Performance Tracking
Expectancy
The average amount you expect to make per trade — the single most important number for confirming a strategy has a genuine, statistically sound edge in the market.
Target range: 0.3+ per trade
The Fundamentals
What Is Expectancy?
The Formula
E = (W% × Avg Win) − (L% × Avg Loss)
W% = win rate (percentage of winning trades). Avg Win = average profit per winning trade. L% = loss rate. Avg Loss = average loss per losing trade (positive number).
Example: Win rate 55%, avg win $200, avg loss $150 → Expectancy = (0.55 × $200) − (0.45 × $150) = $110 − $67.50 = $42.50 per trade
Why It Validates Your Edge
Expectancy is the answer to the most fundamental question in trading: "Does this strategy actually make money over many repetitions?" Win rate and average win in isolation are misleading — Expectancy synthesizes them into one definitive number.
"A casino has an edge because its Expectancy per game is positive. Your strategy needs the same."
If Expectancy is positive, the strategy has a mathematical edge — it will make money given enough trades. If negative, no amount of "good trading instincts" can save it. This is why professional traders always calculate Expectancy before committing capital.
Benchmarks
What Is a Good Expectancy?
Expectancy is often expressed as a percentage of the average trade risk, making it comparable across different position sizes.
< 0
Negative Edge
The strategy loses money on average per trade. No amount of capital will save a negative-expectancy system over time.
0 – 0.3%
Marginal
Positive but easily erased by transaction costs or slippage. Optimize further before live deployment.
0.3% – 1%
Solid Edge
Good expectancy that survives realistic trading costs. Strategies in this range have a proven, repeatable edge.
1%+
Exceptional
High per-trade expectancy. Very strong edge — verify with out-of-sample testing to ensure results hold beyond the backtest period.
Deep Dive
Mastering Expectancy Analysis
High Win Rate Trap
A system with 75% win rate can have negative expectancy if average losses are 4× average wins. Many retail traders fall into the high-win-rate trap — holding losing trades and cutting winners early. Expectancy reveals this pattern immediately. You cannot fake a positive expectancy.
Compounding with Expectancy
Expectancy scales beautifully with trade frequency. A strategy with $50 expectancy that takes 5 trades per day generates $250/day in expected value. This is how automated trading systems compound small edges into significant returns — frequency multiplies the mathematical advantage.
Fee-Adjusted Expectancy
Always evaluate Expectancy after fees and estimated slippage. A $42 gross expectancy with $25 in round-trip fees becomes only $17 net — still positive but far less impressive. cryptorobot.ai automatically includes configurable fee rates in all Expectancy calculations.
On Our Platform
How cryptorobot.ai Tracks Expectancy
cryptorobot.ai computes fee-adjusted Expectancy on every backtest, automatically incorporating your exchange's trading fee rate. You see both gross and net expectancy side by side in the analytics panel.
Our AI research agent uses Expectancy as a hard gate: any strategy parameter combination that produces negative net Expectancy is immediately discarded during hyperoptimization. This ensures no configuration reaches deployment without a proven mathematical edge.
Live trading also tracks rolling Expectancy across recent trades — so if market conditions shift and your strategy's edge degrades, you'll see the Expectancy trend declining before it becomes a serious problem, giving you time to act proactively.
0.3%+
Our Target Per Trade
Fee-Adj
Includes Exchange Fees
Gated
Hard Requirement to Deploy
Rolling
Tracked in Live Trading