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Systematic discovery & rigorous validation of statistical anomalies in open HF market data (hfmarketdata.io) — pre-registered, artifact-null-driven, fully reproducible. Live atlas: www.anomaly-atlas.io

quant-researchmarket-microstructureanomaliesreproducibilityduckdbapple-silicon
Python 61.4% JavaScript 28.7% CSS 8.6% Shell 0.7% Makefile 0.5%

History of experiments/micro/expF_multiple_testing/README.md · clear filter

  1. expF: survival battery — statistical correction is not artifact correction
    …
    - 372 signed rules from the full C/D/E searched space; funnel:
  232 naive (62%) -> 226 FDR (61%) -> 68 SPA step-1 (18%), all GROSS
- survivors carry absurd Sharpes (10-31 ann.): bounce harvesting +
  frictionless timing; the KNOWN SPX->SPY artifact passes SPA (canary) —
  artifact nulls, search correction and costs are all three required
- expE calendar block: zero survivors (pipeline tripwire did not fire)
- 12/14 artifact-adjusted expC triage cells + ES->SPY form the
  double-filtered pool for expG
- new stats/spa.py (Politis-Romano bootstrap, White RC, Hansen SPA,
  StepM step-1, DSR) with 4-gate synthetic validation; funnel figure
- 0 network requests: entire battery served by the frozen cache

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
    Simon-Pierre Boucher committed 5 h ago (Aug 12, 2026) · 1 file changed +1 −1
  2. Bootstrap: full research skeleton (CLAUDE.md §3, localvm-research layout) + web platform
    …
    Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
    Simon-Pierre Boucher committed 7 h ago (Aug 12, 2026) · 1 file changed +15