The Estimation of Systematic Risk under Differentiated Risk Aversion: A Mean-Extended Gini Approach |
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Authors: | Gregory-Allen Russell B. Shalit Haim |
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Affiliation: | (1) College Retirement Equities Fund (CREF), New York, NY 10017, USA;(2) Department of Economics, Monaster Center for Economic Research, Ben Gurion University of the Negev, Beer Sheva, 84105, Israel |
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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. |
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Keywords: | Beta mean-Gini normality test instrumental variable estimation |
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