• Media type: E-Book
  • Title: Cross-Sectional Skewness
  • Contributor: Oh, Sangmin [Author]; Wachter, Jessica A. [Other]
  • Published: [S.l.]: SSRN, [2019]
  • Extent: 1 Online-Ressource (45 p)
  • Language: English
  • DOI: 10.2139/ssrn.3079715
  • Identifier:
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments December 6, 2019 erstellt
  • Description: What distribution best characterizes the time series and cross section of individual stock returns? To answer this question, we estimate the degree of cross-sectional return skewness relative to a benchmark that nests many models considered in the literature. We find that cross-sectional skewness in monthly returns far exceeds what this benchmark model predicts. However, cross-sectional skewness in long-run returns in the data is substantially below what the model predicts. We show that fat-tailed idiosyncratic events appear to be necessary to explain skewness in the data
  • Access State: Open Access