Higher Moments Matter! Cross-Sectional (Higher) Moments and the Predictability of Stock Returns


In this paper, we investigate the predictive power of signals imputed from the cross-section of stock returns – namely cross-sectional volatility, skewness and kurtosis – to forecast the time series. Adding to the existing literature, which documents cross-sectional volatility to forecast a decline in the equity premium with high in- and out-of-sample predictive power, we highlight the additional role of cross-sectional skewness and cross-sectional kurtosis. Applying a principal component approach, we show that cross-sectional higher moments add statistically and economically significant to the predictive quality of cross-sectional volatility by stabilizing its predictive performance and yielding a positive trend in in-sample and out-of-sample predictive quality for the equity premium. Additionally, we show that cross-sectional skewness and cross-sectional kurtosis span the predictive power of cross-sectional volatility for disaggregated returns with respect to size and value.

Review of Financial Economics, 39(4)
Sebastian Stöckl
Sebastian Stöckl
Assistant Professor in Financial Economics (tenured)

My research interests include Financial and Economic Uncertainty as well as Empirical Asset Pricing.