IDEAS home Printed from https://ideas.repec.org/a/igg/jrcm00/v11y2022i1p1-21.html
   My bibliography  Save this article

An Analysis of Global Stock Markets With the Autoregressive Distributed Lag Method

Author

Listed:
  • Hakan Altin

    (University of Aksaray, Turkey)

Abstract

The primary objective of this study is to create the first examination of the global stock markets using the ARDL method. The ARDL model provides a solution that shows the short-run and long-run relationships together by removing the constraint of the series that are stationary in the traditional cointegration models. The period examined in the study, in which daily data is used, is between 01/03/2000 – 12/31/2022. Two significant results were obtained as a consequence of the implementation phase. First, there is a causal cointegration relationship between European stock markets, BRIC stocks, and American stock markets in the short run and long run. The cointegration relationship between global stock markets transforms national economies into international economies. The interdependence between global stock markets is considerably strong. This situation diminishes the utility of international diversification explained in portfolio management. Second, the relatively new ARDL technique gives similar results to conventional cointegration tests.

Suggested Citation

  • Hakan Altin, 2022. "An Analysis of Global Stock Markets With the Autoregressive Distributed Lag Method," International Journal of Risk and Contingency Management (IJRCM), IGI Global, vol. 11(1), pages 1-21, January.
  • Handle: RePEc:igg:jrcm00:v:11:y:2022:i:1:p:1-21
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJRCM.304900
    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:jrcm00:v:11:y:2022:i:1:p:1-21. 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.