YUCLAW v5.3.0
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Evidence-First Financial AI

Every signal traces to a real SEC filing.

Agent Research API · MCP · LangChain/LlamaIndex · pip install yuclaw
Disclaimer — Research & education only. Not investment advice. Signal labels are research classifications, not buy/sell recommendations.
Current signals — Forward Tracking Ledger
Current research classifications — not recommendations
TickerSignal label Score Evidence coverage
PFEBULLISH+0.53374
FXIBULLISH+0.5160
BMYBULLISH+0.45658
TMOBULLISH+0.45263
XLVBULLISH+0.4240
ABTNEUTRAL+0.39566
XLBNEUTRAL+0.3860
BACNEUTRAL+0.38136
PYPLNEUTRAL+0.35296
DHRNEUTRAL+0.33768
XLFNEUTRAL+0.3320
WFCNEUTRAL+0.31657
MRKNEUTRAL+0.31662
GSNEUTRAL+0.30786
IBBNEUTRAL+0.2950
LLYNEUTRAL+0.28054
PSXNEUTRAL+0.27762
SPYNEUTRAL+0.2750
DIANEUTRAL+0.2740
XLYNEUTRAL+0.2740
JPMNEUTRAL+0.26079
SLVNEUTRAL+0.24925
XLRENEUTRAL+0.2490
MDYNEUTRAL+0.2470
XBINEUTRAL+0.2430
GLDNEUTRAL+0.24059
IWMNEUTRAL+0.2390
UNHNEUTRAL+0.23338
ABBVNEUTRAL+0.22367
QQQNEUTRAL+0.2220
UUPNEUTRAL+0.22125
IEFNEUTRAL+0.2190
TAILNEUTRAL+0.2020
TLTWATCH+0.1870
XLIWATCH+0.1860
AXPWATCH+0.18676
CWATCH+0.17936
HPEWATCH+0.179100
KREWATCH+0.1740
XLPWATCH+0.1690
RKLBWEAKENING-0.14888
VIXYWATCH+0.14425
GOOGLWEAKENING-0.14389
XOMWATCH+0.14161
COSTWATCH+0.13966
LRCXWEAKENING-0.13675
MRVLWEAKENING-0.13699
SLBWATCH+0.13370
MSFTWATCH+0.13295
VXXWATCH+0.12938
JNJWATCH+0.12884
COPWATCH+0.12757
EEMWATCH+0.1210
PGWATCH+0.11568
MUWEAKENING-0.11595
MSWATCH+0.11087
AMDWEAKENING-0.109100
XLKWATCH+0.1040
AMATWEAKENING-0.09775
TSLAWATCH+0.07469
METAWEAKENING-0.07294
LUNRWATCH+0.06599
PEPWATCH+0.06567
VWATCH+0.06284
CRCLWATCH+0.060100
INTCWEAKENING-0.03982
SMHWEAKENING-0.0380
DELLWATCH+0.03892
XLUWEAKENING-0.0350
MAWATCH+0.03087
AAPLWATCH+0.02687
AMZNWEAKENING-0.02590
ARMWATCH+0.02495
XLCWATCH+0.0190
KOWATCH+0.01786
WMTWATCH+0.01787
XLEWATCH+0.0100
NVDAWEAKENING-0.00788
CVXWEAKENING-0.00075

Evidence coverage = how much evidence stands under this classification — coverage, not prediction (Evidence Coverage v1, registered protocol). Score = composite research score. It is not an expected return, a probability, a price target, or a recommendation.

Data through 2026-08-05 (last completed U.S. trading day) · regenerated daily after market close
Public signal vocabulary

Labels are research classifications, not buy/sell recommendations:

STRONG_BULLISH · BULLISH · NEUTRAL · WATCH · WEAKENING · NEGATIVE_EVENT · BEARISH_WATCH · RISK_ALERT

There is no SELL or SHORT label. The SDK's _validate_label() is invoked on every signal-bearing return.

How it works

1 · Evidence layer

SEC EDGAR filings (Form 4, 8-K, 10-Q, 10-K, 6-K, 40-F) are extracted with a local Llama 3.1 70B model. A deterministic SourceLock Guard validates every extraction against the source text before any signal sees it.

2 · Composite scoring

Nine components combine into a confidence-weighted composite. C6 event impact carries the highest weight (0.18) — by design, the evidence layer leads.

