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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 study 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 & Management Discussion Papers em-dp2019-10, Henley Business School, Reading University.
  • 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
    1. 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.
    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. repec:eee:intfor:v:35:y:2019:i:2:p:712-721 is not listed on IDEAS
    4. Steven D. Levitt, 2004. "Why are gambling markets organised so differently from financial markets?," Economic Journal, Royal Economic Society, vol. 114(495), pages 223-246, April.
    5. Tim Kuypers, 2000. "Information and efficiency: an empirical study of a fixed odds betting market," Applied Economics, Taylor & Francis Journals, vol. 32(11), pages 1353-1363.
    6. 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.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    prediction markets; Efficient Market Hypothesis; favourite-longshot bias; forecast efficiency;

    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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