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.

[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.]