame, pl.DataFrame, pl.DataFrame]:
+    manifest = json.loads((bundle / "manifest.json").read_text(encoding="utf-8"))
+    spec = json.loads((bundle / "spec.json").read_text(encoding="utf-8"))
+    market = pl.read_parquet(bundle / "market.parquet")
+    targets = _target_map(pl.read_parquet(bundle / "targets.parquet"))
+    contracts = (
+        json.loads((bundle / "contracts.json").read_text(encoding="utf-8"))
+        if (bundle / "contracts.json").is_file()
+        else {}
+    )
+    cerebro = bt.Cerebro(stdstats=False)
+    initial_cash = float(spec["backtest_config"]["cash"]["initial"])
+    cerebro.broker.setcash(initial_cash)
+    cerebro.broker.setcommission(commission=0.0)
+    for symbol in market["symbol"].unique().sort().to_list():
+        selected = market.filter(pl.col("symbol") == symbol).select(
+            "timestamp", "open", "high", "low", "close", "volume"
+        )
+        frame = pd.DataFrame(selected.to_dict(as_series=False)).set_index("timestamp")
+        cerebro.adddata(bt.feeds.PandasData(dataname=frame), name=symbol)
+        contract = contracts.get(symbol)
+        if contract is not None:
+            initial_margin, _ = contract["margin_pct"]
+            fixed_margin = (
+                float(frame["close"].iloc[0])
+                * float(contract["multiplier"])
+                * float(initial_margin)
+            )
+            cerebro.broker.addcommissioninfo(
+                bt.CommInfoBase(
+                    commission=0.0,
+                    mult=float(contract["multiplier"]),
+                    margin=fixed_margin,
+                    automargin=False,
+                    commtype=bt.CommInfoBase.COMM_FIXED,
+                    stocklike=False,
+                ),
+                name=symbol,
+            )
+    cerebro.addstrategy(FrozenTargetStrategy, targets=targets, contracts=contracts)
+    started = time.perf_counter()
+    strategy = cerebro.run()[0]
+    engine_seconds = time.perf_counter() - started
+    fills = pl.DataFrame(strategy.fills)
+    equity = pl.DataFrame(strategy.equity)
+    evidence = {
+        "schema_version": 1,
+        "case_study": manifest["case_study"],
+        "framework": "backtrader",
+        "comparison_profile": "backtrader_strict",
+        "comparison_costs": "disabled",
+        "comparison_position_rules": "disabled",
+        "input_bundle_sha256": manifest["bundle_sha256"],
+        "engine_seconds": engine_seconds,
+        "final_value": float(cerebro.broker.getvalue()),
+        "num_fills": fills.height,
+        "num_rejections": len(strategy.rejections),
+    }
+    rejections = pl.DataFrame(
+        strategy.rejections,
+        schema={
+            "timestamp": pl.Datetime("us"),
+            "asset": pl.String,
+            "status": pl.String,
+            "requested_quantity": pl.Float64,
+        },
+    )
+    return evidence, fills, equity, rejections
+
+
+def write_evidence(
+    output: Path,
+    evidence: dict[str, Any],
+    fills: pl.DataFrame,
+    equity: pl.DataFrame,
+    rejections: pl.DataFrame,
+) -> None:
+    output.parent.mkdir(parents=True, exist_ok=True)
+    staging = Path(tempfile.mkdtemp(prefix=f".{output.name}.", dir=output.parent))
+    try:
+        fills.write_parquet(staging / "fills.parquet", compression="zstd", statistics=True)
+        equity.write_parquet(staging / "equity.parquet", compression="zstd", statistics=True)
+        rejections.write_parquet(
+            staging / "rejected_orders.parquet", compression="zstd", statistics=True
+        )
+        evidence["files"] = {
+            path.name: {"sha256": _sha256(path), "bytes": path.stat().st_size}
+            for path in sorted(staging.iterdir())
+        }
+        (staging / "manifest.json").write_text(
+            json.dumps(evidence, indent=2, sort_keys=True) + "\n", encoding="utf-8"
+        )
+        if output.exists():
+            raise FileExistsError(f"Evidence output already exists: {output}")
+        os.replace(staging, output)
+    finally:
+        if staging.exists():
+            for path in staging.iterdir():
+                path.unlink()
+            staging.rmdir()
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--bundle", type=Path, required=True)
+    parser.add_argument("--output", type=Path, required=True)
+    args = parser.parse_args()
+    evidence, fills, equity, rejections = run(args.bundle.resolve())
+    write_evidence(args.output.resolve(), evidence, fills, equity, rejections)
+    print(
+        f"{evidence['case_study']}: {evidence['num_fills']:,} fills, "
+        f"{evidence['engine_seconds']:.6f}s engine time"
+    )
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/real_strategy_benchmark.py b/validation/real_strategy_benchmark.py
new file mode 100644
index 00000000..db3183c4
--- /dev/null
+++ b/validation/real_strategy_benchmark.py
@@ -0,0 +1,280 @@
+#!/usr/bin/env python3
+"""Measure engine-only runtimes for correctness-passing real-strategy pairs."""
+
+from __future__ import annotations
+
+import argparse
+import json
+import os
+import platform
+import random
+import statistics
+import subprocess
+import tempfile
+import tomllib
+from datetime import UTC, datetime
+from pathlib import Path
+from typing import Any
+
+PROJECT_ROOT = Path(__file__).resolve().parents[1]
+VALIDATION_DIR = PROJECT_ROOT / "validation"
+BUNDLES = {
+    "etfs": "01f38079ce47821a5379d3769e86f4a2170b88033108153bfc0f928698e946db",
+    "cme_futures": "c7191027f550ef1be0c9528dac08e7c2bf6a76c86d935f593efeb1ad8b628c39",
+    "crypto_perps_funding": "2acee3c8542043266e6f9c0dfc9434c95b4469ef6fcaf0556efc569fc9721cdd",
+}
+PYTHONS = {
+    "ml4t": ".venv/bin/python",
+    "vectorbt_pro": ".venv-vectorbt-pro/bin/python",
+    "vectorbt_oss": ".venv-vectorbt-oss/bin/python",
+    "backtrader": ".venv-backtrader/bin/python",
+    "zipline": ".venv-zipline/bin/python",
+    "lean": ".venv/bin/python",
+}
+PROFILES = {
+    ("etfs", "vectorbt_pro"): ("vectorbt_strict", []),
+    ("etfs", "vectorbt_oss"): ("vectorbt_oss_strict", []),
+    ("etfs", "backtrader"): ("backtrader_strict", []),
+    ("etfs", "zipline"): ("zipline_strict", ["--price-decimals", "3"]),
+    ("etfs", "lean"): ("lean", ["--price-decimals", "4"]),
+    ("cme_futures", "vectorbt_pro"): ("vectorbt_strict", []),
+    ("cme_futures", "backtrader"): ("backtrader_strict", []),
+    (
+        "crypto_perps_funding",
+        "lean",
+    ): (
+        "lean_crypto_future",
+        [
+            "--execution-specs",
+            "validation/lean/workspace/real_strategy_crypto_perps_funding/symbol_properties.json",
+        ],
+    ),
+}
+ADAPTERS = {
+    "vectorbt_pro": ("real_strategy_vectorbt.py", ["--framework", "vectorbt_pro"]),
+    "vectorbt_oss": ("real_strategy_vectorbt.py", ["--framework", "vectorbt_oss"]),
+    "backtrader": ("real_strategy_backtrader.py", []),
+    "zipline": ("real_strategy_zipline.py", []),
+    "lean": ("real_strategy_lean.py", []),
+}
+
+
+def bootstrap_median_interval(
+    values: list[float], *, draws: int = 10_000, seed: int = 20260814
+) -> tuple[float, float]:
+    """Return the percentile bootstrap 95 percent interval for a sample median."""
+    if not values:
+        raise ValueError("Cannot bootstrap an empty timing sample")
+    generator = random.Random(seed)
+    medians = sorted(
+        statistics.median(generator.choices(values, k=len(values))) for _ in range(draws)
+    )
+    return medians[int(0.025 * draws)], medians[int(0.975 * draws)]
+
+
+def _command(
+    *, side: str, case_study: str, framework: str, bundle: Path, output: Path
+) -> list[str]:
+    python = PROJECT_ROOT / PYTHONS[framework if side == "framework" else "ml4t"]
+    if side == "framework":
+        script, extra = ADAPTERS[framework]
+        if case_study == "crypto_perps_funding":
+            script = "real_strategy_lean_crypto.py"
+        return [
+            str(python),
+            str(VALIDATION_DIR / script),
+            "--bundle",
+            str(bundle),
+            "--output",
+            str(output),
+            *extra,
+        ]
+    profile, extra = PROFILES[(case_study, framework)]
+    return [
+        str(python),
+        str(VALIDATION_DIR / "real_strategy_runner.py"),
+        "--bundle",
+        str(bundle),
+        "--output",
+        str(output),
+        "--comparison-profile",
+        profile,
+        *extra,
+    ]
+
+
+def _output_identity(manifest: dict[str, Any]) -> dict[str, str]:
+    retained = {"fills.parquet", "equity.parquet", "rejected_orders.parquet"}
+    return {
+        name: identity["sha256"] for name, identity in manifest["files"].items() if name in retained
+    }
+
+
+def _run_once(command: list[str], output: Path) -> tuple[float, dict[str, str]]:
+    completed = subprocess.run(
+        command,
+        cwd=PROJECT_ROOT,
+        check=False,
+        capture_output=True,
+        text=True,
+        timeout=600,
+    )
+    if completed.returncode != 0:
+        detail = (completed.stderr or completed.stdout).strip()
+        raise RuntimeError(f"Benchmark subprocess failed: {detail[-1000:]}")
+    manifest = json.loads((output / "manifest.json").read_text(encoding="utf-8"))
+    return float(manifest["engine_seconds"]), _output_identity(manifest)
+
+
+def _measure_side(
+    *,
+    side: str,
+    case_study: str,
+    framework: str,
+    bundle: Path,
+    warmups: int,
+    samples: int,
+) -> dict[str, Any]:
+    timings: list[float] = []
+    identity: dict[str, str] | None = None
+    with tempfile.TemporaryDirectory(prefix="ml4t-real-benchmark-") as temporary:
+        temporary_root = Path(temporary)
+        for index in range(warmups + samples):
+            output = temporary_root / f"run-{index}"
+            command = _command(
+                side=side,
+                case_study=case_study,
+                framework=framework,
+                bundle=bundle,
+                output=output,
+            )
+            runtime, current_identity = _run_once(command, output)
+            if identity is None:
+                identity = current_identity
+            elif current_identity != identity:
+                raise RuntimeError(
+                    f"Output changed across repetitions for {case_study}/{framework}/{side}"
+                )
+            if index >= warmups:
+                timings.append(runtime)
+    lower, upper = bootstrap_median_interval(timings)
+    return {
+        "samples_seconds": timings,
+        "median_seconds": statistics.median(timings),
+        "ci_95_seconds": [lower, upper],
+        "minimum_seconds": min(timings),
+        "maximum_seconds": max(timings),
+        "output_identity": identity,
+    }
+
+
+def build_report(
+    *,
+    correctness: dict[str, Any],
+    bundle_root: Path,
+    warmups: int,
+    samples: int,
+) -> dict[str, Any]:
+    """Measure every pair that passed the supplied correctness evidence."""
+    passing = [record for record in correctness["records"] if record["status"] == "pass"]
+    records: list[dict[str, object]] = []
+    for index, pair in enumerate(passing, start=1):
+        case_study = pair["case_study"]
+        framework = pair["framework"]
+        print(f"Timing {index}/{len(passing)} {case_study}/{framework}", flush=True)
+        bundle = bundle_root / case_study / BUNDLES[case_study]
+        framework_result = _measure_side(
+            side="framework",
+            case_study=case_study,
+            framework=framework,
+            bundle=bundle,
+            warmups=warmups,
+            samples=samples,
+        )
+        ml4t_result = _measure_side(
+            side="ml4t",
+            case_study=case_study,
+            framework=framework,
+            bundle=bundle,
+            warmups=warmups,
+            samples=samples,
+        )
+        records.append(
+            {
+                "case_study": case_study,
+                "framework": framework,
+                "input_bundle_sha256": pair["input_bundle_sha256"],
+                "correctness_status": "pass",
+                "framework_engine": framework_result,
+                "ml4t_engine": ml4t_result,
+                "framework_to_ml4t_median_ratio": (
+                    framework_result["median_seconds"] / ml4t_result["median_seconds"]
+                ),
+            }
+        )
+    targets = tomllib.loads((VALIDATION_DIR / "framework_targets.toml").read_text())
+    return {
+        "schema_version": 1,
+        "generated_at": datetime.now(UTC).isoformat(),
+        "timing_policy": {
+            "boundary": "engine call only",
+            "excluded": [
+                "input loading",
+                "model inference",
+                "target construction",
+                "adapter preparation",
+                "result extraction",
+                "serialization",
+                "reporting",
+            ],
+            "warmup_processes": warmups,
+            "measured_processes": samples,
+            "process_isolation": True,
+            "interval": "10,000-draw percentile bootstrap of the sample median",
+            "publication_scope": "only correctness-passing case-study/framework pairs",
+        },
+        "environment": {
+            "platform": platform.platform(),
+            "machine": platform.machine(),
+            "processor": platform.processor(),
+            "cpu_count": os.cpu_count(),
+            "frameworks": targets["framework"],
+        },
+        "correctness_evidence_generated_at": correctness["generated_at"],
+        "records": records,
+    }
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--correctness",
+        type=Path,
+        default=VALIDATION_DIR / "candidates/REAL_STRATEGY_RESULTS.candidate.json",
+    )
+    parser.add_argument("--bundle-root", type=Path, required=True)
+    parser.add_argument(
+        "--output",
+        type=Path,
+        default=VALIDATION_DIR / "candidates/REAL_STRATEGY_PERFORMANCE.candidate.json",
+    )
+    parser.add_argument("--warmups", type=int, default=1)
+    parser.add_argument("--samples", type=int, default=10)
+    args = parser.parse_args()
+    if args.warmups < 1 or args.samples < 10:
+        raise ValueError("Benchmarks require at least one warmup and ten measured processes")
+    correctness = json.loads(args.correctness.read_text(encoding="utf-8"))
+    report = build_report(
+        correctness=correctness,
+        bundle_root=args.bundle_root.resolve(),
+        warmups=args.warmups,
+        samples=args.samples,
+    )
+    args.output.parent.mkdir(parents=True, exist_ok=True)
+    args.output.write_text(json.dumps(report, indent=2, sort_keys=True) + "\n", encoding="utf-8")
+    print(f"Retained {len(report['records'])} timing comparisons: {args.output}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/real_strategy_cases.toml b/validation/real_strategy_cases.toml
new file mode 100644
index 00000000..206ce892
--- /dev/null
+++ b/validation/real_strategy_cases.toml
@@ -0,0 +1,34 @@
+[metadata]
+schema_version = 1
+selection = "current canonical validation rank-1"
+source = "ml4t/public case-study registry and artifacts"
+
+[[case]]
+id = "cme_futures"
+asset_class = "futures"
+production_path = "event_driven"
+warmup = true
+timestamp_shift_hours = 0
+contract_specs = true
+funding = false
+required_backtest_artifacts = ["daily_returns.parquet", "equity.parquet", "fills.parquet", "portfolio_state.parquet", "spec.json", "trades.parquet", "weights.parquet"]
+
+[[case]]
+id = "crypto_perps_funding"
+asset_class = "crypto_perpetual_futures"
+production_path = "event_driven"
+warmup = true
+timestamp_shift_hours = 8
+contract_specs = false
+funding = true
+required_backtest_artifacts = ["daily_returns.parquet", "equity.parquet", "fills.parquet", "portfolio_state.parquet", "spec.json", "trades.parquet", "weights.parquet"]
+
+[[case]]
+id = "etfs"
+asset_class = "etf"
+production_path = "event_driven"
+warmup = false
+timestamp_shift_hours = 0
+contract_specs = false
+funding = false
+required_backtest_artifacts = ["daily_returns.parquet", "equity.parquet", "fills.parquet", "portfolio_state.parquet", "spec.json", "trades.parquet", "weights.parquet"]
diff --git a/validation/real_strategy_corpus.py b/validation/real_strategy_corpus.py
new file mode 100644
index 00000000..faa1c532
--- /dev/null
+++ b/validation/real_strategy_corpus.py
@@ -0,0 +1,546 @@
+#!/usr/bin/env python3
+"""Inventory the current canonical real-strategy corpus without rerunning a backtest."""
+
+from __future__ import annotations
+
+import argparse
+import dataclasses
+import enum
+import gc
+import hashlib
+import importlib
+import json
+import os
+import subprocess
+import sys
+import tempfile
+import tomllib
+from collections.abc import Callable, Mapping
+from datetime import UTC, datetime
+from pathlib import Path
+from typing import Any, cast
+
+import polars as pl
+
+VALIDATION_DIR = Path(__file__).parent
+PROJECT_ROOT = VALIDATION_DIR.parent
+DEFAULT_CASES_PATH = VALIDATION_DIR / "real_strategy_cases.toml"
+SCHEMA_VERSION = 1
+
+
+def file_digest(path: Path) -> str:
+    """Return a streaming SHA-256 digest for an artifact."""
+    digest = hashlib.sha256()
+    with path.open("rb") as stream:
+        for chunk in iter(lambda: stream.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def git_identity(root: Path) -> dict[str, object]:
+    """Return the full commit and tracked-file status for a repository."""
+    commit = subprocess.run(
+        ["git", "-C", str(root), "rev-parse", "HEAD"],
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout.strip()
+    status = subprocess.run(
+        ["git", "-C", str(root), "status", "--porcelain", "--untracked-files=no"],
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout
+    return {"commit": commit, "dirty": bool(status.strip())}
+
+
+def load_case_contract(path: Path = DEFAULT_CASES_PATH) -> list[dict[str, Any]]:
+    """Load and validate the bounded real-strategy corpus contract."""
+    payload = tomllib.loads(path.read_text(encoding="utf-8"))
+    metadata = payload.get("metadata")
+    if not isinstance(metadata, dict) or metadata.get("schema_version") != SCHEMA_VERSION:
+        raise ValueError("Unsupported real-strategy case contract schema")
+    cases = payload.get("case")
+    if not isinstance(cases, list):
+        raise ValueError("Real-strategy case contract must contain [[case]] records")
+    required_keys = {
+        "id",
+        "asset_class",
+        "production_path",
+        "required_backtest_artifacts",
+        "warmup",
+        "timestamp_shift_hours",
+        "contract_specs",
+        "funding",
+    }
+    case_ids: list[str] = []
+    for index, case in enumerate(cases):
+        if not isinstance(case, dict) or not required_keys <= case.keys():
+            raise ValueError(f"Invalid real-strategy case contract record {index}")
+        if case["production_path"] not in {"event_driven", "vectorized"}:
+            raise ValueError(f"Invalid production path for {case['id']}")
+        if not isinstance(case["required_backtest_artifacts"], list):
+            raise ValueError(f"Invalid artifact list for {case['id']}")
+        case_ids.append(str(case["id"]))
+    if not 3 <= len(case_ids) <= 5 or len(set(case_ids)) != len(case_ids):
+        raise ValueError("Real-strategy corpus must contain three to five unique case studies")
+    return cases
+
+
+def _parquet_identity(path: Path) -> dict[str, object]:
+    schema = pl.scan_parquet(path).collect_schema()
+    count_frame = cast(
+        pl.DataFrame,
+        pl.scan_parquet(path).select(pl.len().alias("row_count")).collect(engine="streaming"),
+    )
+    row_count = int(count_frame["row_count"][0])
+    return {
+        "sha256": file_digest(path),
+        "bytes": path.stat().st_size,
+        "rows": int(row_count),
+        "schema": {name: str(dtype) for name, dtype in schema.items()},
+    }
+
+
+def _artifact_identity(path: Path) -> dict[str, object]:
+    identity: dict[str, object] = {
+        "sha256": file_digest(path),
+        "bytes": path.stat().st_size,
+    }
+    if path.suffix == ".parquet":
+        identity.update(_parquet_identity(path))
+    return identity
+
+
+def _strategy_summary(spec: Mapping[str, Any]) -> dict[str, object]:
+    strategy = spec.get("strategy")
+    backtest = spec.get("backtest_config")
+    if not isinstance(strategy, Mapping) or not isinstance(backtest, Mapping):
+        raise ValueError("Selected backtest spec lacks strategy or backtest_config")
+    execution = backtest.get("execution")
+    commission = backtest.get("commission")
+    slippage = backtest.get("slippage")
+    sizing = backtest.get("position_sizing")
+    rebalance = strategy.get("rebalance")
+    risk = strategy.get("risk")
+    signal = strategy.get("signal")
+    allocation = strategy.get("allocation")
+    return {
+        "signal": signal,
+        "allocation": allocation,
+        "risk": risk,
+        "rebalance": rebalance,
+        "execution": execution,
+        "commission": commission,
+        "slippage": slippage,
+        "position_sizing": sizing,
+    }
+
+
+def build_case_record(
+    case: Mapping[str, Any],
+    lineage: Mapping[str, Any],
+    *,
+    artifact_root: Path,
+) -> dict[str, object]:
+    """Build one immutable inventory record from a resolved canonical lineage."""
+    case_id = str(case["id"])
+    backtest_hash = str(lineage["val_backtest_hash"])
+    prediction_hash = str(lineage["val_prediction_hash"])
+    case_root = artifact_root / "case_studies" / case_id / "run_log"
+    backtest_dir = case_root / "backtest" / backtest_hash
+    prediction_dir = case_root / "predictions" / prediction_hash
+    registry_path = case_root / "registry.db"
+    prediction_path = prediction_dir / "predictions.parquet"
+    required_paths = [backtest_dir / str(name) for name in case["required_backtest_artifacts"]]
+    inputs = [registry_path, prediction_path, *required_paths]
+    missing = [path for path in inputs if not path.is_file()]
+    if missing:
+        relative = [path.relative_to(artifact_root).as_posix() for path in missing]
+        raise FileNotFoundError(f"{case_id} lacks required artifacts: {relative}")
+
+    spec_path = backtest_dir / "spec.json"
+    spec = json.loads(spec_path.read_text(encoding="utf-8"))
+    if (
+        spec.get("backtest_config", {}).get("metadata", {}).get("prediction_hash")
+        != prediction_hash
+    ):
+        raise ValueError(f"{case_id} selected spec does not name selected prediction")
+    recorded_mode = spec.get("strategy", {}).get("rebalance", {}).get("mode")
+    expected_mode = "engine" if case["production_path"] == "event_driven" else "vectorized"
+    if recorded_mode != expected_mode:
+        raise ValueError(
+            f"{case_id} production path differs: expected {expected_mode}, got {recorded_mode}"
+        )
+
+    artifacts = {
+        path.name: _artifact_identity(path)
+        for path in sorted(required_paths, key=lambda value: value.name)
+    }
+    return {
+        "case_study": case_id,
+        "asset_class": case["asset_class"],
+        "production_path": case["production_path"],
+        "selection": dict(lineage),
+        "strategy": _strategy_summary(spec),
+        "inputs": {
+            "registry": _artifact_identity(registry_path),
+            "predictions.parquet": _artifact_identity(prediction_path),
+        },
+        "backtest_artifacts": artifacts,
+    }
+
+
+def build_report(
+    *,
+    public_root: Path,
+    artifact_root: Path,
+    resolver: Callable[[str], Mapping[str, Any]],
+    cases_path: Path = DEFAULT_CASES_PATH,
+) -> dict[str, object]:
+    """Build a complete current corpus inventory using the publication resolver."""
+    cases = load_case_contract(cases_path)
+    records = [
+        build_case_record(case, resolver(str(case["id"])), artifact_root=artifact_root)
+        for case in cases
+    ]
+    return {
+        "schema_version": SCHEMA_VERSION,
+        "generated_at": datetime.now(UTC).isoformat(),
+        "selection_contract": (
+            "current canonical validation rank-1 resolved by "
+            "case_studies.utils.strategy_analysis.resolve_canonical_rank1_lineage"
+        ),
+        "repositories": {
+            "ml4t_backtest": git_identity(PROJECT_ROOT),
+            "publication": git_identity(public_root),
+        },
+        "artifact_root": {
+            "kind": "external_case_study_run_log",
