Keywords

idiosyncratic skewness, expected returns, cross-sectional regression

Abstract

We test the prediction of recent theories that stocks with high idiosyncratic skewness should have low expected returns. Because lagged skewness alone does not adequately forecast skewness, we estimate a cross-sectional model of expected skewness that uses additional predictive variables. Consistent with recent theories, we find that expected idiosyncratic skewness and returns are negatively correlated. Specifically, the Fama-French alpha of a low-expected-skewness quintile exceeds the alpha of a high-expected-skewness quintile by 1.00% per month. Furthermore, the coefficients on expected skewness in Fama-MacBeth cross-sectional regressions are negative and significant. In addition, we find that expected skewness helps explain the phenomenon that stocks with high idiosyncratic volatility have low expected returns. (JEL D03, G11, G12)

Original Publication Citation

Expected Idiosyncratic Skewness (with Todd Mitton and Keith Vorkink) 2010, Review of Financial Studies, 23, 169-202.

Document Type

Peer-Reviewed Article

Publication Date

2009

Publisher

Review of Financial Studies

Language

English

College

Marriott School of Business

Department

Finance

University Standing at Time of Publication

Associate Professor

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