IDEAS home Printed from https://ideas.repec.org/a/spr/digfin/v1y2019i1d10.1007_s42521-019-00006-x.html
   My bibliography  Save this article

Price discovery on Bitcoin markets

Author

Listed:
  • Paolo Pagnottoni

    () (University of Pavia)

  • Thomas Dimpfl

    () (University of Tübingen)

Abstract

Abstract Trading of Bitcoin is spread about multiple venues where buying and selling is offered in various currencies. However, all exchanges trade one common good and by the law of one price, the different prices should not deviate in the long run. In this context, we are interested in which platform is the most important one in terms of price discovery. To this end, we use a pairwise approach accounting for a potential impact of exchange rates. The contribution to price discovery is measured by Hasbrouck’s and Gonzalo and Granger’s information share. We then derive an ordering with respect to the importance of each market which reveals that the Chinese OKCoin platform is the leader in price discovery of Bitcoin, followed by BTC China. Overall, the exchange rate is neither affected by Bitcoin trading nor does it contribute decisively to its price discovery.

Suggested Citation

  • Paolo Pagnottoni & Thomas Dimpfl, 2019. "Price discovery on Bitcoin markets," Digital Finance, Springer, vol. 1(1), pages 139-161, November.
  • Handle: RePEc:spr:digfin:v:1:y:2019:i:1:d:10.1007_s42521-019-00006-x
    DOI: 10.1007/s42521-019-00006-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s42521-019-00006-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

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

    More about this item

    Keywords

    Price discovery; Bitcoin; Hasbrouck information shares;

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

    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:spr:digfin:v:1:y:2019:i:1:d:10.1007_s42521-019-00006-x. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Sonal Shukla) or (Springer Nature Abstracting and Indexing). General contact details of provider: http://www.springer.com .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.