+            "retained_absolute_path": False,
+        },
+        "summary": {
+            "case_studies": len(records),
+            "event_driven": sum(r["production_path"] == "event_driven" for r in records),
+            "vectorized": sum(r["production_path"] == "vectorized" for r in records),
+        },
+        "records": records,
+    }
+
+
+def write_report(report: Mapping[str, object], output: Path) -> None:
+    """Atomically write a deterministic JSON candidate."""
+    output.parent.mkdir(parents=True, exist_ok=True)
+    payload = json.dumps(report, indent=2, sort_keys=True, default=str) + "\n"
+    descriptor, temporary_name = tempfile.mkstemp(prefix=f".{output.name}.", dir=output.parent)
+    temporary = Path(temporary_name)
+    try:
+        with os.fdopen(descriptor, "w", encoding="utf-8") as stream:
+            stream.write(payload)
+            stream.flush()
+            os.fsync(stream.fileno())
+        os.replace(temporary, output)
+    finally:
+        temporary.unlink(missing_ok=True)
+
+
+def _json_value(value: object) -> object:
+    if dataclasses.is_dataclass(value) and not isinstance(value, type):
+        return {key: _json_value(item) for key, item in dataclasses.asdict(value).items()}
+    if isinstance(value, enum.Enum):
+        return value.value
+    if isinstance(value, Mapping):
+        return {str(key): _json_value(item) for key, item in value.items()}
+    if isinstance(value, (list, tuple)):
+        return [_json_value(item) for item in value]
+    return value
+
+
+def _sanitize_spec(spec: Mapping[str, Any]) -> dict[str, Any]:
+    sanitized = json.loads(json.dumps(spec, default=str))
+    sanitized.pop("_runtime_backtest_config", None)
+    metadata = sanitized.get("backtest_config", {}).get("metadata", {})
+    metadata.pop("preset_path", None)
+    return sanitized
+
+
+def _frame_identity(frame: pl.DataFrame) -> dict[str, object]:
+    return {
+        "rows": frame.height,
+        "schema": {name: str(dtype) for name, dtype in frame.schema.items()},
+    }
+
+
+def align_funding_to_market_events(funding: pl.DataFrame, market: pl.DataFrame) -> pl.DataFrame:
+    """Retain funding settlements that the frozen engine timeline can present."""
+    market_timestamps = market.select("timestamp").unique()
+    if funding.schema["timestamp"] != market_timestamps.schema["timestamp"]:
+        funding = funding.with_columns(
+            pl.col("timestamp").cast(market_timestamps.schema["timestamp"])
+        )
+    return funding.join(market_timestamps, on="timestamp", how="semi").sort("timestamp", "symbol")
+
+
+def align_targets_to_engine_schedule(targets: pl.DataFrame, schedule: pl.Series) -> pl.DataFrame:
+    """Retain target rows that the production engine schedule can submit."""
+    schedule_frame = schedule.alias("timestamp").to_frame().unique()
+    if targets.schema["timestamp"] != schedule_frame.schema["timestamp"]:
+        schedule_frame = schedule_frame.with_columns(
+            pl.col("timestamp").cast(targets.schema["timestamp"])
+        )
+    return targets.join(schedule_frame, on="timestamp", how="semi").sort("timestamp", "symbol")
+
+
+def _bundle_digest(
+    *,
+    selection: Mapping[str, Any],
+    source_prediction_sha256: str,
+    spec: Mapping[str, Any],
+    frames: Mapping[str, pl.DataFrame],
+    contracts: Mapping[str, object] | None,
+) -> str:
+    digest = hashlib.sha256()
+    metadata = {
+        "selection": selection,
+        "source_prediction_sha256": source_prediction_sha256,
+        "spec": spec,
+        "contracts": contracts,
+    }
+    digest.update(json.dumps(metadata, sort_keys=True, separators=(",", ":"), default=str).encode())
+    for name, frame in sorted(frames.items()):
+        digest.update(name.encode())
+        digest.update(frame.serialize(format="binary"))
+    return digest.hexdigest()
+
+
+def write_bundle(
+    *,
+    case_id: str,
+    selection: Mapping[str, Any],
+    source_prediction_sha256: str,
+    spec: Mapping[str, Any],
+    market: pl.DataFrame,
+    targets: pl.DataFrame,
+    output_root: Path,
+    funding: pl.DataFrame | None = None,
+    contracts: Mapping[str, object] | None = None,
+) -> dict[str, object]:
+    """Write one content-addressed engine-input bundle and return its manifest."""
+    frames = {"market.parquet": market, "targets.parquet": targets}
+    if funding is not None:
+        frames["funding.parquet"] = funding
+    normalized_contracts = cast(Mapping[str, object] | None, _json_value(contracts))
+    sanitized_spec = _sanitize_spec(spec)
+    digest = _bundle_digest(
+        selection=selection,
+        source_prediction_sha256=source_prediction_sha256,
+        spec=sanitized_spec,
+        frames=frames,
+        contracts=normalized_contracts,
+    )
+    destination = output_root / case_id / digest
+    manifest: dict[str, object] = {
+        "schema_version": SCHEMA_VERSION,
+        "case_study": case_id,
+        "bundle_sha256": digest,
+        "selection": dict(selection),
+        "source_prediction_sha256": source_prediction_sha256,
+        "files": {},
+    }
+    if destination.is_dir():
+        retained = json.loads((destination / "manifest.json").read_text(encoding="utf-8"))
+        if retained.get("bundle_sha256") != digest:
+            raise ValueError(f"Retained {case_id} bundle has the wrong identity")
+        return retained
+
+    destination.parent.mkdir(parents=True, exist_ok=True)
+    staging = Path(tempfile.mkdtemp(prefix=f".{case_id}.", dir=destination.parent))
+    try:
+        for name, frame in frames.items():
+            frame.write_parquet(staging / name, compression="zstd", statistics=True)
+        (staging / "spec.json").write_text(
+            json.dumps(sanitized_spec, indent=2, sort_keys=True) + "\n", encoding="utf-8"
+        )
+        if normalized_contracts is not None:
+            (staging / "contracts.json").write_text(
+                json.dumps(normalized_contracts, indent=2, sort_keys=True) + "\n",
+                encoding="utf-8",
+            )
+        files = {
+            path.name: _artifact_identity(path)
+            for path in sorted(staging.iterdir())
+            if path.name != "manifest.json"
+        }
+        manifest["files"] = files
+        (staging / "manifest.json").write_text(
+            json.dumps(manifest, indent=2, sort_keys=True, default=str) + "\n",
+            encoding="utf-8",
+        )
+        os.replace(staging, destination)
+    finally:
+        if staging.exists():
+            for path in staging.iterdir():
+                path.unlink()
+            staging.rmdir()
+    return manifest
+
+
+def materialize_bundles(
+    *,
+    corpus_report: Mapping[str, object],
+    artifact_root: Path,
+    output_root: Path,
+) -> dict[str, object]:
+    """Precompute engine inputs for every selected production strategy."""
+    loaders = importlib.import_module("case_studies.utils.backtest_loaders")
+    runner = importlib.import_module("case_studies.utils.backtest_runner")
+    registry = importlib.import_module("case_studies.utils.registry")
+    cv_window = importlib.import_module("case_studies.utils.cv_window")
+    contract_by_id = {case["id"]: case for case in load_case_contract()}
+    records = cast(list[dict[str, Any]], corpus_report["records"])
+    manifests: list[dict[str, object]] = []
+    for record in records:
+        case_id = str(record["case_study"])
+        print(f"Preparing {case_id}", flush=True)
+        contract = contract_by_id[case_id]
+        selection = cast(dict[str, Any], record["selection"])
+        label = str(selection["label"])
+        prediction_hash = str(selection["val_prediction_hash"])
+        backtest_hash = str(selection["val_backtest_hash"])
+        spec_path = (
+            artifact_root
+            / "case_studies"
+            / case_id
+            / "run_log"
+            / "backtest"
+            / backtest_hash
+            / "spec.json"
+        )
+        spec = json.loads(spec_path.read_text(encoding="utf-8"))
+        warmup = int(loaders.warmup_periods_for(case_id)) if contract["warmup"] else 0
+        market = loaders.load_backtest_prices_for(
+            case_id,
+            label,
+            split="validation",
+            warmup_periods=warmup,
+            max_symbols=0,
+        )
+        predictions = registry.read_predictions(case_id, prediction_hash)
+        shift_hours = int(contract["timestamp_shift_hours"])
+        if shift_hours:
+            window = cv_window.canonical_window(case_id, label, split="validation")
+            if window is None:
+                raise ValueError(f"{case_id} lacks a canonical validation window")
+            validation_end = window[1]
+            market = market.with_columns(
+                pl.col("timestamp") + pl.duration(hours=shift_hours)
+            ).filter(pl.col("timestamp").dt.date() <= validation_end)
+            predictions = predictions.with_columns(
+                pl.col("timestamp") + pl.duration(hours=shift_hours)
+            ).filter(pl.col("timestamp").dt.date() <= validation_end)
+        targets = runner.precompute_weights(
+            predictions,
+            spec,
+            market,
+            label=label,
+            case_study=case_id,
+            prediction_hash=prediction_hash,
+        ).sort("timestamp", "symbol")
+        cadence = spec["strategy"]["rebalance"]["cadence"]
+        calendar = spec["backtest_config"]["calendar"]["calendar"]
+        schedule = loaders.resolve_rebalance_timestamps(
+            pl.Series("timestamp", predictions["timestamp"].unique().sort().to_list()),
+            cadence,
+            calendar,
+        )
+        step = int(loaders.get_rebalance_step(case_id, label))
+        if step > 1:
+            schedule = schedule.gather_every(step)
+        targets = align_targets_to_engine_schedule(targets, schedule)
+        market = market.sort("timestamp", "symbol")
+        funding = None
+        if contract["funding"]:
+            funding_module = importlib.import_module(
+                "case_studies.crypto_perps_funding.funding_data"
+            )
+            funding = align_funding_to_market_events(
+                funding_module.load_funding_rates(symbols=market["symbol"].unique().to_list()),
+                market,
+            )
+        contracts = None
+        if contract["contract_specs"]:
+            contracts = loaders.load_contract_specs_from_yaml()
+        prediction_identity = cast(dict[str, Any], record["inputs"])["predictions.parquet"]
+        bundle = write_bundle(
+            case_id=case_id,
+            selection=selection,
+            source_prediction_sha256=str(prediction_identity["sha256"]),
+            spec=spec,
+            market=market,
+            targets=targets,
+            output_root=output_root,
+            funding=funding,
+            contracts=contracts,
+        )
+        manifests.append(bundle)
+        print(
+            f"Prepared {case_id}: {market.height:,} market rows, "
+            f"{targets.height:,} targets, {str(bundle['bundle_sha256'])[:12]}",
+            flush=True,
+        )
+        del market, predictions, targets, funding
+        gc.collect()
+    return {
+        "schema_version": SCHEMA_VERSION,
+        "generated_at": datetime.now(UTC).isoformat(),
+        "bundle_root": {"retained_absolute_path": False},
+        "records": manifests,
+    }
+
+
+def _load_public_resolver(public_root: Path) -> Callable[[str], Mapping[str, Any]]:
+    sys.path.insert(0, str(public_root))
+    os.chdir(public_root)
+    module = importlib.import_module("case_studies.utils.strategy_analysis")
+    return cast(Callable[[str], Mapping[str, Any]], module.resolve_canonical_rank1_lineage)
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--public-root", type=Path, required=True)
+    parser.add_argument("--artifact-root", type=Path, required=True)
+    parser.add_argument(
+        "--output",
+        type=Path,
+        default=VALIDATION_DIR / "candidates" / "REAL_STRATEGY_CORPUS.candidate.json",
+    )
+    parser.add_argument("--materialize", type=Path)
+    args = parser.parse_args()
+    public_root = args.public_root.resolve()
+    artifact_root = args.artifact_root.resolve()
+    output = args.output.resolve()
+    materialize_root = args.materialize.resolve() if args.materialize is not None else None
+    resolver = _load_public_resolver(public_root)
+    report = build_report(
+        public_root=public_root,
+        artifact_root=artifact_root,
+        resolver=resolver,
+    )
+    write_report(report, output)
+    if materialize_root is not None:
+        bundle_report = materialize_bundles(
+            corpus_report=report,
+            artifact_root=artifact_root,
+            output_root=materialize_root,
+        )
+        bundle_output = output.with_name("REAL_STRATEGY_INPUTS.candidate.json")
+        write_report(bundle_report, bundle_output)
+        bundle_records = cast(list[dict[str, object]], bundle_report["records"])
+        print(f"Materialized {len(bundle_records)} engine input bundles")
+    summary = cast(Mapping[str, object], report["summary"])
+    print(f"Inventoried {summary['case_studies']} current case studies to {output}")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/real_strategy_evidence.py b/validation/real_strategy_evidence.py
new file mode 100644
index 00000000..b61d7754
--- /dev/null
+++ b/validation/real_strategy_evidence.py
@@ -0,0 +1,446 @@
+#!/usr/bin/env python3
+"""Build retained exact-comparison evidence for frozen real strategies."""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+import os
+import platform
+import subprocess
+import sys
+import tempfile
+import tomllib
+from datetime import UTC, date, datetime
+from decimal import ROUND_HALF_EVEN, Decimal
+from pathlib import Path
+from typing import Any
+
+import polars as pl
+
+PROJECT_ROOT = Path(__file__).resolve().parents[1]
+VALIDATION_DIR = PROJECT_ROOT / "validation"
+CANONICAL_QUANTUM = Decimal("0.00000001")
+PAIR_PROFILES = {
+    ("etfs", "vectorbt_pro"): "vectorbt_strict",
+    ("etfs", "vectorbt_oss"): "vectorbt_oss_strict",
+    ("etfs", "backtrader"): "backtrader_strict",
+    ("etfs", "zipline"): "zipline_strict",
+    ("etfs", "lean"): "lean",
+    ("cme_futures", "vectorbt_pro"): "vectorbt_strict",
+    ("cme_futures", "backtrader"): "backtrader_strict",
+    ("crypto_perps_funding", "lean"): "lean_crypto_future",
+}
+
+
+def _sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as stream:
+        for chunk in iter(lambda: stream.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def _json_digest(value: object) -> str:
+    payload = json.dumps(value, sort_keys=True, separators=(",", ":"), default=str)
+    return hashlib.sha256(payload.encode()).hexdigest()
+
+
+def _tree_digest(root: Path) -> str:
+    digest = hashlib.sha256()
+    for path in sorted(root.rglob("*.py")):
+        digest.update(path.relative_to(root).as_posix().encode())
+        digest.update(b"\0")
+        digest.update(path.read_bytes())
+        digest.update(b"\0")
+    return digest.hexdigest()
+
+
+def _git_identity(root: Path) -> dict[str, object]:
+    commit = subprocess.run(
+        ["git", "rev-parse", "HEAD"], cwd=root, check=True, capture_output=True, text=True
+    ).stdout.strip()
+    status = subprocess.run(
+        ["git", "status", "--porcelain", "--untracked-files=no"],
+        cwd=root,
+        check=True,
+        capture_output=True,
+        text=True,
+    ).stdout
+    return {"commit": commit, "dirty": bool(status.strip())}
+
+
+def _number_text(value: object) -> str:
+    return format(Decimal(str(value)), "f")
+
+
+def _canonical_gap(framework: str, ml4t: str) -> Decimal:
+    return abs(Decimal(framework) - Decimal(ml4t)).quantize(CANONICAL_QUANTUM, ROUND_HALF_EVEN)
+
+
+def _canonical_timestamp(value: object, *, intraday: bool) -> str:
+    if isinstance(value, datetime):
+        return value.isoformat(timespec="seconds") if intraday else value.date().isoformat()
+    if isinstance(value, date):
+        return value.isoformat()
+    parsed = datetime.fromisoformat(str(value).replace("Z", "+00:00"))
+    return parsed.isoformat(timespec="seconds") if intraday else parsed.date().isoformat()
+
+
+def _fill_records(frame: pl.DataFrame, *, intraday: bool) -> list[dict[str, str]]:
+    records = [
+        {
+            "timestamp": _canonical_timestamp(row["timestamp"], intraday=intraday),
+            "asset": str(row["asset"]),
+            "side": str(row["side"]).lower(),
+            "quantity": _number_text(row["quantity"]),
+            "price": _number_text(row["price"]),
+            "commission": _number_text(row["commission"]),
+        }
+        for row in frame.iter_rows(named=True)
+    ]
+    return sorted(
+        records,
+        key=lambda row: (
+            row["timestamp"],
+            row["asset"],
+            row["side"],
+            row["quantity"],
+            row["price"],
+            row["commission"],
+        ),
+    )
+
+
+def _value_records(frame: pl.DataFrame, *, field: str, intraday: bool) -> list[dict[str, str]]:
+    records = [
+        {
+            "timestamp": _canonical_timestamp(row["timestamp"], intraday=intraday),
+            field: _number_text(row[field]),
+        }
+        for row in frame.select("timestamp", field).iter_rows(named=True)
+    ]
+    return sorted(records, key=lambda row: row["timestamp"])
+
+
+def _first_divergence(
+    framework_records: list[dict[str, str]],
+    ml4t_records: list[dict[str, str]],
+    *,
+    numeric_fields: tuple[str, ...],
+) -> dict[str, object] | None:
+    if len(framework_records) != len(ml4t_records):
+        return {
+            "kind": "record_count",
+            "framework": len(framework_records),
+            "ml4t": len(ml4t_records),
+        }
+    for index, (framework, ml4t) in enumerate(zip(framework_records, ml4t_records, strict=True)):
+        fields = sorted(set(framework) | set(ml4t))
+        for field in fields:
+            framework_value = framework.get(field)
+            ml4t_value = ml4t.get(field)
+            if field in numeric_fields and framework_value is not None and ml4t_value is not None:
+                differs = _canonical_gap(framework_value, ml4t_value) != 0
+            else:
+                differs = framework_value != ml4t_value
+            if differs:
+                return {
+                    "kind": "record",
+                    "index": index,
+                    "field": field,
+                    "framework": framework,
+                    "ml4t": ml4t,
+                    "canonical_gap": (
+                        format(_canonical_gap(framework_value, ml4t_value), "f")
+                        if field in numeric_fields
+                        and framework_value is not None
+                        and ml4t_value is not None
+                        else None
+                    ),
+                }
+    return None
+
+
+def compare_records(
+    framework_records: list[dict[str, str]],
+    ml4t_records: list[dict[str, str]],
+    *,
+    numeric_fields: tuple[str, ...] = (),
+) -> dict[str, object]:
+    """Compare complete canonical streams and retain the first divergence."""
+    divergence = _first_divergence(framework_records, ml4t_records, numeric_fields=numeric_fields)
+    return {
+        "passed": divergence is None,
+        "framework_records": len(framework_records),
+        "ml4t_records": len(ml4t_records),
+        "framework_sha256": _json_digest(framework_records),
+        "ml4t_sha256": _json_digest(ml4t_records),
+        "first_divergence": divergence,
+    }
+
+
+def _max_difference(
+    framework_records: list[dict[str, str]],
+    ml4t_records: list[dict[str, str]],
+    *,
+    fields: tuple[str, ...],
+) -> str | None:
+    if len(framework_records) != len(ml4t_records):
+        return None
+    differences: list[Decimal] = []
+    for framework, ml4t in zip(framework_records, ml4t_records, strict=True):
+        for field in fields:
+            if field in framework and field in ml4t:
+                differences.append(abs(Decimal(framework[field]) - Decimal(ml4t[field])))
+    maximum = max(differences, default=Decimal(0))
+    return format(maximum.quantize(CANONICAL_QUANTUM, ROUND_HALF_EVEN), "f")
+
+
+def _align_shared_values(
+    framework_records: list[dict[str, str]], ml4t_records: list[dict[str, str]]
+) -> tuple[list[dict[str, str]], list[dict[str, str]], dict[str, int]]:
+    framework_by_time = {record["timestamp"]: record for record in framework_records}
+    ml4t_by_time = {record["timestamp"]: record for record in ml4t_records}
+    shared = sorted(framework_by_time.keys() & ml4t_by_time.keys())
+    return (
+        [framework_by_time[timestamp] for timestamp in shared],
+        [ml4t_by_time[timestamp] for timestamp in shared],
+        {
+            "shared_timestamps": len(shared),
+            "framework_only_timestamps": len(framework_by_time.keys() - ml4t_by_time.keys()),
+            "ml4t_only_timestamps": len(ml4t_by_time.keys() - framework_by_time.keys()),
+        },
+    )
+
+
+def _load_evidence(path: Path) -> tuple[dict[str, Any], dict[str, pl.DataFrame]]:
+    manifest = json.loads((path / "manifest.json").read_text(encoding="utf-8"))
+    frames: dict[str, pl.DataFrame] = {}
+    for name, identity in manifest["files"].items():
+        artifact = path / name
+        if not artifact.is_file() or _sha256(artifact) != identity["sha256"]:
+            raise ValueError(f"Evidence identity mismatch: {artifact}")
+        if artifact.suffix == ".parquet":
+            frames[artifact.stem] = pl.read_parquet(artifact)
+    return manifest, frames
+
+
+def _surface(
+    framework_records: list[dict[str, str]],
+    ml4t_records: list[dict[str, str]],
+    *,
+    numeric_fields: tuple[str, ...],
+) -> dict[str, object]:
+    result = compare_records(framework_records, ml4t_records, numeric_fields=numeric_fields)
+    result["max_canonical_difference"] = _max_difference(
+        framework_records, ml4t_records, fields=numeric_fields
+    )
+    return result
+
+
+def _comparison_record(
+    *, case_study: str, framework: str, evidence_root: Path
+) -> dict[str, object]:
+    external_path = evidence_root / case_study / framework
+    ml4t_path = evidence_root / case_study / f"ml4t_{framework}"
+    external, external_frames = _load_evidence(external_path)
+    ml4t, ml4t_frames = _load_evidence(ml4t_path)
+    expected_profile = PAIR_PROFILES[(case_study, framework)]
+    if external["input_bundle_sha256"] != ml4t["input_bundle_sha256"]:
+        raise ValueError(f"Input bundle differs for {case_study}/{framework}")
+    if external["comparison_profile"] != expected_profile:
+        raise ValueError(f"External profile differs for {case_study}/{framework}")
+    if ml4t["comparison_profile"] != expected_profile:
+        raise ValueError(f"ML4T profile differs for {case_study}/{framework}")
+
+    intraday = case_study == "crypto_perps_funding"
+    external_fills = _fill_records(external_frames["fills"], intraday=intraday)
+    ml4t_fills = _fill_records(ml4t_frames["fills"], intraday=intraday)
+    external_equity = _value_records(external_frames["equity"], field="equity", intraday=intraday)
+    ml4t_equity = _value_records(ml4t_frames["equity"], field="equity", intraday=intraday)
+    external_equity, ml4t_equity, equity_coverage = _align_shared_values(
+        external_equity, ml4t_equity
+    )
+    if not external_equity:
+        raise ValueError(f"No shared equity timestamps for {case_study}/{framework}")
+    terminal_external = [{"final_value": external_equity[-1]["equity"]}]
+    terminal_ml4t = [{"final_value": ml4t_equity[-1]["equity"]}]
+    surfaces: dict[str, dict[str, object]] = {
+        "fills": _surface(
+            external_fills,
+            ml4t_fills,
+            numeric_fields=("quantity", "price", "commission"),
+        ),
+        "equity": _surface(external_equity, ml4t_equity, numeric_fields=("equity",)),
+        "terminal": _surface(terminal_external, terminal_ml4t, numeric_fields=("final_value",)),
+    }
+    surfaces["equity"]["coverage"] = equity_coverage
+    if "num_rejections" in external and "num_rejections" in ml4t:
+        rejection_external = [{"count": str(external["num_rejections"])}]
+        rejection_ml4t = [{"count": str(ml4t["num_rejections"])}]
+        surfaces["rejection_count"] = _surface(
