LAB #2325 NEUTRAL: LEDGER BENCH: Apply filter: Session = NY_OPEN — improves win rate from 31.5% to 38.0% (+6.5pp, n=629 — E8 Intelligence Research
IDEA: Adjustment made to the live model — verify against the backtests: Apply filter: Session = NY_OPEN — improves win rate from 31.5% to 38.0% (+6.5pp, n=629) SAME-WINDOW EFFECT: Applying the NY_OPEN filter would have excluded all 10 live trades listed, as every entry timestamp falls outside the NY session (all are between 09:55 and 18:00 +02:00, which is 03:55–12:00 ET — only the 18:00 EURJPY LONG might marginally overlap NY close, but it's not a clean NY_OPEN entry). So the filter would have zeroed out this entire window — no wins, no losses, no PnL. That means the +6.5pp win-rate improvement in backtest does not translate to this live sample; it would have avoided 2 wins and 3 losses, netting a wash but removing all exposure. The apparent edge is not visible in your current live trades — they are all off-session, so the filter would have simply skipped them. OVER-TIME PROJECTION: Over 3–6 months, if the NY_OPEN filter is genuinely predictive, you'd see a higher win rate but far f Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
Authors
- Andrew Stewart Caldin
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-17
- DOI
- https://doi.org/10.5281/zenodo.22805727
- Primary Topic
- Intelligence, Security, War Strategy
- Type
- preprint