MODEL ADOPTION #1144: REJECT — LEDGER BENCH: Apply filter: Min confirmations >= 5 — improves win rate from 31.7% to 33.3% — E8 Intelligence Research

Andrew Stewart Caldin

doi:10.5281/zenodo.21989536

August 18, 2026Open Access

MODEL ADOPTION #1144: REJECT — LEDGER BENCH: Apply filter: Min confirmations >= 5 — improves win rate from 31.7% to 33.3% — E8 Intelligence Research

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Key Points

To assess whether requiring a minimum threshold of five trade confirmations enhances net profitability and performance within algorithmic trading systems.
Analyzed historical backtesting data comprising 1,329 trade instances (n=1329) using a minimum confirmation filter of at least 5 signals.
Evaluated projected impacts on win rates, trade frequency reductions, and overall profit-and-loss (PnL) against existing live model baselines.
The filter increased backtest win rate by 1.6 percentage points from 31.7% to 33.3%, which was evaluated as statistically marginal noise.
Trade volume was projected to decline by 10% to 20%, resulting in flat or negative net PnL due to the exclusion of high-reward trades during strong directional trends.

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Implication

Backtest analysis demonstrates marginal win-rate gains from confirmation filters in algorithmic trading, suggesting negligible net profitability improvements due to missed high-reward trades.

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Andrew Stewart Caldin (2026) studied this question.

synapsesocial.com/papers/6a86b5da8a91293e6a1cd585 https://doi.org/10.5281/zenodo.21989536

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MODEL ADOPTION #1144: REJECT — LEDGER BENCH: Apply filter: Min confirmations >= 5 — improves win rate from 31.7% to 33.3% — E8 Intelligence Research

Key Points

No abstract yet

Implication

Discussion

Cite This Study

MODEL ADOPTION #1144: REJECT — LEDGER BENCH: Apply filter: Min confirmations >= 5 — improves win rate from 31.7% to 33.3% — E8 Intelligence Research

Key Points

No abstract yet

Implication

Discussion

Cite This Study

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