Money management

Expectancy in trading: your edge in numbers

6 min read · by the GetBacktest team

Expectancy is the average gain you can expect per trade over the long run. It's THE figure that decides: a positive-expectancy strategy wins over time; a negative one loses, however good “trading well” feels. It also debunks the high-win-rate myth.

The formula

Expectancy = (Win rate × Average win) − (Loss rate × Average loss). The result is an amount (or a multiple of R, your unit risk) expected per trade.

Example: 40% of trades winning +2R and 60% losing −1R → (0.40 × 2) − (0.60 × 1) = +0.20R per trade. Positive: the strategy wins long-term despite a sub-50% win rate.

Why win rate alone misleads

A 90% win rate looks gorgeous — but if the 10% of losses are huge, expectancy can be negative. Conversely, a 35% win-rate system can be very profitable if wins dwarf losses.

It's the win rate × payoff (win/loss ratio) interaction that counts, not either in isolation. Expectancy combines both into one verdict.

Express it in R, not currency

Thinking in “R” (multiples of risk per trade) makes expectancy independent of position size and comparable across strategies. +0.3R per trade is a solid edge; you then just need enough trades.

Our expectancy calculator (/en/outils/esperance) converts your statistics into expectancy per trade and projects the expected curve.

From expectancy to a plan

A positive expectancy proven by a large backtest is the foundation. The rest — position sizing, risk of ruin, discipline — is about harvesting that expectancy without being knocked out by variance.

Beware: expectancy computed on a small sample or overfit data is an illusion. Validate it out-of-sample (walk-forward) before believing it.

Don't believe it — prove it

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Frequently asked questions

What expectancy should I target?

Any positive AND stable expectancy is exploitable. Expressed in R, +0.2 to +0.3R per trade is already a good edge if it holds over a large sample and out-of-sample.

Can you win with a low win rate?

Yes. With a high win/loss ratio, a 35-40% win-rate strategy can have strongly positive expectancy. The payoff compensates.

How do I make my expectancy reliable?

Compute it over many trades, then check it survives walk-forward (out-of-sample) and Monte-Carlo. Expectancy that collapses out-of-sample = overfitting.