The number of trades needed before a measured edge is distinguishable from luck, which is far larger than most traders assume.
A workable rule: n ≈ (2 x standard deviation of R / expectancy in R)^2 for a result whose interval clears zero. Small edges with wide result distributions need enormous samples; large edges with tight distributions need few.
Concrete numbers. Expectancy plus 0.3R with 1.5R standard deviation needs about 100 trades. Expectancy plus 0.1R with the same spread needs about 900. Expectancy plus 0.3R in an outlier-driven system with 3R standard deviation needs about 400. Anyone claiming a proven edge from 25 trades is describing a coin-flipping result, regardless of how good the trades looked.
Two practical consequences. Low-frequency strategies are nearly unverifiable within a career, so they must be justified by mechanism rather than by statistics. And every parameter you tune consumes evidence - see sharpe-inflation - so tested variants must be counted, not forgotten.
Original diagrams for the ideas on this page. Illustrative, not real market data.
Expectancy: the average trade. Forty trades sorted by outcome: 24 small losses and 16 larger wins. Weighting each side by how often it happens gives the average result per trade, marked here by the dashed line at +$120.
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