Positive Expectancy, Win Rates, and Risk in Trading

Summary

The article explains why a high win rate alone does not ensure long-run profits. Traders may close winners too early and let losing positions grow, so the size of gains and losses matters alongside their probabilities. It also argues that trading systems tend to work under particular market conditions: range-based approaches can struggle in directional markets, and trend approaches can struggle in ranges. Losses from testing a system are presented as an expected cost, while stop losses are necessary but insufficient without a positive expected value.

Using a dice game, the author introduces expectancy as the probability-weighted average of outcomes. A hypothetical gold strategy then shows how a low win rate can still yield positive expectancy when average winners are large enough relative to average losses. The examples are illustrative calculations, not independently validated results; their assumptions about stops, market ranges, fills, and win rates may not hold in live trading. The article emphasizes discipline, preserving capital, and accepting that losing streaks and drawdowns can occur.

Key ideas

• Win rate alone does not determine profitability; average win and average loss also matter.
• A strategy needs positive expectancy, calculated from the probabilities and sizes of gains and losses.
• Trading systems have market conditions in which they work better and can lose when conditions change.
• Stop losses limit risk, but they cannot make a negative-expectancy strategy profitable.
• The numerical examples illustrate a framework and do not establish that the assumed strategy will work in practice.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.