What trading expectancy means
Trading expectancy is the average amount a set of trading rules has gained or lost per trade over a series of past trades. It combines how often you win with how much you win or lose each time.
Expectancy describes the past results of your rules. It does not tell you what the next trade will do. Even a positive figure can come with long losing runs, and leveraged forex and CFD trading can lose money fast.
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The expectancy formula in trading
The standard expectancy formula is:
Expectancy = win% × average win − loss% × average loss
- Win% is the share of your trades that closed in profit.
- Loss% is the share that closed at a loss.
- Average win and average loss are the typical sizes of those outcomes. Both are written as positive amounts, and the minus sign in the formula handles the loss.
Why use R units
R is the amount you planned to risk on a trade, the distance from entry to stop loss multiplied by position size. You can express any result as a multiple of R. For example, a trade that made twice the planned risk is "two R", and a trade that hit the stop is a loss of a full R.
Measuring in R lets you compare trades of different sizes, instruments and account balances. An expectancy in R tells you how much of your planned risk you gained or lost per trade on average. To turn it into money, multiply it by the amount you risk per trade. See Risk per trade and Position sizing.
How to calculate expectancy from your trades
- Take closed trades from your trading journal that all follow the same rules.
- For each trade, divide the profit or loss by the planned risk to get the result in R.
- Count the winners and the losers. Divide each count by the total number of trades to get win% and loss%. Decide in advance how you treat break-even trades, and apply that choice every time.
- Average the R results of the winners, and separately average the R results of the losers.
- Put the four figures into the formula.
A quicker method gives the same answer: add up all R results and divide by the number of trades.
Win rate and reward size work together. A low win rate can still produce a positive expectancy if the average win is large compared with the average loss. A high win rate can still produce a negative expectancy if the losses are much larger. The Break-even win rate and Risk-reward ratio guides cover this in more detail.
Include all trading costs
Calculate expectancy on net results, after spread, commission and overnight swap. These costs reduce every trade. They have the most effect on strategies with small targets and frequent trades. A strategy that looks positive before costs can be negative after them. See Swap fees for how overnight charges work in general.
Why sample size matters
A short series of trades is heavily influenced by luck. A handful of large winners can make poor rules look strong, and an early losing run can make sound rules look broken.
Keep these points in mind:
- More trades give a more reliable average. The figure from a small sample can change a lot as new trades come in.
- Do not mix different setups. Rules for different setups, instruments or market conditions have different expectancies. Mixing them hides which part actually works.
- Markets change. Past expectancy can fade when volatility, spreads or market behaviour shift. Recalculate regularly.
- Back-tests are optimistic. Results tuned on historical data usually look better than live trading, where slippage and your own mistakes also affect the results.
Test the spread of outcomes
The simulator below runs a Monte Carlo model of a fixed-risk strategy. A Monte Carlo model replays many random orderings of trades based on the win rate and R values you enter. It shows how far results can spread and how deep drawdowns can get. It is a model, not a forecast.
500 random runs of the same rules. This is a model of arithmetic, not a forecast: real markets have costs, slippage and streaks the model ignores.
Try a positive expectancy and look at the worst paths. Many traders are surprised by how long the losing streaks and drawdowns can be even when the average is positive. For more on drawdowns, see Drawdown and Risk of ruin.
Expectancy and position size
Expectancy tells you whether a set of rules has been positive per unit of risk. Position size decides how hard each losing run hits your balance. Risking too much per trade can wipe out an account during a normal losing streak, even when the expectancy is positive.
Methods such as the Kelly criterion and Fixed fractional vs fixed lot sizing try to link size to your results. All of them depend on an expectancy estimate that may be wrong. Build these limits into your personal risk plan.
Frequent questions
What is a good trading expectancy?
No figure is "good" on its own. A positive net expectancy measured over a large, consistent sample is the minimum to look for. Even then it does not guarantee future results.
Can I calculate expectancy in money instead of R?
Yes. However, if your position size changed over time, results in money mix size changes with strategy quality. R units keep them separate.
How many trades do I need?
More is better. Use the simulator to see how widely results vary for your inputs. If small changes in the sample swing the expectancy from positive to negative, the sample is too small.
Does a positive expectancy mean I will make money?
No. It describes past trades. Costs, changing markets, mistakes and losing runs can all lead to losses. Leveraged trading can lose money quickly.
Should I test on a demo account first?
A demo account lets you log trades in R without risking money. Keep in mind that demo fills and your emotions differ from live trading.