MODEL ADOPTION #4385: REJECT — LEDGER BENCH: Apply filter: Pool density HIGH (>=90) — improves win rate from 31.6% to 33. — E8 Intelligence Research

DECISION: REJECT ELEMENT: No single rule survives — the pool density ≥90 filter is a statistical artifact, not an E8-geometry-compatible edge. EXPECTED IMPACT: The +1.4pp win-rate gain (n=1903) is within noise for a binary filter; over 3–6 months, it likely reduces trade count by 10–20% while cutting only ~1 in 70 trades as a net loser. Net PnL improvement is near zero after slippage and missed opportunities. The wkjudas exclusion in the 10-trade window is anecdotal — those losses were not density-driven but timing-driven (E8 rhythm violation). RISK: The filter is regime-correlated — high pool density often coincides with trending conditions; in choppy/mean-reverting regimes, density drops but FADE setups remain valid. Applying this filter would suppress exactly those trades, degrading the model's adaptability. Also, live pool density computation may differ from backtest (lookback window, data feed), causing silent divergence. TEST: Before any reconsideration, run a 12-month ro Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-10-19
DOI
https://doi.org/10.5281/zenodo.23465357
Primary Topic
Financial Markets and Investment Strategies
Type
preprint
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MODEL ADOPTION #4385: REJECT — LEDGER BENCH: Apply filter: Pool density HIGH (>=90) — improves win rate from 31.6% to 33. — E8 Intelligence Research

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

MODEL ADOPTION #4385: REJECT — LEDGER BENCH: Apply filter: Pool density HIGH (>=90) — improves win rate from 31.6% to 33. — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

DECISION: REJECT ELEMENT: No single rule survives — the pool density ≥90 filter is a statistical artifact, not an E8-geometry-compatible edge. EXPECTED IMPACT: The +1.4pp win-rate gain (n=1903) is within noise for a binary filter; over 3–6 months, it likely reduces trade count by 10–20% while cutting only ~1 in 70 trades as a net loser. Net PnL improvement is near zero after slippage and missed opportunities. The wkjudas exclusion in the 10-trade window is anecdotal — those losses were not density-driven but timing-driven (E8 rhythm violation). RISK: The filter is regime-correlated — high pool density often coincides with trending conditions; in choppy/mean-reverting regimes, density drops but FADE setups remain valid. Applying this filter would suppress exactly those trades, degrading the model's adaptability. Also, live pool density computation may differ from backtest (lookback window, data feed), causing silent divergence. TEST: Before any reconsideration, run a 12-month ro 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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