IDEAS home Printed from
   My bibliography  Save this article

Forecasting the Thailand Stock Market Using Evolution Strategies


  • Phaisarn Sutheebanjard

    () (Graduate School of Information Technology, Siam University Bangkok 10163, Thailand)

  • Wichian Premchaiswadi

    (Graduate School of Information Technology, Siam University Bangkok 10163, Thailand)


This paper proposes a new prediction function for the Stock Exchange of Thailand (SET index). Included in the proposed prediction function are the important economic factors: namely, the Dow Jones, Nikkei, and Hang Seng indexes; the minimum loan rate (MLR); and the previous SET index. The tuning coefficients of each factor in this research were calculated using the two-membered evolution strategy (ES) technique. The experiment was conducted by analysing the SET index during three different time periods. The first time period extended from January 2004 to December 2004, and the second time period extended from 9 August 2005 to December 2005. These data were used to evaluate the performance of the proposed prediction function for short-term periods by comparing the results with those achieved using the existing methods. Lastly, the long-term period data extending from January 2005 to March 2009, which covered 1040 days in totals, were used to predict the SET index. The results show that the proposed prediction function not only yields the lowest mean absolute percentage error (MAPE) for short-term periods but also yields a MAPE lower than 1% for long-term periods.

Suggested Citation

  • Phaisarn Sutheebanjard & Wichian Premchaiswadi, 2010. "Forecasting the Thailand Stock Market Using Evolution Strategies," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 6(2), pages 85-114.
  • Handle: RePEc:usm:journl:aamjaf00602_85-114

    Download full text from publisher

    File URL:
    Download Restriction: no


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Md. Zahangir Alam & Md. Noman Siddikee & Md. Masukujjaman, 2013. "Forecasting Volatility of Stock Indices with ARCH Model," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 4(2), pages 126-143, April.


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:usm:journl:aamjaf00602_85-114. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Journal Division, Penerbit Universiti Sains Malaysia). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.