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Arbitrage Strategies for Cross-Track Betting on Major Horse Races

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  • Hausch, Donald B
  • Ziemba, William T

Abstract

Cross-track betting permits bettors to place their local tracks on a race being run at another track. Since each track operates a separate betting pool, the odds can vary across the tracks. The data suggest that the odds vary, and they often vary dramatically, allowing arbitrage opportunities. This article employs a risk-free arbitrage model to demonstrate the cross-track inefficiency and recommends an optimal capital growth model for exploiting it. A simple method is proposed for a single bettor at a single cross track. The results indicate that these methods would have worked well in practice on a number of recent Triple Crown races. Copyright 1990 by the University of Chicago.

Suggested Citation

  • Hausch, Donald B & Ziemba, William T, 1990. "Arbitrage Strategies for Cross-Track Betting on Major Horse Races," The Journal of Business, University of Chicago Press, vol. 63(1), pages 61-78, January.
    • Handle: RePEc:ucp:jnlbus:v:63:y:1990:i:1:p:61-78
    DOI: 10.1086/296483
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    Cited by:

    1. Martin Kukuk & Stefan Winter, 2008. "An Alternative Explanation of the Favorite-Longshot Bias," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 2(2), pages 79-96, September.
    2. Egon Franck & Erwin Verbeek & Stephan Nüesch, 2013. "Inter-market Arbitrage in Betting," Economica, London School of Economics and Political Science, vol. 80(318), pages 300-325, April.
    3. Marshall, Ben R., 2009. "How quickly is temporary market inefficiency removed?," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 917-930, August.
    4. Alasdair Brown, 2013. "Information Acquisition in Ostensibly Efficient Markets," University of East Anglia Applied and Financial Economics Working Paper Series 043, School of Economics, University of East Anglia, Norwich, UK..
    5. John Board & Charles Sutcliffe & William T. Ziemba, 2003. "Applying Operations Research Techniques to Financial Markets," Interfaces, INFORMS, vol. 33(2), pages 12-24, April.
    6. Egon Franck & Erwin Verbeek & Stephan Nuesch, 2009. "Inter- market Arbitrage in Sports Betting," NCER Working Paper Series 48, National Centre for Econometric Research.
    7. Bernardo, Giovanni & Ruberti, Massimo & Verona, Roberto, 2015. "Testing semi-strong efficiency in a fixed odds betting market: Evidence from principal European football leagues," MPRA Paper 66414, University Library of Munich, Germany.
    8. Bernardo, Giovanni & Ruberti, Massimo & Verona, Roberto, 2019. "Semi-strong inefficiency in the fixed odds betting market: Underestimating the positive impact of head coach replacement in the main European soccer leagues," The Quarterly Review of Economics and Finance, Elsevier, vol. 71(C), pages 239-246.
    9. Masahiro Ashiya, 2015. "Lock! Risk-Free Arbitrage in the Japanese Racetrack Betting Market," Journal of Sports Economics, , vol. 16(3), pages 322-330, April.
    10. M. Sung & J. E. V. Johnson, 2010. "Revealing Weak‐Form Inefficiency in a Market for State Contingent Claims: The Importance of Market Ecology, Modelling Procedures and Investment Strategies," Economica, London School of Economics and Political Science, vol. 77(305), pages 128-147, January.
    11. David Edelman & Nigel O'Brian, 2004. "Tote arbitrage and lock opportunities in racetrack betting," The European Journal of Finance, Taylor & Francis Journals, vol. 10(5), pages 370-378.
    12. Martin S. Fridson, 1993. "I'Ve Got The Horse Right Here: Sports Betting And Market Efficiency," Journal of Applied Corporate Finance, Morgan Stanley, vol. 6(2), pages 88-90, June.
    13. W. David Walls & Kelly Busche, 1996. "Betting volume and market efficiency in Hong Kong race track betting," Applied Economics Letters, Taylor & Francis Journals, vol. 3(12), pages 783-787.
    14. Swidler, Steve & Shaw, Ron, 1995. "Racetrack wagering and the "uninformed" bettor: A study of market efficiency," The Quarterly Review of Economics and Finance, Elsevier, vol. 35(3), pages 305-314.
    15. Strumbelj, E. & Sikonja, M. Robnik, 2010. "Online bookmakers' odds as forecasts: The case of European soccer leagues," International Journal of Forecasting, Elsevier, vol. 26(3), pages 482-488, July.
    16. Nikolaos Vlastakis & George Dotsis & Raphael N. Markellos, 2009. "How efficient is the European football betting market? Evidence from arbitrage and trading strategies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(5), pages 426-444.
    17. Stefan Winter & Martin Kukuk, 2008. "Do horses like vodka and sponging? - On market manipulation and the favourite-longshot bias," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 75-87.

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