HEC Research Papers Series,
HEC Paris

Abstract: We provide a new methodology to empirically investigate the respective roles of systematic and idiosyncratic skewness in explaining expected stock returns. Forming a risk factor that captures systematic skewness risk and forming idiosyncratic skewness sorted portfolios only require the ordering of stocks with respect to each skewness measure. Accordingly, we use a large number of predictors to forecast the cross-sectional ranks of systematic and idiosyncratic skewness which are considerably easier to predict than their actual values. Compared to other measures of ex ante systematic skewness, our forecasts create a significant spread in ex post systematic skewness. A predicted systematic skewness risk factor carries a significant risk premium that ranges from 7% to 12% per year and is robust to the inclusion of downside beta, size, value, momentum, profitability, and investment factors. In contrast to systematic skewness, the role of idiosyncratic skewness in pricing stocks is less robust. Finally, we document how the determinants of systematic skewness differ from those of idiosyncratic skewness.

Keywords: Systematic skewness; coskewness; idiosyncratic skewness; large panel regression; forecasting

JEL-codes: G12

47 pages, First version: March 15, 2018. Revised: May 29, 2019.

Full text files

papers.cfm?abstract_id=3141416  Full text

Download statistics

• HEC Paris
• Ordering Working Papers
• Home page for this series

Questions (including download problems) about the papers in this series should be directed to Antoine Haldemann ()
Report other problems with accessing this service to Sune Karlsson ().

RePEc:ebg:heccah:1256This page generated on 2024-09-13 22:19:53.