The Formation of Optimal Portfolio of Mutual Shares Funds using Multi-Objective Genetic Algorithm
Abstract: 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.
Keywords: Investing, Mutual
Fund Shares, Genetic Algorithms, Portfolio
Author: Yandra Arkeman, Akhmad
Yusuf, Mushthofa Mushthofa, Gibtha FitriLaxmi, Kudang Boro Seminar
Journal Code: jptkomputergg130093
