Skewness (Returns)
Skewness measures the asymmetry of a return distribution around its mean, with negative skewness indicating a distribution with a longer left tail — more exposure to large losses — and positive skewness indicating a longer right tail with more exposure to large gains.
Skewness is the third statistical moment of a distribution. A perfectly symmetric distribution, like the theoretical normal distribution, has skewness of zero. Most equity return series exhibit slightly negative skewness — the left tail (large losses) is longer and heavier than the right tail — a property that reflects the tendency of markets to fall faster and more sharply than they rise.
Negative skewness is particularly relevant for strategy evaluation. A strategy that earns small, steady profits most of the time but occasionally suffers a massive loss will have negative skewness even if its average return is positive and its volatility appears modest. Selling options (especially naked puts or short straddles), credit spread strategies, and carry trades all tend to produce negatively skewed return profiles. The strategy looks appealing on a Sharpe ratio basis until the tail event arrives.
Positive skewness is the more desirable characteristic for long-term compounding. A strategy with positive skewness has its worst outcomes clustering toward the center while occasional large gains pull the right tail out. Buying options (long calls or puts), trend-following strategies, and venture-style equity portfolios tend to exhibit positive skew — many small losses offset by infrequent large winners.
The relationship between skewness and compound returns is important. Due to the mathematics of compounding, negative skew is especially harmful because large drawdowns require proportionally larger recoveries to break even. A 50% loss requires a 100% gain to recover. Strategies with negative skew are therefore more likely to suffer the kind of drawdowns that permanently impair compounded wealth.
Portfolio construction should account for skewness explicitly. Combining assets with positive skewness, even if individually volatile, can produce better long-run outcomes than combining assets with negative skewness, even if volatility looks lower. Risk-adjusted metrics that account for skewness, such as the Sortino ratio or the Omega ratio, provide a richer picture than the Sharpe ratio alone.