Hedge Fund Modelling and Analysis

CHAPTER 6 Mean-Variance Optimisation

Hedge fund analysis primarily involves ascertaining relevant statistical properties of the hedge fund returns distribution in order to make informed decisions about the characteristics and performance of a hedge fund. We have already looked in detail at the two prominent statistical parameters most often cited: the mean and standard deviation. In 1953, H.M. Markowitz introduced the topic of modern portfolio theory which opened up the possibility of being able to optimise a portfolio of assets so as to minimise the portfolio risk for an acceptable level of portfolio return. Clearly, such a technique is extremely valuable to hedge fund managers, especially when dealing with asset allocation and the efficient distribution of wealth across a portfolio.

Chapter 6 introduces the main ideas behind mean-variance optimisation and implements the method of Lagrange multipliers to find the set of optimal investment weights for a 10-hedge-fund portfolio.

6.1 The Optimise Class

As in the previous chapters we will be developing another class Optimise in much the same way as we did for the other classes. Source 6.1 shows the basic skeleton of the Optimise class which will we again add to as we develop through the chapter.

Source 6.1: Skeleton of the Optimise class

In Source 6.1, the default constructor and destructor have again been declared and ...