LAB #4589 NEUTRAL: LEDGER BENCH: Apply filter: Session = NY_OPEN — improves win rate from 31.6% to 38.3% (+6.7pp, n=802 — E8 Intelligence Research
- 1Independent Researcher, United Kingdom
Abstract
IDEA: Adjustment made to the live model — verify against the backtests: Apply filter: Session = NY_OPEN — improves win rate from 31.6% to 38.3% (+6.7pp, n=802)
SAME-WINDOW EFFECT: Applying the NY_OPEN filter to the live window above would have excluded all 10 trades, as every entry timestamp falls outside the NY_OPEN session (all are between 09:56 and 15:08 +02:00, which maps to London/early NY overlap but not the defined NY_OPEN bucket). This would have eliminated the 4 wins and 2 losses currently closed, plus the 4 rejected/open trades, yielding zero realized PnL for the window. The backtested +6.7pp win-rate gain is not observable here because the sample is entirely out-of-filter; the filter would have prevented all activity, not improved selectivity within it.
OVER-TIME PROJECTION: Over 3–6 months, this filter would likely reduce trade frequency substantially (possibly 40–60% of signals dropped), concentrating entries into a narrower liquidity window. The +6.7pp win-rate improvem
Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
Related
- LAB #4419 NEUTRAL: LEDGER BENCH: Apply filter: Session = OFF_SESSION — improves win rate from 31.6% to 41.9% (+10.3pp, — E8 Intelligence Research
- LAB #4176 NEUTRAL: LEDGER BENCH: Apply filter: Session = OFF_SESSION — improves win rate from 32.6% to 42.5% (+9.9pp, n — E8 Intelligence Research
- LAB #4462 NEUTRAL: LEDGER BENCH: Apply filter: Session = LONDON_OPEN — improves win rate from 31.5% to 34.8% (+3.3pp, n — E8 Intelligence Research
- LAB #4435 NEUTRAL: LEDGER BENCH: Apply filter: USDCHF SHORT @ OFF_SESSION with 6 conf — improves win rate from 31.5% to — E8 Intelligence Research
- LAB #4494 NEUTRAL: LEDGER BENCH: Apply filter: USDCHF SHORT @ OFF_SESSION with 6 conf — improves win rate from 31.6% to — E8 Intelligence Research
BibTeX
@misc{caldin20264589,
title = {{LAB #4589 NEUTRAL: LEDGER BENCH: Apply filter: Session = NY_OPEN — improves win rate from 31.6% to 38.3% (+6.7pp, n=802 — E8 Intelligence Research}},
author = {Andrew Stewart Caldin},
howpublished = {Zenodo},
year = {2026},
month = oct,
doi = {10.5281/zenodo.23587090},
url = {https://zenodo.org/records/23587090},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - LAB #4589 NEUTRAL: LEDGER BENCH: Apply filter: Session = NY_OPEN — improves win rate from 31.6% to 38.3% (+6.7pp, n=802 — E8 Intelligence Research
AU - Andrew Stewart Caldin
PY - 2026
DA - 2026/10/23
PB - Zenodo
DO - 10.5281/zenodo.23587090
UR - https://zenodo.org/records/23587090
AB - IDEA: Adjustment made to the live model — verify against the backtests: Apply filter: Session = NY_OPEN — improves win rate from 31.6% to 38.3% (+6.7pp, n=802) SAME-WINDOW EFFECT: Applying the NY_OPEN filter to the live window above would have excluded all 10 trades, as every entry timestamp falls outside the NY_OPEN session (all are between 09:56 and 15:08 +02:00, which maps to London/early NY overlap but not the defined NY_OPEN bucket). This would have eliminated the 4 wins and 2 losses currently closed, plus the 4 rejected/open trades, yielding zero realized PnL for the window. The backtested +6.7pp win-rate gain is not observable here because the sample is entirely out-of-filter; the filter would have prevented all activity, not improved selectivity within it. OVER-TIME PROJECTION: Over 3–6 months, this filter would likely reduce trade frequency substantially (possibly 40–60% of signals dropped), concentrating entries into a narrower liquidity window. The +6.7pp win-rate improvem Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
ER -