LAB #2645 NEUTRAL: LEDGER BENCH: Apply filter: Session = NY_OPEN — improves win rate from 31.0% to 37.2% (+6.1pp, n=643 — E8 Intelligence Research

IDEA: Adjustment made to the live model — verify against the backtests: Apply filter: Session = NY_OPEN — improves win rate from 31.0% to 37.2% (+6.1pp, n=643) SAME-WINDOW EFFECT: Applying the NY_OPEN filter would have excluded all 10 listed live trades, since every entry timestamp falls between 10:10 and 11:35 CET (08:10–09:35 ET), which is outside the NY_OPEN session (typically 09:30–11:30 ET, but your filter likely targets a narrower window). If the filter had been live, you would have taken zero trades in this window, eliminating 6 wins and 4 losses — net PnL change is ambiguous but likely negative if those wins were larger than losses. The backtest's +6.1pp win-rate gain does not translate here because the live sample is tiny and all trades fall outside the filter's intended session. OVER-TIME PROJECTION: Over 3–6 months, this filter would reduce trade frequency substantially (likely 40–60% fewer signals), which could improve win rate per trade but may reduce total net profit if Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-24
DOI
https://doi.org/10.5281/zenodo.22931336
Primary Topic
Intelligence, Security, War Strategy
Type
preprint
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LAB #2645 NEUTRAL: LEDGER BENCH: Apply filter: Session = NY_OPEN — improves win rate from 31.0% to 37.2% (+6.1pp, n=643 — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Intelligence, Security, War Strategy
preprint

LAB #2645 NEUTRAL: LEDGER BENCH: Apply filter: Session = NY_OPEN — improves win rate from 31.0% to 37.2% (+6.1pp, n=643 — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

IDEA: Adjustment made to the live model — verify against the backtests: Apply filter: Session = NY_OPEN — improves win rate from 31.0% to 37.2% (+6.1pp, n=643) SAME-WINDOW EFFECT: Applying the NY_OPEN filter would have excluded all 10 listed live trades, since every entry timestamp falls between 10:10 and 11:35 CET (08:10–09:35 ET), which is outside the NY_OPEN session (typically 09:30–11:30 ET, but your filter likely targets a narrower window). If the filter had been live, you would have taken zero trades in this window, eliminating 6 wins and 4 losses — net PnL change is ambiguous but likely negative if those wins were larger than losses. The backtest's +6.1pp win-rate gain does not translate here because the live sample is tiny and all trades fall outside the filter's intended session. OVER-TIME PROJECTION: Over 3–6 months, this filter would reduce trade frequency substantially (likely 40–60% fewer signals), which could improve win rate per trade but may reduce total net profit if Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Intelligence, Security, War Strategy
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LAB #2645 NEUTRAL: LEDGER BENCH: Apply filter: Session = NY_OPEN — improves win rate from 31.0% to 37.2% (+6.1pp, n=643 — E8 Intelligence Research — Andrew Stewart Caldin · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS