anomaly-atlas
Honesty doctrine. Every candidate anomaly is an artifact until proven otherwise; in-sample results are never findings; past statistical regularity does not imply future returns. This is research on statistical properties of market data — not investment advice, not a trading system.

Publications

Formal write-ups of the project's results, versioned in the repository like everything else. Every number is regenerated from committed results.json files and every figure is rendered live from them — nothing is hand-typed. Each publication states its evidence level; negative results are published with the same care as positive ones.

P001 · Tue Aug 11 2026 20:00:00 GMT-0400 (heure avancée de l’Est) · v1

The Artifact Frontier: What Survives Honest Testing in Open High-Frequency Market Data?

Part I — Methods, artifact taxonomy, and train-period results (2000–2016)

We systematically scan open 1-minute-to-daily market data (hfmarketdata.io, sole source) for short-horizon mean-reversion, lead-lag, and calendar anomalies, under a pre-registered protocol: every detector must first pass a synthetic-data gate; every scan runs …

published