Do outliers matter? The predictive ability of average skewness on market returns using robust skewness measures

Xu Chong Bo, Jianlei Han, Yin Liao, Jing Shi, Wu Yan

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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.
Original languageEnglish
Number of pages30
JournalAccounting and Finance
DOIs
Publication statusE-pub ahead of print - 10 Nov 2020

Keywords

  • Average skewness
  • Market returns
  • Outliers
  • Predictive ability
  • Robust measures

Fingerprint Dive into the research topics of 'Do outliers matter? The predictive ability of average skewness on market returns using robust skewness measures'. Together they form a unique fingerprint.

Cite this