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Prediction Accuracy of Different Market Structures – Bookmakers versus a Betting Exchange

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Author Info

  • Egon Franck

    ()
    (Institute for Strategy and Business Economics, University of Zurich)

  • Erwin Verbeek

    ()
    (Institute for Strategy and Business Economics, University of Zurich)

  • Stephan Nüesch

    ()
    (Institute for Strategy and Business Economics, University of Zurich)

Abstract

There is a well-established literature on separately testing the prediction power of different betting market settings. This paper provides an inter-market comparison of the forecasting accuracy between bookmakers and a major betting exchange. Employing a dataset covering all football matches played in the major leagues of the “Big Five” (England, France, Germany, Italy, Spain) during three seasons (5478 games in total), we find evidence that the betting exchange provides more accurate predictions of the same underlying event than bookmakers. A simple betting strategy of selecting bets for which bookmakers offer lower probabilities(higher odds) than the bet exchange generates above average and, in some cases, even positive returns.

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File URL: http://repec.business.uzh.ch/RePEc/rsd/CRSA_WPS/25_CRSA_full.pdf
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Bibliographic Info

Paper provided by University of Zurich, Center for Research in Sports Administration (CRSA) in its series Working Papers with number 0025.

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Length: 25 pages
Date of creation: 2008
Date of revision: 2009
Publication status: Forthcoming International Journal of Forecasting
Handle: RePEc:rsd:wpaper:0025

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Related research

Keywords: Nprediction accuracy; betting; bookmaker; betting exchange; probit regression;

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References

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  1. Cain, Michael & Law, David & Peel, David, 2000. "The Favourite-Longshot Bias and Market Efficiency in UK Football Betting," Scottish Journal of Political Economy, Scottish Economic Society, vol. 47(1), pages 25-36, February.
  2. Wolfers, Justin & Zitzewitz, Eric, 2004. "Prediction Markets," Working paper 259, Regulation2point0.
  3. David Forrest & Robert Simmons, 2008. "Sentiment in the betting market on Spanish football," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 119-126.
  4. Ioannis Asimakopoulos & John Goddard, 2004. "Forecasting football results and the efficiency of fixed-odds betting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(1), pages 51-66.
  5. Martin Spann & Bernd Skiera, 2003. "Internet-Based Virtual Stock Markets for Business Forecasting," Management Science, INFORMS, vol. 49(10), pages 1310-1326, October.
  6. Â Egon Franck & Â Erwin Verbeek & Â Stephan Nuesch, . "Â Sentimental Preferences and the Organizational Regime of Betting Markets," Working Papers 0089, University of Zurich, Institute for Strategy and Business Economics (ISU), revised 2010.
  7. repec:reg:rpubli:259 is not listed on IDEAS
  8. Martin Spann & Bernd Skiera, 2009. "Sports forecasting: a comparison of the forecast accuracy of prediction markets, betting odds and tipsters," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 55-72.
  9. 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.
  10. Dixon, Mark J. & Pope, Peter F., 2004. "The value of statistical forecasts in the UK association football betting market," International Journal of Forecasting, Elsevier, vol. 20(4), pages 697-711.
  11. Boulier, Bryan L. & Stekler, H. O., 2003. "Predicting the outcomes of National Football League games," International Journal of Forecasting, Elsevier, vol. 19(2), pages 257-270.
  12. Karen Croxson & J. James Reade, 2011. "Information and Efficiency: Goal Arrival in Soccer Betting," Discussion Papers 11-01, Department of Economics, University of Birmingham.
  13. Berg, Joyce E. & Nelson, Forrest D. & Rietz, Thomas A., 2008. "Prediction market accuracy in the long run," International Journal of Forecasting, Elsevier, vol. 24(2), pages 285-300.
  14. Forrest, David & Goddard, John & Simmons, Robert, 2005. "Odds-setters as forecasters: The case of English football," International Journal of Forecasting, Elsevier, vol. 21(3), pages 551-564.
  15. Vaughan Williams, Leighton, 1999. "Information Efficiency in Betting Markets: A Survey," Bulletin of Economic Research, Wiley Blackwell, vol. 51(1), pages 1-30, January.
  16. Dobson,Stephen & Goddard,John, 2011. "The Economics of Football," Cambridge Books, Cambridge University Press, number 9780521517140, October.
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Citations

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Cited by:
  1. Štrumbelj, Erik & Vračar, Petar, 2012. "Simulating a basketball match with a homogeneous Markov model and forecasting the outcome," International Journal of Forecasting, Elsevier, vol. 28(2), pages 532-542.
  2. Babatunde Buraimo & David Peel & Rob Simmons, 2013. "Systematic Positive Expected Returns in the UK Fixed Odds Betting Market: An Analysis of the Fink Tank Predictions," International Journal of Financial Studies, MDPI, Open Access Journal, vol. 1(4), pages 168-182, December.
  3. St'ephane Dupraz & Daniel Muller & Lionel Page, 2013. "Tactical Voting and Voter's Sophistication in British Elections," QuBE Working Papers 011, QUT Business School.
  4. Raphael Flepp & Stephan Nüesch & Egon Franck, 2013. " The Liquidity Advantage of Quote-driven Markets: Evidence from the Betting Industry," Working Papers 342, University of Zurich, Department of Business Administration (IBW).
  5. 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.

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