IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v301y2001i1p473-482.html
   My bibliography  Save this article

Predictability of multifractal analysis of Hang Seng stock index in Hong Kong

Author

Listed:
  • Sun, Xia
  • Chen, Huiping
  • Yuan, Yongzhuang
  • Wu, Ziqin

Abstract

In this paper, the daily Hang Seng index in Hong Kong stock market is studied by multifractal analysis. The main parameter of multifractal spectra used is Δf, which can be used to characterize the ratio of number of highest index moments to that of lowest ones. The dependence of today's gain probability (G%) and the day's index increase probability (n%) with Δf of the previous 3 days are studied. It is found that G% and n% can reach 70–80% at the large positive Δf region and can be very close to 20% at the big negative Δf region. The predictability decreases with the increasing number of the previous days.

Suggested Citation

  • Sun, Xia & Chen, Huiping & Yuan, Yongzhuang & Wu, Ziqin, 2001. "Predictability of multifractal analysis of Hang Seng stock index in Hong Kong," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 301(1), pages 473-482.
  • Handle: RePEc:eee:phsmap:v:301:y:2001:i:1:p:473-482 DOI: 10.1016/S0378-4371(01)00433-2
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437101004332
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kaniadakis, G., 2001. "Non-linear kinetics underlying generalized statistics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 296(3), pages 405-425.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Predictability; Multifractal; Hong Kong index;

    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:eee:phsmap:v:301:y:2001:i:1:p:473-482. 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: (Dana Niculescu). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.