Entry filters are often judged by running an EA with and without enforcement, then comparing net profit, drawdown, and trade activity. That A/B test captures operational path changes from occupancy, compounding, sizing, and constraints, but it does not isolate whether accepted trades are an unusually favorable subset of base trades.
FilterEdgeAnalyzer.mqh separates these claims. A diagnostic run executes all base entries while tagging each position as accepted or rejected at entry. Completed positions are reconstructed from deals, net profit is aggregated per position, and accepted vs rejected mean outcomes are compared against fixed-count placebo selections that preserve the same acceptance count.
Three null models are supported: full mask permutation, equal-block permutation, and circular shifts. A finite-sample–corrected upper-tail p-value is report...
👉 Read | Freelance | @mql5dev
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1August 26, 2026 14K 6
