Skewness

A perfectly symmetrical distribution, such as the normal distribution, has zero skewness. Its left and right sides mirror each other.

A distribution with positive skewness has a long tail on the right. Most outcomes are modest, but there is a small chance of very large positive outcomes. For example, start-up investments are positively skewed: most fail or return little, but a few return many times the money invested. Lottery tickets are also strongly positively skewed.

A distribution with negative skewness has a long tail on the left. Most outcomes are modestly positive, but there is a small chance of large losses. Strategies such as selling options can be negatively skewed, producing steady small gains for long periods but occasionally suffering large losses.

Skewness matters because averages and standard deviations alone do not capture it. Two investments with the same average return and volatility can have very different risk profiles if one is negatively skewed. Many investors are wary of negative skewness, since it means rare but painful losses. Stock market returns have often shown slight negative skewness, with sharp falls more common than equally sharp rises.