Skewness & Kurtosis
Trading Intelligence
9 min read
skewnesskurtosis
Go beyond mean and variance to examine the asymmetry and tail thickness of return distributions and why they matter for risk.
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9 min read
Go beyond mean and variance to examine the asymmetry and tail thickness of return distributions and why they matter for risk.
Not all trading results follow a normal distribution — and ignoring this fact can ruin even statistically sound strategies.
You’ve built a system.
But then:
What happened?
It’s not randomness. It’s skewness and kurtosis — critical statistical traits of your trade distribution that tell you how your edge plays out over time.
Skewness measures the asymmetry of your trade outcome distribution.
In trading terms:
Most retail systems are negatively skewed — they feel good (frequent wins), but blow up occasionally.
| Type | Skew | Example |
|---|---|---|
| Scalping | Negative | 80% win rate, but one –5R loss ruins a week |
| Trend-following | Positive | 30% win rate, but occasional +6R or +10R wins |
| Martingale | Very Negative | Many small wins, occasional total wipeout |
Kurtosis measures the fatness of the tails — how common extreme outcomes are.
In trading:
Strategies with high kurtosis carry tail risk — rare, extreme outcomes that matter more than they should.
Most trading books assume a bell curve (Gaussian distribution) — where:
But in reality:
If you only evaluate based on short-term win rate, you will misjudge the system.
Don’t use the same risk model across all strategies — match sizing to distribution shape, not just EV.
Sort trades by R
Plot a histogram
Look for:
Frequent small gains or losses
Rare outliers
Long “tails” of performance
Know what game you’re playing — and whether it fits your psychology and capital constraints.
Your edge doesn’t just live in the average. It lives in the shape of your results — and how you handle the extremes.
Ignoring skew and kurtosis is like flying without knowing your plane's stall speed.
Understand the profile of your trades. Respect the tails. Size and evaluate your system based on distribution, not hope.