Evolutionary Approach to Multiobjective Optimization of Portfolios That Reflect the Behaviour of Investment Funds

This paper addresses a problem of finding portfolios that perform better than investment funds while showing similar behaviour. The quality of investment portfolio can be measured using various criteria such as the return and some kind of risk measurement. Investors seek to maximize return while minimizing risk. In order to achieve this goal various instruments are considered. One of the possibilities is to entrust the assets to an investment fund. Investment funds build their own portfolios of stocks, bonds, commodities, currencies, etc. In this paper we consider the problem of finding a portfolio which outperforms a given investment fund with respect to both the return and the risk and which also behave in a similar way to the given fund. The rationale behind such an approach is that investment strategies of mutual funds are prepared by experts and are therefore expected to be reasonably good in terms of both the return and the risk. To achieve the presented goal we use a multiobjective evolutionary algorithm with a dedicated ”division mutation” operator and a local search procedure. Presented method seems capable of building portfolios with desired qualities.