Do outliers matter? The predictive ability of average skewness on market returns using robust skewness measures. (10th November 2020)

• Record Type: Journal Article
• Authors: Bo, Xu Chong; Han, Jianlei; Liao, Yin; Shi, Jing; Yan, Wu
• Is Part Of: Accounting and finance. Volume 61:Number 3(2021)
• Page Start: 3977
• Page End: 4006
• Publication Date: 2020-11-10
• Subjects: Average skewness -- Market returns -- Outliers -- Predictive ability -- Robust measures; Accounting -- Periodicals; Finance -- Periodicals; 657.05
• DOI: 10.1111/acfi.12723
• Languages: English
• ISSNs: 0810-5391

Abstract

Abstract: We used robust skewness measures to revisit a recent theory that the average asymmetry (measured by the average monthly skewness values across firms) can negatively predict future market returns. Skewness measures employed in previous studies are moment‐based which are normally sensitive to outliers of returns. We thus consider a quantile‐based robust skewness measure and find that the predictive power of the average skewness to market returns no longer exists. Instead, we find a negative relation between the average expected (or ex‐ante) skewness and market returns, suggesting that investors' average expectation on skewness can negatively predict market returns.