A model of portfolio optimization using time adapting genetic network programming

Authors:
Yan Chen;Shingo Mabu;Kotaro Hirasawa
Affiliations:
School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai 200433, China and Graduate School of Information, Production and Systems, Waseda University, Kitakyushu ...;Graduate School of Information, Production and Systems, Waseda University, Kitakyushu 8080135, Japan;Graduate School of Information, Production and Systems, Waseda University, Kitakyushu 8080135, Japan
Venue:
Computers and Operations Research
Year:
2010

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Abstract

This paper describes a decision-making model of dynamic portfolio optimization for adapting to the change of stock prices based on an evolutionary computation method named genetic network programming (GNP). The proposed model, making use of the information from technical indices and candlestick chart, is trained to generate portfolio investment advice. Experimental results on the Japanese stock market show that the decision-making model using time adapting genetic network programming (TA-GNP) method outperforms other traditional models in terms of both accuracy and efficiency. A comprehensive analysis of the results is provided, and it is clarified that the TA-GNP method is effective on the portfolio optimization problem.