Trading expectancy estimates the average result per trade across a recorded sample. It is useful because it combines how often trades win with the average size of wins and losses. It does not predict the outcome of the next trade.
The expectancy formula
Expectancy = (win rate × average win) − (loss rate × average loss). Use average loss as a positive magnitude in the subtraction. The output uses the same unit as your win and loss values: dollars, percentage points, or units of risk.
- Win rate = winning trades ÷ closed trades
- Loss rate = losing trades ÷ closed trades
- Average win = total winning value ÷ winning trades
- Average loss = absolute total losing value ÷ losing trades
A simple example
Suppose a sample contains 40 closed trades: 18 winners and 22 losers. The win rate is 45% and the loss rate is 55%. Average win is $180 and average loss is $100.
Expectancy = (0.45 × $180) − (0.55 × $100) = $81 − $55 = $26 per trade. That describes this historical sample before any costs not already included.
Calculate net expectancy
For a more realistic view, calculate each trade after applicable commissions, exchange charges, and other transaction costs before deriving the averages. Subtracting an average fee later can be a rough shortcut, but trade-by-trade net results are clearer when costs vary.
Sample size and stability
A positive expectancy based on a few trades can be dominated by chance or one outlier. There is no universal sample size that guarantees reliability. Compare rolling windows, inspect the range of outcomes, and note whether the strategy or market conditions changed during the sample.
Common expectancy mistakes
Do not mix gross winners with net losers, combine unrelated setups without checking them separately, ignore breakeven-trade treatment, or assume the historical average will persist. Expectancy is a review tool, not a forecast.
THE TAKEAWAY