Trading Expectancy
A framework for combining win rate, average win and average loss to evaluate a trading process over many trades.
Expectancy asks what the process earns or loses on average
Trading expectancy combines how often trades win with the average size of wins and losses. It is a framework for evaluating a series of trades, not predicting the outcome of the next trade.
(Win rate × average win) − (Loss rate × average loss)
Example
If a hypothetical process wins 40% of the time, averages $200 on winners and loses $100 on losing trades, its arithmetic expectancy is $20 per trade before fees and execution effects: (0.40 × $200) − (0.60 × $100).
Why a high win rate can still lose
A strategy can win frequently but give back more on its occasional losses than it earns on winners. Conversely, a lower-win-rate approach can have positive expectancy if winners are sufficiently larger than losses.
Use meaningful samples
Expectancy estimates are unstable with very small samples and can change as market conditions change. Track actual results after costs, separate strategies where possible, and avoid treating historical expectancy as a guarantee.