Expectancy
A simplified per-trade expectancy can be expressed as: probability of winning × average win, minus probability of losing × average loss.
This explains why win rate alone cannot determine whether a strategy has positive historical expectancy.
Simple expectancy example
If 45% of trades win an average of 2R and 55% lose an average of 1R, simplified expectancy is (0.45 × 2R) − (0.55 × 1R) = +0.35R per trade before costs.
Win rate needs payoff context
A strategy can win frequently but lose more on its losing trades than it earns on winners. Another can win less often while maintaining larger average wins.
Win rate should therefore be interpreted together with average win, average loss and trading costs.
Drawdown
Maximum drawdown measures the largest peak-to-trough decline in the tested equity curve under the chosen methodology.
Drawdown affects capital requirements and the practical ability to continue following a strategy.
Sample size
A small number of trades creates substantial uncertainty. A high win rate from ten trades is much weaker evidence than a similar result across a large and diverse sample.
The independence and market diversity of observations also matter; hundreds of highly correlated trades may contain less information than the raw count suggests.
Risk-adjusted performance
Metrics that compare returns with variability or downside can add useful context, but every metric has assumptions and limitations.
No single ratio should replace inspection of the underlying return distribution and drawdowns.
Robustness
A robust strategy should not depend on one exact parameter value, one exceptional market period or unrealistic execution.
Sensitivity testing can examine whether small changes to parameters destroy the historical result.
Historical performance is not future certainty
Even a carefully tested strategy can degrade as market structure, competition, liquidity or volatility changes.
Ongoing evaluation is therefore part of systematic trading.
A strong win rate, profit factor or historical return can hide unacceptable drawdown, small sample size or overfitting.
Key takeaways
- Expectancy combines win probability with average win and average loss.
- Win rate alone is insufficient.
- Drawdown and risk matter alongside return.
- Sample size and market diversity affect confidence.
- Robustness and out-of-sample evidence matter before trusting historical results.
Sources & further reading
This lesson is educational material. Market structure, exchange rules, fees, margin requirements and derivatives mechanics can differ by venue and can change over time. Verify current rules with the venue you use.