Trading Styles & Strategy Development · Intermediate · 4 min
Edge and expectancy
You can calculate the expectancy of a rule set in R from its win rate and average win and loss, and explain why a small sample cannot prove an edge.
Win rate is not enough
Ask traders about their strategy and many quote a win rate: "I win 70% of my trades." It sounds impressive, and it tells you almost nothing.
A rule set that wins four trades in ten can grow an account steadily. One that wins seven in ten can empty it. The number that decides is the average result per trade, and it needs both the win rate and the size of wins and losses.
Wins minus losses
Expectancy is the average result per trade, usually measured in R, the amount risked per trade:
- expectancy = win rate × average win − loss rate × average loss.
For a rule set that wins 40% of trades with an average win of 2R and loses 60% with an average loss of 1R:
0.4 × 2R − 0.6 × 1R = +0.2R. Risking 100 per trade, it would earn about 20 per trade on average, before costs.
Costs belong inside the calculation. Spread, commission and slippage are paid on every trade. If they average 0.05R, the expectancy drops to 0.15R. A rule set with a small positive expectancy before costs can easily turn negative after them.
A trading edge is a positive expectancy after costs that holds up over many trades and changing market conditions. One good month is not an edge. Neither is a backtest that has been tuned until it looks perfect, a topic of the next chapter.
Only visible over many trades
Thirty fictional trades with exactly this expectancy, 12 wins of 2R and 18 losses of 1R, risking 1% each:
The account grows from 10,000 to about 10,584, but the path is uneven. There are three losses in a row twice, and stretches where the balance goes nowhere. Someone looking at trades 6 to 8 alone would have called the rules broken.
The reverse is just as important. After only 20 trades, a rule set with no edge at all can show an impressive result by chance. Results scatter widely over small samples, so judging an edge needs a large number of trades, ideally hundreds, across different market phases.
Common mistakes
- Judging by win rate alone. A 70% win rate with large losses can lose money.
- Leaving out costs. Small edges often disappear after spreads and commissions.
- Calling a short winning run an edge. Luck dominates small samples.
- Abandoning rules during a normal losing run. Losing streaks are part of positive expectancy too.
The takeaway
Expectancy is the average result per trade: wins times average win minus losses times average loss. A positive number is an edge only if it lasts.
Check yourself
Quick quiz
4 questions. Instant feedback, nothing is saved.
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1Tap the line that shows the average result per trade.
Tap the chart.
0.4 × 2R − 0.6 × 1R = +0.2R. On average, each trade adds a fifth of the amount risked.
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2A rule set wins 55% of trades with an average win of 1R and loses 45% with an average loss of 1.5R. What is its expectancy?
0.55 × 1 − 0.45 × 1.5 = 0.55 − 0.675 = −0.125R. A high win rate can still lose money.
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3After 20 trades, a rule set shows +0.3R per trade. What does that prove?
Results scatter widely over small samples. Hundreds of trades, across different market conditions, say much more.
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4Why are costs part of expectancy?
A rule set with +0.05R before costs may be negative after them.
of 4 correct.