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IDEA: Adjustment made to the live model — verify against the backtests: Apply filter: Pool density HIGH (>=90) — improves win rate from 31.5% to 33.0% (+1.4pp, n=1910) SAME-WINDOW EFFECT: Applying a pool-density ≥90 filter would have excluded the three wkjudas trades (all losses) and likely the two rizzy7m AUDUSD trades (density unknown, but if below threshold, both the loss and the open/rejected win would drop). In the live window, this removes 3 confirmed losses and 1 confirmed win (GBPUSD LONG loss, USDJPY SHORT loss, NZDUSD SHORT loss, AUDUSD SHORT loss) — net effect: win rate improves from 4/8 (50%) to 4/5 (80%) on remaining trades, but sample shrinks drastically. PnL delta is positive but fragile — you're trading a smaller, higher-quality subset, yet the two REJECTED/open trades (EURJPY SHORT, AUDUSD LONG) would remain unfiltered and unverified, so real-time impact is uncertain. OVER-TIME PROJECTION: Over 3–6 months, a density ≥90 filter likely reduces trade frequency by 40–60% Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com
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Andrew Stewart Caldin (2026) studied this question.
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