A model of portfolio optimization using time adapting genetic network programming

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@Article{Chen2009,

• author = "Yan Chen and Shingo Mabu and Kotaro Hirasawa",
• title = "A model of portfolio optimization using time adapting genetic network programming",
• journal = "Computers \& Operations Research",
• year = "2010",
• volume = "37",
• number = "10",
• pages = "1697--1707",
• month = oct,
• ISSN = "0305-0548",
• DOI = "doi:10.1016/j.cor.2009.12.003",
• URL = "http://www.sciencedirect.com/science/article/B6VC5-4Y0D6CX-1/2/2b2154c00eb0c11cef64666b20be06e1",
• keywords = "genetic algorithms, genetic programming, Genetic network programming, Portfolio optimisation, Reinforcement learning, Technical indices, Candlestick chart",
• abstract = "This paper describes a decision-making model of dynamic portfolio optimisation 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.",

}

Genetic Programming entries for Yan Chen Shingo Mabu Kotaro Hirasawa

Citations