A portfolio selection model using genetic relation algorithm and genetic network programming

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@InProceedings{Chen:2009:ieeeSMC,

• author = "Yan Chen and Kotaro Hirasawa and Shingo Mabu",
• title = "A portfolio selection model using genetic relation algorithm and genetic network programming",
• booktitle = "IEEE International Conference on Systems, Man and Cybernetics, SMC 2009",
• year = "2009",
• month = "11-14 " # oct,
• pages = "4378--4383",
• abstract = "In this paper, a new evolutionary method named genetic relation algorithm (GRA) has been proposed and applied to the portfolio selection problem. The number of brands in the stock market is generally very large, therefore, techniques for selecting the effective portfolio are likely to be of interest in the financial field. In order to pick up a fixed number of the most efficient portfolio, the proposed model considers the correlation coefficient between stocks as strength, which indicates the relationship between nodes in GRA. The algorithm evaluates the relationships between stock brands using a specific measure of strength and generates the optimal portfolio in the final generation. The efficiency of GRA method is confirmed by the stock trading model using genetic network programming (GNP) that has been proposed in the previous study. We present the experimental results obtained by GRA and compare them with those obtained by traditional method, and it is clarified that the proposed model can obtain much higher profits than the traditional one.",
• keywords = "genetic algorithms, genetic programming, genetic network programming, correlation coefficient, evolutionary method, genetic relation algorithm, portfolio selection model, stock market, stock markets",
• DOI = "doi:10.1109/ICSMC.2009.5346940",
• ISSN = "1062-922X",
• notes = "Also known as \cite{5346940}",

}

Genetic Programming entries for Yan Chen Kotaro Hirasawa Shingo Mabu

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