遺伝的アルゴリズムとヒューリスティックローカルサーチを用いたインデックスファンドの最適化 Index Fund Optimization Using a Genetic Algorithm and a Heuristic Local Search

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It is well known that index funds are popular passively managed portfolios and have been used very extensively for the hedge trading. Index funds consist of a certain number of stocks of listed companies on a stock market such that the fund's return rates follow a similar path to the changing rates of the market indices. However it is hard to make a perfect index fund consisting of all companies included in the given market index. Thus, the index fund optimization can be viewed as a combinatorial optimization for portfolio managements. In this paper, we propose an optimization method that consists of a genetic algorithm and a heuristic local search algorithm to make strong linear association between the fund's return rates and the changing rates of market index. We apply the method to the Tokyo Stock Exchange and make index funds whose return rates follow a similar path to the changing rates of Tokyo Stock Price Index (TOPIX). The results show that our proposal method makes the index funds with strong linear association to the market index by small computing time.

収録刊行物

  • 電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society  

    電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society 128(3), 407-415, 2008-03-01 

    The Institute of Electrical Engineers of Japan

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各種コード

  • NII論文ID(NAID)
    10021131678
  • NII書誌ID(NCID)
    AN10065950
  • 本文言語コード
    JPN
  • 資料種別
    ART
  • ISSN
    03854221
  • NDL 記事登録ID
    9401016
  • NDL 雑誌分類
    ZN31(科学技術--電気工学・電気機械工業)
  • NDL 請求記号
    Z16-795
  • データ提供元
    CJP書誌  CJP引用  NDL  J-STAGE 
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