Distribution of Trade Returns
9 min read
Examine how trade returns are distributed and why that shape tells you everything about your risk, volatility, and potential.
9 min read
Examine how trade returns are distributed and why that shape tells you everything about your risk, volatility, and potential.
Your trading edge isn’t a fixed number. It’s a distribution — and that shape tells you everything about your risk, volatility, and potential.
Most traders ask:
"What’s my win rate?" "What’s my average R?"
But those numbers are just summary stats.
To really understand your edge, you need to ask: "What does the full distribution of my trade outcomes look like?"
That distribution tells you:
Let’s break it down.
It’s a histogram of all your trade results (usually in R-multiples), grouped into bins.
Each bin shows how many trades ended with:
This gives you a visual fingerprint of your strategy.
| Trader A | Trader B |
|---|---|
| Avg R = +0.7R | Avg R = +0.7R |
| Tight cluster around +1R | Mostly losers, one +15R trade |
Same average. Completely different risk profiles.
The average hides the truth. The distribution reveals it.
A strategy with 70% win rate can still be dangerous if losses are 3× bigger than wins.
Let’s say your trade histogram looks like this:
| R-Multiple Bin | # of Trades |
|---|---|
| –2R or worse | 3 |
| –1.5 to –1R | 12 |
| –1 to –0.5R | 20 |
| –0.5 to 0R | 10 |
| 0 to +0.5R | 15 |
| +0.5 to +1.5R | 25 |
| +1.5R to +3R | 10 |
| +3R+ | 5 |
Observation:
This is a right-skewed, relatively stable distribution — ideal for compounding with confidence.
Plot a cumulative PnL line on top of your histogram.
You’ll see:
Drag the skewness slider to see how the shape of a return distribution changes. Positive skew creates a longer right tail (more big wins); negative skew creates a longer left tail (more big losses).
"You don’t trade an average — you trade a distribution."
If you want to survive long enough to let your edge play out:
A clean distribution is the blueprint for scaling, sizing, and improving.