3 · Time-machine replay

Any signal can be recomputed as of a past date. Point-in-time filtering (available_as_of <= as_of) is leak-audited; reproducible via the yuclaw replay CLI or REST API.

4 · Verified Research Ledger

Each day's published signals have their content hashes committed to a public git repo (yuclaw-trust). Anyone can call yuclaw verify to confirm a signal hasn't been edited since publication.

Full disclaimer & methodology

Open-source equity research where every composite signal traces back to a verifiable SEC filing or deterministic supply-chain cascade. Replayable point-in-time. Tamper-evidenced via a public git-anchored Verified Research Ledger. Research and education only.

Disclaimer — YUCLAW research output. Not investment advice. Past performance does not guarantee future results. Signal labels are research classifications, not buy/sell recommendations. YUCLAW is not a registered investment adviser. Past results — in-sample or forward-tracked — do not predict future performance.
Use YUCLAW in your research
1 · Verify the record

pip install yuclaw then yuclaw replay-lab.
No install: tools/replay_lab.py (stdlib only) against the published bundle.
Exit 0 = every statistic and ledger root reproduced. How to report a replication →

2 · Inspect one evidence trace

One real Suncor 6-K, end to end:
filing → exhibit → extracted prose → event type → grade → C6 posture.
Open the trace → · example evidence memo (Suncor) →

3 · Cite a research lens

Every evidence packet ships a ready citation snippet
(version, data-through, build date, source commit).
Get the citation →

📖 User Guide (PDF) — from pip install to full verification, six pages. · 📖 Guide de l'utilisateur (FR)

Status — proven · not proven · accruing

Rendered from one shared source (v3/web/useful_blocks.py) on every page that shows it, so the copies cannot drift. Statuses are measured, not aspirational.

Proven (verifiable today)
  • ✓ Replay works — one command reproduces every Lab statistic and ledger root from published data
  • ✓ Ledger anchored daily — sha-256 daily roots committed to a public git repository before pages update
  • ✓ Evidence traces to filings — every accepted event carries a source URL, accession number, and verified excerpt
  • ✓ Coverage measured — SEC-filer weight per lens is stated as measured, never rounded up
  • ✓ Snapshots are point-in-time — daily as-of writes, zero retroactive edits (outage window disclosed, not repaired)
  • ✓ Evidence-tier names are never scored — enforced by positive gating and a standing negative check
Not proven
  • ✗ Forward alpha — no spread, IC, or alpha significant at 5% with adequate power
  • ✗ C6 risk-gate sign — rareness confirmed OOS 2026-07-06 (22% fire rate, n=9 held-out); sign confirmation pending (elevated arm n=2; accrual live from 2026-07-16)
  • ✗ Peer-model CAR lead — event-study lead over peer models is not established; live-era sample remains small
Accruing
  • · Forward out-of-sample record — one period per trading day, accruing daily
  • · Matured CAR events — each accepted event matures into the event study after its forward window completes
  • · C6 elevated arm — live Form-4 ingestion since 2026-07-16 restores the insider stream to production inputs
  • · External replications — the replication log accrues as independent runs are reported
For AI agents & researchers

YUCLAW is the open evidence layer underneath AI research tools. Start with llms.txt and the machine-readable evidence_index.json (every page, packet, and protocol with stable URLs and data-through dates). Packets carry derived statistics, event CSVs, engine run JSONs, and citation snippets; yuclaw replay-lab re-computes the published statistics from the public bundle. Derived data only — preserve the disclaimers when quoting; nothing here is advice or a recommendation.

Install + try it
pip install yuclaw
yuclaw demo                         # 3-minute guided "Why AMD?" journey
yuclaw why AMD --as-of 2026-05-20   # bundled offline signal
yuclaw verify AMD --date 2026-05-20 # check the ledger record
# all tickers/dates: connect the local backend — see README

SDK + REST API + MCP server documented at github.com/YuClawLab/yuclaw-brain. REST API terms at /API_TERMS.md.

YUCLAW v5.3.0 · YuClawLab · Full Disclaimer · 🚀 5-minute tour · 🤖 For AI builders · 📐 EvidenceBench · 📖 User Guide (PDF) · 📖 Guide de l'utilisateur (FR) · Methodology · Replication · Today's Evidence Changes · YUCLAW's Lane · Weekly Note · Apache-2.0 Licensed