YUCLAW

The open evidence layer for financial research — every claim carries its own audit trail.

Statistics pre-registered before data. Adverse results published. Every number reproducible by strangers.

Verify us before you read us — three commands:

pip install yuclaw && yuclaw replay-lab     # rebuilds every published Lab statistic — exit 0 = reproduced
curl -sO https://raw.githubusercontent.com/YuClawLab/yuclaw-brain/main/registry/protocols.jsonl   # the protocol chain — statistics locked BEFORE computation, tamper-evident
make replicate                              # full clean-environment replication

How we compare → · Take the 5-minute tour →

What you'll find inside: the baseline test our own composite lost at current sample sizes — published under the pre-registered protocol · a label-calibration panel that says "directional meaning not yet demonstrated" · retired hypotheses preserved with their grounds · 500+ filings shown to be 3 evidence stories · robustness grids that print where results break.

Research and education only — not investment advice. Signal labels are research classifications, not buy/sell recommendations.

Live site (yuclaw.ca) · Validation Lab · SMH Evidence Lens · XLK Evidence Lens · Canada Resources · Forward Tracking · 📖 User Guide (EN) · 📖 Guide (FR) · Weekly Note · For AI agents → llms.txt · ⚠️ Disclaimer · PyPI

Important

Research and education only — not investment advice. Signal labels are research classifications, not buy/sell recommendations. Hypothetical research; past results do not predict future performance.

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Why this is different

• Statistics are registered before they are computed. Every published statistic names its protocol in a hash-chained, append-only registry (registry/protocols.jsonl); estimator changes are supersessions, never edits. Check the chain yourself:

  python3 - <<'EOF'
  import sys; sys.path.insert(0, 'tools')
  from yuclaw_protocol_registry import Registry
  Registry('registry/protocols.jsonl').verify_chain(); print('chain OK')
  EOF

• Self-audits publish as measured. A pre-registered champion-challenger test found a persistence baseline ahead of our own composite at the primary horizon — that table is on the Lab page, not in a drawer. The label-calibration panel prints where labels carry no demonstrated directional meaning.

• Lenses pass a published admission standard or they don't ship. The XLK lens is live because it passed the same admission standard the SMH lens registered; verdicts and their reasons print on each page.

• The evidence layer is machine-readable. llms.txt and evidence_index.json give AI agents stable URLs for every page, packet, and protocol.

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What YUCLAW does

• Every signal traces to a filing. Each composite score decomposes into nine components, and every evidence event links to the SEC document it was extracted from — checked against the source text before any signal sees it.
• Every snapshot is hashed to a public, tamper-evident ledger — git-anchored, never edited. Daily signal sets are content-hashed and committed to yuclaw-trust before pages publish. Outages are disclosed, never backfilled.
• Every Lab chart is reproducible bit-for-bit. yuclaw replay-lab (or a standalone stdlib script) rebuilds the cohorts, recomputes every statistic, and re-derives every ledger hash root from published derived data.

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Sixty seconds

pip install yuclaw
yuclaw demo                        # 3-minute guided journey — works offline, zero config
yuclaw why AMD --as-of 2026-05-20  # bundled offline signal, no backend needed

Live signals for all tickers need the local backend (docs/v4/backend_setup.md); the published-data commands work anywhere with no backend. At the v5.1.0 release, replay-lab ran from a fresh venv with nothing but pip install yuclaw and reproduced 33 daily ledger roots exactly (2,926 leaf hashes recomputed) and every published statistic, exit 0. It exits non-zero on any mismatch.

