IDEAS home Printed from https://ideas.repec.org/p/bir/birmec/11-19.html
   My bibliography  Save this paper

Exchange vs Dealers: A High-Frequency Analysis of In-Play Betting Prices

Author

Listed:
  • Karen Croxson
  • J. James Reade

Abstract

We conduct the first high-frequency comparison of pricing behaviour in betting markets making use of a novel dataset of prices from the UK's two largest bookmakers and the world's largest betting exchange. We investigate price competitiveness, finding that the betting exchange structure offers customers superior returns and substantial liquidity. Given the persistence of large bookmakers, we speculate that switching costs (e.g. learning costs) must be significant. We also compare information arrival in betting markets across these two market structures. We find some support for the hypothesis that the betting exchange leads price discovery, with traditional bookmakers following.

Suggested Citation

  • Karen Croxson & J. James Reade, 2011. "Exchange vs Dealers: A High-Frequency Analysis of In-Play Betting Prices," Discussion Papers 11-19, Department of Economics, University of Birmingham.
  • Handle: RePEc:bir:birmec:11-19
    as

    Download full text from publisher

    File URL: ftp://ftp.bham.ac.uk/pub/RePEc/pdf/11-19.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Banerjee, Anindya & Dolado, Juan J. & Galbraith, John W. & Hendry, David, 1993. "Co-integration, Error Correction, and the Econometric Analysis of Non-Stationary Data," OUP Catalogue, Oxford University Press, number 9780198288107.
    2. Paul Klemperer, 1987. "Markets with Consumer Switching Costs," The Quarterly Journal of Economics, Oxford University Press, vol. 102(2), pages 375-394.
    3. Franck, Egon & Verbeek, Erwin & Nüesch, Stephan, 2010. "Prediction accuracy of different market structures -- bookmakers versus a betting exchange," International Journal of Forecasting, Elsevier, vol. 26(3), pages 448-459, July.
    4. Michael A. Smith & David Paton & Leighton Vaughan Williams, 2006. "Market Efficiency in Person-to-Person Betting," Economica, London School of Economics and Political Science, vol. 73(292), pages 673-689, November.
    5. Pesaran, M. Hashem & Smith, Ron, 1995. "Estimating long-run relationships from dynamic heterogeneous panels," Journal of Econometrics, Elsevier, vol. 68(1), pages 79-113, July.
    6. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
    7. Karen Croxson & J. James Reade, 2014. "Information and Efficiency: Goal Arrival in Soccer Betting," Economic Journal, Royal Economic Society, vol. 124(575), pages 62-91, March.
    8. Woodland, Linda M & Woodland, Bill M, 1994. " Market Efficiency and the Favorite-Longshot Bias: The Baseball Betting Market," Journal of Finance, American Finance Association, vol. 49(1), pages 269-279, March.
    9. Bruno Deschamps & Olivier Gergaud, 2007. "Efficiency in Betting Markets: Evidence from English Football," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 61-73, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. James Reade, 2014. "Information and Predictability: Bookmakers, Prediction Markets and Tipsters as Forecasters," Economics & Management Discussion Papers em-dp2014-05, Henley Business School, Reading University.
    2. Flepp, Raphael & Nüesch, Stephan & Franck, Egon, 2017. "The liquidity advantage of the quote-driven market: Evidence from the betting industry," The Quarterly Review of Economics and Finance, Elsevier, vol. 64(C), pages 306-317.
    3. Leighton Vaughan Williams & J. James Reade, 2016. "Prediction Markets, Social Media and Information Efficiency," Kyklos, Wiley Blackwell, vol. 69(3), pages 518-556, August.
    4. John Goddard & Peter Sloane (ed.), 2014. "Handbook on the Economics of Professional Football," Books, Edward Elgar Publishing, number 14821.
    5. J. James Reade & Sachiko Akie, 2013. "Using Forecasting to Detect Corruption in International Football," Working Papers 2013-005, The George Washington University, Department of Economics, Research Program on Forecasting.
    6. James Reade, 2014. "Detecting corruption in football," Chapters,in: Handbook on the Economics of Professional Football, chapter 25, pages 419-446 Edward Elgar Publishing.

    More about this item

    Keywords

    Information; market efficiency; gambling;

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • D0 - Microeconomics - - General
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

    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:bir:birmec:11-19. 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: (Colin Rowat). General contact details of provider: http://edirc.repec.org/data/debhauk.html .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.