Estimating Beta

Estimating Beta 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Quantitative Finance and Accounting Springer Journals
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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2002 by Kluwer Academic Publishers
Subject
Finance; Corporate Finance; Accounting/Auditing; Econometrics; Operation Research/Decision Theory
ISSN
0924-865X
eISSN
1573-7179
D.O.I.
10.1023/A:1014594617251
Publisher site
See Article on Publisher Site

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.

Journal

Review of Quantitative Finance and AccountingSpringer Journals

Published: Oct 13, 2004

References

  • The Cross-Section of Expected Stock Returns
    Fama, E. F.; French, K. R.
  • Industry Costs of Equity
    Fama, E. F.; French, K. R.
  • The Estimation of Systematic Risk under Differentiated Risk Aversion: A Mean-Extended Gini Approach
    Gregory-Allen, R. B.; Shalit, H.
  • Portfolio Inefficiency and the Cross-Section of Expected Returns
    Kandel, S.; Stambaugh, R. F.
  • Correlation and the Time Interval over which Variables are Measured
    Levy, H.; Schwarz, G.
  • Using Generalized Methods of Moments to Test Mean-Variance Efficiency
    MacKinlay, A. C.; Richardson, M. P.

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