Cross-Sectional Skewness

67 Pages Posted: 5 Dec 2017 Last revised: 14 Jun 2021

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
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Philadelphia, PA 19104
United States
215-898-7634 (Phone)
215-898-6200 (Fax)

National Bureau of Economic Research (NBER)

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Cambridge, MA 02138
United States

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