Estimating beta

Haim Shalit, Shlomo Yitzhaki

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

This paper presents evidence that Ordinary Least Squares estimators of beta coefficients of major firms and portfolios are highly sensitive to observations of extremes in market index returns. This sensitivity is rooted in the inconsistency of the quadratic loss function in financial theory. By introducing considerations of risk aversion into the estimation procedure using alternative estimators derived from Gini measures of variability one can overcome this lack of robustness and improve the reliability of the results.

Original languageEnglish
Pages (from-to)95-118
Number of pages24
JournalReview of Quantitative Finance and Accounting
Volume18
Issue number2
DOIs
StatePublished - 1 Jan 2002

Keywords

  • Mean-Gini
  • OLS estimators
  • Systematic risk

Fingerprint

Dive into the research topics of 'Estimating beta'. Together they form a unique fingerprint.

Cite this