Risk minimization with self-organizing maps for mutual fund investment

  • Authors:

  • Andrei A. Lukyanitsa;Sergei V. Nosov;Alexei G. Shishkin

  • Affiliations:

  • Department of Computational Mathematics & Cybernetics, Moscow State University, Moscow, Russia;Department of Computational Mathematics & Cybernetics, Moscow State University, Moscow, Russia and Financial Department, Savings Bank of the Russian Federation;Department of Computational Mathematics & Cybernetics, Moscow State University, Moscow, Russia

  • Venue:
  • CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
  • Year:
  • 2009

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Abstract

The problem of optimal mutual fund investment taking into account possible risks is considered. In this paper we consider lost profit in the growing market and a loss in a falling market as a possible risk. Our studies show that the efficiency of mutual funds can be estimated by nine main parameters obtained by historical data. Evaluation and ranking criteria sets for mutual funds are defined by the help of Kohonen Self-Organizing Maps. We propose to use a simplified ranking consisting of five categories. The methodology of constructing optimal strategies for risk-sensitive portfolio optimization is proposed. The performance of constructed portfolio is superior to the most mutual funds and other portfolios. The proposed methodology underwent a test for last four years and showed high efficiency and robustness both in growing and falling (during current world financial crisis) markets.