Analyst Forecast Skewness and Cross Section Stock Returns

In the paper, we show a significant economic linkage between analyst EPS forecast skewness and cross section stock returns. The effect on stock return of our skewness measure is quite different from that based on skewness calculated from options or high frequency data. Literature shows that, using such skewness as a signal, trading profit is generated mostly from over-valued stocks with high positive skewness, which is consistent with Barberis and Huang (2008)'s lottery arguments. However, we find that for our analyst forecast skewness, trading profit mainly comes from those stocks with negative skewness. Long-short strategy purchasing stocks with low forecast skewness and shorting those with high forecast skewness earns annualized abnormal returns 11% with sharpe ratio 0.64. Our study suggests that negative skewness stocks tend to be undervalued (risk-adjusted returns for negative skewness stocks are significantly positive), while stocks with high positive skewness have fair prices (risk-adjusted returns for positive skewness stocks are not significant). Our empirical results are closely related with investors learning behavior and consistent with Veronesi (1999) theory. In the model, Veronesi shows that when investors cannot observe cash flow growth rate, they tend to overreact to bad news, push current stock price down, such behavior will lead to higher future stock returns. Our results also hold when using robust skewness defined as the gap between analyst EPS forecast mean and median