In short
- Expectancy = hit rate × average win − (1 − hit rate) × average loss.
- Count in R (multiples of risk) to compare markets and strategies.
- After 20 trades the uncertainty around the hit rate is huge — judge by hundreds.
Hit rate is tempting but it does not pay the bills
"90% winning signals" sounds great until the 10% of losses take more than the 90% of wins. What matters is not how often you are right, but how much you make per trade on average.
The formula
Expectancy (in R) = hit rate × average win in R − (1 − hit rate) × average loss in R.
Examples:
- 40% hit rate, 2 R win, 1 R loss: 0.4 × 2 − 0.6 × 1 = +0.2 R per trade.
- 70% hit rate, 0.3 R win, 1 R loss: 0.7 × 0.3 − 0.3 × 1 = −0.09 R per trade.
The first strategy loses more often and makes money. The second wins more often and loses money. R is the result divided by the risk (the distance to the stop-loss) — it lets you compare gold, indices and forex with one measure.
How many trades to judge
With 20 trades and a 60% hit rate, the true hit rate could be roughly between 39% and 78% (95% Wilson confidence interval). Only hundreds of trades let you tell skill from luck. That is why in the lab we compare every strategy with random entries.
Costs flip the sign
In our research many strategies had a positive expectancy before costs (for example +0.3 bp per trade) and a negative one after broker costs (about 1.1 bp). In short-term trading the cost is often the biggest number in the whole calculation.
Questions
What is R?
A trade’s result divided by the amount at risk. A loss at the full stop is −1 R, a win twice the risk is +2 R.
Is a high hit rate bad?
No — but without the average win and loss it says nothing. Always ask for expectancy after costs.