Alternate Mathematical Approaches to Estimating Portfolio Efficiency: Incorporating a Multi-Asset Framework

Dear Colleagues,

This Special Issue is devoted to exploring alternative approaches to measuring portfolio efficiency. While the distinction between an optimal and efficient portfolio is clear, it is not yet well understood how various tests perform under a multi-asset framework. The distributions of equities, bonds, corporate bonds, REITs, commodities, and currencies are often different, yet most tests assume the standard Gaussian distribution while evaluating portfolio efficiency and optimization. The issue will look at papers that discuss/utilize any or all of the following in their portfolio test designs:

1. A multi-asset framework;
2. Non-normal distributions underlying the data generating processes for asset prices: Non-normal return distributions, such as Poisson distribution, Merton's jump-diffusion model, and asymptotic Chi-Square return distribution, among others;
3. Statistical tests such as tests in mean-variance space that explore the trigonometric properties (Gustafson, 2010) of the location of Markowitz-style efficient portfolios, tests utilizing GMM processes, or the likelihood ratio test (LRT) ((Zhou (1991), Gibbons, Ross, Shanken (1989)) and others;
4. Efficiency tests could then be factored into additional tests related to portfolio performance (Sharpe, Treynor, Jensen tests, and other more recent methods).

Prof. Dr. Pankaj Agrrawal
Dr. Doureige Jurdi
Prof. Dr. Ramesh Gupta
Guest Editors

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