The Markowitz’s mean-variance methodology is hardly applicable for hedge fund risk assessment. Since its introduction, the mean-variance methodology became the primary tool for portfolio diversification used by the majority of pension and mutual funds globally. However, despite its popularity, the mean-variance approach suffers several important drawbacks limiting its applicability, especially, when it comes to hedge funds. The main limitations of the mean-variance approach for hedge fund assessment can be briefly outlined as follows.
First, the estimate of risk by variance is only appropriate, when returns are normally distributed or investors exhibit quadratic preferences. Examination of returns of different asset classes shows that traditional instruments, like stocks or bonds, demonstrate distributions more or less approximated by normal, whereas derivatives evidence a high level of irregularities as skewness and kurtosis excess. Numerous studies evidence that most of hedge funds expose asymmetrical returns, thus making the mean-variance model hardly applicable in principle.
Second, the mean-variance framework assumes that investors focus on a single time horizon and will never alter their asset allocation once it is chosen.
Third, according to the mean-variance approach, the main objective of investors is to minimize the volatility under a defined mean of returns or vice versa. It does not cope with today’s sophisticated investment techniques and complex financial instruments. For example, the objective of a fund of funds may be in minimization of fund’s correlation with the chosen index, thus employing a market-neutral strategy.
The hardest aspect about hedge fund properties is to understand that they present an entirely distinct category of investment vehicles, therefore, deploying a traditional methodology commonly used for stocks and bonds, will lead to unexpected and most questionable results.
