LAB #2920 NEUTRAL: LEDGER BENCH: Apply filter: Quarterly phase = DISTRIBUTION — improves win rate from 31.1% to 37.8% ( — E8 Intelligence Research

IDEA: Adjustment made to the live model — verify against the backtests: Apply filter: Quarterly phase = DISTRIBUTION — improves win rate from 31.1% to 37.8% (+6.6pp, n=98) SAME-WINDOW EFFECT: Applying the DISTRIBUTION-phase filter would have blocked all 10 live trades above, since the window (Aug 3–7, 2026) falls within a distribution phase per your quarterly calendar. That yields 0 trades instead of 6 wins/4 losses — a 60% win rate in the sample, but with zero exposure and zero PnL. The backtest's +6.6pp win-rate gain is not reproduced here; instead, you'd have missed 6 winning trades (including 3 GBPUSD/XAUUSD wins) to avoid 4 losses. Net PnL impact is negative in this specific window, but the filter's value is in avoiding drawdown clusters, not maximizing per-window wins. OVER-TIME PROJECTION: Over 3–6 months, a DISTRIBUTION-only filter would cut trade frequency substantially (likely 40–60% fewer signals), which may raise win rate but reduce total PnL if wins are large and losses Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-30
DOI
https://doi.org/10.5281/zenodo.23052607
Primary Topic
Intelligence, Security, War Strategy
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
preprint

LAB #2920 NEUTRAL: LEDGER BENCH: Apply filter: Quarterly phase = DISTRIBUTION — improves win rate from 31.1% to 37.8% ( — E8 Intelligence Research

Andrew Stewart Caldin
Zenodo (CERN European Organization for Nuclear Research)
Intelligence, Security, War Strategy
preprint

LAB #2920 NEUTRAL: LEDGER BENCH: Apply filter: Quarterly phase = DISTRIBUTION — improves win rate from 31.1% to 37.8% ( — E8 Intelligence Research

Andrew Stewart Caldin
preprint en

Abstract

IDEA: Adjustment made to the live model — verify against the backtests: Apply filter: Quarterly phase = DISTRIBUTION — improves win rate from 31.1% to 37.8% (+6.6pp, n=98) SAME-WINDOW EFFECT: Applying the DISTRIBUTION-phase filter would have blocked all 10 live trades above, since the window (Aug 3–7, 2026) falls within a distribution phase per your quarterly calendar. That yields 0 trades instead of 6 wins/4 losses — a 60% win rate in the sample, but with zero exposure and zero PnL. The backtest's +6.6pp win-rate gain is not reproduced here; instead, you'd have missed 6 winning trades (including 3 GBPUSD/XAUUSD wins) to avoid 4 losses. Net PnL impact is negative in this specific window, but the filter's value is in avoiding drawdown clusters, not maximizing per-window wins. OVER-TIME PROJECTION: Over 3–6 months, a DISTRIBUTION-only filter would cut trade frequency substantially (likely 40–60% fewer signals), which may raise win rate but reduce total PnL if wins are large and losses Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

Zenodo (CERN European Organization for Nuclear Research)
Intelligence, Security, War Strategy
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.