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The Estimation of Systematic Risk under Differentiated Risk Aversion: A Mean-Extended Gini Approach

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Author Info
 Gregory-Allen, Russell B
Shalit, Haim

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Abstract

This paper examines a mean-Gini model of systematic risk estimation that resolves some econometric problems with mean-variance beta estimation and allows for heterogeneous risk aversion across investors. Using the mean-extended Gini (MEG) model, we estimate systematic risks for different degrees of risk aversion. MEG betas are shown to be instrumental variable estimators that provide econometric solutions to biases generated by the estimation of mean-variance (MV) betas. When security returns are not normally distributed, MEG betas are proved to differ from MV betas. We design an econometric test that assesses whether these differences are significant. As an application using daily returns, we estimate MEG and MV betas for U.S. securities. Copyright 1999 by Kluwer Academic Publishers

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Publisher Info
Article provided by Springer in its journal Review of Quantitative Finance and Accounting.

Volume (Year): 12 (1999)
Issue (Month): 2 (March)
Pages: 135-57
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Handle: RePEc:kap:rqfnac:v:12:y:1999:i:2:p:135-57

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Web page: http://springerlink.metapress.com/link.asp?id=102990

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  1. Shlomo Yitzhaki & Edna Schechtman, 2005. "The properties of the extended Gini measures of variability and inequality," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(3), pages 401-433. [Downloadable!]
  2. E. Schechtman & S. Yitzhaki, 2003. "A Family of Correlation Coefficients Based on the Extended Gini Index," Journal of Economic Inequality, Springer, vol. 1(2), pages 129-146, August. [Downloadable!] (restricted)
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