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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

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# project: anomaly-atlas document: candidate_02/hypothesis author: Simon-Pierre Boucher contact: contact@spboucher.ai data_source: hfmarketdata.io created: 2026-08-12 status: draft

# Hypothesis — candidate_02

text
Hypothesis
  <what we believe and why — pre-specified BEFORE looking at results>

Falsification criterion
  <the concrete measurable outcome that would prove this wrong>

Artifact null(s)
  <the fake-signal baseline(s) this must beat: bounce / staleness /
   non-synchronous timestamps / permuted calendar / random walk>

Method
  <exact procedure, universe, split (train/validation/holdout), seeds,
   number of hypotheses tested, correction applied>

Result
  <filled after the run: effect size, bootstrap CIs, corrected p-values,
   OOS status, cost-adjusted effect, credits used>

Interpretation
  <what the numbers mean, WITH confidence level (0-3); alternative
   explanations considered — artifact first>

Next experiment
  <the most informative follow-up given this result>