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What shipped in v5.1

Component	Measured / Shipped	Status
Full command surface on PyPI	events / lens / export / memo subcommands ship in the published wheel (previously main-checkout only)	Live
Protocol registry	hash-chained, append-only pre-registration ledger; 60+ entries; supersession-only edits; chain-verified in the daily gate suite	Live
Public engine panels	evidence structure, context robustness, evidence lifecycle — derived from run artifacts, regenerated daily	Live
Champion-challenger baselines	pre-registered; the persistence baseline finished ahead of the composite at the primary horizon at current n — published as measured	Published
Label calibration	pooled consistency with CIs; panels state where directional meaning is not yet demonstrated	Published
SMH + XLK evidence lenses	both passed the published admission standard; foreign-filer 6-K/20-F/40-F prose paths live	Live
Layer 0/1 evidence swarm	10 event-type specialists on local models; prose-first ingestion (grounding 0.52 → 0.75, citation fidelity 0.66 → 0.85)	Live
C6 risk channel	rareness confirmed OOS (22.2% fire rate, n=9 held-out); sign unconfirmed — first read under the v2 protocol printed INCONCLUSIVE (2026-07-30); accrual continues	Partial — sign pending
Layers 2–10	roadmap — explicitly gated on out-of-sample sign confirmation for the risk channel	Gated, not built
Canada Resources evidence tier	49 SEC filers across XEG/ZEO/GDX/URNM; 6-K/40-F prose path; evidence-only, never scored (live page)	Live

Command surface

yuclaw why TICKER                  # Composite signal + ranked evidence w/ SEC source URLs
yuclaw replay TICKER --date DATE   # Point-in-time signal at end of date
yuclaw replay-lab                  # Reproduce the Validation Lab from the public bundle
yuclaw validation                  # In-sample event validation + forward tracking ledger
yuclaw events --ticker SU --since 2026-05-01   # Accepted-events export (derived data only)
yuclaw lens canada --lens XEG      # Lens summary-card data as JSON (same numbers the page renders)
yuclaw export --lens GDX --format csv          # Lens events export; --page builds the evidence packet
yuclaw memo --ticker SU --days 30  # Evidence memo — grounded, citation-verified, linted (docs/usage.md)
yuclaw verify TICKER --date DATE   # Verified Research Ledger integrity check

Worked examples with real output: docs/usage.md.

Public signal vocabulary: STRONG_BULLISH, BULLISH, NEUTRAL, WATCH, WEAKENING, NEGATIVE_EVENT, BEARISH_WATCH, RISK_ALERT. There is no SELL or SHORT label — these are research classifications, not trade directions.

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How it works

SEC EDGAR (Form 4 / 8-K / 10-Q / 10-K / 6-K / 20-F / 40-F)
  │
  ▼ systemd poller (always-on, 5-min sweep)
  ├──▶ Form 4 → deterministic XML parser (no LLM, zero GPU) → events table
  ▼ prose-first text acquisition (exhibit / MD&A prose; XBRL cover fallback)
  ▼ Llama 3.1 70B extraction + SourceLock Guard (checked against source text)
  ▼ events table — the evidence layer
  ▼ Layer-1 specialist swarm (10 specialists; risk channel kept SEPARATE from direction)
  ▼ 9-component composite (C1..C9)
  ▼ signal_snapshots (content-hashed)
  ├──▶ Verified Research Ledger (git-anchored, public)
  ├──▶ Forward Tracking Ledger (outcomes vs SPY at 1 / 5 / 20 days)
  ├──▶ Live landing + Validation Lab pages (regenerated daily)
  └──▶ SDK / REST / MCP server

132-name coverage: a 79-name scoring universe (equities + sector ETFs + broad ETFs + macro instruments) plus a 53-filer evidence tier — ingested and dashboarded, never scored; the boundary is machine-enforced.

Deep dives: system architecture, operations, hardware · OpenClaw / MCP integration · methodology.

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Signal Validation Lab

A decile-cohort event study of whether YUCLAW's composite score carries forward information — built from feedback by Prof. Deng Shijie (Georgia Tech):

• Regenerated daily after U.S. market close, freshness-stamped, with a staleness alarm in the health monitor.
• Statistical rigor panel: bootstrap confidence intervals, Newey–West and clustered inference, market-model alpha, and a statistical power meter that quantifies what the current n can and cannot detect.
• Statistics computed per-regime (in-sample vs forward) and never blended across the boundary.
• Reproduce this page: yuclaw replay-lab or the standalone stdlib script.

