IDEAS home Printed from https://ideas.repec.org/p/dkn/ecomet/fe_2015_01.html

A GARCH model for testing market efficiency

Author

Listed:
  • Narayan, Paresh Kumar
  • Liu, Ruipeng

Abstract

In this paper we propose a generalised autoregressive conditional heteroskedasticity (GARCH) model-based test for a unit root. The model allows for two endogenous structural breaks. We test for unit roots in 156 US stocks listed on the NYSE over the period 1980 to 2007. We find that the unit root null hypothesis is rejected in 40% of the stocks, and only in four out of the nine sectors the null is rejected for over 50% of stocks. We conclude with an economic significance analysis, showing that mostly stocks with mean reverting prices tend to outperform stocks with non-stationary prices.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Narayan, Paresh Kumar & Liu, Ruipeng, 2015. "A GARCH model for testing market efficiency," Working Papers fe_2015_01, Deakin University, Department of Economics.
  • Handle: RePEc:dkn:ecomet:fe_2015_01
    DOI: 10.1016/j.intfin.2015.12.008
    as

    Download full text from publisher

    File URL: http://www.dx.doi.org/10.1016/j.intfin.2015.12.008
    Download Restriction: no

    File URL: https://libkey.io/10.1016/j.intfin.2015.12.008?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
    ---><---

    Other versions of this item:

    More about this item

    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:dkn:ecomet:fe_2015_01. 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: Xueli Tang (email available below). General contact details of provider: https://edirc.repec.org/data/sedeaau.html .

    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.