LAB #2864 PROMISING: LEDGER BENCH: Apply filter: Pool density HIGH (>=90) — improves win rate from 31.1% to 32.7% (+1.6pp — E8 Intelligence Research

IDEA: Adjustment made to the live model — verify against the backtests: Apply filter: Pool density HIGH (>=90) — improves win rate from 31.1% to 32.7% (+1.6pp, n=1425) SAME-WINDOW EFFECT: Applying the pool-density ≥90 filter to the current 10-trade window would have excluded trades lacking that condition. Based on the backtest lift (+1.6pp), roughly 2–3 of these trades likely fall below the density threshold; if those are the two losses (USDJPY, XAUUSD SHORT on 08-04) and one win (GBPUSD SHORT on 08-03), the filtered window would show 5W/2L instead of 6W/4L — a win-rate jump from 60% to ~71%. Expected PnL delta is modestly positive, roughly +0.5R to +1.0R, but the sample is too small to confirm the filter's causal effect versus noise. OVER-TIME PROJECTION: Over 3–6 months, a +1.6pp win-rate improvement on ~1,400 trades translates to roughly +23 additional wins, which at average risk/reward could add +0.5% to +1.0% monthly return. However, the filter likely reduces trade frequency (po 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
2026-09-29
DOI
https://doi.org/10.5281/zenodo.23031087
Primary Topic
Competitive and Knowledge Intelligence
Type
preprint
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LAB #2864 PROMISING: LEDGER BENCH: Apply filter: Pool density HIGH (>=90) — improves win rate from 31.1% to 32.7% (+1.6pp — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Competitive and Knowledge Intelligence
preprint

LAB #2864 PROMISING: LEDGER BENCH: Apply filter: Pool density HIGH (>=90) — improves win rate from 31.1% to 32.7% (+1.6pp — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

IDEA: Adjustment made to the live model — verify against the backtests: Apply filter: Pool density HIGH (>=90) — improves win rate from 31.1% to 32.7% (+1.6pp, n=1425) SAME-WINDOW EFFECT: Applying the pool-density ≥90 filter to the current 10-trade window would have excluded trades lacking that condition. Based on the backtest lift (+1.6pp), roughly 2–3 of these trades likely fall below the density threshold; if those are the two losses (USDJPY, XAUUSD SHORT on 08-04) and one win (GBPUSD SHORT on 08-03), the filtered window would show 5W/2L instead of 6W/4L — a win-rate jump from 60% to ~71%. Expected PnL delta is modestly positive, roughly +0.5R to +1.0R, but the sample is too small to confirm the filter's causal effect versus noise. OVER-TIME PROJECTION: Over 3–6 months, a +1.6pp win-rate improvement on ~1,400 trades translates to roughly +23 additional wins, which at average risk/reward could add +0.5% to +1.0% monthly return. However, the filter likely reduces trade frequency (po Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Decent work and economic growth
Competitive and Knowledge Intelligence
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LAB #2864 PROMISING: LEDGER BENCH: Apply filter: Pool density HIGH (>=90) — improves win rate from 31.1% to 32.7% (+1.6pp — E8 Intelligence Research — Andrew Stewart Caldin · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS