trade-edge-audit

name

trade-edge-audit

description

The EDGE LENS for trading peers — recalls EVERY factor/indicator running from the live forecast ledger (no enumeration) and renders the whole pile through the edge arsenal off ONE call: multi-horizon scoring (the ladder) + deflated Sharpe (overfit) + Benjamini-Hochberg FDR (multiple-testing across the fleet) + spread-bounce + maker-fee falsification, then ranks only what survives ALL of it. Use when a peer must answer "does ANY running factor have real, overfit-corrected, multiple-testing-corrected, fee-surviving edge, and at which horizon" without hand-assembling 6 tools. The trade-engine analog of quantum-hypothesis-simulation.

Trade Edge Audit — the edge lens

The trading analog of quantum-hypothesis-simulation: a capability-wrapper that hands a peer YURI's whole edge arsenal off one invocation. The peer picks the lens (edge); the skill hauls in everything running and runs the battery behind it. No re-assembling six tools, no enumerating indicators.

Engine: _SYSTEM/Scripts/alpha-factor-library/trade-edge-audit.mjs (capability trade-edge-audit, 11/0). It ORCHESTRATES existing capabilities — it does not re-implement their math.

The two moves

1. RECALL (the recollection layer). recallFactors(ledgerPath) reads the live forecast ledger (_SYSTEM/state/strategy-forecasts.jsonl) and returns every factor that has fired + a per-market price series. That ledger IS "everything running" — every price signal, funding/basis, cross-asset, social overlay the orchestrator records. The peer never lists indicators; the skill recalls them.

2. RENDER through the arsenal. auditEdge({ledgerPath, q}) runs, per horizon rung (15m → weekly):

• Multi-horizon edge — per-factor forward-return mean / std / per-period Sharpe / one-sided t p-value / hit-rate, non-overlapping (independent obs).
• Deflated Sharpe (factor-evaluator.deflatedSharpe) — kills overfit; nTrials = the FULL (factor × rung) selection universe (selectionTrials), so the bar reflects every comparison the audit made, not one rung's.
• Benjamini-Hochberg FDR (factor-evaluator.benjaminiHochberg) — kills multiple-testing luck across the fleet (with 100+ factors, some look good by chance; this is exactly where you catch it).
• Falsification — spread-correction (bid-ask-bounce artifact + lag-1 autocorr) + maker-fill-sim (fee reality: taker vs maker net, break-even adverse-selection).
• Survivor = positive mean AND deflated-Sharpe-passes AND FDR-discovered AND not a bounce-prone (meanrev) family. Ranked by DSR.

Output: a structured verdict — which factors (if any) have real, overfit-and-multiple-testing-corrected, fee-surviving edge, at which horizon. It is built to say "NO edge" when there is none — that honesty is the product, not a failure.

Method map

Need	Call
Recall everything running	recallFactors(ledgerPath) → {rows, series, byFactor, factorIds, markets}
Per-factor edge stats at one horizon	factorEdgeStats(recall, {horizonS, strideS}) → {[id]:{n,mean,std,sharpe,tStat,pValue,hitRate,market}}
Full battery + verdict	auditEdge({ledgerPath, q=0.1, makerSchedule='real-tier0'}) → {recall, selectionTrials, rungs, falsification, verdict}
CLI (live ledger)	node _SYSTEM/Scripts/alpha-factor-library/trade-edge-audit.mjs --audit
Self-test	… trade-edge-audit.mjs --test

Dual consumption (both peer lanes)

• Native Sonnet agent: dispatch with "run/extend the edge lens — .claude/skills/trade-edge-audit/SKILL.md; call auditEdge on the live ledger and return the verdict + any survivors." The agent reads this file.
• ollama nano-swarm lane: inject this body as the procedure preamble (no filesystem) + the deltas. The lane runs --audit (or auditEdge) and reports.

Either way: the result is ADVISORY until a local run verifies it (the standing doctrine). Re-run --audit yourself before trusting a survivor.

Limitations (honest)

• Long rungs need data. 12h/weekly stay empty until enough non-overlapping observations accrue (12h ~2 days, weekly ~1 month). Not a bug — evaluated=0 is honest.
• Brier/calibration not yet fused. The forecast ledger stores direction, not a probability, so calibration (Brier) lives in the decoded-outcome AFL ledger path — a v2 fusion.
• vwap- classified meanrev.* classifyFamily (shared spread tool) puts any vwap name in the bounce-prone meanrev family, so a vwap-momentum factor is conservatively EXCLUDED. False-negative only (drops a real edge, never admits a fake one) — acceptable for an honesty-first audit; don't loosen the shared classifier just for this.
• Per-rung FDR. FDR is controlled within each horizon's fleet; cross-rung multiplicity is handled by the deflated-Sharpe nTrials (full selection universe), not by a cross-rung BH.

Sibling lenses (planned)

• trade-decision-sim — the DECISION lens: recall the live snapshot + render through factor-circuit (order-optimal sequencing) + decision-sim (CVaR/robust sizing). "Given everything now, what's the order-optimal, risk-robust call + size."
• peer-redteam — generic adversarial-review contract (sibling of peer-signal-build).

Session Notes

2026-06-17

• tools: Read, Edit, Bash, Agent (Sonnet red-team), capability-scan
• origin: built from Marcel's reframe — "turn all the indicators running into ONE skill that renders everything through an evaluator/decision-sim, like quantum-sim, so peers dig in quick + powerful." This is the edge lens; recall-everything + render-through-arsenal.
• red-team (Sonnet): SHIP, no CRITICAL/HIGH. Verified correct: per-period Sharpe input, one-sided p-value + CDF accuracy, BH index-alignment (input-order), no look-ahead in forward pairing, fail-soft complete. Fixed the MED: nTrials now the cross-rung selection universe (was per-rung → DSR bar too low).
• live verdict: 205 factors recalled, selectionTrials 247, 0 survivors — no overfit/FDR/fee-robust edge yet (the honest core). Cross-validates the standalone maker-fill verdict exactly (taker −245 / maker −47 bps).
• self-inflicted catch: first cut had the '..','state' path bug + a 'mean-reversion' vs 'meanrev' family typo — both caught by verify-locally, the exact discipline peer-signal-build encodes.