• DocumentCode
    3500323
  • Title

    Global Asset Allocation Using XCS Experts in Country-Specific ETFs

  • Author

    Tsai, Wen-Chih ; Chen, An-Pin

  • Author_Institution
    Inst. of Inf. Manage., Nat. Chiao Tung Univ., Hsinchu
  • Volume
    2
  • fYear
    2008
  • fDate
    11-13 Nov. 2008
  • Firstpage
    1170
  • Lastpage
    1176
  • Abstract
    There are several studies extended classification system (XCS) in past years, the model can dynamically learn and adapt to the change of environments for maximizing the desired goals. This paper conducts simulation the experiment to evolve XCS for global asset allocation in the country-specific Exchanged Traded Funds (ETFs). Since international stock price trend is influenced by unknown and unpredictable surrounding, using XCS to model the fluctuations on global financial market allows for the capability to discover the patterns of the future trends. The benefits of international diversification can be achieved with country-specific ETFs at a low cost, with a low transaction cost, tracking error and in a tax-efficient way. These empirical results indicate that XCS is capable of evolving from generation to generation, and in this way can provide the highest profit for future global asset allocation decision-making.
  • Keywords
    investment; stock markets; XCS experts; country-specific ETF; exchanged traded funds; extended classification system; global asset allocation; global financial market; international diversification; international stock price trend; Asset management; Costs; Decision making; Fluctuations; Information analysis; Information management; Information technology; Mutual funds; Portfolios; Working environment noise; ETFs; Global asset allocation; XCS;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Convergence and Hybrid Information Technology, 2008. ICCIT '08. Third International Conference on
  • Conference_Location
    Busan
  • Print_ISBN
    978-0-7695-3407-7
  • Type

    conf

  • DOI
    10.1109/ICCIT.2008.418
  • Filename
    4682406