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Assessing skewness in financial markets.

  • Published In: Statistica Neerlandica, 2023, v. 77, n. 1. P. 48 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Campisi, Giovanni; La Rocca, Luca; Muzzioli, Silvia 3 of 3

Abstract

It is a matter of common observation that investors value substantial gains but are averse to heavy losses. Obvious as it may sound, this translates into an interesting preference for right‐skewed return distributions, whose right tails are heavier than their left tails. Skewness is thus not only a way to describe the shape of a distribution, but also a tool for risk measurement. We review the statistical literature on skewness and provide a comprehensive framework for its assessment. Then, we present a new measure of skewness, based on the decomposition of variance in its upward and downward components. We argue that this measure fills a gap in the literature and show in a simulation study that it strikes a good balance between robustness and sensitivity. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Statistica Neerlandica. 2023/02, Vol. 77, Issue 1, p48
  • Document Type:Article
  • Subject Area:Business and Management
  • Publication Date:2023
  • ISSN:0039-0402
  • DOI:10.1111/stan.12273
  • Accession Number:160530072
  • Copyright Statement:Copyright of Statistica Neerlandica is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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