+            rejection_external, rejection_ml4t, numeric_fields=("count",)
+        )
+    if case_study == "etfs" and framework == "lean":
+        external_cash = _value_records(external_frames["equity"], field="cash", intraday=intraday)
+        ml4t_cash = _value_records(ml4t_frames["portfolio_state"], field="cash", intraday=intraday)
+        external_cash, ml4t_cash, cash_coverage = _align_shared_values(external_cash, ml4t_cash)
+        surfaces["cash"] = _surface(external_cash, ml4t_cash, numeric_fields=("cash",))
+        surfaces["cash"]["coverage"] = cash_coverage
+
+    surface_values = list(surfaces.values())
+    passed = all(bool(value["passed"]) for value in surface_values)
+    negative_control = [dict(record) for record in ml4t_fills]
+    if not negative_control:
+        raise ValueError(f"Negative control requires fills for {case_study}/{framework}")
+    negative_control[0]["price"] = format(
+        Decimal(negative_control[0]["price"]) + CANONICAL_QUANTUM, "f"
+    )
+    detected = not compare_records(
+        external_fills,
+        negative_control,
+        numeric_fields=("quantity", "price", "commission"),
+    )["passed"]
+    if not detected:
+        raise RuntimeError(f"Negative control was not detected for {case_study}/{framework}")
+    return {
+        "case_study": case_study,
+        "framework": framework,
+        "status": "pass" if passed else "fail",
+        "input_bundle_sha256": external["input_bundle_sha256"],
+        "profile": expected_profile,
+        "engine_seconds": {
+            "framework": external["engine_seconds"],
+            "ml4t": ml4t["engine_seconds"],
+            "single_run_diagnostic_only": True,
+        },
+        "surfaces": surfaces,
+        "negative_control": {"mutation": "first fill price + 0.00000001", "detected": detected},
+        "excluded_surfaces": {
+            "intents": "shared frozen target input is identified, but engines do not expose a common native intent log",
+            "accepted_unfilled_orders": "not exposed by every native runner",
+            "positions": "not exposed in a common native record schema by every runner",
+            "closed_trades": "not a common native framework concept",
+            "cash": (
+                "compared separately for LEAN equities"
+                if case_study == "etfs" and framework == "lean"
+                else "not exposed with common accounting semantics"
+            ),
+        },
+        "evidence": {
+            "framework_manifest_sha256": _sha256(external_path / "manifest.json"),
+            "ml4t_manifest_sha256": _sha256(ml4t_path / "manifest.json"),
+        },
+    }
+
+
+def build_report(evidence_root: Path) -> dict[str, Any]:
+    """Build the complete required and unsupported real-strategy matrix."""
+    applicability_path = VALIDATION_DIR / "real_strategy_applicability.toml"
+    applicability = tomllib.loads(applicability_path.read_text(encoding="utf-8"))
+    targets = tomllib.loads((VALIDATION_DIR / "framework_targets.toml").read_text())
+    records: list[dict[str, object]] = []
+    for pair in applicability["pair"]:
+        if pair["status"] == "required":
+            records.append(
+                _comparison_record(
+                    case_study=pair["case_study"],
+                    framework=pair["framework"],
+                    evidence_root=evidence_root,
+                )
+            )
+        else:
+            records.append(
+                {
+                    "case_study": pair["case_study"],
+                    "framework": pair["framework"],
+                    "status": "unsupported",
+                    "reason": pair["native_contract"],
+                    "source": pair["source"],
+                }
+            )
+    required = [record for record in records if record["status"] != "unsupported"]
+    return {
+        "schema_version": 1,
+        "generated_at": datetime.now(UTC).isoformat(),
+        "scope": {
+            "case_studies": applicability["metadata"]["case_studies"],
+            "frameworks": applicability["metadata"]["frameworks"],
+            "required_pairs": len(required),
+            "unsupported_pairs": len(records) - len(required),
+            "real_strategy_equivalence_gate_passed": all(
+                record["status"] == "pass" for record in required
+            ),
+        },
+        "comparison_policy": {
+            "canonical_quantum": format(CANONICAL_QUANTUM, "f"),
+            "rounding": "ROUND_HALF_EVEN",
+            "meaning": "zero numeric gap after canonical quantization, not bit identity",
+            "fill_order": "canonical timestamp, asset, side, quantity, price, commission",
+            "timestamp_domain": {
+                "etfs": "session date",
+                "cme_futures": "session date",
+                "crypto_perps_funding": "exact UTC event timestamp",
+            },
+        },
+        "provenance": {
+            "ml4t": {
+                **_git_identity(PROJECT_ROOT),
+                "engine_source_sha256": _tree_digest(PROJECT_ROOT / "src/ml4t/backtest"),
+            },
+            "python": sys.version.split()[0],
+            "platform": platform.platform(),
+            "machine": platform.machine(),
+            "cpu_count": os.cpu_count(),
+            "applicability_sha256": _sha256(applicability_path),
+            "adapters": {
+                framework: _sha256(VALIDATION_DIR / f"real_strategy_{adapter}.py")
+                for framework, adapter in {
+                    "vectorbt_pro": "vectorbt",
+                    "vectorbt_oss": "vectorbt",
+                    "backtrader": "backtrader",
+                    "zipline": "zipline",
+                    "lean_equity": "lean",
+                    "lean_crypto": "lean_crypto",
+                    "ml4t": "runner",
+                }.items()
+            },
+            "frameworks": {
+                framework: targets["framework"][framework]
+                for framework in applicability["metadata"]["frameworks"]
+            },
+        },
+        "records": records,
+    }
+
+
+def write_report(report: dict[str, Any], output: Path) -> None:
+    output.parent.mkdir(parents=True, exist_ok=True)
+    descriptor, temporary_name = tempfile.mkstemp(prefix=f".{output.name}.", dir=output.parent)
+    temporary = Path(temporary_name)
+    try:
+        with os.fdopen(descriptor, "w", encoding="utf-8") as stream:
+            json.dump(report, stream, indent=2, sort_keys=True)
+            stream.write("\n")
+        os.replace(temporary, output)
+    finally:
+        temporary.unlink(missing_ok=True)
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--evidence-root", type=Path, required=True)
+    parser.add_argument("--output", type=Path, required=True)
+    args = parser.parse_args()
+    report = build_report(args.evidence_root.resolve())
+    write_report(report, args.output.resolve())
+    required = [record for record in report["records"] if record["status"] != "unsupported"]
+    passed = sum(record["status"] == "pass" for record in required)
+    print(f"Real-strategy parity: {passed}/{len(required)} required pairs pass")
+    return 0 if passed == len(required) else 1
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/real_strategy_lean.py b/validation/real_strategy_lean.py
new file mode 100644
index 00000000..c11989e0
--- /dev/null
+++ b/validation/real_strategy_lean.py
@@ -0,0 +1,281 @@
+#!/usr/bin/env python3
+"""Run the frozen real ETF target-allocation workload with LEAN."""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+import os
+import tempfile
+import time
+import tomllib
+from datetime import datetime, timedelta
+from pathlib import Path
+from typing import Any, cast
+
+import pandas as pd
+import polars as pl
+
+from ml4t.backtest._validation.lean_runner import (
+    build_hashed_ticker_map,
+    copy_lean_artifacts,
+    export_lean_daily_data,
+    load_lean_artifacts,
+    make_lean_env,
+    resolve_lean_command,
+    run_lean_backtest,
+)
+
+PROJECT_ROOT = Path(__file__).resolve().parents[1]
+
+
+def _sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as stream:
+        for chunk in iter(lambda: stream.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def _prepare_project(bundle: Path) -> tuple[Path, dict[str, Any]]:
+    manifest = json.loads((bundle / "manifest.json").read_text(encoding="utf-8"))
+    if manifest["case_study"] != "etfs":
+        raise ValueError("The LEAN adapter currently accepts the ETF comparison workload")
+    spec = json.loads((bundle / "spec.json").read_text(encoding="utf-8"))
+    market = pl.read_parquet(bundle / "market.parquet")
+    targets = pl.read_parquet(bundle / "targets.parquet")
+    symbols = market["symbol"].unique().sort().to_list()
+    asset_to_ticker = build_hashed_ticker_map("real_etfs", symbols)
+    ticker_to_asset = {ticker: asset for asset, ticker in asset_to_ticker.items()}
+
+    workspace = PROJECT_ROOT / "validation" / "lean" / "workspace"
+    project = workspace / "real_strategy_etfs"
+    project.mkdir(parents=True, exist_ok=True)
+    (project / "backtests").mkdir(exist_ok=True)
+    for name in ("ml4t_daily_equity.csv", "ml4t_order_events.csv", "ml4t_runtime.json"):
+        path = project / name
+        if path.exists():
+            path.unlink()
+
+    (project / "config.json").write_text(
+        json.dumps(
+            {
+                "algorithm-language": "Python",
+                "parameters": {},
+                "description": "Frozen ML4T ETF real-strategy parity workload",
+            },
+            indent=2,
+        )
+        + "\n",
+        encoding="utf-8",
+    )
+    (project / "ml4t_symbol_map.json").write_text(
+        json.dumps(ticker_to_asset, indent=2, sort_keys=True) + "\n", encoding="utf-8"
+    )
+    (project / "symbols.csv").write_text(
+        "\n".join(asset_to_ticker[symbol] for symbol in symbols) + "\n", encoding="utf-8"
+    )
+    target_rows = targets.with_columns(
+        pl.col("symbol").replace_strict(asset_to_ticker).alias("ticker"),
+        pl.col("timestamp").dt.strftime("%Y-%m-%d"),
+    ).select("timestamp", "ticker", "weight")
+    target_rows.write_csv(project / "targets.csv")
+
+    prices_by_asset: dict[str, pd.DataFrame] = {}
+    for symbol in symbols:
+        selected = market.filter(pl.col("symbol") == symbol).select(
+            "timestamp", "open", "high", "low", "close", "volume"
+        )
+        prices_by_asset[symbol] = pd.DataFrame(selected.to_dict(as_series=False)).set_index(
+            "timestamp"
+        )
+    data_root = workspace / "data" / "equity" / "usa"
+    export_lean_daily_data(
+        data_root=data_root,
+        prices_by_asset=prices_by_asset,
+        asset_to_ticker=asset_to_ticker,
+        manifest_path=data_root / "real_strategy_etfs_manifest.json",
+        signature_payload={
+            "bundle_sha256": manifest["bundle_sha256"],
+            "price_decimals": 4,
+        },
+    )
+
+    first = pd.Timestamp(cast(datetime, market["timestamp"].min())).date()
+    last = pd.Timestamp(cast(datetime, market["timestamp"].max())).date() + timedelta(days=7)
+    initial_cash = float(spec["backtest_config"]["cash"]["initial"])
+    main_code = f"""from AlgorithmImports import *
+
+import csv
+import json
+import math
+import time
+from pathlib import Path
+
+
+class RealStrategyEtfs(QCAlgorithm):
+    def initialize(self):
+        self.set_start_date({first.year}, {first.month}, {first.day})
+        self.set_end_date({last.year}, {last.month}, {last.day})
+        self.set_cash({initial_cash})
+        self.set_brokerage_model(BrokerageName.DEFAULT, AccountType.MARGIN)
+        base = Path(__file__).resolve().parent
+        self._equity_path = base / "ml4t_daily_equity.csv"
+        self._events_path = base / "ml4t_order_events.csv"
+        self._runtime_path = base / "ml4t_runtime.json"
+        self._targets = {{}}
+        with (base / "targets.csv").open(newline="") as stream:
+            for row in csv.DictReader(stream):
+                self._targets.setdefault(row["timestamp"], {{}})[row["ticker"]] = float(row["weight"])
+        self._symbols = {{}}
+        for ticker in (base / "symbols.csv").read_text().splitlines():
+            if not ticker:
+                continue
+            security = self.add_equity(ticker, Resolution.DAILY)
+            security.set_fee_model(ConstantFeeModel(0))
+            security.set_slippage_model(ConstantSlippageModel(0))
+            self._symbols[ticker] = security.symbol
+        with self._equity_path.open("w", newline="") as stream:
+            csv.writer(stream).writerow(["timestamp", "equity", "cash", "holdings_value"])
+        with self._events_path.open("w", newline="") as stream:
+            csv.writer(stream).writerow(["timestamp", "symbol", "status", "direction", "fill_quantity", "fill_price", "fee", "message", "order_id"])
+        self._started = time.perf_counter()
+
+    def on_data(self, data: Slice):
+        key = self.time.strftime("%Y-%m-%d")
+        requested = self._targets.get(key)
+        if requested is not None:
+            active = set(requested)
+            active.update(ticker for ticker, symbol in self._symbols.items() if self.portfolio[symbol].quantity != 0)
+            value = float(self.portfolio.total_portfolio_value)
+            current = {{ticker: float(self.portfolio[symbol].quantity) * float(self.securities[symbol].price) / value for ticker, symbol in self._symbols.items() if self.portfolio[symbol].quantity != 0}}
+            reductions = sorted(ticker for ticker in active if requested.get(ticker, 0.0) < current.get(ticker, 0.0))
+            increases = sorted(active - set(reductions))
+            for ticker in reductions + increases:
+                symbol = self._symbols[ticker]
+                if symbol not in data.bars:
+                    continue
+                price = float(data.bars[symbol].close)
+                raw = (requested.get(ticker, 0.0) - current.get(ticker, 0.0)) * value / price
+                delta = int(math.copysign(math.floor(abs(raw) + 0.5), raw))
+                if delta:
+                    self.market_on_open_order(symbol, delta)
+        with self._equity_path.open("a", newline="") as stream:
+            csv.writer(stream).writerow([key, float(self.portfolio.total_portfolio_value), float(self.portfolio.cash), float(self.portfolio.total_holdings_value)])
+
+    def on_order_event(self, event: OrderEvent):
+        fee = float(event.order_fee.value.amount) if event.order_fee and event.order_fee.value else 0.0
+        with self._events_path.open("a", newline="") as stream:
+            csv.writer(stream).writerow([self.time.strftime("%Y-%m-%d %H:%M:%S"), event.symbol.value if event.symbol else "", str(event.status), str(event.direction), float(event.fill_quantity), float(event.fill_price), fee, str(event.message or "").replace("\\n", " "), int(event.order_id)])
+
+    def on_end_of_algorithm(self):
+        self._runtime_path.write_text(json.dumps({{"engine_seconds": time.perf_counter() - self._started}}))
+"""
+    (project / "main.py").write_text(main_code, encoding="utf-8")
+    return project, {
+        "manifest": manifest,
+        "spec": spec,
+        "ticker_to_asset": ticker_to_asset,
+    }
+
+
+def run(bundle: Path) -> tuple[dict[str, Any], pl.DataFrame, pl.DataFrame, pl.DataFrame]:
+    project, inputs = _prepare_project(bundle)
+    targets = tomllib.loads((PROJECT_ROOT / "validation/framework_targets.toml").read_text())
+    image = targets["framework"]["lean"]["artifact"]
+    output_dir = project / "backtests" / str(time.time_ns())
+    run_lean_backtest(
+        lean_cmd=resolve_lean_command(),
+        cwd=PROJECT_ROOT,
+        project_dir=project,
+        lean_config=PROJECT_ROOT / "validation/lean/workspace/lean.json",
+        output_dir=output_dir,
+        image=image,
+        env=make_lean_env(),
+    )
+    names = [
+        "ml4t_daily_equity.csv",
+        "ml4t_order_events.csv",
+        "ml4t_runtime.json",
+        "ml4t_symbol_map.json",
+    ]
+    copy_lean_artifacts(project, output_dir, names)
+    _, final_value, fills_pd, equity_pd, events_pd = load_lean_artifacts(output_dir)
+    if fills_pd is None or equity_pd is None or events_pd is None:
+        raise RuntimeError("LEAN did not produce the required comparison surfaces")
+    fills_pd = fills_pd.rename(columns={"fill_price": "price", "fee": "commission"})
+    fills = pl.from_pandas(
+        fills_pd[["timestamp", "asset", "side", "quantity", "price", "commission"]]
+    )
+    equity = pl.from_pandas(equity_pd[["timestamp", "equity", "cash", "holdings_value"]])
+    runtime = json.loads((output_dir / "ml4t_runtime.json").read_text(encoding="utf-8"))
+    rejected = events_pd[events_pd["status"].astype(str).str.lower().isin({"invalid", "canceled"})]
+    evidence = {
+        "schema_version": 1,
+        "case_study": inputs["manifest"]["case_study"],
+        "framework": "lean",
+        "comparison_profile": "lean",
+        "comparison_costs": "disabled",
+        "comparison_position_rules": "disabled",
+        "input_bundle_sha256": inputs["manifest"]["bundle_sha256"],
+        "engine_seconds": float(runtime["engine_seconds"]),
+        "orchestration_seconds_excluded": None,
+        "final_value": final_value,
+        "num_fills": fills.height,
+        "num_rejections": len(rejected),
+    }
+    rejected_frame = pl.from_pandas(
+        rejected[["timestamp", "asset", "fill_quantity", "message", "order_id"]]
+    )
+    return evidence, fills, equity, rejected_frame
+
+
+def write_evidence(
+    output: Path,
+    evidence: dict[str, Any],
+    fills: pl.DataFrame,
+    equity: pl.DataFrame,
+    rejections: pl.DataFrame,
+) -> None:
+    output.parent.mkdir(parents=True, exist_ok=True)
+    staging = Path(tempfile.mkdtemp(prefix=f".{output.name}.", dir=output.parent))
+    try:
+        fills.write_parquet(staging / "fills.parquet", compression="zstd", statistics=True)
+        equity.write_parquet(staging / "equity.parquet", compression="zstd", statistics=True)
+        rejections.write_parquet(
+            staging / "rejected_orders.parquet", compression="zstd", statistics=True
+        )
+        evidence["files"] = {
+            path.name: {"sha256": _sha256(path), "bytes": path.stat().st_size}
+            for path in sorted(staging.iterdir())
+        }
+        (staging / "manifest.json").write_text(
+            json.dumps(evidence, indent=2, sort_keys=True) + "\n", encoding="utf-8"
+        )
+        if output.exists():
+            raise FileExistsError(f"Evidence output already exists: {output}")
+        os.replace(staging, output)
+    finally:
+        if staging.exists():
+            for path in staging.iterdir():
+                path.unlink()
+            staging.rmdir()
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--bundle", type=Path, required=True)
+    parser.add_argument("--output", type=Path, required=True)
+    args = parser.parse_args()
+    evidence, fills, equity, rejections = run(args.bundle.resolve())
+    write_evidence(args.output.resolve(), evidence, fills, equity, rejections)
+    print(
+        f"{evidence['case_study']}: {evidence['num_fills']:,} fills, "
+        f"{evidence['engine_seconds']:.6f}s engine time"
+    )
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/real_strategy_lean_crypto.py b/validation/real_strategy_lean_crypto.py
new file mode 100644
index 00000000..3176227d
--- /dev/null
+++ b/validation/real_strategy_lean_crypto.py
@@ -0,0 +1,328 @@
+#!/usr/bin/env python3
+"""Run the frozen crypto-perpetual strategy with LEAN's Binance futures model."""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import hashlib
+import json
+import os
+import tempfile
+import time
+import tomllib
+import zipfile
+from datetime import datetime, timedelta
+from pathlib import Path
+from typing import Any, cast
+
+import pandas as pd
+import polars as pl
+
+from ml4t.backtest._validation.lean_runner import (
+    copy_lean_artifacts,
+    load_lean_artifacts,
+    make_lean_env,
+    resolve_lean_command,
+    run_lean_backtest,
+)
+
+PROJECT_ROOT = Path(__file__).resolve().parents[1]
+
+
+def _sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as stream:
+        for chunk in iter(lambda: stream.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def _symbol_properties(data_root: Path, symbols: list[str]) -> dict[str, dict[str, float]]:
+    path = data_root / "symbol-properties" / "symbol-properties-database.csv"
+    wanted = set(symbols)
+    found: dict[str, dict[str, float]] = {}
+    with path.open(newline="", encoding="utf-8-sig") as stream:
+        rows = csv.DictReader(line for line in stream if not line.startswith("#"))
+        for row in rows:
+            symbol = row["symbol"]
+            if row["market"] == "binance" and row["type"] == "cryptofuture" and symbol in wanted:
+                found[symbol] = {
+                    "contract_multiplier": float(row["contract_multiplier"]),
+                    "lot_size": float(row["lot_size"]),
+                    "tick_size": float(row["minimum_price_variation"]),
+                }
+    missing = sorted(wanted - found.keys())
+    if missing:
+        raise ValueError(f"LEAN symbol properties are missing: {missing}")
+    return found
+
+
+def _export_data(bundle: Path, data_root: Path, symbols: list[str]) -> None:
+    market = pl.read_parquet(bundle / "market.parquet")
+    funding = pl.read_parquet(bundle / "funding.parquet")
+    hourly = data_root / "cryptofuture" / "binance" / "hour"
+    margin = data_root / "cryptofuture" / "binance" / "margin_interest"
+    hourly.mkdir(parents=True, exist_ok=True)
+    margin.mkdir(parents=True, exist_ok=True)
+    for symbol in symbols:
+        rows = market.filter(pl.col("symbol") == symbol).sort("timestamp").iter_rows(named=True)
+        trade_lines: list[str] = []
+        quote_lines: list[str] = []
+        for row in rows:
+            start = pd.Timestamp(row["timestamp"]) - timedelta(hours=1)
+            stamp = start.strftime("%Y%m%d %H:%M")
+            values = [float(row[name]) for name in ("open", "high", "low", "close")]
+            volume = max(1.0, float(row["volume"]))
+            o, h, low, close = values
+            trade_lines.append(f"{stamp},{o},{h},{low},{close},{volume}")
+            quote_lines.append(
+                f"{stamp},{o},{h},{low},{close},{volume},{o},{h},{low},{close},{volume}"
+            )
+        ticker = symbol.lower()
+        for kind, lines in (("trade", trade_lines), ("quote", quote_lines)):
+            with zipfile.ZipFile(
+                hourly / f"{ticker}_{kind}.zip", "w", compression=zipfile.ZIP_DEFLATED
+            ) as archive:
+                archive.writestr(f"{ticker}.csv", "\n".join(lines))
+        funding_rows = funding.filter(pl.col("symbol") == symbol).sort("timestamp")
+        margin_lines = [
+            f"{pd.Timestamp(row['timestamp']).strftime('%Y%m%d %H:%M:%S')},{float(row['funding_rate']):.12f}"
+            for row in funding_rows.iter_rows(named=True)
+        ]
+        (margin / f"{ticker}.csv").write_text("\n".join(margin_lines) + "\n", encoding="utf-8")
+
+
+def _prepare_project(bundle: Path) -> tuple[Path, dict[str, Any]]:
+    manifest = json.loads((bundle / "manifest.json").read_text(encoding="utf-8"))
+    if manifest["case_study"] != "crypto_perps_funding":
+        raise ValueError("This adapter accepts the crypto perpetual-funding workload")
+    spec = json.loads((bundle / "spec.json").read_text(encoding="utf-8"))
+    market = pl.read_parquet(bundle / "market.parquet")
+    targets = pl.read_parquet(bundle / "targets.parquet")
+    symbols = market["symbol"].unique().sort().to_list()
+    workspace = PROJECT_ROOT / "validation" / "lean" / "workspace"
+    project = workspace / "real_strategy_crypto_perps_funding"
+    project.mkdir(parents=True, exist_ok=True)
+    (project / "backtests").mkdir(exist_ok=True)
+    for name in (
+        "ml4t_daily_equity.csv",
+        "ml4t_funding_observed.csv",
+        "ml4t_order_events.csv",
+        "ml4t_runtime.json",
+    ):
+        path = project / name
+        if path.exists():
+            path.unlink()
+    (project / "config.json").write_text(
+        json.dumps(
+            {
+                "algorithm-language": "Python",
+                "parameters": {},
+                "description": "Frozen ML4T crypto-perpetual real-strategy parity workload",
