Evolving asset portfolios by genetic relation algorithm

Victor Parque Tenorio, Shingo Mabu, Kotaro Hirasawa

    Research output: Contribution to journalArticle

    4 Citations (Scopus)

    Abstract

    Global financial development have opened innumerable risks and opportunities for investments. A global view of the portfolio allocation through diversification brings advantages for the risk allocation in investments. In this paper, an asset allocation framework under the return, risk and liquidity considerations is proposed for short term investment using Genetic Relation Algorithm. Simulations using the stocks, bonds and currencies from relevant financial markets in USA, Europe and Asia show that the proposed framework is effective and robust. The efficacy of the proposed method is compared against the relevant constructs in finance and computational fields.

    Original languageEnglish
    Pages (from-to)464-474
    Number of pages11
    JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
    Volume14
    Issue number5
    Publication statusPublished - 2010 Jul

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    Finance
    Financial markets

    Keywords

    • Asset allocation
    • Capital allocation
    • Computational finance
    • Portfolio optimization

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Vision and Pattern Recognition
    • Human-Computer Interaction

    Cite this

    Evolving asset portfolios by genetic relation algorithm. / Parque Tenorio, Victor; Mabu, Shingo; Hirasawa, Kotaro.

    In: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 14, No. 5, 07.2010, p. 464-474.

    Research output: Contribution to journalArticle

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