Mean-Gini, Portfolio Theory, and the Pricing of Risky Assets




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    • Shalit from the University of Maryland and the Hebrew University of Jerusalem. Yitzhaki from the Hebrew University of Jerusalem. This research was supported by a grant from the Government of Israel, the National Committee for Research and Development, Grant No. 5107. We are grateful to Haim Levy and the late Vijay Bawa, who as anonymous referees provided useful comments. All the remaining errors are, of course, ours.


This paper presents the mean-Gini (MG) approach to analyze risky prospects and construct optimum portfolios. The proposed method has the simplicity of a mean-variance model and the main features of stochastic dominance efficiency. Since mean-Gini is consistent with investor behavior under uncertainty for a wide class of probability distributions, Gini's mean difference is shown to be more adequate than the variance for evaluating the variability of a prospect. The MG approach is then applied to capital markets and the security valuation theorem is derived as a general relationship between average return and risk. This is further extended to include a degree of risk aversion that can be estimated from capital market data. The analysis is concluded with the concentration ratio to allow for the classification of different securities with respect to their relative riskiness.