Ontology type: schema:ScholarlyArticle
1999-03
AUTHORSRussell B. Gregory-Allen, Haim Shalit
ABSTRACTThis 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. More... »
PAGES135-158
http://scigraph.springernature.com/pub.10.1023/a:1008348104882
DOIhttp://dx.doi.org/10.1023/a:1008348104882
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