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Profiting On Inefficiencies In Betting Derivative Markets: The Case Of Uefa Euro 2012

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  • Dominic Cortis
  • Steve Hales
  • Frank Bezzina

Abstract

This paper investigates whether it is possible to profit from market inefficiencies on betting exchanges during short tournaments. We describe how a Monte Carlo simulation method, with an inbuilt noise parameter applied on '1X2' markets, can be used to determine odds for derivative markets. In cases of mismatch between model and market odds, a modified Kelly strategy is proposed to determine the percentage of own funds placed against the market. When this proposal is applied to the UEFA European Nations association football tournament 2012, two important findings emerge: (a) a profit of circa 12% of allocated funds was generated, and (b) the profit is not contingent on the noise parameter, thus indicating the possibility of arbitrage between different betting markets. The proposed method can be extended to other sports provided the competition consists of a group stage held over a short period of time.

Suggested Citation

  • Dominic Cortis & Steve Hales & Frank Bezzina, 2013. "Profiting On Inefficiencies In Betting Derivative Markets: The Case Of Uefa Euro 2012," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 7(1), pages 39-51.
    • Handle: RePEc:buc:jgbeco:v:7:y:2013:i:1:p:39-51
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    References listed on IDEAS

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    8. 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.
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    Cited by:

    1. Dominic Cortis, 2015. "Expected Values And Variances In Bookmaker Payouts: A Theoretical Approach Towards Setting Limits On Odds," Journal of Prediction Markets, University of Buckingham Press, vol. 9(1), pages 1-14.
    2. Philip W. S. Newall & Dominic Cortis, 2021. "Are Sports Bettors Biased toward Longshots, Favorites, or Both? A Literature Review," Risks, MDPI, vol. 9(1), pages 1-9, January.
    3. Vincenzo Candila & Lucio Palazzo, 2020. "Neural Networks and Betting Strategies for Tennis," Risks, MDPI, vol. 8(3), pages 1-19, June.
    4. Buhagiar, Ranier & Cortis, Dominic & Newall, Philip W.S., 2018. "Why do some soccer bettors lose more money than others?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 18(C), pages 85-93.

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    More about this item

    Keywords

    Euro 2012; Arbitrage; Betting; Monte Carlo; Betfair; Modeling;
    All these keywords.

    JEL classification:

    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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