IDEAS home Printed from https://ideas.repec.org/a/wsi/afexxx/v05y2009i01ns201049520950002x.html
   My bibliography  Save this article

Are Nonlinear Trading Rules Profitable In The Chinese Stock Market?

Author

Listed:
  • TERENCE TAI-LEUNG CHONG

    (Department of Economics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong)

  • TAU-HING LAM

    (Department of Economics, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong)

  • MELVIN J. HINICH

    (Applied Research Laboratories, University of Texas at Austin, USA)

Abstract

The rise of China in the world economy has attracted a great deal of international attention. This paper investigates the performance of nonlinear self-exciting threshold autoregressive (SETAR) model-based trading rules in the Chinese stock market. We compare the performance of the SETAR model with the autoregressive (AR) model and the moving average (MA) trading rules. Our results indicate that trading rules are profitable in the B-share market, and that the nonlinear SETAR rule outperforms the other two linear rules in general.

Suggested Citation

  • Terence Tai-Leung Chong & Tau-Hing Lam & Melvin J. Hinich, 2009. "Are Nonlinear Trading Rules Profitable In The Chinese Stock Market?," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 5(01), pages 1-20.
  • Handle: RePEc:wsi:afexxx:v:05:y:2009:i:01:n:s201049520950002x
    DOI: 10.1142/S201049520950002X
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S201049520950002X
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S201049520950002X?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    Citations

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


    Cited by:

    1. Chong, Terence Tai Leung & Tang, Alan Tsz Chung & Chan, Kwun Ho, 2016. "An Empirical Comparison of Fast and Slow Stochastics," MPRA Paper 80559, University Library of Munich, Germany.
    2. Chong, Terence Tai-Leung & Lam, Tau-Hing & Yan, Isabel Kit-Ming, 2012. "Is the Chinese stock market really inefficient?," China Economic Review, Elsevier, vol. 23(1), pages 122-137.
    3. Kim man Lui & Terence T. L. Chong, 2013. "Do Technical Analysts Outperform Novice Traders: Experimental Evidence," Economics Bulletin, AccessEcon, vol. 33(4), pages 3080-3087.
    4. Lawrence Xaba & Ntebogang Moroke & Johnson Arkaah & Charlemagne Pooe, 2015. "A Comparative Study of Stock Price Forecasting using nonlinear models," Proceedings of International Academic Conferences 2704207, International Institute of Social and Economic Sciences.

    More about this item

    Keywords

    SETAR model; bootstrap; GARCH-M model; G11; G14;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:wsi:afexxx:v:05:y:2009:i:01:n:s201049520950002x. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/afe/afe.shtml .

    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.