• DocumentCode
    1641124
  • Title

    Risk minimization with self-organizing maps for mutual fund investment

  • Author

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

  • Author_Institution
    Dept. of Comput. Math.&Cybern., Moscow State Univ., Moscow
  • fYear
    2009
  • Firstpage
    2361
  • Lastpage
    2365
  • 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.
  • Keywords
    genetic algorithms; investment; probability; profitability; risk management; self-organising feature maps; genetic algorithm; mutual fund investment; probability; profitability; risk minimization; risk-sensitive portfolio optimization; self-organizing Kohonen map; Cybernetics; Instruments; Investments; Mathematics; Mutual funds; Optimization methods; Portfolios; Risk management; Robustness; Self organizing feature maps;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 2009. CEC '09. IEEE Congress on
  • Conference_Location
    Trondheim
  • Print_ISBN
    978-1-4244-2958-5
  • Electronic_ISBN
    978-1-4244-2959-2
  • Type

    conf

  • DOI
    10.1109/CEC.2009.4983235
  • Filename
    4983235