IDEAS home Printed from https://ideas.repec.org/a/igg/joris0/v3y2012i3p74-86.html
   My bibliography  Save this article

A Data-Integrated Tree-Based Simulation to Predict Financial Market Movement

Author

Listed:
  • Durai Sundaramoorthi

    (Washington University in St. Louis, USA)

  • Andrew Coult

    (Missouri Western State University, USA)

  • Dung Hai Nguyen

    (Washington University in St. Louis, USA)

Abstract

The Standard and Poor’s 500 Index (S&P500) is one of the commonly used indices on the New York Stock Exchange. The 500 publicly traded companies that make up the index are chosen by a committee to best reflect the overall market of the United States. The broader objective of this research is to estimate the dynamics of the financial market movement in the United States. It is achieved by developing a data-integrated tree-based simulation model to predict S&P500 open and close values for a week. Classification and Regression Trees (CART) - a data mining method - is utilized to extract patterns of the financial market dynamics based on a data set collected from May 1, 2008 to November 30, 2009. The data set included the daily movement of financial markets in seven countries in Asia and Europe in relation to the daily movement of the S&P500. CART also utilized data on the currency exchange rates to capture the financial dynamics between the US and other countries. The simulation model repeatedly samples from four trees developed by CART to know how the opening and closing values of the S&P500 move in tandem with the other markets.

Suggested Citation

  • Durai Sundaramoorthi & Andrew Coult & Dung Hai Nguyen, 2012. "A Data-Integrated Tree-Based Simulation to Predict Financial Market Movement," International Journal of Operations Research and Information Systems (IJORIS), IGI Global, vol. 3(3), pages 74-86, July.
    • Handle: RePEc:igg:joris0:v:3:y:2012:i:3:p:74-86
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/joris.2012070105
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    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:igg:joris0:v:3:y:2012:i:3:p:74-86. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.