IDEAS home Printed from https://ideas.repec.org/p/dal/wpaper/daleconwp2020-02.html

Information Flow and Price Discovery Dynamics

Author

Listed:
  • Lei Wu

    (School of Economics and Management, Beihang University)

  • Kuan Xu

    (Department of Economics, Dalhousie University)

  • Qingbin Meng

    (School of Business, Renmin University of China)

Abstract

Non-homogeneous and time-varying information flow that affects the price discovery processes within and across markets is a common occurrence in reality but is often neglected in the literature of price discovery. To analyze such information flow within and across markets, we propose a new strategy with a new dynamic price discovery measure. We use this strategy to test the efficient home market hypothesis and the sector effect hypothesis based on the intraday data of the 115 stocks cross-listed and traded in the Canadian and U.S. stock markets. We find that the Canadian stock market is more efficient in price discovery for the Canadian stocks cross-listed in the U.S. stock market. A higher trading volume in the Canadian market makes price discovery in that market more efficient. The Canadian stock market is more efficient in price discovery for stocks in the basic materials sector but not in the technology and financial sectors. The NYSE Alternext is more efficient for junior stocks while the NASDAQ is more efficient for technology stocks.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Lei Wu & Kuan Xu & Qingbin Meng, 2020. "Information Flow and Price Discovery Dynamics," Working Papers daleconwp2020-02, Dalhousie University, Department of Economics.
  • Handle: RePEc:dal:wpaper:daleconwp2020-02
    as

    Download full text from publisher

    File URL: http://wp.economics.dal.ca/RePEc/dal/wpaper/DalEconWP2020-02.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    More about this item

    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • F3 - International Economics - - International Finance
    • G1 - Financial Economics - - General Financial Markets

    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:dal:wpaper:daleconwp2020-02. 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: James McNeil (email available below). General contact details of provider: https://edirc.repec.org/data/dedalca.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.