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

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. Justin Wolfers & Eric Zitzewitz, 2004. "Prediction Markets," Journal of Economic Perspectives, American Economic Association, vol. 18(2), pages 107-126, Spring.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Shin, Hyun Song, 1993. "Measuring the Incidence of Insider Trading in a Market for State-Contingent Claims," Economic Journal, Royal Economic Society, vol. 103(420), pages 1141-1153, September.
    8. 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.
    9. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    10. Hasbrouck, Joel, 1995. "One Security, Many Markets: Determining the Contributions to Price Discovery," Journal of Finance, American Finance Association, vol. 50(4), pages 1175-1199, September.
    11. Paul Klemperer, 1987. "Markets with Consumer Switching Costs," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(2), pages 375-394.
    12. repec:bla:econom:v:56:y:1989:i:223:p:323-41 is not listed on IDEAS
    13. 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.
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    Citations

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    Cited by:

    1. Leighton Vaughan Williams & J. James Reade, 2016. "Prediction Markets, Social Media and Information Efficiency," Kyklos, Wiley Blackwell, vol. 69(3), pages 518-556, August.
    2. James Reade, 2014. "Information And Predictability: Bookmakers, Prediction Markets And Tipsters As Forecasters," Journal of Prediction Markets, University of Buckingham Press, vol. 8(1), pages 43-76.
    3. 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, H. O. Stekler Research Program on Forecasting.
    4. James Reade, 2014. "Detecting corruption in football," Chapters, in: John Goddard & Peter Sloane (ed.), Handbook on the Economics of Professional Football, chapter 25, pages 419-446, Edward Elgar Publishing.
    5. 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.
    6. John Goddard & Peter Sloane (ed.), 2014. "Handbook on the Economics of Professional Football," Books, Edward Elgar Publishing, number 14821.

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    More about this item

    Keywords

    Information; market efficiency; gambling;
    All these keywords.

    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

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