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The Formation of Optimal Portfolio of Mutual Shares Funds using Multi-Objective Genetic Algorithm

Author(s): Yandra Arkeman | Akhmad Yusuf | Mushthofa Mushthofa | Gibtha Fitri Laxmi | Kudang Boro Seminar

ISSN 1693-6930

Volume: 11;
Issue: 3;
Date: 2013;
Original page

Keywords: investing | mutual shares fund | genetic algorithms | portfolio

Investments in financial assets have become a trend in the globalization era, especially the investment in mutual fund shares. Investors who want to invest in stock mutual funds can set up an investment portfolio in order to generate a minimal risk and maximum return. In this study the authors used the Multi-Objective Genetic Algorithm Non-dominated Sorting II (MOGA NSGA-II) technique with the Markowitz portfolio principle to find the best portfolio from several mutual funds. The data used are 10 company stock mutual funds with a period of 12 months, 24 months and 36 months. The genetic algorithm parameters used are crossover probability of 0.65, mutation probability of 0.05, Generation 400 and a population numbering 20 individuals. The study produced a combination of the best portfolios for the period of 24 months with a computing time of 63,289 seconds.
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