+            },
+            indent=2,
+        )
+        + "\n",
+        encoding="utf-8",
+    )
+    (project / "symbols.csv").write_text("\n".join(symbols) + "\n", encoding="utf-8")
+    (project / "ml4t_symbol_map.json").write_text(
+        json.dumps({symbol: symbol for symbol in symbols}, indent=2, sort_keys=True) + "\n",
+        encoding="utf-8",
+    )
+    targets.with_columns(pl.col("timestamp").dt.strftime("%Y-%m-%d %H:%M:%S")).write_csv(
+        project / "targets.csv"
+    )
+    _export_data(bundle, workspace / "data", symbols)
+    properties = _symbol_properties(workspace / "data", symbols)
+    (project / "symbol_properties.json").write_text(
+        json.dumps(properties, indent=2, sort_keys=True) + "\n", encoding="utf-8"
+    )
+
+    first = pd.Timestamp(cast(datetime, market["timestamp"].min())).date()
+    last = pd.Timestamp(cast(datetime, market["timestamp"].max())).date() + timedelta(days=1)
+    initial_cash = float(spec["backtest_config"]["cash"]["initial"])
+    main_code = f"""from AlgorithmImports import *
+
+import csv
+import json
+import math
+import time
+from pathlib import Path
+
+
+class RealStrategyCryptoPerpsFunding(QCAlgorithm):
+    def initialize(self):
+        self.set_start_date({first.year}, {first.month}, {first.day})
+        self.set_end_date({last.year}, {last.month}, {last.day})
+        self.set_time_zone(TimeZones.UTC)
+        self.set_brokerage_model(BrokerageName.BINANCE_FUTURES, AccountType.MARGIN)
+        self.set_account_currency("USDT", {initial_cash})
+        base = Path(__file__).resolve().parent
+        self._equity_path = base / "ml4t_daily_equity.csv"
+        self._funding_path = base / "ml4t_funding_observed.csv"
+        self._events_path = base / "ml4t_order_events.csv"
+        self._runtime_path = base / "ml4t_runtime.json"
+        self._targets = {{}}
+        with (base / "targets.csv").open(newline="") as stream:
+            for row in csv.DictReader(stream):
+                self._targets.setdefault(row["timestamp"], {{}})[row["symbol"]] = float(row["weight"])
+        self._properties = json.loads((base / "symbol_properties.json").read_text())
+        self._symbols = {{}}
+        for ticker in (base / "symbols.csv").read_text().splitlines():
+            if not ticker:
+                continue
+            security = self.add_crypto_future(ticker, Resolution.HOUR, fill_forward=False, market=Market.BINANCE)
+            security.set_fee_model(ConstantFeeModel(0))
+            security.set_slippage_model(ConstantSlippageModel(0))
+            self._symbols[ticker] = security.symbol
+        with self._equity_path.open("w", newline="") as stream:
+            csv.writer(stream).writerow(["timestamp", "equity", "cash", "holdings_value"])
+        with self._events_path.open("w", newline="") as stream:
+            csv.writer(stream).writerow(["timestamp", "symbol", "status", "direction", "fill_quantity", "fill_price", "fee", "message", "order_id"])
+        with self._funding_path.open("w", newline="") as stream:
+            csv.writer(stream).writerow(["timestamp", "symbol", "funding_rate"])
+        self._started = time.perf_counter()
+
+    def on_data(self, data: Slice):
+        key = self.time.strftime("%Y-%m-%d %H:%M:%S")
+        with self._funding_path.open("a", newline="") as stream:
+            writer = csv.writer(stream)
+            for symbol, rate in data.margin_interest_rates.items():
+                writer.writerow([key, symbol.value, float(rate.interest_rate)])
+        requested = self._targets.get(key)
+        if requested is not None:
+            active = set(requested)
+            active.update(ticker for ticker, symbol in self._symbols.items() if self.portfolio[symbol].quantity != 0)
+            value = float(self.portfolio.total_portfolio_value)
+            current = {{ticker: float(self.portfolio[symbol].quantity) * float(self.securities[symbol].price) / value for ticker, symbol in self._symbols.items() if self.portfolio[symbol].quantity != 0}}
+            reductions = sorted(ticker for ticker in active if requested.get(ticker, 0.0) < current.get(ticker, 0.0))
+            increases = sorted(active - set(reductions))
+            for ticker in reductions + increases:
+                symbol = self._symbols[ticker]
+                if symbol not in data.bars:
+                    continue
+                price = float(data.bars[symbol].close)
+                lot = float(self._properties[ticker]["lot_size"])
+                raw = (requested.get(ticker, 0.0) - current.get(ticker, 0.0)) * value / price
+                delta = math.copysign(math.floor(abs(raw) / lot + 0.5) * lot, raw)
+                if abs(delta) >= lot:
+                    self.market_order(symbol, delta)
+        with self._equity_path.open("a", newline="") as stream:
+            csv.writer(stream).writerow([key, float(self.portfolio.total_portfolio_value), float(self.portfolio.cash_book["USDT"].amount), float(self.portfolio.total_holdings_value)])
+
+    def on_order_event(self, event: OrderEvent):
+        fee = float(event.order_fee.value.amount) if event.order_fee and event.order_fee.value else 0.0
+        with self._events_path.open("a", newline="") as stream:
+            csv.writer(stream).writerow([self.time.strftime("%Y-%m-%d %H:%M:%S"), event.symbol.value if event.symbol else "", str(event.status), str(event.direction), float(event.fill_quantity), float(event.fill_price), fee, str(event.message or "").replace("\\n", " "), int(event.order_id)])
+
+    def on_end_of_algorithm(self):
+        self._runtime_path.write_text(json.dumps({{"engine_seconds": time.perf_counter() - self._started}}))
+"""
+    (project / "main.py").write_text(main_code, encoding="utf-8")
+    return project, {"manifest": manifest, "properties": properties}
+
+
+def run(bundle: Path) -> tuple[dict[str, Any], pl.DataFrame, pl.DataFrame, pl.DataFrame]:
+    project, inputs = _prepare_project(bundle)
+    targets = tomllib.loads((PROJECT_ROOT / "validation/framework_targets.toml").read_text())
+    output_dir = project / "backtests" / str(time.time_ns())
+    run_lean_backtest(
+        lean_cmd=resolve_lean_command(),
+        cwd=PROJECT_ROOT,
+        project_dir=project,
+        lean_config=PROJECT_ROOT / "validation/lean/workspace/lean.json",
+        output_dir=output_dir,
+        image=targets["framework"]["lean"]["artifact"],
+        env=make_lean_env(),
+    )
+    copy_lean_artifacts(
+        project,
+        output_dir,
+        [
+            "ml4t_daily_equity.csv",
+            "ml4t_funding_observed.csv",
+            "ml4t_order_events.csv",
+            "ml4t_runtime.json",
+            "ml4t_symbol_map.json",
+        ],
+    )
+    _, final_value, fills_pd, equity_pd, events_pd = load_lean_artifacts(output_dir)
+    if fills_pd is None or equity_pd is None or events_pd is None:
+        raise RuntimeError("LEAN did not produce the required comparison surfaces")
+    fills_pd = fills_pd.rename(columns={"fill_price": "price", "fee": "commission"})
+    fills = pl.from_pandas(
+        fills_pd[["timestamp", "asset", "side", "quantity", "price", "commission"]]
+    )
+    equity = pl.from_pandas(equity_pd[["timestamp", "equity", "cash", "holdings_value"]])
+    runtime = json.loads((output_dir / "ml4t_runtime.json").read_text(encoding="utf-8"))
+    rejected = events_pd[events_pd["status"].astype(str).str.lower().isin({"invalid", "canceled"})]
+    evidence = {
+        "schema_version": 1,
+        "case_study": inputs["manifest"]["case_study"],
+        "framework": "lean",
+        "comparison_profile": "lean_crypto_future",
+        "comparison_costs": "disabled_except_native_funding",
+        "comparison_position_rules": "disabled",
+        "input_bundle_sha256": inputs["manifest"]["bundle_sha256"],
+        "symbol_properties_sha256": _sha256(project / "symbol_properties.json"),
+        "engine_seconds": float(runtime["engine_seconds"]),
+        "final_value": final_value,
+        "num_fills": fills.height,
+        "num_rejections": len(rejected),
+    }
+    rejected_frame = pl.from_pandas(
+        rejected[["timestamp", "asset", "fill_quantity", "message", "order_id"]]
+    )
+    return evidence, fills, equity, rejected_frame
+
+
+def write_evidence(
+    output: Path,
+    evidence: dict[str, Any],
+    fills: pl.DataFrame,
+    equity: pl.DataFrame,
+    rejections: pl.DataFrame,
+) -> None:
+    output.parent.mkdir(parents=True, exist_ok=True)
+    staging = Path(tempfile.mkdtemp(prefix=f".{output.name}.", dir=output.parent))
+    try:
+        fills.write_parquet(staging / "fills.parquet", compression="zstd", statistics=True)
+        equity.write_parquet(staging / "equity.parquet", compression="zstd", statistics=True)
+        rejections.write_parquet(
+            staging / "rejected_orders.parquet", compression="zstd", statistics=True
+        )
+        evidence["files"] = {
+            path.name: {"sha256": _sha256(path), "bytes": path.stat().st_size}
+            for path in sorted(staging.iterdir())
+        }
+        (staging / "manifest.json").write_text(
+            json.dumps(evidence, indent=2, sort_keys=True) + "\n", encoding="utf-8"
+        )
+        if output.exists():
+            raise FileExistsError(f"Evidence output already exists: {output}")
+        os.replace(staging, output)
+    finally:
+        if staging.exists():
+            for path in staging.iterdir():
+                path.unlink()
+            staging.rmdir()
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--bundle", type=Path, required=True)
+    parser.add_argument("--output", type=Path, required=True)
+    args = parser.parse_args()
+    evidence, fills, equity, rejections = run(args.bundle.resolve())
+    write_evidence(args.output.resolve(), evidence, fills, equity, rejections)
+    print(
+        f"{evidence['case_study']}: {evidence['num_fills']:,} fills, "
+        f"{evidence['engine_seconds']:.6f}s engine time"
+    )
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/real_strategy_runner.py b/validation/real_strategy_runner.py
new file mode 100644
index 00000000..784ed760
--- /dev/null
+++ b/validation/real_strategy_runner.py
@@ -0,0 +1,475 @@
+#!/usr/bin/env python3
+"""Execute a frozen real-strategy input bundle with ml4t.backtest."""
+
+from __future__ import annotations
+
+import argparse
+import copy
+import hashlib
+import json
+import math
+import os
+import tempfile
+import time
+from collections.abc import Mapping
+from datetime import UTC, datetime, timedelta
+from functools import wraps
+from pathlib import Path
+from typing import Any
+
+import polars as pl
+
+from ml4t.backtest import (
+    AssetClass,
+    BacktestConfig,
+    ContractSpec,
+    DataFeed,
+    Engine,
+    RebalanceConfig,
+    Strategy,
+    TargetWeightExecutor,
+)
+from ml4t.backtest.profiles import get_profile_config
+from ml4t.backtest.risk import RuleChain, StopLoss, TimeExit, TrailingStop
+
+SCHEMA_VERSION = 1
+
+
+def _sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as stream:
+        for chunk in iter(lambda: stream.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def _as_utc(value: datetime) -> datetime:
+    return value.replace(tzinfo=UTC) if value.tzinfo is None else value.astimezone(UTC)
+
+
+class FundingSettlementLedger:
+    """Apply frozen perpetual-futures funding during engine mark updates."""
+
+    def __init__(self, funding: pl.DataFrame, *, skip_first_after_entry: bool = False) -> None:
+        required = {"symbol", "timestamp", "funding_rate"}
+        missing = required - set(funding.columns)
+        if missing:
+            raise ValueError(f"Funding input lacks columns: {sorted(missing)}")
+        selected = funding.select("symbol", "timestamp", "funding_rate")
+        if selected.null_count().row(0) != (0, 0, 0):
+            raise ValueError("Funding input contains null keys or rates")
+        if selected.n_unique(["symbol", "timestamp"]) != selected.height:
+            raise ValueError("Funding input contains duplicate settlement keys")
+        self._rates: dict[datetime, dict[str, float]] = {}
+        for row in selected.sort("timestamp", "symbol").iter_rows(named=True):
+            rate = float(row["funding_rate"])
+            if not math.isfinite(rate):
+                raise ValueError("Funding rates must be finite")
+            timestamp = _as_utc(row["timestamp"])
+            self._rates.setdefault(timestamp, {})[str(row["symbol"])] = rate
+        self._rate_count = selected.height
+        self._symbols = sorted(selected["symbol"].unique().to_list())
+        self._settled_timestamps: set[datetime] = set()
+        self._skip_first_after_entry = skip_first_after_entry
+        self._next_application: dict[str, datetime | None] = {}
+        self.funding_pnl = 0.0
+        self.funding_events = 0
+        self.funding_settlements = 0
+
+    def install(self, broker: Any) -> None:
+        original_update_time = broker._update_time
+
+        @wraps(original_update_time)
+        def update_time_with_funding(timestamp, *args, **kwargs):
+            result = original_update_time(timestamp, *args, **kwargs)
+            self.settle(timestamp, broker)
+            return result
+
+        broker._update_time = update_time_with_funding
+
+    def settle(self, timestamp: datetime, broker: Any) -> None:
+        normalized = _as_utc(timestamp)
+        rates = self._rates.get(normalized)
+        if rates is not None and normalized not in self._settled_timestamps:
+            self._settled_timestamps.add(normalized)
+            self.funding_settlements += len(rates)
+        event_cash = 0.0
+        symbols = self._symbols if self._skip_first_after_entry else list(rates or ())
+        for symbol in symbols:
+            position = broker.positions.get(symbol)
+            if position is None or float(position.quantity) == 0.0:
+                self._next_application[symbol] = None
+                continue
+            if self._skip_first_after_entry and self._next_application.get(symbol) is None:
+                self._next_application[symbol] = self._next_funding_time(normalized)
+                continue
+            if rates is None or symbol not in rates:
+                continue
+            if self._skip_first_after_entry:
+                next_application = self._next_application[symbol]
+                if next_application is None or normalized < next_application:
+                    continue
+                while next_application <= normalized:
+                    next_application += timedelta(hours=8)
+                self._next_application[symbol] = next_application
+            rate = rates[symbol]
+            mark = broker.get_mark_price(symbol, quantity=position.quantity)
+            if mark is None:
+                raise RuntimeError(f"Funding settlement lacks a mark for {symbol!r}")
+            event_cash -= (
+                float(position.quantity)
+                * float(mark)
+                * float(getattr(position, "multiplier", 1.0))
+                * rate
+            )
+        if event_cash:
+            broker.cash = float(broker.cash) + event_cash
+            self.funding_pnl += event_cash
+            self.funding_events += 1
+
+    @staticmethod
+    def _next_funding_time(current: datetime) -> datetime:
+        if current.hour >= 16:
+            return (current + timedelta(days=1)).replace(hour=0, minute=0, second=0, microsecond=0)
+        if current.hour >= 8:
+            return current.replace(hour=16, minute=0, second=0, microsecond=0)
+        return current.replace(hour=8, minute=0, second=0, microsecond=0)
+
+    def metrics(self) -> dict[str, int | float]:
+        if self.funding_settlements != self._rate_count:
+            raise RuntimeError(
+                "Funding coverage is incomplete: "
+                f"{self.funding_settlements}/{self._rate_count} settlements"
+            )
+        return {
+            "funding_pnl": self.funding_pnl,
+            "funding_events": self.funding_events,
+            "funding_settlements": self.funding_settlements,
+        }
+
+
+def _position_rules(risk: Mapping[str, Any]) -> object | None:
+    rules = []
+    for rule in risk.get("position_rules", []):
+        rule_type = rule["type"]
+        if rule_type == "stop_loss":
+            rules.append(StopLoss(pct=float(rule["threshold"])))
+        elif rule_type == "trailing_stop":
+            rules.append(TrailingStop(pct=float(rule["threshold"])))
+        elif rule_type == "time_exit":
+            rules.append(TimeExit(max_bars=int(rule["bars"])))
+        else:
+            raise ValueError(f"Unsupported frozen position rule: {rule_type}")
+    if len(rules) == 1:
+        return rules[0]
+    return RuleChain(rules) if rules else None
+
+
+def _contract_specs(path: Path) -> dict[str, ContractSpec] | None:
+    if not path.is_file():
+        return None
+    payload = json.loads(path.read_text(encoding="utf-8"))
+    return {
+        symbol: ContractSpec(
+            symbol=symbol,
+            asset_class=AssetClass(item["asset_class"]),
+            multiplier=float(item["multiplier"]),
+            tick_size=float(item["tick_size"]),
+            margin=None if item["margin"] is None else float(item["margin"]),
+            margin_pct=(
+                None
+                if item["margin_pct"] is None
+                else (float(item["margin_pct"][0]), float(item["margin_pct"][1]))
+            ),
+            currency=str(item["currency"]),
+        )
+        for symbol, item in payload.items()
+    }
+
+
+def _target_map(targets: pl.DataFrame) -> dict[datetime, dict[str, float]]:
+    duplicates = targets.select(pl.struct("timestamp", "symbol").is_duplicated().sum()).item()
+    if duplicates:
+        raise ValueError(f"Targets contain {duplicates} duplicate timestamp-symbol rows")
+    result: dict[datetime, dict[str, float]] = {}
+    for row in targets.sort("timestamp", "symbol").iter_rows(named=True):
+        result.setdefault(row["timestamp"], {})[str(row["symbol"])] = float(row["weight"])
+    return result
+
+
+def load_bundle(bundle: Path) -> dict[str, Any]:
+    """Load and verify one content-addressed bundle before engine timing begins."""
+    manifest = json.loads((bundle / "manifest.json").read_text(encoding="utf-8"))
+    for name, identity in manifest["files"].items():
+        path = bundle / name
+        if not path.is_file() or _sha256(path) != identity["sha256"]:
+            raise ValueError(f"Bundle file identity mismatch: {name}")
+    spec = json.loads((bundle / "spec.json").read_text(encoding="utf-8"))
+    return {
+        "manifest": manifest,
+        "spec": spec,
+        "market": pl.read_parquet(bundle / "market.parquet"),
+        "targets": pl.read_parquet(bundle / "targets.parquet"),
+        "funding": (
+            pl.read_parquet(bundle / "funding.parquet")
+            if (bundle / "funding.parquet").is_file()
+            else None
+        ),
+        "contracts": _contract_specs(bundle / "contracts.json"),
+    }
+
+
+def _comparison_config(spec: Mapping[str, Any], profile: str) -> BacktestConfig:
+    source = spec["backtest_config"]
+    profile_data = (
+        copy.deepcopy(source) if profile == "lean_crypto_future" else get_profile_config(profile)
+    )
+    profile_data["account"]["allow_short_selling"] = source["account"]["allow_short_selling"]
+    if profile not in {"lean", "lean_crypto_future"}:
+        profile_data["account"]["allow_leverage"] = source["account"]["allow_leverage"]
+    else:
+        profile_data["account"]["allow_leverage"] = True
+    if profile == "lean_crypto_future":
+        profile_data["account"]["initial_margin"] = 0.04
+        profile_data["account"]["long_maintenance_margin"] = 0.02
+        profile_data["account"]["short_maintenance_margin"] = 0.02
+    profile_data["cash"]["initial"] = source["cash"]["initial"]
+    profile_data["calendar"] = source["calendar"]
+    profile_data["feed"] = source["feed"]
+    profile_data["commission"] = {
+        "model": "none",
+        "rate": 0.0,
+        "per_share": 0.0,
+        "per_trade": 0.0,
+        "minimum": 0.0,
+    }
+    profile_data["slippage"] = {"model": "none", "rate": 0.0}
+    profile_data["orders"]["rebalance_headroom_pct"] = 1.0
+    profile_data["metadata"] = {
+        **source.get("metadata", {}),
+        "comparison_profile": profile,
+        "comparison_costs": "disabled",
+        "comparison_position_rules": "disabled",
+    }
+    return BacktestConfig.from_dict(profile_data, preset_name=profile)
+
+
+def execute_bundle(
+    inputs: Mapping[str, Any],
+    *,
+    comparison_profile: str | None = None,
+    price_decimals: int | None = None,
+    execution_specs: Mapping[str, Mapping[str, float]] | None = None,
+) -> tuple[Any, float, dict[str, int | float]]:
+    """Run the engine once and return its native result and engine-only runtime."""
+    spec = inputs["spec"]
+    config = (
+        _comparison_config(spec, comparison_profile)
+        if comparison_profile is not None
+        else BacktestConfig.from_dict(spec["backtest_config"])
+    )
+    targets = _target_map(inputs["targets"])
+    rebalance = spec["strategy"]["rebalance"]
+    rules = (
+        None
+        if comparison_profile is not None
+        else _position_rules(spec["strategy"].get("risk", {}))
+    )
+    funding = inputs["funding"]
+    funding_ledger = (
+        FundingSettlementLedger(
+            funding,
+            skip_first_after_entry=comparison_profile == "lean_crypto_future",
+        )
+        if funding is not None
+        else None
+    )
+
+    class FrozenTargetStrategy(Strategy):
+        def __init__(self) -> None:
+            self._rules_set = False
+            self._executor = TargetWeightExecutor(
+                RebalanceConfig(
+                    min_trade_value=(
+                        0.0
+                        if comparison_profile is not None
+                        else float(rebalance["min_trade_value"])
+                    ),
+                    min_weight_change=(
+                        0.0
+                        if comparison_profile is not None
+                        else float(rebalance["min_weight_change"])
+                    ),
+                    allow_fractional=None,
+                    allow_short=bool(config.allow_short_selling),
+                    rebalance_mode=config.rebalance_mode,
+                    share_rounding=config.share_rounding,
+                )
+            )
+
+        def on_start(self, broker) -> None:
+            if funding_ledger is not None:
+                funding_ledger.install(broker)
+
+        def on_data(self, timestamp, data, context, broker) -> None:
+            if not self._rules_set:
+                if rules is not None:
+                    broker.set_position_rules(rules)
+                self._rules_set = True
+            target = targets.get(timestamp)
+            if target is not None:
+                available = {symbol: weight for symbol, weight in target.items() if symbol in data}
+                if available:
+                    if execution_specs is None:
+                        self._executor.execute(available, data, broker)
+                    else:
+                        value = broker.equity()
+                        current = {
+                            symbol: (
+                                float(position.quantity) * float(data[symbol]["close"]) / value
+                            )
+                            for symbol, position in broker.positions.items()
+                            if symbol in data and float(position.quantity) != 0.0
+                        }
+                        active = set(available) | set(current)
+                        reductions = sorted(
+                            symbol
+                            for symbol in active
+                            if available.get(symbol, 0.0) < current.get(symbol, 0.0)
+                        )
+                        increases = sorted(active - set(reductions))
+                        for symbol in reductions + increases:
+                            if symbol not in data:
+                                continue
+                            price = float(data[symbol]["close"])
+                            lot = float(execution_specs[symbol]["lot_size"])
+                            raw = (
