IDEAS home Printed from https://ideas.repec.org/p/sek/iacpro/0902655.html
   My bibliography  Save this paper

Sttock Market Behavoir: A Fractal Analysis of Saudi Stock Exchange

Author

Listed:
  • Shekar Shetty

    (Gulf University for Science & Technology)

  • Dhari AlAbdulhadi

    (Gulf university for Science & Technology)

  • Mansour AlShamali

    (Kuwait Public Authority for Education)

Abstract

The Saudi stock market is analyzed, using rescaled range analysis to estimate the fractal dimension of price returns and to test the Efficient Market Hypothesis. In order to determine the predictability of a time series, Hurst Exponent for each time series is measured and we find that Saudi market is not totally random during the time period under study. There exists long range dependene in Saudi stock market returns. For most instances, it is determined that the Saudi stock market returns comply with neither the weak form of the efficient market hypothesis nor the random walk assumption. Additionally, for completeness and as part of literature review we bring out Bachelier-Einstein?s absolute Brownian dynamics, and Samuelson-Merton models of Martingale with geometric Brownian dynamic structure of equations.

Suggested Citation

  • Shekar Shetty & Dhari AlAbdulhadi & Mansour AlShamali, 2014. "Sttock Market Behavoir: A Fractal Analysis of Saudi Stock Exchange," Proceedings of International Academic Conferences 0902655, International Institute of Social and Economic Sciences.
    • Handle: RePEc:sek:iacpro:0902655
    as

    Download full text from publisher

    File URL: https://iises.net/proceedings/14th-international-academic-conference-malta/table-of-content/detail?cid=9&iid=72&rid=2655
    File Function: First version, 2014
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Fractal analysis; Hurst exponent; Efficient Market Hypothesis; Saudi stock market;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:sek:iacpro:0902655. 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: Klara Cermakova (email available below). General contact details of provider: https://iises.net/ .

    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.