This lesson is the numerical heart of trading. Master it and you can evaluate any strategy honestly; skip it and no chart pattern will save you. The companion reference is Risk Management.
Everything in R
Define R as the amount you risk per trade — entry to stop, times size. Measure every outcome in R: a stop-out is −1R, a double is +2R. This makes results comparable across account sizes and assets.
Position sizing
Risk a fixed, small fraction of your account per trade (commonly 1%). Set the stop first, then size to fit the risk.
Expectancy
Expectancy is the average R you earn per trade. It is the number that decides profitability.
Worked example:
| Metric | Value |
|---|---|
| Win rate | 40% |
| Average win | +2.5R |
| Average loss | −1R |
| Expectancy | (0.40 × 2.5) − (0.60 × 1) = +0.40R |
You lose 60% of the time and still make 0.40R per trade on average — because winners are larger than losers. Win rate alone tells you nothing; payoff matters just as much.
Why the 1% rule survives streaks
Even a positive-expectancy system has losing streaks. Small per-trade risk keeps any streak survivable, so you are still around when the edge plays out.
Expectancy is an average over many trades. Any single trade is mostly luck; the edge only shows up across a large sample. Protect your capital so you get to take that many trades.
Sample size and ruin
Risk too much per trade and a normal losing streak can wipe you out before your edge ever appears — that is “risk of ruin.” The cure is small position size, not a better win rate.
Next: the discipline to execute all of this — Mastering Trading Psychology.