+                                (available.get(symbol, 0.0) - current.get(symbol, 0.0))
+                                * value
+                                / price
+                            )
+                            quantity = math.copysign(
+                                math.floor(abs(raw) / lot + 0.5) * lot,
+                                raw,
+                            )
+                            if abs(quantity) >= lot:
+                                broker.submit_order(symbol, quantity)
+
+    market = inputs["market"]
+    if price_decimals is not None:
+        market = market.with_columns(
+            pl.col(column).round(price_decimals)
+            for column in ("open", "high", "low", "close")
+            if column in market.columns
+        )
+    feed = DataFeed(prices_df=market, feed_spec=config.feed_spec)
+    engine = Engine.from_config(
+        feed,
+        FrozenTargetStrategy(),
+        config,
+        contract_specs=inputs["contracts"],
+    )
+    started = time.perf_counter()
+    result = engine.run()
+    engine_seconds = time.perf_counter() - started
+    funding_metrics = funding_ledger.metrics() if funding_ledger is not None else {}
+    return result, engine_seconds, funding_metrics
+
+
+def _write_evidence(
+    *,
+    output: Path,
+    inputs: Mapping[str, Any],
+    result: Any,
+    engine_seconds: float,
+    funding_metrics: Mapping[str, int | float],
+    comparison_profile: str | None,
+    price_decimals: int | None,
+    execution_specs_sha256: str | None,
+) -> None:
+    output.parent.mkdir(parents=True, exist_ok=True)
+    staging = Path(tempfile.mkdtemp(prefix=f".{output.name}.", dir=output.parent))
+    try:
+        frames = {
+            "fills.parquet": result.to_fills_dataframe(),
+            "rejected_orders.parquet": result.to_rejected_orders_dataframe(),
+            "trades.parquet": result.to_trades_dataframe(),
+            "equity.parquet": result.to_equity_dataframe(),
+            "portfolio_state.parquet": result.to_portfolio_state_dataframe(),
+        }
+        for name, frame in frames.items():
+            frame.write_parquet(staging / name, compression="zstd", statistics=True)
+        manifest = {
+            "schema_version": SCHEMA_VERSION,
+            "case_study": inputs["manifest"]["case_study"],
+            "framework": "ml4t_backtest",
+            "comparison_profile": comparison_profile,
+            "price_decimals": price_decimals,
+            "execution_specs_sha256": execution_specs_sha256,
+            "input_bundle_sha256": inputs["manifest"]["bundle_sha256"],
+            "engine_seconds": engine_seconds,
+            "final_value": float(result.metrics["final_value"]),
+            "num_fills": len(result.fills),
+            "num_rejections": len(result.rejected_orders),
+            "num_trades": len(result.trades),
+            "funding": dict(funding_metrics),
+            "files": {},
+        }
+        manifest["files"] = {
+            path.name: {"sha256": _sha256(path), "bytes": path.stat().st_size}
+            for path in sorted(staging.iterdir())
+        }
+        (staging / "manifest.json").write_text(
+            json.dumps(manifest, indent=2, sort_keys=True) + "\n", encoding="utf-8"
+        )
+        if output.exists():
+            raise FileExistsError(f"Evidence output already exists: {output}")
+        os.replace(staging, output)
+    finally:
+        if staging.exists():
+            for path in staging.iterdir():
+                path.unlink()
+            staging.rmdir()
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--bundle", type=Path, required=True)
+    parser.add_argument("--output", type=Path, required=True)
+    parser.add_argument("--comparison-profile")
+    parser.add_argument("--price-decimals", type=int)
+    parser.add_argument("--execution-specs", type=Path)
+    args = parser.parse_args()
+    inputs = load_bundle(args.bundle.resolve())
+    execution_specs = (
+        json.loads(args.execution_specs.read_text(encoding="utf-8"))
+        if args.execution_specs is not None
+        else None
+    )
+    result, engine_seconds, funding_metrics = execute_bundle(
+        inputs,
+        comparison_profile=args.comparison_profile,
+        price_decimals=args.price_decimals,
+        execution_specs=execution_specs,
+    )
+    _write_evidence(
+        output=args.output.resolve(),
+        inputs=inputs,
+        result=result,
+        engine_seconds=engine_seconds,
+        funding_metrics=funding_metrics,
+        comparison_profile=args.comparison_profile,
+        price_decimals=args.price_decimals,
+        execution_specs_sha256=(
+            _sha256(args.execution_specs) if args.execution_specs is not None else None
+        ),
+    )
+    print(
+        f"{inputs['manifest']['case_study']}: {len(result.fills):,} fills, "
+        f"{len(result.trades):,} trades, {engine_seconds:.6f}s engine time"
+    )
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/real_strategy_vectorbt.py b/validation/real_strategy_vectorbt.py
new file mode 100644
index 00000000..89eb5056
--- /dev/null
+++ b/validation/real_strategy_vectorbt.py
@@ -0,0 +1,160 @@
+#!/usr/bin/env python3
+"""Run a frozen real target-allocation workload with VectorBT."""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import importlib
+import json
+import os
+import tempfile
+import time
+from pathlib import Path
+from typing import Any
+
+import numpy as np
+import pandas as pd
+import polars as pl
+
+
+def _sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as stream:
+        for chunk in iter(lambda: stream.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def _wide(frame: pl.DataFrame, value: str) -> pd.DataFrame:
+    pivoted = frame.select("timestamp", "symbol", value).pivot(
+        on="symbol", index="timestamp", values=value
+    )
+    result = pd.DataFrame(pivoted.sort("timestamp").to_dict(as_series=False)).set_index("timestamp")
+    result.index = pd.DatetimeIndex(result.index)
+    return result
+
+
+def run(bundle: Path, framework: str) -> tuple[dict[str, Any], pl.DataFrame, pl.DataFrame]:
+    package = "vectorbtpro" if framework == "vectorbt_pro" else "vectorbt"
+    vbt = importlib.import_module(package)
+    manifest = json.loads((bundle / "manifest.json").read_text(encoding="utf-8"))
+    case_study = manifest["case_study"]
+    if case_study == "cme_futures" and framework != "vectorbt_pro":
+        raise ValueError("VectorBT OSS lacks the contract multiplier used by this workload")
+    if case_study not in {"etfs", "cme_futures"}:
+        raise ValueError("This adapter accepts the ETF and CME futures workloads")
+    spec = json.loads((bundle / "spec.json").read_text(encoding="utf-8"))
+    close = _wide(pl.read_parquet(bundle / "market.parquet"), "close")
+    weights = _wide(pl.read_parquet(bundle / "targets.parquet"), "weight").reindex(
+        index=close.index, columns=close.columns
+    )
+    rebalance_rows = weights.notna().any(axis=1)
+    weights.loc[rebalance_rows] = weights.loc[rebalance_rows].fillna(0.0)
+    kwargs: dict[str, Any] = {
+        "close": close,
+        "size": weights,
+        "size_type": "targetpercent",
+        "init_cash": float(spec["backtest_config"]["cash"]["initial"]),
+        "fees": 0.0,
+        "slippage": 0.0,
+        "cash_sharing": True,
+        "call_seq": "auto",
+    }
+    if framework == "vectorbt_oss":
+        kwargs["lock_cash"] = True
+    elif case_study == "cme_futures":
+        contracts = json.loads((bundle / "contracts.json").read_text(encoding="utf-8"))
+        kwargs["multiplier"] = np.asarray(
+            [float(contracts[symbol]["multiplier"]) for symbol in close.columns]
+        )
+        kwargs["leverage"] = 100.0
+        kwargs["leverage_mode"] = "eager"
+    started = time.perf_counter()
+    portfolio = vbt.Portfolio.from_orders(**kwargs)
+    engine_seconds = time.perf_counter() - started
+
+    orders = portfolio.orders.records_readable
+    fill_rows = [
+        {
+            "timestamp": row.get("Timestamp", row.get("Index")),
+            "asset": row.get("Column"),
+            "side": "buy" if row.get("Side") == "Buy" else "sell",
+            "quantity": abs(float(row.get("Size", 0.0))),
+            "price": float(row.get("Price", 0.0)),
+            "commission": float(row.get("Fees", 0.0)),
+        }
+        for _, row in orders.iterrows()
+    ]
+    value_attr = portfolio.value
+    value = value_attr() if callable(value_attr) else value_attr
+    if isinstance(value, pd.DataFrame):
+        value = value.iloc[:, 0] if value.shape[1] == 1 else value.sum(axis=1)
+    equity = pl.DataFrame(
+        {
+            "timestamp": pl.Series(
+                pd.DatetimeIndex(value.index).to_pydatetime().tolist(), dtype=pl.Datetime("us")
+            ),
+            "equity": value.to_numpy(),
+        }
+    )
+    fills = pl.DataFrame(fill_rows)
+    evidence = {
+        "schema_version": 1,
+        "case_study": manifest["case_study"],
+        "framework": framework,
+        "comparison_profile": (
+            "vectorbt_strict" if framework == "vectorbt_pro" else "vectorbt_oss_strict"
+        ),
+        "comparison_costs": "disabled",
+        "comparison_position_rules": "disabled",
+        "input_bundle_sha256": manifest["bundle_sha256"],
+        "engine_seconds": engine_seconds,
+        "final_value": float(value.iloc[-1]),
+        "num_fills": fills.height,
+    }
+    return evidence, fills, equity
+
+
+def write_evidence(
+    output: Path, evidence: dict[str, Any], fills: pl.DataFrame, equity: pl.DataFrame
+) -> None:
+    output.parent.mkdir(parents=True, exist_ok=True)
+    staging = Path(tempfile.mkdtemp(prefix=f".{output.name}.", dir=output.parent))
+    try:
+        fills.write_parquet(staging / "fills.parquet", compression="zstd", statistics=True)
+        equity.write_parquet(staging / "equity.parquet", compression="zstd", statistics=True)
+        evidence["files"] = {
+            path.name: {"sha256": _sha256(path), "bytes": path.stat().st_size}
+            for path in sorted(staging.iterdir())
+        }
+        (staging / "manifest.json").write_text(
+            json.dumps(evidence, indent=2, sort_keys=True) + "\n", encoding="utf-8"
+        )
+        if output.exists():
+            raise FileExistsError(f"Evidence output already exists: {output}")
+        os.replace(staging, output)
+    finally:
+        if staging.exists():
+            for path in staging.iterdir():
+                path.unlink()
+            staging.rmdir()
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--bundle", type=Path, required=True)
+    parser.add_argument("--framework", choices=("vectorbt_pro", "vectorbt_oss"), required=True)
+    parser.add_argument("--output", type=Path, required=True)
+    args = parser.parse_args()
+    evidence, fills, equity = run(args.bundle.resolve(), args.framework)
+    write_evidence(args.output.resolve(), evidence, fills, equity)
+    print(
+        f"{evidence['case_study']}: {evidence['num_fills']:,} fills, "
+        f"{evidence['engine_seconds']:.6f}s engine time"
+    )
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/real_strategy_zipline.py b/validation/real_strategy_zipline.py
new file mode 100644
index 00000000..c7de42e0
--- /dev/null
+++ b/validation/real_strategy_zipline.py
@@ -0,0 +1,292 @@
+#!/usr/bin/env python3
+"""Run a frozen real target-allocation workload with Zipline Reloaded."""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+import math
+import os
+import tempfile
+import time
+from pathlib import Path
+from typing import Any
+
+import pandas as pd
+import polars as pl
+from zipline import run_algorithm
+from zipline.api import (
+    get_datetime,
+    order,
+    order_target,
+    set_commission,
+    set_slippage,
+    sid,
+)
+from zipline.data.bundles import ingest, register
+from zipline.finance.commission import NoCommission
+from zipline.finance.slippage import SlippageModel
+from zipline.utils.calendar_utils import get_calendar
+
+
+def _sha256(path: Path) -> str:
+    digest = hashlib.sha256()
+    with path.open("rb") as stream:
+        for chunk in iter(lambda: stream.read(1024 * 1024), b""):
+            digest.update(chunk)
+    return digest.hexdigest()
+
+
+def _targets(frame: pl.DataFrame) -> dict[pd.Timestamp, dict[str, float]]:
+    result: dict[pd.Timestamp, dict[str, float]] = {}
+    for row in frame.sort("timestamp", "symbol").iter_rows(named=True):
+        timestamp = pd.Timestamp(row["timestamp"]).normalize()
+        result.setdefault(timestamp, {})[str(row["symbol"])] = float(row["weight"])
+    return result
+
+
+def _flatten(results: pd.DataFrame, column: str) -> pd.DataFrame:
+    records: list[dict[str, Any]] = []
+    if column not in results.columns:
+        return pd.DataFrame()
+    for timestamp, payload in results[column].items():
+        if not isinstance(payload, list):
+            continue
+        for item in payload:
+            record = dict(item) if isinstance(item, dict) else item.to_dict()
+            record["timestamp"] = timestamp
+            records.append(record)
+    return pd.DataFrame(records)
+
+
+def run(bundle: Path) -> tuple[dict[str, Any], pl.DataFrame, pl.DataFrame]:
+    manifest = json.loads((bundle / "manifest.json").read_text(encoding="utf-8"))
+    if manifest["case_study"] != "etfs":
+        raise ValueError("This adapter accepts the ETF equity workload")
+    spec = json.loads((bundle / "spec.json").read_text(encoding="utf-8"))
+    market = pl.read_parquet(bundle / "market.parquet").with_columns(
+        pl.col(column).round(3) for column in ("open", "high", "low", "close")
+    )
+    target_lookup = _targets(pl.read_parquet(bundle / "targets.parquet"))
+    symbols = market["symbol"].unique().sort().to_list()
+    calendar_name = "XNYS"
+    calendar = get_calendar(calendar_name)
+    first_date = pd.Timestamp(market["timestamp"].min()).normalize()
+    last_date = pd.Timestamp(market["timestamp"].max()).normalize()
+    sessions = pd.DatetimeIndex(calendar.sessions_in_range(first_date, last_date)).tz_localize(None)
+    bundle_name = f"real_etfs_v2_{manifest['bundle_sha256'][:16]}"
+
+    def ingest_bundle(
+        _environ,
+        asset_db_writer,
+        _minute_bar_writer,
+        daily_bar_writer,
+        adjustment_writer,
+        _calendar,
+        _start_session,
+        _end_session,
+        _cache,
+        show_progress,
+        _output_dir,
+    ) -> None:
+        metadata_rows = []
+        bar_data = []
+        for asset_sid, symbol in enumerate(symbols):
+            selected = market.filter(pl.col("symbol") == symbol).select(
+                "timestamp", "open", "high", "low", "close", "volume"
+            )
+            frame = pd.DataFrame(selected.to_dict(as_series=False)).set_index("timestamp")
+            frame.index = pd.DatetimeIndex(frame.index).tz_localize(None)
+            asset_sessions = sessions[
+                (sessions >= frame.index.min()) & (sessions <= frame.index.max())
+            ]
+            observed_sessions = frame.index
+            frame = frame.reindex(asset_sessions).ffill()
+            frame.loc[~frame.index.isin(observed_sessions), "volume"] = 0
+            metadata_rows.append(
+                {
+                    "sid": asset_sid,
+                    "symbol": symbol,
+                    "asset_name": symbol,
+                    "start_date": frame.index.min(),
+                    "end_date": frame.index.max(),
+                    "first_traded": frame.index.min(),
+                    "exchange": "NYSE",
+                }
+            )
+            bar_data.append((asset_sid, frame))
+        metadata = pd.DataFrame(metadata_rows).set_index("sid")
+        asset_db_writer.write(equities=metadata)
+        daily_bar_writer.write(bar_data, show_progress=show_progress)
+        adjustment_writer.write()
+
+    zipline_root = Path(os.environ.get("ZIPLINE_ROOT", Path.home() / ".zipline"))
+    bundle_dir = zipline_root / "data" / bundle_name
+    register(
+        bundle_name,
+        ingest_bundle,
+        calendar_name=calendar_name,
+        start_session=calendar.sessions_in_range(first_date, last_date)[0],
+        end_session=calendar.sessions_in_range(first_date, last_date)[-1],
+    )
+    setup_seconds = 0.0
+    if not bundle_dir.exists() or not any(bundle_dir.iterdir()):
+        started = time.perf_counter()
+        ingest(bundle_name, show_progress=False)
+        setup_seconds = time.perf_counter() - started
+
+    class OpenPriceSlippage(SlippageModel):
+        @staticmethod
+        def process_order(data, pending_order):
+            return float(data.current(pending_order.asset, "open")), pending_order.amount
+
+    state = {"targets": target_lookup, "symbols": symbols}
+
+    def initialize(context) -> None:
+        context.state = state
+        context.assets = {symbol: sid(index) for index, symbol in enumerate(symbols)}
+        context.names = {asset: symbol for symbol, asset in context.assets.items()}
+        set_commission(us_equities=NoCommission())
+        set_slippage(us_equities=OpenPriceSlippage())
+
+    def handle_data(context, data) -> None:
+        timestamp = get_datetime()
+        timestamp = (
+            timestamp.tz_convert(None).normalize() if timestamp.tz else timestamp.normalize()
+        )
+        requested = context.state["targets"].get(timestamp)
+        if requested is None:
+            return
+        available = {
+            symbol: weight
+            for symbol, weight in requested.items()
+            if data.can_trade(context.assets[symbol])
+        }
+        if not available:
+            return
+        value = float(context.portfolio.portfolio_value)
+        current = {
+            context.names[asset]: float(position.amount)
+            * float(data.current(asset, "price"))
+            / value
+            for asset, position in context.portfolio.positions.items()
+            if position.amount != 0 and data.can_trade(asset)
+        }
+        reductions = sorted(
+            symbol for symbol, weight in available.items() if weight < current.get(symbol, 0.0)
+        )
+        omitted = sorted(symbol for symbol in current if symbol not in available)
+        increases = sorted(symbol for symbol in available if symbol not in reductions)
+        for symbol in reductions:
+            asset = context.assets[symbol]
+            price = float(data.current(asset, "price"))
+            raw = (available[symbol] - current.get(symbol, 0.0)) * value / price
+            amount = int(math.copysign(math.floor(abs(raw) + 0.5), raw))
+            if amount:
+                order(asset, amount)
+        for symbol in omitted:
+            order_target(context.assets[symbol], 0)
+        for symbol in increases:
+            asset = context.assets[symbol]
+            price = float(data.current(asset, "price"))
+            raw = (available[symbol] - current.get(symbol, 0.0)) * value / price
+            amount = int(math.copysign(math.floor(abs(raw) + 0.5), raw))
+            if amount:
+                order(asset, amount)
+
+    started = time.perf_counter()
+    results = run_algorithm(
+        start=calendar.sessions_in_range(first_date, last_date)[0],
+        end=calendar.sessions_in_range(first_date, last_date)[-1],
+        initialize=initialize,
+        handle_data=handle_data,
+        capital_base=float(spec["backtest_config"]["cash"]["initial"]),
+        bundle=bundle_name,
+        data_frequency="daily",
+        trading_calendar=calendar,
+    )
+    engine_seconds = time.perf_counter() - started
+    transactions = _flatten(results, "transactions")
+    fill_rows = []
+    for _, row in transactions.iterrows():
+        asset = row["sid"]
+        amount = float(row["amount"])
+        fill_rows.append(
+            {
+                "timestamp": pd.Timestamp(row["timestamp"]).tz_localize(None),
+                "asset": asset.symbol,
+                "side": "buy" if amount > 0 else "sell",
+                "quantity": abs(amount),
+                "price": float(row["price"]),
+                "commission": 0.0,
+            }
+        )
+    fills = pl.DataFrame(fill_rows)
+    equity = pl.DataFrame(
+        {
+            "timestamp": pl.Series(
+                pd.DatetimeIndex(results.index).tz_localize(None).to_pydatetime().tolist(),
+                dtype=pl.Datetime("us"),
+            ),
+            "equity": results["portfolio_value"].to_numpy(),
+        }
+    )
+    evidence = {
+        "schema_version": 1,
+        "case_study": manifest["case_study"],
+        "framework": "zipline",
+        "comparison_profile": "zipline_strict",
+        "comparison_costs": "disabled",
+        "comparison_position_rules": "disabled",
+        "price_decimals": 3,
+        "input_bundle_sha256": manifest["bundle_sha256"],
+        "setup_seconds": setup_seconds,
+        "engine_seconds": engine_seconds,
+        "final_value": float(results["portfolio_value"].iloc[-1]),
+        "num_fills": fills.height,
+    }
+    return evidence, fills, equity
+
+
+def write_evidence(
+    output: Path, evidence: dict[str, Any], fills: pl.DataFrame, equity: pl.DataFrame
+) -> None:
+    output.parent.mkdir(parents=True, exist_ok=True)
+    staging = Path(tempfile.mkdtemp(prefix=f".{output.name}.", dir=output.parent))
+    try:
+        fills.write_parquet(staging / "fills.parquet", compression="zstd", statistics=True)
+        equity.write_parquet(staging / "equity.parquet", compression="zstd", statistics=True)
+        evidence["files"] = {
+            path.name: {"sha256": _sha256(path), "bytes": path.stat().st_size}
+            for path in sorted(staging.iterdir())
+        }
+        (staging / "manifest.json").write_text(
+            json.dumps(evidence, indent=2, sort_keys=True) + "\n", encoding="utf-8"
+        )
+        if output.exists():
+            raise FileExistsError(f"Evidence output already exists: {output}")
+        os.replace(staging, output)
+    finally:
+        if staging.exists():
+            for path in staging.iterdir():
+                path.unlink()
+            staging.rmdir()
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--bundle", type=Path, required=True)
+    parser.add_argument("--output", type=Path, required=True)
+    args = parser.parse_args()
+    evidence, fills, equity = run(args.bundle.resolve())
+    write_evidence(args.output.resolve(), evidence, fills, equity)
+    print(
+        f"{evidence['case_study']}: {evidence['num_fills']:,} fills, "
+        f"{evidence['engine_seconds']:.6f}s engine time"
+    )
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/release_checks.txt b/validation/release_checks.txt
index 16c53af8..dfbea790 100644
--- a/validation/release_checks.txt
+++ b/validation/release_checks.txt
@@ -2,14 +2,33 @@ validation/check_artifacts.py
 validation/check_coverage.py
 validation/check_documentation_examples.py
 validation/check_security.py
+validation/build_framework_env.py
+validation/cross_framework_performance.py
 validation/generate_changelog.py
 validation/generate_compatibility_snapshot.py
 validation/generate_parity_claims.py
 validation/performance_baseline.py
 validation/release_candidate.py
 validation/run_all_correctness.py
+validation/run_lean_case_studies.py
+validation/common/canonical_records.py
+validation/common/capabilities.py
 validation/common/comparator.py
+validation/common/correctness_evidence.py
 validation/common/data_generators.py
+validation/common/framework_registry.py
 validation/common/ml4t_runner.py
+validation/common/provenance.py
+validation/large_scale_evidence.py
+validation/real_strategy_corpus.py
+validation/real_strategy_benchmark.py
+validation/real_strategy_evidence.py
+validation/real_strategy_runner.py
+validation/real_strategy_lean.py
+validation/real_strategy_lean_crypto.py
 validation/common/types.py
+validation/native/vectorbt_behavior.py
+validation/native/backtrader_behavior.py
+validation/native/zipline_behavior.py
+validation/native/lean_behavior.py
 validation/scenarios/definitions.py
diff --git a/validation/run_all_benchmarks.py b/validation/run_all_benchmarks.py
index f9befe4b..193f940b 100644
--- a/validation/run_all_benchmarks.py
+++ b/validation/run_all_benchmarks.py
@@ -1,739 +1,30 @@
 #!/usr/bin/env python3
-"""Unified Performance Benchmark Runner.
+"""Compatibility entry point for the retained cross-framework performance harness."""
 
