How large a real effect is relative to the random variation around it; in financial returns it is usually tiny.
Daily equity index returns have a standard deviation around 1%. A very good long-run edge might be 0.03% a day. That is a signal-to-noise ratio of about 1 to 33 on a single day, which is why a month of results tells you almost nothing.
The consequence is sample size. To detect a 0.03% daily edge with any confidence you need thousands of observations, and markets only produce about 252 trading days a year. This is the single most underappreciated fact in strategy research.
It also explains why plots deceive. An equity curve is a cumulative sum, and cumulative sums of noise look like trends. Always look at the distribution of individual returns alongside the curve.
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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