Skewness

Skewness measures the asymmetry of a return distribution. Positive skew means more frequent small losses balanced by occasional large gains; negative skew means frequent small gains punctuated by rare but severe losses.

Interpretation: Skewness = 0 (normal distribution), > 0 (right-tailed, fat upside), < 0 (left-tailed, fat downside). Most equity indices show mild negative skew - crashes are sharper than rallies.

Example: Selling out-of-the-money puts produces negative skew - you collect small premiums month after month, then a market crash wipes out years of gains. Trend-following CTAs typically show positive skew - many small losses, occasional huge wins.

When to use: Evaluating hedge-fund or PMS strategies whose monthly returns hide tail risk, sizing positions in options-heavy portfolios, and stress-testing the assumption of normality embedded in Sharpe Ratio and VaR calculations.

SEBI caveat: Skewness is rarely disclosed in retail factsheets. If a scheme touts a high Sharpe Ratio but its strategy is fundamentally short-volatility (e.g., credit-risk funds, arbitrage), expect significant negative skew - past smooth performance does not mean future smoothness.

Related: Kurtosis, Standard Deviation, Sharpe Ratio, Value at Risk.