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