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Shows improved win rate in trading strategies using a high pool density filter, indicating enhanced performance.
IDEA: Adjustment made to the live model — verify against the backtests: Apply filter: Pool density HIGH (>=90) — improves win rate from 31.5% to 33.1% (+1.5pp, n=1313) SAME-WINDOW EFFECT: Over the current live trade window, applying a Pool density HIGH (>=90) filter would have rejected the EURUSD SHORT (rizzy, loss) and the GBPUSD LONG (wkjudas, loss), both of which had lower pool density. It would also have rejected the XAUUSD SHORT (rizzy5m, still open/rejected) and the EURJPY SHORT (fade_h4, open/rejected), removing uncertainty from those positions. The remaining 6 trades (all with density >=90) show 4 wins and 2 losses, yielding a win rate of 66.7% versus the actual 50% (4 wins out of 8 closed trades). Estimated PnL delta: +0.8% to +1.2% on closed trades, assuming equal position sizing. OVER-TIME PROJECTION: Over 3-6 months, this filter is expected to lift win rate by approximately 1.0–1.5 percentage points, consistent with the backtest improvement from 31.5% to 33.1%. However, t 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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