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New EDHEC Risk Institute research shows that without the use of robust estimators, minimising extreme risks may be worse than not minimising them-continued

The results show that in trying to minimise extreme risk and make their risk evaluation more sophisticated, many asset managers increase the number of risk parameters to be estimated, which in turn leads to less robust and less relevant results than if they had stuck with a simple measure of portfolio volatility.

As outlined in the research, one key problem with explicitly introducing a focus on extreme risk in portfolio diversification techniques is that such techniques require estimates not only for variance-covariance parameters, but also for higher-order moments and comoments of the return distribution, the so-called coskewness and cokurtosis parameters, which describe how the portfolio constituents contribute to the overall fat-tailed and asymmetric distribution of the portfolio (skewness refers to the degree to which the distribution is skewed to the left or the right; kurtosis measures the “peakedness” of the distribution; a “fat tail” distribution is tilted towards the extremes). This is a formidable challenge that significantly exacerbates the dimensionality problem already present with mean-variance analysis.

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view EDHEC-Risk Working Paper Improved Estimates of Higher-Order Comoments and Implications for Portfolio Selection working paper

Source: EDHEC