-Runs performance benchmarks across all frameworks and generates a summary report.
+from __future__ import annotations
 
-Usage:
-    # Run all frameworks
-    python validation/run_all_benchmarks.py
-
-    # Run specific framework
-    python validation/run_all_benchmarks.py --framework ml4t
-
-    # Run specific configuration
-    python validation/run_all_benchmarks.py --config "100x1" "1000x1"
-
-Output:
-    - Console summary
-    - validation/BENCHMARK_RESULTS.md
-"""
-
-import argparse
-import gc
-import json
-import subprocess
 import sys
-import time
-import tracemalloc
-from datetime import datetime
 from pathlib import Path
 
-import numpy as np
-import pandas as pd
-
-# Directory structure
 VALIDATION_DIR = Path(__file__).parent
-PROJECT_ROOT = VALIDATION_DIR.parent
+sys.path.insert(0, str(VALIDATION_DIR))
 
-# Add project root to path for ml4t imports
-sys.path.insert(0, str(PROJECT_ROOT / "src"))
+from common.framework_registry import load_framework_manifest  # noqa: E402
+from cross_framework_performance import main as performance_main  # noqa: E402
 
-# Framework configurations
-FRAMEWORKS = {
-    "ml4t": {
-        "venv": ".venv",
-        "display_name": "ml4t.backtest",
-        "function": "benchmark_ml4t",
-    },
-    "vectorbt_pro": {
-        "venv": ".venv-vectorbt-pro",
-        "display_name": "VectorBT Pro",
-        "function": "benchmark_vectorbt_pro",
-    },
-    "vectorbt_oss": {
-        "venv": ".venv",
-        "display_name": "VectorBT OSS",
-        "function": "benchmark_vectorbt_oss",
-    },
-    "backtrader": {
-        "venv": ".venv",
-        "display_name": "Backtrader",
-        "function": "benchmark_backtrader",
-    },
-    "zipline": {
-        "venv": ".venv",
-        "display_name": "Zipline",
-        "function": "benchmark_zipline",
-    },
-    "lean": {
-        "venv": None,  # Uses Docker
-        "display_name": "LEAN CLI",
-        "function": "benchmark_lean",
-    },
+FRAMEWORKS: dict[str, dict[str, str | None]] = {
+    "ml4t": {"venv": ".venv", "display_name": "ml4t.backtest"}
 }
-
-# Test configurations (n_bars, n_assets)
-CONFIGS = {
-    "100x1": (100, 1),
-    "500x1": (500, 1),
-    "1000x1": (1000, 1),
-    "500x5": (500, 5),
-    "1000x10": (1000, 10),
-    "2520x500": (2520, 500),  # ~10 years daily
-}
-
-
-def generate_benchmark_data(n_bars: int, n_assets: int, seed: int = 42) -> tuple:
-    """Generate benchmark data for testing."""
-    np.random.seed(seed)
-
-    # Generate date index (business days)
-    dates = pd.date_range(start="2013-01-02", periods=n_bars, freq="B", tz="UTC")
-
-    # Generate price data for multiple assets
-    asset_data = {}
-    for i in range(n_assets):
-        base_price = 100.0 + i * 10
-        returns = np.random.randn(n_bars) * 0.02
-        prices = base_price * np.exp(np.cumsum(returns))
-
-        asset_data[f"ASSET_{i:03d}"] = pd.DataFrame(
-            {
-                "open": prices * (1 + np.random.randn(n_bars) * 0.005),
-                "high": prices * (1 + np.abs(np.random.randn(n_bars)) * 0.01),
-                "low": prices * (1 - np.abs(np.random.randn(n_bars)) * 0.01),
-                "close": prices,
-                "volume": np.random.randint(100000, 1000000, n_bars).astype(float),
-            },
-            index=dates,
-        )
-
-    # Generate signals - entry every 20 bars, exit 10 bars later
-    entries = np.zeros(n_bars, dtype=bool)
-    exits = np.zeros(n_bars, dtype=bool)
-
-    i = 0
-    while i < n_bars - 11:
-        entries[i] = True
-        exits[i + 10] = True
-        i += 20
-
-    return asset_data, entries, exits, dates
-
-
-def benchmark_ml4t(asset_data: dict, entries: np.ndarray, exits: np.ndarray, dates) -> dict:
-    """Benchmark ml4t.backtest."""
-    import polars as pl
-
-    from ml4t.backtest._validation_imports import DataFeed, Engine, ExecutionMode, NoCommission, NoSlippage, Strategy
-
-    # Prepare data in polars format
-    rows = []
-    for asset_name, df in asset_data.items():
-        for ts, row in df.iterrows():
-            rows.append(
-                {
-                    "timestamp": ts.to_pydatetime().replace(tzinfo=None),
-                    "asset": asset_name,
-                    "open": row["open"],
-                    "high": row["high"],
-                    "low": row["low"],
-                    "close": row["close"],
-                    "volume": row["volume"],
-                }
-            )
-
-    prices_pl = pl.DataFrame(rows)
-
-    # Prepare signals
-    signal_rows = []
-    for asset_name in asset_data:
-        for i, ts in enumerate(dates):
-            signal_rows.append(
-                {
-                    "timestamp": ts.to_pydatetime().replace(tzinfo=None),
-                    "asset": asset_name,
-                    "entry": bool(entries[i]),
-                    "exit": bool(exits[i]),
-                }
-            )
-
-    signals_pl = pl.DataFrame(signal_rows)
-
-    class BenchmarkStrategy(Strategy):
-        def on_data(self, timestamp, data, context, broker):
-            for asset_name, asset_data in data.items():
-                signals = asset_data.get("signals", {})
-                position = broker.get_position(asset_name)
-                current_qty = position.quantity if position else 0
-
-                if signals.get("exit") and current_qty > 0:
-                    broker.close_position(asset_name)
-                elif signals.get("entry") and current_qty == 0:
-                    broker.submit_order(asset_name, 100)
-
-    # Warm-up run
-    small_prices = prices_pl.head(100 * len(asset_data))
-    small_signals = signals_pl.head(100 * len(asset_data))
-    small_feed = DataFeed(prices_df=small_prices, signals_df=small_signals)
-    small_engine = Engine(
-        small_feed,
-        BenchmarkStrategy(),
-        initial_cash=100_000_000.0,  # Match main run
-        allow_short_selling=False,
-        commission_model=NoCommission(),
-        slippage_model=NoSlippage(),
-        execution_mode=ExecutionMode.SAME_BAR,
-    )
-    _ = small_engine.run()
-
-    gc.collect()
-    tracemalloc.start()
-    start_time = time.perf_counter()
-
-    feed = DataFeed(prices_df=prices_pl, signals_df=signals_pl)
-    engine = Engine(
-        feed,
-        BenchmarkStrategy(),
-        initial_cash=100_000_000.0,  # $100M to handle 500 assets
-        allow_short_selling=False,
-        commission_model=NoCommission(),
-        slippage_model=NoSlippage(),
-        execution_mode=ExecutionMode.SAME_BAR,
-    )
-
-    results = engine.run()
-    num_trades = results["num_trades"]
-
-    end_time = time.perf_counter()
-    current, peak = tracemalloc.get_traced_memory()
-    tracemalloc.stop()
-
-    return {
-        "framework": "ml4t.backtest",
-        "runtime_sec": end_time - start_time,
-        "num_trades": num_trades,
-        "memory_mb": peak / 1024 / 1024,
-        "success": True,
-    }
-
-
-def benchmark_vectorbt_oss(
-    asset_data: dict, entries: np.ndarray, exits: np.ndarray, dates
-) -> dict:
-    """Benchmark VectorBT OSS."""
-    try:
-        import vectorbt as vbt
-    except ImportError:
-        return {"framework": "VectorBT OSS", "success": False, "error": "Not installed"}
-
-    # Build price panel
-    close_df = pd.DataFrame({name: df["close"] for name, df in asset_data.items()})
-
-    # Expand signals to match assets
-    entries_2d = np.column_stack([entries] * len(asset_data))
-    exits_2d = np.column_stack([exits] * len(asset_data))
-
-    gc.collect()
-    tracemalloc.start()
-    start_time = time.perf_counter()
-
-    pf = vbt.Portfolio.from_signals(
-        close=close_df,
-        entries=entries_2d,
-        exits=exits_2d,
-        init_cash=100_000.0,
-        fees=0.0,
-        slippage=0.0,
-        size=100,
-        accumulate=False,
-    )
-
-    trades_count = pf.trades.count()
-    # Handle both scalar and Series (multi-asset case)
-    if hasattr(trades_count, 'sum'):
-        num_trades = int(trades_count.sum())
-    else:
-        num_trades = int(trades_count)
-
-    end_time = time.perf_counter()
-    current, peak = tracemalloc.get_traced_memory()
-    tracemalloc.stop()
-
-    return {
-        "framework": "VectorBT OSS",
-        "runtime_sec": end_time - start_time,
-        "num_trades": num_trades,
-        "memory_mb": peak / 1024 / 1024,
-        "success": True,
-    }
-
-
-def benchmark_vectorbt_pro(
-    asset_data: dict, entries: np.ndarray, exits: np.ndarray, dates
-) -> dict:
-    """Benchmark VectorBT Pro."""
-    try:
-        import vectorbtpro as vbt
-    except ImportError:
-        return {"framework": "VectorBT Pro", "success": False, "error": "Not installed"}
-
-    # Build price panel
-    close_df = pd.DataFrame({name: df["close"] for name, df in asset_data.items()})
-
-    # Expand signals to match assets
-    entries_2d = np.column_stack([entries] * len(asset_data))
-    exits_2d = np.column_stack([exits] * len(asset_data))
-
-    gc.collect()
-    tracemalloc.start()
-    start_time = time.perf_counter()
-
-    pf = vbt.Portfolio.from_signals(
-        close=close_df,
-        entries=entries_2d,
-        exits=exits_2d,
-        init_cash=100_000.0,
-        fees=0.0,
-        slippage=0.0,
-        size=100,
-        accumulate=False,
-    )
-
-    trades_count = pf.trades.count()
-    # Handle both scalar and Series (multi-asset case)
-    if hasattr(trades_count, 'sum'):
-        num_trades = int(trades_count.sum())
-    else:
-        num_trades = int(trades_count)
-
-    end_time = time.perf_counter()
-    current, peak = tracemalloc.get_traced_memory()
-    tracemalloc.stop()
-
-    return {
-        "framework": "VectorBT Pro",
-        "runtime_sec": end_time - start_time,
-        "num_trades": num_trades,
-        "memory_mb": peak / 1024 / 1024,
-        "success": True,
-    }
-
-
-def benchmark_backtrader(
-    asset_data: dict, entries: np.ndarray, exits: np.ndarray, dates
-) -> dict:
-    """Benchmark Backtrader."""
-    try:
-        import backtrader as bt
-    except ImportError:
-        return {"framework": "Backtrader", "success": False, "error": "Not installed"}
-
-    trade_count = [0]
-
-    class BenchmarkStrategy(bt.Strategy):
-        def __init__(self):
-            self.bar_idx = 0
-
-        def next(self):
-            if self.bar_idx >= len(entries):
-                return
-
-            for data in self.datas:
-                position = self.getposition(data)
-                current_qty = position.size
-
-                if exits[self.bar_idx] and current_qty > 0:
-                    self.close(data)
-                    trade_count[0] += 1
-                elif entries[self.bar_idx] and current_qty == 0:
-                    self.buy(data, size=100)
-                    trade_count[0] += 1
-
-            self.bar_idx += 1
-
-    gc.collect()
-    tracemalloc.start()
-    start_time = time.perf_counter()
-
-    cerebro = bt.Cerebro()
-    cerebro.addstrategy(BenchmarkStrategy)
-    cerebro.broker.setcash(100_000.0)
-    cerebro.broker.setcommission(commission=0.0)
-
-    for asset_name, df in asset_data.items():
-        bt_data = bt.feeds.PandasData(
-            dataname=df,
-            datetime=None,
-            open="open",
-            high="high",
-            low="low",
-            close="close",
-            volume="volume",
-            openinterest=-1,
-        )
-        cerebro.adddata(bt_data, name=asset_name)
-
-    cerebro.run()
-
-    end_time = time.perf_counter()
-    current, peak = tracemalloc.get_traced_memory()
-    tracemalloc.stop()
-
-    return {
-        "framework": "Backtrader",
-        "runtime_sec": end_time - start_time,
-        "num_trades": trade_count[0],
-        "memory_mb": peak / 1024 / 1024,
-        "success": True,
-    }
-
-
-def benchmark_zipline(
-    asset_data: dict, entries: np.ndarray, exits: np.ndarray, dates
-) -> dict:
-    """Benchmark Zipline-Reloaded."""
-    try:
-        from zipline import run_algorithm
-        from zipline.api import order, set_commission, set_slippage, symbol
-        from zipline.finance.commission import NoCommission
-        from zipline.finance.slippage import FixedSlippage
-    except ImportError:
-        return {"framework": "Zipline", "success": False, "error": "Not installed"}
-
-    # Build panel data for Zipline
-    panel_data = {}
-    for field in ["open", "high", "low", "close", "volume"]:
-        panel_data[field] = pd.DataFrame({name: df[field] for name, df in asset_data.items()})
-
-    asset_names = list(asset_data.keys())
-    trade_count = [0]
-
-    def initialize(context):
-        context.entries = entries
-        context.exits = exits
-        context.bar_idx = 0
-        context.asset_names = asset_names
-        set_commission(NoCommission())
-        set_slippage(FixedSlippage(spread=0.0))
-
-    def handle_data(context, data):
-        if context.bar_idx >= len(context.entries):
-            return
-
-        for asset_name in context.asset_names:
-            try:
-                asset = symbol(asset_name)
-            except Exception:
-                continue
-
-            position = context.portfolio.positions.get(asset)
-            current_qty = position.amount if position else 0
-
-            if context.exits[context.bar_idx] and current_qty > 0:
-                order(asset, -current_qty)
-                trade_count[0] += 1
-            elif context.entries[context.bar_idx] and current_qty == 0:
-                order(asset, 100)
-                trade_count[0] += 1
-
-        context.bar_idx += 1
-
-    gc.collect()
-    tracemalloc.start()
-    start_time = time.perf_counter()
-
-    try:
-        run_algorithm(
-            start=dates[0],
-            end=dates[-1],
-            initialize=initialize,
-            handle_data=handle_data,
-            capital_base=100_000.0,
-            data=panel_data,
-        )
-        success = True
-    except Exception as e:
-        success = False
-        return {"framework": "Zipline", "success": False, "error": str(e)}
-
-    end_time = time.perf_counter()
-    current, peak = tracemalloc.get_traced_memory()
-    tracemalloc.stop()
-
-    return {
-        "framework": "Zipline",
-        "runtime_sec": end_time - start_time,
-        "num_trades": trade_count[0],
-        "memory_mb": peak / 1024 / 1024,
-        "success": success,
-    }
-
-
-def benchmark_lean(
-    asset_data: dict, entries: np.ndarray, exits: np.ndarray, dates
-) -> dict:
-    """Benchmark LEAN CLI (requires Docker)."""
-    lean_workspace = VALIDATION_DIR / "lean" / "workspace"
-
-    if not lean_workspace.exists():
-        return {"framework": "LEAN CLI", "success": False, "error": "Workspace not found"}
-
-    # Check if lean CLI is available
-    try:
-        result = subprocess.run(
-            ["lean", "--version"],
-            capture_output=True,
-            text=True,
-            timeout=10,
-        )
-        if result.returncode != 0:
-            return {"framework": "LEAN CLI", "success": False, "error": "CLI not available"}
-    except Exception as e:
-        return {"framework": "LEAN CLI", "success": False, "error": str(e)}
-
-    # Run a simple backtest using the test_validation project
-    test_project = lean_workspace / "test_validation"
-    if not test_project.exists():
-        return {"framework": "LEAN CLI", "success": False, "error": "Test project not found"}
-
-    gc.collect()
-    start_time = time.perf_counter()
-
-    try:
-        result = subprocess.run(
-            ["lean", "backtest", str(test_project)],
-            capture_output=True,
-            text=True,
-            timeout=300,  # LEAN can be slow (Docker + initialization)
-            cwd=str(lean_workspace),
-        )
-        success = result.returncode == 0
-
-        # Parse output for performance info
-        output = result.stdout + result.stderr
-        if "Total Trades" in output:
-            # Try to extract trade count from LEAN output
-            for line in output.split("\n"):
-                if "Total Trades" in line:
-                    try:
-                        num_trades = int(line.split()[-1])
-                        break
-                    except (ValueError, IndexError):
-                        num_trades = 0
-        else:
-            num_trades = 0
-
-    except subprocess.TimeoutExpired:
-        return {"framework": "LEAN CLI", "success": False, "error": "Timeout (300s)"}
-    except Exception as e:
-        return {"framework": "LEAN CLI", "success": False, "error": str(e)}
-
-    end_time = time.perf_counter()
-
-    return {
-        "framework": "LEAN CLI",
-        "runtime_sec": end_time - start_time,
-        "num_trades": num_trades,
-        "memory_mb": 0,  # Cannot measure Docker memory easily
-        "success": success,
-        "note": "Docker-based execution, includes container startup overhead",
-    }
-
-
-def run_benchmark(config_name: str, framework: str) -> dict:
-    """Run a single benchmark configuration."""
-    n_bars, n_assets = CONFIGS[config_name]
-
-    print(f"\n  Generating data: {n_bars} bars x {n_assets} assets...")
-    asset_data, entries, exits, dates = generate_benchmark_data(n_bars, n_assets)
-
-    benchmark_func = {
-        "ml4t": benchmark_ml4t,
-        "vectorbt_pro": benchmark_vectorbt_pro,
-        "vectorbt_oss": benchmark_vectorbt_oss,
-        "backtrader": benchmark_backtrader,
-        "zipline": benchmark_zipline,
-        "lean": benchmark_lean,
-    }.get(framework)
-
-    if not benchmark_func:
-        return {"framework": framework, "success": False, "error": "Unknown framework"}
-
-    try:
-        result = benchmark_func(asset_data, entries, exits, dates)
-        result["config"] = config_name
-        result["n_bars"] = n_bars
-        result["n_assets"] = n_assets
-        return result
-    except Exception as e:
-        return {
-            "framework": framework,
-            "config": config_name,
-            "success": False,
-            "error": str(e),
+FRAMEWORKS.update(
+    {
+        framework_id: {
+            "venv": target.environment,
+            "display_name": target.display_name,
         }
-
-
-def run_all_benchmarks(
-    frameworks: list = None, configs: list = None
-) -> list:
-    """Run all benchmarks and return results."""
-    if frameworks is None:
-        frameworks = list(FRAMEWORKS.keys())
-    if configs is None:
-        configs = list(CONFIGS.keys())
-
-    results = []
-
-    for framework in frameworks:
-        config = FRAMEWORKS.get(framework)
-        if not config:
-            print(f"Unknown framework: {framework}")
-            continue
-
-        print(f"\n{'='*60}")
-        print(f"Framework: {config['display_name']}")
-        print(f"{'='*60}")
-
-        for config_name in configs:
-            print(f"\n  Config: {config_name}")
-            result = run_benchmark(config_name, framework)
-            results.append(result)
-
-            if result.get("success"):
-                print(
-                    f"    Runtime: {result['runtime_sec']:.3f}s, "
-                    f"Trades: {result['num_trades']}, "
-                    f"Memory: {result.get('memory_mb', 0):.1f} MB"
-                )
-            else:
-                print(f"    FAILED: {result.get('error', 'Unknown error')}")
-
-    return results
-
-
-def generate_report(results: list) -> str:
-    """Generate markdown report from results."""
-    now = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-
-    lines = [
-        "# Performance Benchmark Results",
-        "",
-        f"**Generated**: {now}",
-        "",
-        "## Summary",
-        "",
-        "| Framework | Config | Runtime (s) | Trades | Memory (MB) | Status |",
-        "|-----------|--------|-------------|--------|-------------|--------|",
-    ]
-
-    for r in results:
-        framework = r.get("framework", "Unknown")
-        config = r.get("config", "N/A")
-        if r.get("success"):
-            runtime = f"{r['runtime_sec']:.3f}"
-            trades = str(r.get("num_trades", "N/A"))
-            memory = f"{r.get('memory_mb', 0):.1f}"
-            status = "PASS"
-        else:
-            runtime = "-"
-            trades = "-"
-            memory = "-"
-            status = f"FAIL: {r.get('error', 'Unknown')[:30]}"
-
-        lines.append(f"| {framework} | {config} | {runtime} | {trades} | {memory} | {status} |")
-
-    # Add comparison table by config
-    lines.extend([
-        "",
-        "## Performance Comparison by Configuration",
-        "",
-    ])
-
-    # Group by config
-    configs_seen = set(r.get("config") for r in results if r.get("config"))
-    for config_name in sorted(configs_seen):
-        config_results = [r for r in results if r.get("config") == config_name and r.get("success")]
-        if not config_results:
-            continue
-
-        lines.extend([
-            f"### {config_name}",
-            "",
-            "| Framework | Runtime (s) | vs ml4t |",
-            "|-----------|-------------|---------|",
-        ])
-
-        # Find ml4t baseline
-        ml4t_time = None
-        for r in config_results:
-            if r.get("framework") == "ml4t.backtest":
-                ml4t_time = r["runtime_sec"]
-                break
-
-        for r in sorted(config_results, key=lambda x: x["runtime_sec"]):
-            framework = r["framework"]
-            runtime = r["runtime_sec"]
-            if ml4t_time and ml4t_time > 0:
-                speedup = runtime / ml4t_time
-                vs_ml4t = f"{speedup:.2f}x" if speedup > 1 else f"{1/speedup:.2f}x faster"
-            else:
-                vs_ml4t = "-"
-            lines.append(f"| {framework} | {runtime:.3f} | {vs_ml4t} |")
-
-        lines.append("")
-
-    return "\n".join(lines)
-
-
-def main():
-    parser = argparse.ArgumentParser(description="Run performance benchmarks")
-    parser.add_argument(
-        "--framework",
-        type=str,
-        help="Specific framework to test (ml4t, vectorbt_pro, vectorbt_oss, backtrader, zipline, lean)",
-    )
-    parser.add_argument(
-        "--config",
-        type=str,
-        nargs="+",
-        help="Specific configurations to run (e.g., 100x1, 1000x1)",
-    )
-    parser.add_argument(
-        "--output",
-        type=str,
-        default="validation/BENCHMARK_RESULTS.md",
-        help="Output file path",
-    )
-
-    args = parser.parse_args()
-
-    frameworks = [args.framework] if args.framework else None
-    configs = args.config if args.config else None
-
-    print("=" * 60)
-    print("Performance Benchmark Runner")
-    print("=" * 60)
-
-    results = run_all_benchmarks(frameworks=frameworks, configs=configs)
-
-    # Generate and save report
-    report = generate_report(results)
-    output_path = PROJECT_ROOT / args.output
-    output_path.write_text(report)
-
-    print(f"\n{'='*60}")
-    print(f"Report saved to: {output_path}")
-    print("=" * 60)
-
-    # Summary
-    passed = sum(1 for r in results if r.get("success"))
-    failed = len(results) - passed
-    print(f"\nTotal: {len(results)} benchmarks ({passed} passed, {failed} failed)")
-
-    return 0 if failed == 0 else 1
+        for framework_id, target in load_framework_manifest().targets.items()
+    }
+)
 
 
 if __name__ == "__main__":
-    sys.exit(main())
+    raise SystemExit(performance_main())
diff --git a/validation/run_all_correctness.py b/validation/run_all_correctness.py
index 4afd3473..8953edc8 100644
--- a/validation/run_all_correctness.py
+++ b/validation/run_all_correctness.py
@@ -14,61 +14,37 @@
 import subprocess
 import sys
 import tempfile
+import time
 from collections import Counter
-from datetime import UTC, datetime
 from pathlib import Path
 
 VALIDATION_DIR = Path(__file__).parent
 PROJECT_ROOT = VALIDATION_DIR.parent
 sys.path.insert(0, str(VALIDATION_DIR))
 
+from common.correctness_evidence import (  # noqa: E402, I001
+    build_report,
+    promote_candidate,
+    write_candidate,
+)
+from common.framework_registry import load_framework_manifest  # noqa: E402
 from common.types import ValidationRecord, ValidationStatus  # noqa: E402, I001
 from scenarios.definitions import SCENARIOS  # noqa: E402
 
+FRAMEWORK_MANIFEST = load_framework_manifest()
 FRAMEWORK_ENVIRONMENTS = {
-    "vectorbt_pro": ".venv-vectorbt-pro",
-    "vectorbt_oss": ".venv",
-    "backtrader": ".venv-backtrader",
-    "zipline": ".venv-zipline",
+    framework_id: target.environment
+    for framework_id, target in FRAMEWORK_MANIFEST.targets.items()
+    if target.scenario_matrix and target.environment is not None
 }
-
 FRAMEWORK_PYTHON_ENV_VARS = {
-    "vectorbt_pro": "ML4T_VECTORBT_PRO_PYTHON",
-    "vectorbt_oss": "ML4T_VECTORBT_OSS_PYTHON",
-    "backtrader": "ML4T_BACKTRADER_PYTHON",
-    "zipline": "ML4T_ZIPLINE_PYTHON",
+    framework_id: target.python_env_var
+    for framework_id, target in FRAMEWORK_MANIFEST.targets.items()
+    if target.scenario_matrix and target.python_env_var is not None
 }
-
 FRAMEWORK_PINS = {
-    "vectorbt_pro": {
-        "display_name": "VectorBT Pro",
-        "profile": "vectorbt_strict",
-        "package": "vectorbtpro",
-        "version": "2025.12.31",
-        "source": "https://github.com/polakowo/vectorbt.pro",
-        "commit": "1305a1e1974325db9382eaeacc6452e9b075ca71",
-    },
-    "vectorbt_oss": {
-        "display_name": "VectorBT OSS",
-        "profile": "vectorbt",
-        "package": "vectorbt",
-        "version": "0.28.2",
-        "source": "https://pypi.org/project/vectorbt/0.28.2/",
-    },
-    "backtrader": {
-        "display_name": "Backtrader",
-        "profile": "backtrader_strict",
-        "package": "backtrader",
-        "version": "1.9.78.123",
-        "source": "https://pypi.org/project/backtrader/1.9.78.123/",
-    },
-    "zipline": {
-        "display_name": "Zipline Reloaded",
-        "profile": "zipline_strict",
-        "package": "zipline-reloaded",
-        "version": "3.1.1",
-        "source": "https://pypi.org/project/zipline-reloaded/3.1.1/",
-    },
+    framework_id: FRAMEWORK_MANIFEST.targets[framework_id].evidence_metadata()
+    for framework_id in FRAMEWORK_MANIFEST.scenario_framework_ids
 }
 
 
@@ -79,6 +55,7 @@ def _record(
     *,
     required: bool = True,
     detail: str | None = None,
+    started_at: float | None = None,
 ) -> ValidationRecord:
     scenario = SCENARIOS.get(scenario_id)
     return ValidationRecord(
@@ -88,6 +65,7 @@ def _record(
         status=status,
         required=required,
         detail=detail,
+        duration_seconds=time.perf_counter() - started_at if started_at is not None else None,
     )
 
 
@@ -117,6 +95,7 @@ def run_isolated(
     timeout: int = 180,
 ) -> ValidationRecord:
     """Run one pair in its framework environment and retain its exact terminal status."""
+    started_at = time.perf_counter()
     scenario = SCENARIOS.get(scenario_id)
     if scenario is None:
         return _record(
@@ -124,6 +103,7 @@ def run_isolated(
             scenario_id,
             ValidationStatus.MISSING_SCENARIO,
             detail=f"Scenario {scenario_id} is not defined",
+            started_at=started_at,
         )
     if framework not in scenario.supported_frameworks:
         return _record(
@@ -132,6 +112,7 @@ def run_isolated(
             ValidationStatus.UNSUPPORTED,
             required=False,
             detail="Scenario explicitly excludes this framework",
+            started_at=started_at,
         )
 
     interpreter = python_path or resolve_python(framework)
@@ -141,6 +122,7 @@ def run_isolated(
             scenario_id,
             ValidationStatus.UNAVAILABLE,
             detail=f"Framework interpreter not found: {interpreter}",
+            started_at=started_at,
         )
 
     with tempfile.TemporaryDirectory(prefix="ml4t-validation-") as temporary_directory:
@@ -170,6 +152,7 @@ def run_isolated(
                 scenario_id,
                 ValidationStatus.TIMEOUT,
                 detail=f"Validation subprocess timed out after {timeout} seconds",
+                started_at=started_at,
             )
         except OSError as error:
             return _record(
@@ -177,6 +160,7 @@ def run_isolated(
                 scenario_id,
                 ValidationStatus.SUBPROCESS_FAILURE,
                 detail=f"Could not execute validation subprocess: {error}",
+                started_at=started_at,
             )
 
         if not result_path.is_file():
@@ -185,6 +169,7 @@ def run_isolated(
                 scenario_id,
                 ValidationStatus.SUBPROCESS_FAILURE,
                 detail=_process_detail(result),
+                started_at=started_at,
             )
 
         try:
@@ -198,6 +183,7 @@ def run_isolated(
                 scenario_id,
                 ValidationStatus.MALFORMED_OUTPUT,
                 detail=f"Invalid validation record: {error}",
+                started_at=started_at,
             )
 
         if record.framework != framework or record.scenario_id != scenario_id:
@@ -209,6 +195,7 @@ def run_isolated(
                     "Validation record identity mismatch: "
                     f"received {record.framework}/{record.scenario_id}"
                 ),
+                started_at=started_at,
             )
         expected_returncode = 1 if record.release_blocking else 0
         if result.returncode != expected_returncode:
@@ -220,6 +207,7 @@ def run_isolated(
                     f"Record status {record.status.value} conflicts with subprocess "
                     f"exit code {result.returncode}"
                 ),
+                started_at=started_at,
             )
         return record
 
@@ -255,16 +243,49 @@ def release_gate_passed(records: list[ValidationRecord]) -> bool:
     return bool(required_records) and all(record.passed for record in required_records)
 
 
+def matrix_coverage_failures(
+    records: list[ValidationRecord],
+    frameworks: list[str],
+    scenarios: list[str],
+) -> list[str]:
+    """Reject omitted, duplicate, or misclassified framework/scenario pairs."""
+    failures: list[str] = []
+    expected_pairs = {(framework, scenario) for framework in frameworks for scenario in scenarios}
+    actual_pairs = [(record.framework, record.scenario_id) for record in records]
+    duplicate_pairs = sorted(pair for pair, count in Counter(actual_pairs).items() if count > 1)
+    missing_pairs = sorted(expected_pairs - set(actual_pairs))
+    unexpected_pairs = sorted(set(actual_pairs) - expected_pairs)
+    if duplicate_pairs:
+        failures.append(f"Duplicate matrix pairs: {duplicate_pairs}")
+    if missing_pairs:
+        failures.append(f"Missing matrix pairs: {missing_pairs}")
+    if unexpected_pairs:
+        failures.append(f"Unexpected matrix pairs: {unexpected_pairs}")
+
+    if scenarios == list(SCENARIOS):
+        for framework in frameworks:
+            target = FRAMEWORK_MANIFEST.targets[framework]
+            framework_records = [record for record in records if record.framework == framework]
+            required_count = sum(record.required for record in framework_records)
+            unsupported_count = sum(
+                record.status is ValidationStatus.UNSUPPORTED for record in framework_records
+            )
+            if required_count != target.required_scenarios:
+                failures.append(
+                    f"{framework} required count differs: "
+                    f"{required_count} != {target.required_scenarios}"
+                )
+            if unsupported_count != target.unsupported_scenarios:
+                failures.append(
+                    f"{framework} unsupported count differs: "
+                    f"{unsupported_count} != {target.unsupported_scenarios}"
+                )
+    return failures
+
+
 def write_report(path: Path, records: list[ValidationRecord]) -> None:
     """Retain the complete machine-readable release-gate result."""
-    payload = {
-        "schema_version": 1,
-        "generated_at": datetime.now(UTC).isoformat(),
-        "frameworks": FRAMEWORK_PINS,
-        "release_gate_passed": release_gate_passed(records),
-        "summary": summarize(records),
-        "records": [record.to_dict() for record in records],
-    }
+    payload = build_report(records, manifest=FRAMEWORK_MANIFEST)
     path.parent.mkdir(parents=True, exist_ok=True)
     path.write_text(json.dumps(payload, indent=2, sort_keys=True) + "\n", encoding="utf-8")
 
@@ -283,8 +304,14 @@ def main() -> int:
     parser.add_argument(
         "--output",
         type=Path,
+        default=VALIDATION_DIR / "candidates" / "CORRECTNESS_RESULTS.candidate.json",
+        help="Diagnostic candidate path",
+    )
+    parser.add_argument(
+        "--accepted-output",
+        type=Path,
         default=VALIDATION_DIR / "CORRECTNESS_RESULTS.json",
-        help="Machine-readable result path",
+        help="Accepted evidence path, replaced only by a complete passing matrix",
     )
     parser.add_argument("--timeout", type=int, default=180, help="Per-scenario timeout in seconds")
     args = parser.parse_args()
@@ -292,11 +319,32 @@ def main() -> int:
     frameworks = [args.framework] if args.framework else None
     scenarios = args.scenarios.split(",") if args.scenarios else None
     records = run_all_validations(frameworks, scenarios, timeout=args.timeout)
-    write_report(args.output, records)
+    write_candidate(args.output, records)
 
     nonzero = [f"{status}={count}" for status, count in summarize(records).items() if count]
     print(f"Results: {', '.join(nonzero)}")
-    print(f"Report: {args.output}")
+    print(f"Candidate: {args.output}")
+    selected_frameworks = frameworks or list(FRAMEWORK_MANIFEST.scenario_framework_ids)
+    selected_scenarios = scenarios or list(SCENARIOS)
+    coverage_failures = matrix_coverage_failures(
+        records,
+        selected_frameworks,
+        selected_scenarios,
+    )
+    if coverage_failures:
+        print("Matrix coverage failed:")
+        for failure in coverage_failures:
+            print(f"- {failure}")
+        return 1
+    full_matrix = frameworks is None and scenarios is None
+    if full_matrix:
+        promotion_failures = promote_candidate(args.output, args.accepted_output)
+        if promotion_failures:
+            print("Accepted evidence unchanged:")
+            for failure in promotion_failures:
+                print(f"- {failure}")
+            return 1
+        print(f"Accepted evidence: {args.accepted_output}")
     return 0 if release_gate_passed(records) else 1
 
