The one-sentence definition
Expectancy is the average result per trade: how much you'd expect to make (or lose) on a typical trade, combining your win rate with the average size of your wins and losses.
How it's calculated
Expectancy = (win rate × average win) - (loss rate × average loss).
Multiply the chance of winning by the average winning amount, subtract the chance of losing multiplied by the average losing amount. A positive result means the strategy makes money on average per trade.
A worked example
Take a strategy that wins just 40% of the time. Its average win is $300; its average loss is $100.
Expectancy = (0.40 × $300) - (0.60 × $100) = $120 - $60 = $60 per trade.
Despite losing 60% of its trades, it makes $60 on average every time it trades, because the wins are three times the size of the losses. Now flip it: a strategy that wins 70% of the time but whose average loss ($300) dwarfs its average win ($100) has expectancy of (0.70 × $100) - (0.30 × $300) = $70 - $90 = -$20 per trade - a loser, despite the high win rate.
Why it matters for backtesting
Expectancy is the bridge between a backtest and what you'd actually earn. Multiply it by how many trades a strategy takes and you get a sense of its total edge. A tiny positive expectancy over thousands of trades can be excellent; a large one over five trades is just luck.
It also immunises you against the most seductive trap in trading: chasing win rate. The market doesn't pay you for being right often - it pays you for being right big and wrong small.
Common mistakes
Where expectancy gets misread:
- Chasing win rate instead. A 90% win rate with occasional catastrophic losses can still have negative expectancy.
- Computing it from too few trades. Expectancy is an average; it only means something across a decent sample.
- Ignoring costs. Fees and slippage come straight out of expectancy and can flip a marginal strategy negative.
- Assuming it's stable. Expectancy measured in one market regime can change in another - test across varied conditions.