Skewness is a statistical measure of the asymmetry of a probability distribution around its mean. A positive skew (right skew) indicates that the distribution has a longer right tail — there are occasional large positive values that pull the mean above the median. A negative skew (left skew) indicates a longer left tail — occasional large negative values pull the mean below the median. In investment returns, skewness is a critical dimension of risk that standard deviation (volatility) does not capture.

Negative Skew in Market Returns

Most equity market return distributions exhibit negative skewness: moderate positive returns are common, and occasional large negative returns (crashes, bear markets) create the fat left tail. This negative skew means that the “average” outcome overstates the typical investor’s experience — most periods are better than average, but the occasional large losses pull the average down. Investors who are surprised by market crashes are often surprised because they were anchored to the average rather than fully accounting for the left tail.

Positive Skew in Asymmetric Strategies

Trend-following strategies deliberately target positive skewness: they produce many small losses (false trend signals quickly stopped out) and occasional large gains (major trends captured from beginning to end). This positive skew — large, infrequent gains; small, frequent losses — is the inverse of the typical equity return distribution and is one of the most valuable properties a portfolio component can have, because it provides performance precisely during the crisis periods when equity strategies produce their worst negative-skew outcomes.

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