LAB #1896 NEUTRAL: LEDGER BENCH: Apply filter: Pool density HIGH (>=90) — improves win rate from 32.0% to 33.6% (+1.6pp — E8 Intelligence Research
Year: 2026
Type: preprint
Abstract: IDEA: Adjustment made to the live model — verify against the backtests: Apply filter: Pool density HIGH (>=90) — improves win rate from 32.0% to 33.6% (+1.6pp, n=1349) SAME-WINDOW EFFECT: Applying the pool-density filter (≥90) would have excluded the three rizzy5m XAUUSD and GBPUSD shorts that all closed as losses, as those entries occurred during low-density pool conditions. It would also have excluded the EURJPY SHORT that won, reducing the sample to the remaining wins (EURJPY LONG, GBPUSD LONG, GBPUSD LONG via wkjudas) — net effect on this tiny window is roughly neutral on PnL but removes 3 of 4 losses, improving the visible win rate from 4/9 (44%) to 4/6 (67%). However, the single excluded winner means the filter is not a pure loss-remover; it trades volume for selectivity. The +1.6pp backtest gain is directionally consistent but not statistically distinguishable from noise at n=1349. OVER-TIME PROJECTION: Over 3–6 months, a +1.6pp win-rate improvement at fixed risk/reward would Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
Author: Caldin, Andrew Stewart
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7210267291
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