LAB #3898 PROMISING: LEDGER BENCH: Apply filter: Pool density HIGH (>=90) — improves win rate from 32.5% to 34.0% (+1.5pp — E8 Intelligence Research

IDEA: Adjustment made to the live model — verify against the backtests: Apply filter: Pool density HIGH (>=90) — improves win rate from 32.5% to 34.0% (+1.5pp, n=1808) SAME-WINDOW EFFECT: Applying the pool-density filter (>=90) to the 10 live trades above would have excluded only those signals generated when pool density was below threshold. Given the backtest delta (+1.5pp win rate), roughly 1–2 of the 10 trades would likely have been filtered out — most plausibly the two losses from rizzy5m (NZDUSD and XAUUSD) if their density readings were low. This would have removed two losing trades, improving the window's win rate from 3/10 to 3/8 (37.5%) and reducing net PnL bleed. However, the filter could also have excluded a winner (e.g., GBPUSD SHORT via rizzy5m), so the net PnL delta is uncertain but likely positive given the backtest edge. OVER-TIME PROJECTION: Over 3–6 months, a +1.5pp win-rate improvement on ~1,800 trades translates to roughly 27 additional winning trades, but the PnL 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
2026-10-09
DOI
https://doi.org/10.5281/zenodo.23254772
Primary Topic
Financial Markets and Investment Strategies
Type
preprint
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LAB #3898 PROMISING: LEDGER BENCH: Apply filter: Pool density HIGH (>=90) — improves win rate from 32.5% to 34.0% (+1.5pp — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Financial Markets and Investment Strategies
preprint

LAB #3898 PROMISING: LEDGER BENCH: Apply filter: Pool density HIGH (>=90) — improves win rate from 32.5% to 34.0% (+1.5pp — 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 32.5% to 34.0% (+1.5pp, n=1808) SAME-WINDOW EFFECT: Applying the pool-density filter (>=90) to the 10 live trades above would have excluded only those signals generated when pool density was below threshold. Given the backtest delta (+1.5pp win rate), roughly 1–2 of the 10 trades would likely have been filtered out — most plausibly the two losses from rizzy5m (NZDUSD and XAUUSD) if their density readings were low. This would have removed two losing trades, improving the window's win rate from 3/10 to 3/8 (37.5%) and reducing net PnL bleed. However, the filter could also have excluded a winner (e.g., GBPUSD SHORT via rizzy5m), so the net PnL delta is uncertain but likely positive given the backtest edge. OVER-TIME PROJECTION: Over 3–6 months, a +1.5pp win-rate improvement on ~1,800 trades translates to roughly 27 additional winning trades, but the PnL Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Financial Markets and Investment Strategies
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