In the Lab's own words: "No forward alpha has been statistically proven yet."

🔬 Live: Signal Validation Lab · Today's Evidence Digest · Independent Replication Log · Methodology: docs/methodology/validation_lab.md

Hypothetical research illustration — not investment advice, not performance advertising.

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Methodology & honest limitations

Full methodology lives in docs/methodology/backfill.md. The honest limits, stated up front:

• The forward record is young. Forward tracking began 2026-05-20; roughly 50 trading days of look-ahead-free history exist as of early August 2026 — enough to display, not enough for statistical significance; the Lab's power meter quantifies this.
• In-sample is replay reconstruction, not a live backtest. The in-sample panel was materialized after the fact by the replay engine, and the extraction model's training cutoff overlaps that window, so in-sample results carry a parametric look-ahead bias and are systematically optimistic.
• C6 risk channel is partially confirmed. Rareness confirmed OOS; the sign question remains open — the first read under the registered v2 protocol printed INCONCLUSIVE (2026-07-30) and accrual continues. The sign confirmation is the gate for Layers 2–10, and it has not been met.
• C4 macro regime is temporarily frozen as of 2026-05-18 with a staleness disclosure, pending macro-engine restoration. C1/C3/C5/C7 read live price_history; C6/C8/C9 remain point-in-time exact.
• Jun 26 – Jul 3, 2026 outage — disclosed, not patched. A network outage froze price-derived inputs at Jun 25 closes while snapshots continued point-in-time on-box. No snapshot or ledger row was retroactively edited.
• No table of headline % returns appears in this README. Hit rates are reported alongside their n on the live validation page; small-n panels are tagged.

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Community

Live site	yuclaw.ca
Validation Lab	validation_lab.html
SMH Evidence Lens	etf_evidence.html
XLK Evidence Lens	xlk_evidence.html
📖 User Guide (EN / FR)	EN · FR
Twitter	@Vincenzhang2026
GitHub	YuClawLab
PyPI	pypi.org/project/yuclaw
Methodology	docs/methodology/backfill.md

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⚠️ Disclaimer

YUCLAW is open-source research and educational software. It is NOT financial advice, investment advice, or a recommendation to buy, sell, or hold any security. All signals, scores, and analyses are generated by automated AI models and may contain errors.

Past performance does not guarantee future results. Trading involves substantial risk of loss. You are solely responsible for your own investment decisions. Consult a licensed financial advisor before making any investment.

YuClawLab, its contributors, and affiliates accept no liability for any losses arising from use of this software.

For educational and research purposes only. See docs/methodology/backfill.md and DISCLAIMER.md for the long-form versions.

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For AI agents & researchers

The open evidence layer for financial AI.

Agents citing YUCLAW inherit accession-verified, point-in-time, hash-anchored evidence. Start at capabilities.json — one URL discovers the why-JSON API, the Evidence Passport, the schemas, EvidenceBench, and the MCP tools (full pitch).

• Start here: llms.txt and the machine-readable evidence_index.json (every page, packet, and protocol with stable URLs and data-through dates).
• Objects: the five frozen v1 JSON Schemas — SignalSnapshot, EvidenceEvent, ResearchProtocol, RobustnessCell, ResearchMemo — at /schemas/; today's real outputs validate against them in the daily gate suite.
• Consume: evidence packets (derived statistics, event CSVs, engine run JSONs, metadata + citation snippets) from /packets/; the MCP server exposes why / memo / events / lens / universe / validation / verify as tools with friendly no-backend behavior.
• Cite: use the CITATION.txt inside any packet; event-level citations use event IDs resolvable in the packet CSVs.
• Verify: pip install yuclaw && yuclaw replay-lab recomputes the published Lab statistics from the public bundle; the protocol registry (registry/protocols.jsonl) is hash-chained and append-only.
• Rules: derived statistics only; preserve the disclaimers and the frozen implication line when quoting inference; nothing here is advice or a recommendation.

Released under the Apache License 2.0 — free for everyone.

pip install yuclaw