Evolving asset selection using genetic network programming

Victor Parque Tenorio, Shingo Mabu, Kotaro Hirasawa

    Research output: Contribution to journalArticle


    As global financial innovation opens innumerable risks and opportunities, a global view of the asset allocation brings advantages in risk diversification for investments. We propose a novel framework for asset selection under global diversification principles using genetic network programming. Simulations using the stocks, bonds and currencies from relevant financial markets in USA, Europe and Asia show that the proposed framework is effective and offers competitive advantages against the conventional methods in finance and computational fields.

    Original languageEnglish
    Pages (from-to)174-182
    Number of pages9
    JournalIEEJ Transactions on Electrical and Electronic Engineering
    Issue number2
    Publication statusPublished - 2012 Mar



    • Asset selection
    • Evolutionary finance
    • Genetic network programming
    • Value and growth

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering

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