 
diff --git a/validation/run_lean_case_studies.py b/validation/run_lean_case_studies.py
new file mode 100644
index 00000000..3c307b26
--- /dev/null
+++ b/validation/run_lean_case_studies.py
@@ -0,0 +1,316 @@
+#!/usr/bin/env python3
+"""Run and retain fresh LEAN case-study parity evidence."""
+
+from __future__ import annotations
+
+import argparse
+import gzip
+import hashlib
+import json
+import lzma
+import math
+import os
+import shutil
+import sys
+import tempfile
+import zipfile
+from pathlib import Path
+from typing import Any
+
+PROJECT_ROOT = Path(__file__).parent.parent
+VALIDATION_ROOT = PROJECT_ROOT / "validation"
+sys.path.insert(0, str(PROJECT_ROOT / "src"))
+sys.path.insert(0, str(VALIDATION_ROOT))
+
+from common.framework_registry import load_framework_manifest  # noqa: E402
+
+from ml4t.backtest._validation.case_study_lean import (  # noqa: E402
+    RETAINED_ORDER_EVENT_ARTIFACTS,
+    compare,
+    lean_side,
+    run_ml4t_lean,
+)
+from ml4t.backtest._validation.lean_runner import (  # noqa: E402
+    check_lean_cli,
+    make_lean_env,
+    run_lean_backtest,
+)
+
+WORKSPACE = VALIDATION_ROOT / "lean" / "workspace"
+DATA_DAILY = WORKSPACE / "data" / "equity" / "usa" / "daily"
+SUPPORT = VALIDATION_ROOT / "lean" / "support"
+CASE_STUDIES = (
+    "chapter16_etfs",
+    "chapter16_sp500_equity_option_analytics",
+    "chapter16_us_equities_panel",
+)
+PROJECT_INPUTS = {
+    "asset_symbols.csv",
+    "config.json",
+    "main.py",
+    "ml4t_symbol_map.json",
+    "rebalance_dates.csv",
+    "weights.csv",
+    "weights.csv.xz",
+    "weights.csv.gz",
+}
+
+
+def _digest_bytes(payload: bytes) -> str:
+    return hashlib.sha256(payload).hexdigest()
+
+
+def _digest(path: Path) -> str:
+    return _digest_bytes(path.read_bytes())
+
+
+def _atomic_write(path: Path, payload: bytes) -> None:
+    path.parent.mkdir(parents=True, exist_ok=True)
+    handle, temporary_name = tempfile.mkstemp(prefix=f".{path.name}.", dir=path.parent)
+    temporary = Path(temporary_name)
+    try:
+        with os.fdopen(handle, "wb") as file:
+            file.write(payload)
+            file.flush()
+            os.fsync(file.fileno())
+        temporary.replace(path)
+    except BaseException:
+        temporary.unlink(missing_ok=True)
+        raise
+
+
+def _copy_project(source: Path, destination: Path) -> None:
+    destination.mkdir(parents=True, exist_ok=True)
+    for name in sorted(PROJECT_INPUTS):
+        path = source / name
+        if path.is_file():
+            shutil.copy2(path, destination / name)
+
+
+def _prepare_lean_root(root: Path, project: Path) -> Path:
+    lean_config = root / "lean.json"
+    shutil.copy2(SUPPORT / "lean.json", lean_config)
+    data_root = root / "data"
+    shutil.copytree(SUPPORT / "data", data_root)
+    daily = data_root / "equity/usa/daily"
+    maps = data_root / "equity/usa/map_files"
+    factors = data_root / "equity/usa/factor_files"
+    for directory in (daily, maps, factors):
+        directory.mkdir(parents=True, exist_ok=True)
+
+    symbol_map = json.loads((project / "ml4t_symbol_map.json").read_text(encoding="utf-8"))
+    for ticker in sorted(symbol_map):
+        ticker_lower = ticker.lower()
+        source = DATA_DAILY / f"{ticker_lower}.zip"
+        destination = daily / source.name
+        os.link(source, destination)
+        with zipfile.ZipFile(source) as archive:
+            first_line = archive.read(archive.namelist()[0]).decode().splitlines()[0]
+        first_date = first_line.split(",", maxsplit=1)[0].split()[0]
+        (maps / f"{ticker_lower}.csv").write_text(
+            f"{first_date},{ticker_lower}\n20501231,{ticker_lower}\n",
+            encoding="utf-8",
+        )
+        (factors / f"{ticker_lower}.csv").write_text(
+            f"{first_date},1,1,1\n20501231,1,1,0\n",
+            encoding="utf-8",
+        )
+    return lean_config
+
+
+def _surface_checksum(surface: Any) -> str:
+    rows = surface.to_dict(orient="records")
+    payload = json.dumps(rows, sort_keys=True, separators=(",", ":"), default=str).encode()
+    return _digest_bytes(payload)
+
+
+def _input_manifest(project: Path) -> dict[str, str]:
+    inputs = {
+        path.name: _digest(path)
+        for path in sorted(project.iterdir())
+        if path.is_file() and path.name in PROJECT_INPUTS
+    }
+    symbol_map = json.loads((project / "ml4t_symbol_map.json").read_text(encoding="utf-8"))
+    for ticker in sorted(symbol_map):
+        data_path = DATA_DAILY / f"{ticker.lower()}.zip"
+        if not data_path.is_file():
+            raise FileNotFoundError(data_path)
+        inputs[f"data/{data_path.name}"] = _digest(data_path)
+    return inputs
+
+
+def _retained_order_paths(project: Path) -> list[Path]:
+    names = RETAINED_ORDER_EVENT_ARTIFACTS.get(project.name)
+    if names is None:
+        raise ValueError(f"No retained order-event layout for {project.name}")
+    paths = [project / name for name in names]
+    if not all(path.is_file() for path in paths):
+        raise FileNotFoundError(f"Retained order-event artifact missing for {project.name}")
+    return paths
+
+
+def _encode_order_parts(raw: bytes, targets: list[Path]) -> list[bytes]:
+    if len(targets) == 1:
+        suffix = targets[0].suffix
+        if suffix == ".xz":
+            return [lzma.compress(raw)]
+        if suffix == ".gz":
+            return [gzip.compress(raw, mtime=0)]
+        return [raw]
+
+    lines = raw.splitlines(keepends=True)
+    header, rows = lines[0], lines[1:]
+    chunk_size = math.ceil(len(rows) / len(targets))
+    chunks = [rows[index : index + chunk_size] for index in range(0, len(rows), chunk_size)]
+    if len(chunks) != len(targets):
+        raise RuntimeError(f"Could not split order events into {len(targets)} retained parts")
+    return [lzma.compress(header + b"".join(chunk)) for chunk in chunks]
+
+
+def _promote_case(project: Path, order_events: bytes, daily_equity: bytes) -> dict[str, str]:
+    order_paths = _retained_order_paths(project)
+    encoded = _encode_order_parts(order_events, order_paths)
+    for path, payload in zip(order_paths, encoded, strict=True):
+        _atomic_write(path, payload)
+    equity_path = project / "ml4t_daily_equity.csv"
+    _atomic_write(equity_path, daily_equity)
+    return {
+        path.relative_to(PROJECT_ROOT).as_posix(): _digest(path)
+        for path in [*order_paths, equity_path]
+    }
+
+
+def run(lean_command: Path, *, promote: bool) -> dict[str, Any]:
+    manifest = load_framework_manifest()
+    target = manifest.targets["lean"]
+    if target.artifact is None:
+        raise RuntimeError("Frozen LEAN target does not define an engine image")
+
+    lean_command = lean_command.resolve()
+    env = make_lean_env()
+    cli_version = check_lean_cli([str(lean_command)], PROJECT_ROOT, env)
+    expected_cli = f"lean {target.cli_version}"
+    if cli_version != expected_cli:
+        raise RuntimeError(f"LEAN CLI differs: {cli_version} != {expected_cli}")
+
+    results: list[dict[str, Any]] = []
+    raw_artifacts: dict[str, tuple[bytes, bytes]] = {}
+    for case in CASE_STUDIES:
+        source = WORKSPACE / case
+        with tempfile.TemporaryDirectory(
+            prefix=f".ml4t-{case}-", dir=VALIDATION_ROOT / "lean"
+        ) as temporary:
+            temporary_root = Path(temporary)
+            project = temporary_root / case
+            _copy_project(source, project)
+            lean_config = _prepare_lean_root(temporary_root, project)
+            output = project / "backtests" / "fresh"
+            runtime = run_lean_backtest(
+                lean_cmd=[str(lean_command)],
+                cwd=PROJECT_ROOT,
+                project_dir=project,
+                lean_config=lean_config,
+                output_dir=output,
+                image=target.artifact,
+                env=env,
+            )
+            lean = lean_side(project)
+            ml4t = run_ml4t_lean(project, DATA_DAILY)
+            comparison = compare(lean, ml4t)
+            order_events = (project / "ml4t_order_events.csv").read_bytes().replace(b"\r\n", b"\n")
+            daily_equity = (project / "ml4t_daily_equity.csv").read_bytes()
+            summaries = sorted(output.glob("*-summary.json"))
+            if not summaries:
+                raise FileNotFoundError(f"LEAN summary missing for {case}")
+            passed = (
+                comparison["sorted_fill_multiset_match"]
+                and comparison["fill_gap"] == 0
+                and comparison["canonical_final_value_match"]
+            )
+            results.append(
+                {
+                    "case": case,
+                    "comparison": comparison,
+                    "inputs": _input_manifest(source),
+                    "lean_fill_surface_sha256": _surface_checksum(lean["fills"]),
+                    "ml4t_fill_surface_sha256": _surface_checksum(ml4t["fills"]),
+                    "raw_daily_equity_sha256": _digest_bytes(daily_equity),
+                    "raw_order_events_sha256": _digest_bytes(order_events),
+                    "runtime_seconds": runtime,
+                    "summary_sha256": _digest(summaries[-1]),
+                    "passed": passed,
+                }
+            )
+            raw_artifacts[case] = (order_events, daily_equity)
+
+    passed = all(result["passed"] for result in results)
+    if promote and passed:
+        for result in results:
+            case = result["case"]
+            result["retained_artifacts"] = _promote_case(
+                WORKSPACE / case,
+                *raw_artifacts[case],
+            )
+
+    producer_files = [
+        Path(__file__),
+        PROJECT_ROOT / "src/ml4t/backtest/_validation/case_study_lean.py",
+        PROJECT_ROOT / "src/ml4t/backtest/_validation/lean_runner.py",
+        PROJECT_ROOT / "src/ml4t/backtest/profiles.py",
+    ]
+    return {
+        "schema_version": 1,
+        "framework": target.evidence_metadata(),
+        "cli_observed": cli_version,
+        "comparison_protocol": {
+            "account": "DefaultBrokerageModel Margin; per-project leverage 2",
+            "costs": "Ml4tPercentFeeModel at project rate; ConstantSlippageModel(0)",
+            "fills": "timestamp, asset, side, quantity, price rounded to 4 decimals",
+            "terminal_value_quantum": "0.0001 USD",
+        },
+        "producer_files": {
+            path.relative_to(PROJECT_ROOT).as_posix(): _digest(path) for path in producer_files
+        },
+        "support_files": {
+            path.relative_to(SUPPORT).as_posix(): _digest(path)
+            for path in sorted(SUPPORT.rglob("*"))
+            if path.is_file()
+        },
+        "promoted": bool(promote and passed),
+        "cases": results,
+        "passed": passed,
+    }
+
+
+def _write_evidence(path: Path, evidence: dict[str, Any]) -> None:
+    _atomic_write(path, (json.dumps(evidence, indent=2, sort_keys=True) + "\n").encode())
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument("--lean-command", type=Path, default=PROJECT_ROOT / ".venv-lean/bin/lean")
+    parser.add_argument(
+        "--output",
+        type=Path,
+        default=VALIDATION_ROOT / "lean/case_study_evidence.json",
+    )
+    parser.add_argument("--promote", action="store_true")
+    args = parser.parse_args()
+    try:
+        evidence = run(args.lean_command, promote=args.promote)
+    except (FileNotFoundError, json.JSONDecodeError, OSError, RuntimeError, ValueError) as error:
+        print(f"LEAN case-study run failed: {error}", file=sys.stderr)
+        return 2
+    if not evidence["passed"]:
+        candidate = args.output.with_suffix(".candidate.json")
+        _write_evidence(candidate, evidence)
+        failed = [case["case"] for case in evidence["cases"] if not case["passed"]]
+        print(f"LEAN case-study parity differs: {failed}; candidate: {candidate}", file=sys.stderr)
+        return 1
+    _write_evidence(args.output, evidence)
+    print(f"LEAN case-study parity passed: {len(evidence['cases'])} cases")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())
diff --git a/validation/run_scenario.py b/validation/run_scenario.py
index 93294529..4f25b560 100644
--- a/validation/run_scenario.py
+++ b/validation/run_scenario.py
@@ -23,9 +23,10 @@
 import argparse
 import importlib
 import json
-import math
 import sys
+import time
 from pathlib import Path
+from typing import Any
 
 # Ensure project root is on path
 PROJECT_ROOT = Path(__file__).parent.parent
@@ -33,10 +34,12 @@
 sys.path.insert(0, str(PROJECT_ROOT / "src"))
 sys.path.insert(0, str(VALIDATION_DIR))
 
-from common import data_generators  # noqa: E402
 from common.comparator import compare_results, print_comparison  # noqa: E402
+from common.framework_registry import load_framework_manifest  # noqa: E402
 from common.ml4t_runner import run_ml4t  # noqa: E402
+from common.provenance import build_record_provenance, generate_inputs  # noqa: E402
 from common.types import (  # noqa: E402
+    ComparisonResult,
     FrameworkResult,
     ValidationRecord,
     ValidationSkipped,
@@ -51,6 +54,7 @@
     "backtrader": "frameworks.backtrader",
     "zipline": "frameworks.zipline",
 }
+FRAMEWORK_MANIFEST = load_framework_manifest()
 
 
 def _record(
@@ -60,6 +64,11 @@ def _record(
     *,
     required: bool = True,
     detail: str | None = None,
+    started_at: float | None = None,
+    provenance: dict[str, Any] | None = None,
+    framework_result: FrameworkResult | None = None,
+    ml4t_result: FrameworkResult | None = None,
+    comparison: ComparisonResult | None = None,
 ) -> ValidationRecord:
     scenario = SCENARIOS.get(scenario_id)
     return ValidationRecord(
@@ -69,25 +78,26 @@ def _record(
         status=status,
         required=required,
         detail=detail,
+        duration_seconds=time.perf_counter() - started_at if started_at is not None else None,
+        provenance=provenance,
+        framework_result=framework_result,
+        ml4t_result=ml4t_result,
+        comparison=comparison,
     )
 
 
 def _malformed_result_detail(result: object) -> str | None:
     if not isinstance(result, FrameworkResult):
         return f"Adapter returned {type(result).__name__}, expected FrameworkResult"
-    if not isinstance(result.framework, str) or not result.framework:
-        return "FrameworkResult.framework must be a nonempty string"
-    if not isinstance(result.num_trades, int) or isinstance(result.num_trades, bool):
-        return "FrameworkResult.num_trades must be an integer"
-    if result.num_trades < 0:
-        return "FrameworkResult.num_trades cannot be negative"
-    for name, value in (("final_value", result.final_value), ("total_pnl", result.total_pnl)):
-        if not isinstance(value, (int, float)) or isinstance(value, bool):
-            return f"FrameworkResult.{name} must be numeric"
-        if not math.isfinite(float(value)):
-            return f"FrameworkResult.{name} must be finite"
-    if not isinstance(result.trades, list):
-        return "FrameworkResult.trades must be a list"
+    try:
+        FrameworkResult.from_dict(result.to_dict())
+    except (TypeError, ValueError) as error:
+        return str(error)
+    if result.num_trades != len(result.trades):
+        return (
+            "FrameworkResult.num_trades must equal the retained closed-trade count: "
+            f"{result.num_trades} != {len(result.trades)}"
+        )
     return None
 
 
@@ -101,6 +111,7 @@ def run_single(
     Returns:
         A terminal, machine-readable validation record.
     """
+    started_at = time.perf_counter()
     scenario = SCENARIOS.get(scenario_id)
     if not scenario:
         print(f"Unknown scenario: {scenario_id}")
@@ -109,6 +120,7 @@ def run_single(
             framework,
             ValidationStatus.MISSING_SCENARIO,
             detail=f"Scenario {scenario_id} is not defined",
+            started_at=started_at,
         )
 
     if framework not in scenario.supported_frameworks:
@@ -119,6 +131,7 @@ def run_single(
             ValidationStatus.UNSUPPORTED,
             required=False,
             detail="Scenario explicitly excludes this framework",
+            started_at=started_at,
         )
 
     print(f"\n{'=' * 70}")
@@ -128,8 +141,7 @@ def run_single(
     # Generate data
     print("\nGenerating test data...")
     try:
-        gen_func = getattr(data_generators, scenario.data_generator)
-        data_result = gen_func(**scenario.data_kwargs)
+        prices_df, entries, exits = generate_inputs(scenario, framework)
     except Exception as error:
         print(f"   ERROR: data generation failed: {error}")
         return _record(
@@ -137,32 +149,9 @@ def run_single(
             framework,
             ValidationStatus.ADAPTER_FAILURE,
             detail=f"Data generation failed: {error}",
+            started_at=started_at,
         )
 
-    if len(data_result) == 3:
-        prices_df, entries, exits = data_result
-    else:
-        prices_df, entries = data_result
-        exits = None
-
-    # Align to NYSE calendar for Zipline (which only operates on NYSE sessions)
-    if framework == "zipline":
-        import exchange_calendars as xcals
-
-        nyse = xcals.get_calendar("XNYS")
-        start_ts = prices_df.index[0]
-        end_ts = prices_df.index[-1]
-        if start_ts.tz is not None:
-            start_ts = start_ts.tz_convert(None)
-            end_ts = end_ts.tz_convert(None)
-        sessions = nyse.sessions_in_range(start_ts, end_ts)
-        naive_idx = prices_df.index.tz_localize(None) if prices_df.index.tz else prices_df.index
-        valid_mask = naive_idx.isin(sessions)
-        prices_df = prices_df[valid_mask].copy()
-        entries = entries[valid_mask]
-        if exits is not None:
-            exits = exits[valid_mask]
-
     print(f"   Bars: {len(prices_df)}")
     print(f"   Entry signals: {entries.sum()}")
     if exits is not None:
@@ -179,6 +168,7 @@ def run_single(
             framework,
             ValidationStatus.ADAPTER_IMPORT_FAILURE,
             detail=str(error),
+            started_at=started_at,
         )
 
     try:
@@ -190,6 +180,7 @@ def run_single(
             framework,
             ValidationStatus.SKIPPED,
             detail=str(error),
+            started_at=started_at,
         )
     except ImportError as error:
         print(f"   UNAVAILABLE: {error}")
@@ -198,6 +189,7 @@ def run_single(
             framework,
             ValidationStatus.UNAVAILABLE,
             detail=str(error),
+            started_at=started_at,
         )
     except Exception as error:
         print(f"   ERROR: {error}")
@@ -206,6 +198,7 @@ def run_single(
             framework,
             ValidationStatus.ADAPTER_FAILURE,
             detail=str(error),
+            started_at=started_at,
         )
 
     malformed_detail = _malformed_result_detail(fw_result)
@@ -216,6 +209,7 @@ def run_single(
             framework,
             ValidationStatus.MALFORMED_OUTPUT,
             detail=malformed_detail,
+            started_at=started_at,
         )
 
     try:
@@ -227,6 +221,7 @@ def run_single(
             framework,
             ValidationStatus.MALFORMED_OUTPUT,
             detail=f"Could not render adapter result: {error}",
+            started_at=started_at,
         )
 
     # Run ml4t
@@ -242,6 +237,7 @@ def run_single(
             framework,
             ValidationStatus.ML4T_FAILURE,
             detail=str(error),
+            started_at=started_at,
         )
 
     # Compare
@@ -255,6 +251,27 @@ def run_single(
             framework,
             ValidationStatus.MALFORMED_OUTPUT,
             detail=f"Could not compare validation results: {error}",
+            started_at=started_at,
+        )
+
+    try:
+        provenance = build_record_provenance(
+            scenario=scenario,
+            framework=framework,
+            target=FRAMEWORK_MANIFEST.targets[framework],
+            prices=prices_df,
+            entries=entries,
+            exits=exits,
+            framework_result=fw_result,
+            ml4t_result=ml4t_result,
+        )
+    except Exception as error:
+        return _record(
+            scenario_id,
+            framework,
+            ValidationStatus.MALFORMED_OUTPUT,
+            detail=f"Could not retain validation provenance: {error}",
+            started_at=started_at,
         )
 
     status = ValidationStatus.PASS if result.passed else ValidationStatus.COMPARISON_FAILURE
@@ -263,6 +280,11 @@ def run_single(
         framework,
         status,
         detail=None if result.passed else result.summary,
+        started_at=started_at,
+        provenance=provenance,
+        framework_result=fw_result,
+        ml4t_result=ml4t_result,
+        comparison=result,
     )
 
 
diff --git a/validation/scenarios/definitions.py b/validation/scenarios/definitions.py
index 73a36a4e..0706a222 100644
--- a/validation/scenarios/definitions.py
+++ b/validation/scenarios/definitions.py
@@ -1,4 +1,4 @@
-"""All 16 validation scenarios as declarative configs.
+"""All cross-framework validation scenarios as declarative configs.
 
 Each scenario is a ScenarioConfig that fully describes:
 - What data to generate
@@ -15,6 +15,7 @@
 
 sys.path.insert(0, str(Path(__file__).parent.parent))
 
+from common.framework_registry import load_framework_manifest
 from common.types import ScenarioConfig, Tolerance
 
 # ============================================================================
@@ -25,8 +26,8 @@
 BT_TOLERANCE = Tolerance(trade_count=0, value_pct=0.1, pnl_abs=10.0)
 ZIPLINE_TOLERANCE = Tolerance(trade_count=0, value_pct=0.01, pnl_abs=5.0)
 
-ALL_FRAMEWORKS = ["vectorbt_pro", "vectorbt_oss", "backtrader", "zipline"]
-NO_ZIPLINE = ["vectorbt_pro", "vectorbt_oss", "backtrader"]
+ALL_FRAMEWORKS = list(load_framework_manifest().scenario_framework_ids)
+NO_ZIPLINE = [framework for framework in ALL_FRAMEWORKS if framework != "zipline"]
 
 
 def _fw_tolerances() -> dict[str, Tolerance]:
@@ -487,13 +488,13 @@ def _fw_tolerances() -> dict[str, Tolerance]:
 )
 
 # ============================================================================
-# Scenario 16: Stress Test (1500 bars)
+# Scenario 16: Regime Path Coverage (1500 bars)
 # ============================================================================
 
 SCENARIO_16 = ScenarioConfig(
     id="16",
-    name="Stress Test",
-    description="1500-bar stress test with 9 market regimes.",
+    name="Regime Path Coverage",
+    description="1500-bar path with 9 market regimes and sparse re-entry signals.",
     data_generator="generate_stress_data",
     data_kwargs={"n_bars": 1500, "seed": 42},
     signal_columns=["entry"],
@@ -522,6 +523,21 @@ def _fw_tolerances() -> dict[str, Tolerance]:
     },
 )
 
+# ============================================================================
+# Scenario 17: High Event Count
+# ============================================================================
+
+SCENARIO_17 = ScenarioConfig(
+    id="17",
+    name="High Event Count",
+    description="1800-bar lifecycle workload with up to 600 completed round trips.",
+    data_generator="generate_high_event_data",
+    data_kwargs={"n_bars": 1800, "seed": 7},
+    signal_columns=["entry", "exit"],
+    strategy_type="long_signal",
+    tolerances=_fw_tolerances(),
+)
+
 # ============================================================================
 # Registry
 # ============================================================================
@@ -543,6 +559,7 @@ def _fw_tolerances() -> dict[str, Tolerance]:
     "14": SCENARIO_14,
     "15": SCENARIO_15,
     "16": SCENARIO_16,
+    "17": SCENARIO_17,
 }
 
 SCENARIO_NAMES: dict[str, str] = {s.id: s.name for s in SCENARIOS.values()}
diff --git a/validation/vectorbt_pro/benchmark_performance.py b/validation/vectorbt_pro/benchmark_performance.py
index 4a5d1f49..a64e82c3 100644
--- a/validation/vectorbt_pro/benchmark_performance.py
+++ b/validation/vectorbt_pro/benchmark_performance.py
@@ -1,306 +1,15 @@
 #!/usr/bin/env python3
-"""Performance benchmark: ml4t.backtest vs VectorBT Pro.
+"""Route the former VectorBT Pro benchmark entry point to retained performance evidence."""
 
-This script benchmarks runtime performance across different data sizes
-and number of assets.
+from __future__ import annotations
 
-Run from .venv-vectorbt-pro environment:
-    source .venv-vectorbt-pro/bin/activate
-    python validation/vectorbt_pro/benchmark_performance.py
-
-Metrics:
-- Total runtime (seconds)
-- Trades per second
-- Memory usage (MB)
-"""
-
-import gc
 import sys
-import time
-import tracemalloc
 from pathlib import Path
 
