IDEAS home Printed from https://ideas.repec.org/a/wsi/ijtafx/v10y2007i03ns0219024907004305.html
   My bibliography  Save this article

The Linear Dependence And Feedback Spectra Between Stock Market And Economy

Author

Listed:
  • XIA PAN

    (Faculty of Management and Administration, Macao University of Science and Technology, Avenida Wai Long, Taipa, Macao)

Abstract

Geweke studied the measure of linear dependence and spectral feedback for grouped multivariate time series. This paper applies the measure of linear dependence and spectral feedback to examining the relationship between grouped variables of economy and stock market indices. Putting economic variables into one group and stock market variables into another, we examine the between-group relationship within the US, within Japan, and within the European Union. Using a self-developed computing program, the feedback spectra for grouped variables are calculated and displayed. Although risk might exist in that the significance levels for test may not be reliable because the feedback spectra are measured on possibly nonstationary variables in level, the patterns of the feedback spectra still provide information about the cyclical effect between the variable groups.

Suggested Citation

  • Xia Pan, 2007. "The Linear Dependence And Feedback Spectra Between Stock Market And Economy," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 10(03), pages 437-447.
    • Handle: RePEc:wsi:ijtafx:v:10:y:2007:i:03:n:s0219024907004305
    DOI: 10.1142/S0219024907004305
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S0219024907004305
    Download Restriction: Access to full text is restricted to subscribers
    File URL: https://libkey.io/10.1142/S0219024907004305?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. Kun Guo & Wei-Xing Zhou & Si-Wei Cheng & Didier Sornette, 2011. "The US Stock Market Leads the Federal Funds Rate and Treasury Bond Yields," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-9, August.
    2. Jeffrey E. Jarrett & Xia Pan & Shaw Chen, 2009. "Do the Chinese Bourses (Stock Markets) Predict Economic Growth?," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 8(3), pages 201-211, December.

    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:ijtafx:v:10:y:2007:i:03:n:s0219024907004305. 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/ijtaf/ijtaf.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.