Cross-Sectional Skewness

45 Pages Posted: 5 Dec 2017 Last revised: 7 Dec 2019

See all articles by Sangmin Oh

Sangmin Oh

University of Chicago - Booth School of Business

Jessica A. Wachter

University of Pennsylvania - Finance Department; National Bureau of Economic Research (NBER)

Date Written: December 6, 2019

Abstract

What distribution best characterizes the time series and cross section of individual stock returns? To answer this question, we estimate the degree of cross-sectional return skewness relative to a benchmark that nests many models considered in the literature. We find that cross-sectional skewness in monthly returns far exceeds what this benchmark model predicts. However, cross-sectional skewness in long-run returns in the data is substantially below what the model predicts. We show that fat-tailed idiosyncratic events appear to be necessary to explain skewness in the data.

Keywords: rare events, jumps, idiosyncratic volatility, power law

JEL Classification: G11, G12

Suggested Citation

Oh, Sangmin and Wachter, Jessica A., Cross-Sectional Skewness (December 6, 2019). Available at SSRN: https://ssrn.com/abstract=3079715 or http://dx.doi.org/10.2139/ssrn.3079715

Sangmin Oh (Contact Author)

University of Chicago - Booth School of Business ( email )

5807 S. Woodlawn Avenue
Chicago, IL 60637
United States

Jessica A. Wachter

University of Pennsylvania - Finance Department ( email )

The Wharton School
3620 Locust Walk
Philadelphia, PA 19104
United States
215-898-7634 (Phone)
215-898-6200 (Fax)

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Here is the Coronavirus
related research on SSRN

Paper statistics

Downloads
538
Abstract Views
2,500
rank
54,464
PlumX Metrics