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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/107497


    Title: Using grouping genetic algorithm to mine diverse group stock portfolio
    Authors: Chen, Chun-Hao;Lu, Cheng-Yu;Hong, Tzung-Pei;Su, Ja-Hwung
    Keywords: grouping genetic algorithms;group stock portfolio;maximally diverse grouping problem;portfolio optimization
    Date: 2016-07-29
    Issue Date: 2016-09-20 02:10:34 (UTC+8)
    Abstract: In this paper, to increase the diversity of stock portfolios, the diverse group stock portfolio mining algorithm is proposed by grouping genetic algorithm. Each chromosome is represented by grouping, stock and stock portfolio parts. The fitness function that consists of portfolio satisfaction, group balance and diversity factor is designed to evaluate quality of chromosomes. The diversity factor is used to make the numbers of stock categories in groups as similar as possible. The genetic operations are then executed on population to generate offspring to find the near optimal group stock portfolio. Finally, experiments on a real financial data were made to show the proposed approach is effective.
    Relation: 2016 IEEE World Congress on Computational Intelligence (IEEE WCCI), pp. 1-5
    Appears in Collections:[資訊工程學系暨研究所] 會議論文

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