Premium
Do outliers matter? The predictive ability of average skewness on market returns using robust skewness measures
Author(s) -
Bo Xu Chong,
Han Jianlei,
Liao Yin,
Shi Jing,
Yan Wu
Publication year - 2021
Publication title -
accounting and finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.645
H-Index - 49
eISSN - 1467-629X
pISSN - 0810-5391
DOI - 10.1111/acfi.12723
Subject(s) - skewness , outlier , econometrics , quantile , predictive power , economics , asymmetry , statistics , mathematics , philosophy , physics , epistemology , quantum mechanics
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.