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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 31.6% to 33.1% (+1.4pp, n=1902) SAME-WINDOW EFFECT: Applying the pool-density ≥90 filter would have excluded the three wkjudas entries (GBPUSD LONG, USDJPY SHORT, NZDUSD SHORT) — all three closed as LOSSES in the live window. That removes 3 losses from the 10-trade sample, leaving 4 wins and 3 losses among the remaining rizzy entries (excluding the two rejected/open trades). Win rate in this window would rise from 4/7 (57%) to 4/4 (100%) among closed trades, but the sample is tiny and the filter also would have blocked no winning trades here — so the immediate PnL delta is clearly positive but not statistically meaningful. OVER-TIME PROJECTION: Over 3–6 months, a +1.4pp win-rate gain on n=1902 suggests a real but modest edge, likely driven by avoiding low-density, noisy pools where signals degrade. However, the filter also reduces trade frequency — i 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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