Mean-Gini, portfolio theory, and the pricing of risky assets

Article Abstract:

The mean-Gini (MG) approach to analyze risky investments and construct optimum portfolios is presented. The proposed method has the attractiveness and simplicity of a two-parameter model and the main features of stochastic dominance efficiency. Gini's mean difference is shown to be more adequate than the variance for evaluating the variability of a prospect because mean-Gini is consistent with investor behavior under uncertainty for a wide class of probability distributions. The MG approach is applied to capital markets and the security valuation theorem is derived; it is further extended to include a degree of risk aversion that can be estimated from capital market data. Some extensions of the Gini coefficient to portfolio theory, such as the concentration ratio, are presented.

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Portfolio analysis using single index, multi-index, and constant correlation models: a unified treatment

Article Abstract:

A simple common algorithm, applicable to seven models, is proposed for optimal portfolio selection disallowing short sales of uncertain securities. A single index model, four multi-index models, and two constant correlation models are considered. The proposed algorithm does not require explicit ranking of securities, so it is particularly useful for two multi-index models with orthogonol indices which do not provide any ranking criterion. It is also demonstrated in a simulation study that the procedure involved in the search for optimality requires only small numbers of simple iterative steps; thus, the approach enhances the usefulness of these index models and constant correlation models in portfolio analysis.

Methods, Risk management

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More on estimation risk and simple rules for optimal portfolio selection

Article Abstract:

When choosing an expected-utility-maximizing portfolio, risk-averse investors consider estimation risk important, and previous research has shown that the components of the tangency portfolio is not affected by the recognition of estimation risk when the Full Covariance Model is used. However, if the Market Model is used, the components of the tangency portfolio have been shown to be affected by estimation risk recognition. The effect is shown to be not as substantive as previous research has indicated in this research, and it is claimed that the effect can be ignored safely in many situations.

Research, Management, Economic aspects, Risk (Economics), Investments, Investors, Capital

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