The average result of a single trade in R units, which is the cleanest statement of whether an edge exists.
Expectancy per trade = (win rate x average win in R) - (loss rate x average loss in R). With a 42% win rate, average win plus 1.9R and average loss minus 1.0R: (0.42 x 1.9) - (0.58 x 1.0) = 0.798 - 0.58 = plus 0.218R per trade.
Interpret it in dollars to keep perspective. At 0.8% risk per trade on a $40,000 account, 1R is $320, so plus 0.218R is about $70 per trade before costs. Subtract the slippage-budget and the real figure might be plus $52. That is what the edge is worth, and it is usually far less than beginners assume.
Expectancy is an average, not a promise. A plus 0.2R edge produces long stretches of negative results, and the sample needed to distinguish it from zero is in the hundreds of trades - see sample-size-for-edge. It also says nothing about the rate at which you can harvest it, which is expectancy-per-unit-time.
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.The win rate needed to break even. How often a method must win just to stay level, for each reward-to-risk ratio. At 1:1 half the trades must win, at 1:2 a third, and at 1:3 a quarter, because each win covers more losses.
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