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“Mean-Variance Skewness Portfolio Performance Gauging”: Article Analysis Coursework

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Updated: May 11th, 2022

This article was written by Walter Briec, Kristiaan Kerstens, and Octave Jokung presents a new efficiency measurement model for the static portfolio selection. The authors argue that the so-called parametric approach, which determines utility only by mean and variance of portfolio returns, is effective only in those cases when portfolio decisions are taken frequently or even continuously (Briec, Kerstens, & Jokung, 2007, p 136). Yet, it is no longer suitable when the decisions are limited in terms of time and rebalancing. Furthermore, the scholars point out that mean and variance are not the only criteria according to which one can measure the effectiveness of a portfolio. In particular, they focus on skewness since portfolio returns are not usually distributed normally. Moreover, investors prefer positive skewness because it diminishes the probability of large negative returns (2007, p 135). The model is three-dimensional since it takes into account three different parameters mean, variance and skewness (MVS). Their measurement approach relies on the shortage function which enables the investor to differentiate between allocative efficiency and portfolio efficiency. Additionally, this model takes into consideration other factors that affect the value of a portfolio, namely shadow prices and risk aversion necessity (2007, p 144). Briec, Kristiaan Kerstens, and Octave Jokung provide empirical evidence in support of their approach. Their findings indicate that optimal MVS portfolios have higher weights, especially in comparison with MV (mean-variance) portfolios. Nonetheless, the writers admit that at this point there is no optimal solution for MVS utility function. According to them, one has to develop a computational procedure for the hyper-shortage function in order to resolve this problem (2007, p 145). The scholars believe that mean-variance-skewness space necessitates more advanced computational models and currently they are lacking. Overall, this article throws light on a very important question in financial science, especially optimal portfolio diversification.

Reference

Briec W., Kerstens K. & Jokung O., 2007. Mean Variance Skewness Portfolio Performance Gauging: A General Shortage Function and Dual Approach. Management Science, 53(1), 149-135.

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"“Mean-Variance Skewness Portfolio Performance Gauging”: Article Analysis." IvyPanda, 11 May 2022, ivypanda.com/essays/mean-variance-skewness-portfolio-performance-gauging-article-analysis/.

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IvyPanda. "“Mean-Variance Skewness Portfolio Performance Gauging”: Article Analysis." May 11, 2022. https://ivypanda.com/essays/mean-variance-skewness-portfolio-performance-gauging-article-analysis/.

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IvyPanda. 2022. "“Mean-Variance Skewness Portfolio Performance Gauging”: Article Analysis." May 11, 2022. https://ivypanda.com/essays/mean-variance-skewness-portfolio-performance-gauging-article-analysis/.

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IvyPanda. (2022) '“Mean-Variance Skewness Portfolio Performance Gauging”: Article Analysis'. 11 May.

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