Trading Expectancy Calculator
Calculate the expected value of your trading strategy. A positive expectancy means your system is profitable over time — regardless of individual trade outcomes.
Strategy Parameters
How Trading Expectancy Is Calculated
(Win Rate × Avg Win) − (Loss Rate × Avg Loss) − Fee Avg Loss / (Avg Win + Avg Loss) (Win Rate × Avg Win) / (Loss Rate × Avg Loss) Expectancy is the average amount you can expect to gain or lose per trade, expressed as a percentage of your position size. A positive expectancy (e.g. +0.8%) means your system has a statistical edge. A negative expectancy means you will lose money over time regardless of how well you manage individual trades.
Profit Factor above 1.0 indicates a profitable system. Professional traders typically target a profit factor of 1.5–2.5. Below 1.0 means the system loses money in aggregate.
Break-even Win Rate is the minimum win rate needed for your strategy to be profitable given your average win and loss sizes. If your actual win rate is above this threshold, you have a positive edge.
How to Interpret Your Results
| Expectancy per Trade | Profit Factor | Interpretation |
|---|---|---|
| < 0% | < 1.0 | Negative edge — system loses money over time |
| 0% to +0.3% | 1.0 – 1.3 | Marginal edge — fees may erase profits in live trading |
| +0.3% to +1.0% | 1.3 – 1.8 | Solid edge — viable for live trading with discipline |
| > +1.0% | > 1.8 | Strong edge — verify with out-of-sample data |
These thresholds are general guidelines. Results depend heavily on your specific market, timeframe, and position sizing. Always verify with out-of-sample backtests before live trading.
Frequently Asked Questions
What is a good trading expectancy?
A positive expectancy means your strategy is profitable over time. As a benchmark: expectancy above +0.5R (where R = your average risk per trade) is considered solid. Elite systematic traders often target +0.8R to +1.5R. Anything positive is better than zero, but you also need enough trade frequency for the edge to manifest statistically.
What win rate do I need to be profitable?
It depends entirely on your reward-to-risk ratio. With a 2:1 R/R, you only need a 34% win rate to break even. With 1:1 R/R, you need 50%. The break-even win rate formula is: 1 / (1 + R/R ratio). Many professional traders have win rates below 50% but remain profitable because their winners are much larger than their losers.
How does the fee drag affect expectancy?
Trading fees compound negatively. A 0.1% fee per trade (entry + exit = 0.2% round-trip) over 100 trades costs 20% of your position size in fees alone. This calculator accounts for fees by subtracting them from both winning and losing trades, giving you a realistic net expectancy figure.
What is the difference between expectancy and win rate?
Win rate tells you how often you win. Expectancy tells you how much you expect to make per trade on average. A 70% win rate strategy with tiny wins and large losses can have negative expectancy and lose money long-term. Always evaluate both metrics together.
How many trades do I need to validate my edge?
Statistical significance typically requires 100–300 trades minimum. With fewer trades, variance dominates and results are unreliable. Use the "Projected over N trades" output to see how your edge compounds — but remember that past backtest performance doesn't guarantee future results in live trading.
Calculator Limitations
- Assumes consistent R/R: This calculator uses fixed average win and loss percentages. In real trading, individual trade outcomes vary significantly.
- No position sizing: This tool calculates expectancy as a percentage of risk, not in dollar terms. Use the Risk/Reward Calculator for dollar-based position sizing.
- Fees are simplified: Only a single flat fee rate is modelled. Actual costs may include spread, funding rates, and variable maker/taker fees.
- No drawdown modelling: Expectancy doesn't account for the sequence of wins and losses. Use the Risk of Ruin Calculator to model worst-case drawdown scenarios.
- Past performance: Backtest-derived inputs (win rate, avg win/loss) may not reflect future live trading performance due to overfitting, market regime changes, and execution differences.