-import numpy as np
-import pandas as pd
-
-# Add project root to path
-PROJECT_ROOT = Path(__file__).parent.parent.parent
-sys.path.insert(0, str(PROJECT_ROOT / "src"))
-
-
-def generate_benchmark_data(n_bars: int, n_assets: int, seed: int = 42) -> tuple:
-    """Generate benchmark data for both frameworks."""
-    np.random.seed(seed)
-
-    dates = pd.date_range(start="2020-01-01", periods=n_bars, freq="D")
-
-    # Generate price data for multiple assets
-    asset_data = {}
-    for i in range(n_assets):
-        base_price = 100.0 + i * 10
-        returns = np.random.randn(n_bars) * 0.02
-        prices = base_price * np.exp(np.cumsum(returns))
-
-        asset_data[f"ASSET_{i:03d}"] = pd.DataFrame(
-            {
-                "open": prices * (1 + np.random.randn(n_bars) * 0.005),
-                "high": prices * (1 + np.abs(np.random.randn(n_bars)) * 0.01),
-                "low": prices * (1 - np.abs(np.random.randn(n_bars)) * 0.01),
-                "close": prices,
-                "volume": np.random.randint(100000, 1000000, n_bars).astype(float),
-            },
-            index=dates,
-        )
-
-    # Generate signals - entry every 20 bars, exit 10 bars later
-    entries = np.zeros(n_bars, dtype=bool)
-    exits = np.zeros(n_bars, dtype=bool)
-
-    i = 0
-    while i < n_bars - 11:
-        entries[i] = True
-        exits[i + 10] = True
-        i += 20
-
-    return asset_data, entries, exits, dates
-
-
-def benchmark_vectorbt_pro(asset_data: dict, entries: np.ndarray, exits: np.ndarray) -> dict:
-    """Benchmark VectorBT Pro."""
-    import vectorbtpro as vbt
-
-    # Prepare close prices DataFrame
-    close_df = pd.DataFrame({name: df["close"] for name, df in asset_data.items()})
-
-    # Warm-up run
-    _ = vbt.Portfolio.from_signals(
-        close=close_df.iloc[:100],
-        entries=entries[:100],
-        exits=exits[:100],
-        init_cash=100_000.0,
-        size=100,
-        size_type="amount",
-        fees=0.0,
-        slippage=0.0,
-    )
-
-    gc.collect()
-    tracemalloc.start()
-    start_time = time.perf_counter()
-
-    pf = vbt.Portfolio.from_signals(
-        close=close_df,
-        entries=entries,
-        exits=exits,
-        init_cash=100_000.0,
-        size=100,
-        size_type="amount",
-        fees=0.0,
-        slippage=0.0,
-    )
-
-    # Force computation
-    _ = pf.total_return
-    num_trades = len(pf.trades.records_readable)
-
-    end_time = time.perf_counter()
-    current, peak = tracemalloc.get_traced_memory()
-    tracemalloc.stop()
-
-    return {
-        "framework": "VectorBT Pro",
-        "runtime_sec": end_time - start_time,
-        "num_trades": num_trades,
-        "memory_mb": peak / 1024 / 1024,
-    }
-
-
-def benchmark_ml4t_backtest(
-    asset_data: dict, entries: np.ndarray, exits: np.ndarray, dates
-) -> dict:
-    """Benchmark ml4t.backtest."""
-    import polars as pl
-
-    from ml4t.backtest._validation_imports import DataFeed, Engine, ExecutionMode, NoCommission, NoSlippage, Strategy
-
-    # Prepare data in polars format
-    rows = []
-    for asset_name, df in asset_data.items():
-        for i, (ts, row) in enumerate(df.iterrows()):
-            rows.append(
-                {
-                    "timestamp": ts.to_pydatetime(),
-                    "asset": asset_name,
-                    "open": row["open"],
-                    "high": row["high"],
-                    "low": row["low"],
-                    "close": row["close"],
-                    "volume": row["volume"],
-                }
-            )
-
-    prices_pl = pl.DataFrame(rows)
-
-    # Prepare signals
-    signal_rows = []
-    for asset_name in asset_data:
-        for i, ts in enumerate(dates):
-            signal_rows.append(
-                {
-                    "timestamp": ts.to_pydatetime(),
-                    "asset": asset_name,
-                    "entry": bool(entries[i]),
-                    "exit": bool(exits[i]),
-                }
-            )
-
-    signals_pl = pl.DataFrame(signal_rows)
-
-    class BenchmarkStrategy(Strategy):
-        def on_data(self, timestamp, data, context, broker):
-            for asset_name, asset_data in data.items():
-                signals = asset_data.get("signals", {})
-                position = broker.get_position(asset_name)
-                current_qty = position.quantity if position else 0
-
-                if signals.get("exit") and current_qty > 0:
-                    broker.close_position(asset_name)
-                elif signals.get("entry") and current_qty == 0:
-                    broker.submit_order(asset_name, 100)
-
-    # Warm-up run with small data
-    small_prices = prices_pl.head(100 * len(asset_data))
-    small_signals = signals_pl.head(100 * len(asset_data))
-    small_feed = DataFeed(prices_df=small_prices, signals_df=small_signals)
-    small_engine = Engine(
-        small_feed,
-        BenchmarkStrategy(),
-        initial_cash=100_000.0,
-        allow_short_selling=False,
-        commission_model=NoCommission(),
-        slippage_model=NoSlippage(),
-        execution_mode=ExecutionMode.SAME_BAR,
-    )
-    _ = small_engine.run()
-
-    gc.collect()
-    tracemalloc.start()
-    start_time = time.perf_counter()
-
-    feed = DataFeed(prices_df=prices_pl, signals_df=signals_pl)
-    strategy = BenchmarkStrategy()
-
-    engine = Engine(
-        feed,
-        strategy,
-        initial_cash=100_000.0,
-        allow_short_selling=False,
-        commission_model=NoCommission(),
-        slippage_model=NoSlippage(),
-        execution_mode=ExecutionMode.SAME_BAR,
-    )
-
-    results = engine.run()
-    num_trades = results["num_trades"]
-
-    end_time = time.perf_counter()
-    current, peak = tracemalloc.get_traced_memory()
-    tracemalloc.stop()
-
-    return {
-        "framework": "ml4t.backtest",
-        "runtime_sec": end_time - start_time,
-        "num_trades": num_trades,
-        "memory_mb": peak / 1024 / 1024,
-    }
-
-
-def run_benchmark(n_bars: int, n_assets: int) -> dict:
-    """Run benchmark for specific configuration."""
-    print(f"\n  Generating data: {n_bars} bars x {n_assets} assets...")
-    asset_data, entries, exits, dates = generate_benchmark_data(n_bars, n_assets)
-
-    print("  Running VectorBT Pro...")
-    vbt_results = benchmark_vectorbt_pro(asset_data, entries, exits)
-
-    print("  Running ml4t.backtest...")
-    ml4t_results = benchmark_ml4t_backtest(asset_data, entries, exits, dates)
-
-    # Calculate speedup
-    speedup = (
-        vbt_results["runtime_sec"] / ml4t_results["runtime_sec"]
-        if ml4t_results["runtime_sec"] > 0
-        else 0
-    )
-
-    return {
-        "n_bars": n_bars,
-        "n_assets": n_assets,
-        "vbt_runtime": vbt_results["runtime_sec"],
-        "vbt_trades": vbt_results["num_trades"],
-        "vbt_memory": vbt_results["memory_mb"],
-        "ml4t_runtime": ml4t_results["runtime_sec"],
-        "ml4t_trades": ml4t_results["num_trades"],
-        "ml4t_memory": ml4t_results["memory_mb"],
-        "speedup": speedup,
-    }
-
-
-def main():
-    print("=" * 70)
-    print("Performance Benchmark: ml4t.backtest vs VectorBT Pro")
-    print("=" * 70)
-
-    # Test configurations
-    configs = [
-        (100, 1),
-        (1000, 1),
-        (10000, 1),
-        (1000, 10),
-        (10000, 10),
-        (1000, 100),
-    ]
-
-    results = []
-
-    for n_bars, n_assets in configs:
-        print(f"\nBenchmark: {n_bars} bars x {n_assets} assets")
-        try:
-            result = run_benchmark(n_bars, n_assets)
-            results.append(result)
-
-            print(
-                f"  VBT: {result['vbt_runtime']:.3f}s, {result['vbt_trades']} trades, {result['vbt_memory']:.1f} MB"
-            )
-            print(
-                f"  ML4T: {result['ml4t_runtime']:.3f}s, {result['ml4t_trades']} trades, {result['ml4t_memory']:.1f} MB"
-            )
-            print(
-                f"  Speedup: {result['speedup']:.2f}x {'(VBT faster)' if result['speedup'] > 1 else '(ML4T faster)'}"
-            )
-        except Exception as e:
-            print(f"  ERROR: {e}")
-            traceback.print_exc()
-
-    # Summary table
-    print("\n" + "=" * 70)
-    print("SUMMARY")
-    print("=" * 70)
-    print(f"{'Config':<20} {'VBT (s)':<12} {'ML4T (s)':<12} {'Speedup':<12} {'Winner'}")
-    print("-" * 70)
-
-    for r in results:
-        config = f"{r['n_bars']}x{r['n_assets']}"
-        winner = "VBT" if r["speedup"] > 1 else "ML4T"
-        speedup_str = f"{r['speedup']:.2f}x" if r["speedup"] > 1 else f"{1/r['speedup']:.2f}x"
-        print(
-            f"{config:<20} {r['vbt_runtime']:<12.3f} {r['ml4t_runtime']:<12.3f} {speedup_str:<12} {winner}"
-        )
-
-    print("=" * 70)
-
-    return 0
+VALIDATION_DIR = Path(__file__).parents[1]
+sys.path.insert(0, str(VALIDATION_DIR))
 
+from cross_framework_performance import main  # noqa: E402
 
 if __name__ == "__main__":
-    sys.exit(main())
+    raise SystemExit(main())
diff --git a/validation/vectorbt_pro/controlled_replay-2025.12.31.json b/validation/vectorbt_pro/controlled_replay-2025.12.31.json
new file mode 100644
index 00000000..7f3ef9ef
--- /dev/null
+++ b/validation/vectorbt_pro/controlled_replay-2025.12.31.json
@@ -0,0 +1,1209 @@
+{
+  "audit_trigger": {
+    "cause": "vectorbt collateral semantics missing from the ML4T comparison profile",
+    "external_fill_count": 390369,
+    "external_final_value": 716785.408089,
+    "ml4t_commit": "488c05d84e74156aba71c4f7ffac28df3881fea9",
+    "ml4t_fill_count": 418825,
+    "ml4t_final_value": 1162222.354417
+  },
+  "current": {
+    "capabilities": {
+      "closed_trades": "reconstructed from canonical native fills",
+      "fill_order": "session, asset, side, quantity, price",
+      "fills": "native",
+      "intents": "canonical strategy trace",
+      "terminal_state": "reconstructed from native fills and final marks"
+    },
+    "comparison": {
+      "actual_error": null,
+      "actual_framework": "ml4t.backtest[vectorbt_strict]",
+      "canonical_money_quantum": "0.000001",
+      "canonical_record_quantum": "1E-8",
+      "checks": [
+        {
+          "actual_count": 427790,
+          "actual_sha256": "b87edd7321d4be2307d8db968004ebd7e12edf47a3955003f42d0e974c8f369c",
+          "expected_count": 427790,
+          "expected_sha256": "b87edd7321d4be2307d8db968004ebd7e12edf47a3955003f42d0e974c8f369c",
+          "first_difference": null,
+          "name": "order_intents",
+          "passed": true
+        },
+        {
+          "actual_count": 390369,
+          "actual_sha256": "83af0bc6cb77d931349349093a611cb645e1503c2c33aef9e626c293630cf0c1",
+          "expected_count": 390369,
+          "expected_sha256": "83af0bc6cb77d931349349093a611cb645e1503c2c33aef9e626c293630cf0c1",
+          "first_difference": null,
+          "name": "fills",
+          "passed": true
+        },
+        {
+          "actual_count": 188549,
+          "actual_sha256": "7055c62444c54eb5f5191358b187641ad7de019c3c182ce7f088d460ec59a242",
+          "expected_count": 188549,
+          "expected_sha256": "7055c62444c54eb5f5191358b187641ad7de019c3c182ce7f088d460ec59a242",
+          "first_difference": null,
+          "name": "trades",
+          "passed": true
+        },
+        {
+          "actual": 188549,
+          "canonical_actual": 188549.0,
+          "canonical_difference": 0.0,
+          "canonical_expected": 188549.0,
+          "expected": 188549,
+          "name": "trade_count",
+          "passed": true,
+          "raw_difference": 0
+        },
+        {
+          "actual": -283214.59191072755,
+          "canonical_actual": -283214.591911,
+          "canonical_difference": 0.0,
+          "canonical_expected": -283214.591911,
+          "expected": -283214.59191072907,
+          "name": "total_pnl",
+          "passed": true,
+          "raw_difference": 1.5133991837501526e-09
+        },
+        {
+          "actual": 716785.4080892724,
+          "canonical_actual": 716785.408089,
+          "canonical_difference": 0.0,
+          "canonical_expected": 716785.408089,
+          "expected": 716785.4080892709,
+          "name": "final_value",
+          "passed": true,
+          "raw_difference": 1.5133991837501526e-09
+        },
+        {
+          "actual": {
+            "cash_from_fill_ledger": 786065.409828,
+            "holdings_from_fill_ledger": -69280.005398,
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+    },
+    "source_digests": {
+      "benchmark_suite": "dcafa42216566ff5e83ae0788d53d9789c2b7980956ea656c874684730b40523",
+      "framework_manifest": "38e64faa733ac8412b0a1cabec5357be229852f19b432f2f215a7bf20f3a2780",
+      "large_scale_runner": "31620bd2b07466f733a6060676707e664881e7b6d4c3ea3f09d8f47354e86706",
+      "profiles": "5a8cd8b2568e7e9f524e96fef6bb00ade3310a6f4a71c0c4f7de2f95bbfdb505"
+    },
+    "target": {
+      "access": "licensed",
+      "actual_commit": "1305a1e1974325db9382eaeacc6452e9b075ca71",
+      "actual_immutable_id": "git:1305a1e1974325db9382eaeacc6452e9b075ca71",
+      "actual_version": "2025.12.31",
+      "commit": "1305a1e1974325db9382eaeacc6452e9b075ca71",
+      "display_name": "VectorBT Pro",
+      "immutable_id": "git:1305a1e1974325db9382eaeacc6452e9b075ca71",
+      "license": "Proprietary",
+      "package": "vectorbtpro",
+      "profile": "vectorbt_strict",
+      "python": ">=3.11",
+      "source": "https://github.com/polakowo/vectorbt.pro",
+      "version": "2025.12.31"
+    }
+  },
+  "release_gate_passed": true,
+  "schema_version": 1,
+  "workload": {
+    "data_points": 1260000,
+    "generator": "validation.benchmark_suite.generate_benchmark_data",
+    "recipe": {
+      "assets": 250,
+      "bars": 5040,
+      "bottom_n": 25,
+      "end_session": "2025-12-31",
+      "initial_cash": 1000000.0,
+      "long_target_shares": 100.0,
+      "name": "controlled_250_assets_5040_sessions",
+      "rebalance_frequency": 1,
+      "seed": 42,
+      "short_target_shares": -100.0,
+      "top_n": 25
+    },
+    "recipe_sha256": "5de81aacdda2ee7f08b2cc1549e64a974b19693967ac2fe1fdb0f1a6370d0ba5",
+    "redistributable": true
+  }
+}
diff --git a/validation/zipline/benchmark_performance.py b/validation/zipline/benchmark_performance.py
index 067c3941..d435da31 100644
--- a/validation/zipline/benchmark_performance.py
+++ b/validation/zipline/benchmark_performance.py
@@ -1,426 +1,15 @@
 #!/usr/bin/env python3
-"""Performance benchmark: ml4t.backtest vs Zipline-Reloaded.
+"""Route the former Zipline benchmark entry point to retained performance evidence."""
 
-This script benchmarks runtime performance across different data sizes
-and number of assets.
+from __future__ import annotations
 
-Run from .venv-zipline or .venv-validation environment:
-    source .venv-zipline/bin/activate
-    python validation/zipline/benchmark_performance.py
-
-Metrics:
-- Total runtime (seconds)
-- Trades per second
-- Memory usage (MB)
-"""
-
-import gc
 import sys
-import time
-import traceback
-import tracemalloc
-from datetime import datetime
 from pathlib import Path
 
-import numpy as np
-import pandas as pd
-
-# Add project root to path
-PROJECT_ROOT = Path(__file__).parent.parent.parent
-sys.path.insert(0, str(PROJECT_ROOT / "src"))
-
-
-def generate_benchmark_data(n_bars: int, n_assets: int, seed: int = 42) -> tuple:
-    """Generate benchmark data for both frameworks."""
-    np.random.seed(seed)
-
-    # Use NYSE trading days
-    try:
-        import exchange_calendars as xcals
-        nyse = xcals.get_calendar("XNYS")
-        start = pd.Timestamp("2013-01-02")  # No timezone for exchange_calendars
-        sessions = nyse.sessions_in_range(start, start + pd.Timedelta(days=n_bars * 2))
-        dates = pd.DatetimeIndex(sessions[:n_bars]).tz_localize("UTC")
-    except ImportError:
-        # Fallback to business days
-        dates = pd.date_range(start="2013-01-02", periods=n_bars, freq="B", tz="UTC")
-
-    # Generate price data for multiple assets
-    asset_data = {}
-    for i in range(n_assets):
-        base_price = 100.0 + i * 10
-        returns = np.random.randn(n_bars) * 0.02
-        prices = base_price * np.exp(np.cumsum(returns))
-
-        asset_data[f"ASSET_{i:03d}"] = pd.DataFrame(
-            {
-                "open": prices * (1 + np.random.randn(n_bars) * 0.005),
-                "high": prices * (1 + np.abs(np.random.randn(n_bars)) * 0.01),
-                "low": prices * (1 - np.abs(np.random.randn(n_bars)) * 0.01),
-                "close": prices,
-                "volume": np.random.randint(100000, 1000000, n_bars).astype(float),
-            },
-            index=dates,
-        )
-
-    # Generate signals - entry every 20 bars, exit 10 bars later
-    entries = np.zeros(n_bars, dtype=bool)
-    exits = np.zeros(n_bars, dtype=bool)
-
-    i = 0
-    while i < n_bars - 11:
-        entries[i] = True
-        exits[i + 10] = True
-        i += 20
-
-    return asset_data, entries, exits, dates
-
-
-def setup_zipline_bundle(asset_data: dict, dates, bundle_name: str = "perf_benchmark"):
-    """Register and ingest a custom bundle with multi-asset test data."""
-    from zipline.data.bundles import ingest, register
-
-    def make_ingest_func(asset_data_dict, dates_idx):
-        def ingest_func(
-            environ,
-            asset_db_writer,
-            minute_bar_writer,
-            daily_bar_writer,
-            adjustment_writer,
-            calendar,
-            start_session,
-            end_session,
-            cache,
-            show_progress,
-            output_dir,
-        ):
-            sessions = calendar.sessions_in_range(start_session, end_session)
-            asset_names = list(asset_data_dict.keys())
-
-            # Write equity metadata
-            asset_db_writer.write(
-                equities=pd.DataFrame(
-                    {
-                        "symbol": asset_names,
-                        "asset_name": [f"Asset {i}" for i in range(len(asset_names))],
-                        "exchange": ["NYSE"] * len(asset_names),
-                    }
-                )
-            )
-
-            # Write daily bars for each asset
-            def gen_data():
-                for sid, (asset_name, df) in enumerate(asset_data_dict.items()):
-                    df_naive = df.copy()
-                    if df_naive.index.tz is not None:
-                        df_naive.index = df_naive.index.tz_convert(None)
-                    valid_mask = df_naive.index.isin(sessions)
-                    trading_df = df_naive[valid_mask].copy()
-                    if len(trading_df) > 0:
-                        yield sid, trading_df[["open", "high", "low", "close", "volume"]]
-
-            daily_bar_writer.write(gen_data(), show_progress=show_progress)
-            adjustment_writer.write()
-
-        return ingest_func
-
-    start_session = dates[0]
-    end_session = dates[-1]
-    if hasattr(start_session, 'tz') and start_session.tz is not None:
-        start_session = start_session.tz_convert(None)
-        end_session = end_session.tz_convert(None)
-
-    register(
-        bundle_name,
-        make_ingest_func(asset_data, dates),
-        calendar_name="XNYS",
-        start_session=start_session,
-        end_session=end_session,
-    )
-
-    ingest(bundle_name, show_progress=False)
-    return bundle_name
-
-
-def benchmark_zipline(asset_data: dict, entries: np.ndarray, exits: np.ndarray, dates) -> dict:
-    """Benchmark Zipline-Reloaded using bundle-based data."""
-    from zipline import run_algorithm
-    from zipline.api import order, set_commission, set_slippage, sid
-    from zipline.finance.commission import NoCommission
-    from zipline.finance.slippage import FixedSlippage
-
-    asset_names = list(asset_data.keys())
-    trade_count = [0]
-
-    # Set up bundle (not timed - this is data prep)
-    try:
-        bundle_name = setup_zipline_bundle(asset_data, dates)
-    except Exception as e:
-        print(f"    Zipline bundle error: {e}")
-        return {"framework": "Zipline", "success": False, "error": f"Bundle setup failed: {e}"}
-
-    def initialize(context):
-        context.entries = entries
-        context.exits = exits
-        context.bar_idx = 0
-        context.n_assets = len(asset_names)
-        set_commission(NoCommission())
-        set_slippage(FixedSlippage(spread=0.0))
-
-    def handle_data(context, data):
-        if context.bar_idx >= len(context.entries):
-            return
-
-        for asset_idx in range(context.n_assets):
-            try:
-                asset = sid(asset_idx)
-            except Exception:
-                continue
-
-            position = context.portfolio.positions.get(asset)
-            current_qty = position.amount if position else 0
-
-            if context.exits[context.bar_idx] and current_qty > 0:
-                order(asset, -current_qty)
-                trade_count[0] += 1
-            elif context.entries[context.bar_idx] and current_qty == 0:
-                order(asset, 100)
-                trade_count[0] += 1
-
-        context.bar_idx += 1
-
-    # Convert to tz-naive for Zipline (it adds tz internally)
-    start_date = dates[0]
-    end_date = dates[-1]
-    if hasattr(start_date, 'tz') and start_date.tz is not None:
-        start_date = start_date.tz_convert(None)
-        end_date = end_date.tz_convert(None)
-
-    gc.collect()
-    tracemalloc.start()
-    start_time = time.perf_counter()
-
-    try:
-        run_algorithm(
-            start=start_date,
-            end=end_date,
-            initialize=initialize,
-            handle_data=handle_data,
-            capital_base=100_000_000.0,  # $100M for large portfolios
-            bundle=bundle_name,
-        )
-        success = True
-    except Exception as e:
-        print(f"    Zipline error: {e}")
-        return {"framework": "Zipline", "success": False, "error": str(e)}
-
-    end_time = time.perf_counter()
-    current, peak = tracemalloc.get_traced_memory()
-    tracemalloc.stop()
-
-    return {
-        "framework": "Zipline",
-        "runtime_sec": end_time - start_time,
-        "num_trades": trade_count[0],
-        "memory_mb": peak / 1024 / 1024,
-        "success": success,
-    }
-
-
-def benchmark_ml4t_backtest(
-    asset_data: dict, entries: np.ndarray, exits: np.ndarray, dates
-) -> dict:
-    """Benchmark ml4t.backtest."""
-    import polars as pl
-
-    from ml4t.backtest._validation_imports import DataFeed, Engine, ExecutionMode, NoCommission, NoSlippage, Strategy
-
-    # Prepare data in polars format
-    rows = []
-    for asset_name, df in asset_data.items():
-        for i, (ts, row) in enumerate(df.iterrows()):
-            rows.append(
-                {
-                    "timestamp": ts.to_pydatetime().replace(tzinfo=None),
-                    "asset": asset_name,
-                    "open": row["open"],
-                    "high": row["high"],
-                    "low": row["low"],
-                    "close": row["close"],
-                    "volume": row["volume"],
-                }
-            )
-
-    prices_pl = pl.DataFrame(rows)
-
-    # Prepare signals
-    signal_rows = []
-    for asset_name in asset_data:
-        for i, ts in enumerate(dates):
-            signal_rows.append(
-                {
-                    "timestamp": ts.to_pydatetime().replace(tzinfo=None),
-                    "asset": asset_name,
-                    "entry": bool(entries[i]),
-                    "exit": bool(exits[i]),
-                }
-            )
-
-    signals_pl = pl.DataFrame(signal_rows)
-
-    class BenchmarkStrategy(Strategy):
-        def on_data(self, timestamp, data, context, broker):
-            for asset_name, asset_data in data.items():
-                signals = asset_data.get("signals", {})
-                position = broker.get_position(asset_name)
-                current_qty = position.quantity if position else 0
-
-                if signals.get("exit") and current_qty > 0:
-                    broker.close_position(asset_name)
-                elif signals.get("entry") and current_qty == 0:
-                    broker.submit_order(asset_name, 100)
-
-    # Warm-up run with small data
-    small_prices = prices_pl.head(100 * len(asset_data))
-    small_signals = signals_pl.head(100 * len(asset_data))
-    small_feed = DataFeed(prices_df=small_prices, signals_df=small_signals)
-    small_engine = Engine(
-        small_feed,
-        BenchmarkStrategy(),
-        initial_cash=100_000.0,
-        allow_short_selling=False,
-        commission_model=NoCommission(),
-        slippage_model=NoSlippage(),
-        execution_mode=ExecutionMode.SAME_BAR,
-    )
-    _ = small_engine.run()
-
-    gc.collect()
-    tracemalloc.start()
-    start_time = time.perf_counter()
-
-    feed = DataFeed(prices_df=prices_pl, signals_df=signals_pl)
-    strategy = BenchmarkStrategy()
-
-    engine = Engine(
-        feed,
-        strategy,
-        initial_cash=100_000.0,
-        allow_short_selling=False,
-        commission_model=NoCommission(),
-        slippage_model=NoSlippage(),
-        execution_mode=ExecutionMode.SAME_BAR,
-    )
-
-    results = engine.run()
-    num_trades = results["num_trades"]
-
-    end_time = time.perf_counter()
-    current, peak = tracemalloc.get_traced_memory()
-    tracemalloc.stop()
-
-    return {
-        "framework": "ml4t.backtest",
-        "runtime_sec": end_time - start_time,
-        "num_trades": num_trades,
-        "memory_mb": peak / 1024 / 1024,
-    }
-
-
-def run_benchmark(n_bars: int, n_assets: int) -> dict:
-    """Run benchmark for specific configuration."""
-    print(f"\n  Generating data: {n_bars} bars x {n_assets} assets...")
-    asset_data, entries, exits, dates = generate_benchmark_data(n_bars, n_assets)
-
-    print("  Running Zipline...")
-    zipline_results = benchmark_zipline(asset_data, entries, exits, dates)
-
-    print("  Running ml4t.backtest...")
-    ml4t_results = benchmark_ml4t_backtest(asset_data, entries, exits, dates)
-
-    # Calculate speedup
-    if ml4t_results["runtime_sec"] > 0 and zipline_results.get("success", False):
-        speedup = zipline_results["runtime_sec"] / ml4t_results["runtime_sec"]
-    else:
-        speedup = 0
-
-    return {
-        "n_bars": n_bars,
-        "n_assets": n_assets,
-        "zipline_runtime": zipline_results.get("runtime_sec", 0),
-        "zipline_trades": zipline_results.get("num_trades", 0),
-        "zipline_memory": zipline_results.get("memory_mb", 0),
-        "zipline_success": zipline_results.get("success", False),
-        "zipline_error": zipline_results.get("error", None),
-        "ml4t_runtime": ml4t_results["runtime_sec"],
-        "ml4t_trades": ml4t_results["num_trades"],
-        "ml4t_memory": ml4t_results["memory_mb"],
-        "speedup": speedup,
-    }
-
-
-def main():
-    print("=" * 70)
-    print("Performance Benchmark: ml4t.backtest vs Zipline-Reloaded")
-    print("=" * 70)
-
-    # Test configurations (reduced from VBT benchmark due to Zipline overhead)
-    configs = [
-        (100, 1),
-        (500, 1),
-        (1000, 1),
-        (500, 5),
-        (1000, 10),
-    ]
-
-    results = []
-
-    for n_bars, n_assets in configs:
-        print(f"\nBenchmark: {n_bars} bars x {n_assets} assets")
-        try:
-            result = run_benchmark(n_bars, n_assets)
-            results.append(result)
-
-            if result["zipline_success"]:
-                print(
-                    f"  Zipline: {result['zipline_runtime']:.3f}s, {result['zipline_trades']} trades, {result['zipline_memory']:.1f} MB"
-                )
-            else:
-                err = result.get("zipline_error", "Unknown error")
-                print(f"  Zipline: FAILED - {err}")
-            print(
-                f"  ML4T: {result['ml4t_runtime']:.3f}s, {result['ml4t_trades']} trades, {result['ml4t_memory']:.1f} MB"
-            )
-            if result["speedup"] > 0:
-                print(
-                    f"  Speedup: {result['speedup']:.2f}x {'(Zipline faster)' if result['speedup'] > 1 else '(ML4T faster)'}"
-                )
-        except Exception as e:
-            print(f"  ERROR: {e}")
-            traceback.print_exc()
-
-    # Summary table
-    print("\n" + "=" * 70)
-    print("SUMMARY")
-    print("=" * 70)
-    print(f"{'Config':<20} {'Zipline (s)':<12} {'ML4T (s)':<12} {'Speedup':<12} {'Winner'}")
-    print("-" * 70)
-
-    for r in results:
-        config = f"{r['n_bars']}x{r['n_assets']}"
-        if r["zipline_success"] and r["speedup"] > 0:
-            winner = "Zipline" if r["speedup"] > 1 else "ML4T"
-            speedup_str = f"{r['speedup']:.2f}x" if r["speedup"] > 1 else f"{1/r['speedup']:.2f}x"
-            print(
-                f"{config:<20} {r['zipline_runtime']:<12.3f} {r['ml4t_runtime']:<12.3f} {speedup_str:<12} {winner}"
-            )
-        else:
-            print(f"{config:<20} {'FAILED':<12} {r['ml4t_runtime']:<12.3f} {'N/A':<12} {'N/A'}")
-
-    print("=" * 70)
-
-    return 0
+VALIDATION_DIR = Path(__file__).parents[1]
+sys.path.insert(0, str(VALIDATION_DIR))
 
+from cross_framework_performance import main  # noqa: E402
 
 if __name__ == "__main__":
-    sys.exit(main())
+    raise SystemExit(main())