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Information, prices and efficiency in an online betting market

Author

Listed:
  • Guy Elaad

    (Department of Economics and Business Management, Ariel University)

  • J. James Reade

    (Department of Economics, University of Reading)

  • Carl Singleton

    (Department of Economics, University of Reading)

Abstract

We contribute to the discussion on betting market efficiency by studying the odds (or prices) set by fifty-one online bookmakers, for the result outcomes in over 16,000 association football matches in England since 2010. Adapting a methodology typically used to evaluate forecast efficiency, we test the Efficient Market Hypothesis in this context. We find odds are generally not biased when compared against actual match outcomes, both in terms of favourite-longshot or outcome types. But individual bookmakers are not efficient. Their own odds do not appear to use fully the information contained in their competitors' odds.

Suggested Citation

  • Guy Elaad & J. James Reade & Carl Singleton, 2019. "Information, prices and efficiency in an online betting market," Economics Discussion Papers em-dp2019-10, Department of Economics, University of Reading.
    • Handle: RePEc:rdg:emxxdp:em-dp2019-10
    as

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    File URL: http://www.reading.ac.uk/web/FILES/economics/emdp201910.pdf
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. J Reade & C Singleton & L Vaughan Williams, 2020. "Betting Markets for English Premier League Results and Scorelines: Evaluating a Simple Forecasting Model," Economic Issues Journal Articles, Economic Issues, vol. 25(1), pages 87-106, March.
    2. Luca De Angelis & J. James Reade, 2022. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Economics Discussion Papers em-dp2022-01, Department of Economics, University of Reading.
    3. Kai Fischer & Justus Haucap, 2020. "Betting Market Efficiency in the Presence of Unfamiliar Shocks: The Case of Ghost Games during the Covid-19 Pandemic," CESifo Working Paper Series 8526, CESifo.
    4. J. James Reade & Carl Singleton & Alasdair Brown, 2021. "Evaluating strange forecasts: The curious case of football match scorelines," Scottish Journal of Political Economy, Scottish Economic Society, vol. 68(2), pages 261-285, May.
    5. Guy Elaad, 2020. "Home-field advantage and biased prediction markets in English soccer," Applied Economics Letters, Taylor & Francis Journals, vol. 27(14), pages 1170-1174, July.
    6. Kai Fischer & Justus Haucap, 2022. "Home advantage in professional soccer and betting market efficiency: The role of spectator crowds," Kyklos, Wiley Blackwell, vol. 75(2), pages 294-316, May.
    7. He, Xue-Zhong & Treich, Nicolas, 2017. "Prediction market prices under risk aversion and heterogeneous beliefs," Journal of Mathematical Economics, Elsevier, vol. 70(C), pages 105-114.
    8. Pascal Flurin Meier & Raphael Flepp & Egon Franck, 2021. "Are sports betting markets semistrong efficient? Evidence from the COVID-19 pandemic," Working Papers 387, University of Zurich, Department of Business Administration (IBW).
    9. Goto, Shingo & Yamada, Toru, 2023. "What drives biased odds in sports betting markets: Bettors’ irrationality and the role of bookmakers," International Review of Economics & Finance, Elsevier, vol. 86(C), pages 252-270.
    10. David Winkelmann & Marius Ötting & Christian Deutscher & Tomasz Makarewicz, 2024. "Are Betting Markets Inefficient? Evidence From Simulations and Real Data," Journal of Sports Economics, , vol. 25(1), pages 54-97, January.
    11. Dave Cliff, 2021. "BBE: Simulating the Microstructural Dynamics of an In-Play Betting Exchange via Agent-Based Modelling," Papers 2105.08310, arXiv.org.
    12. Ramirez, Philip & Reade, J. James & Singleton, Carl, 2023. "Betting on a buzz: Mispricing and inefficiency in online sportsbooks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1413-1423.
    13. Ruud H. Koning & Renske Zijm, 2023. "Betting market efficiency and prediction in binary choice models," Annals of Operations Research, Springer, vol. 325(1), pages 135-148, June.
    14. Luca De Angelis & J. James Reade, 2023. "Home advantage and mispricing in indoor sports’ ghost games: the case of European basketball," Annals of Operations Research, Springer, vol. 325(1), pages 391-418, June.

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    More about this item

    Keywords

    prediction markets; Efficient Market Hypothesis; favourite-longshot bias; forecast efficiency;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • Z29 - Other Special Topics - - Sports Economics - - - Other

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