IDEAS home Printed from https://ideas.repec.org/p/rdg/emxxdp/em-dp2019-10.html
   My bibliography  Save this paper

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, Reading University.
  • Handle: RePEc:rdg:emxxdp:em-dp2019-10
    as

    Download full text from publisher

    File URL: http://www.reading.ac.uk/web/FILES/economics/emdp201910.pdf
    Download Restriction: no

    Other versions of this item:

    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. Yock Y. Chong & David F. Hendry, 1986. "Econometric Evaluation of Linear Macro-Economic Models," Review of Economic Studies, Oxford University Press, vol. 53(4), pages 671-690.
    4. Angelini, Giovanni & De Angelis, Luca, 2019. "Efficiency of online football betting markets," International Journal of Forecasting, Elsevier, vol. 35(2), pages 712-721.
    5. Nordhaus, William D, 1987. "Forecasting Efficiency: Concepts and Applications," The Review of Economics and Statistics, MIT Press, vol. 69(4), pages 667-674, November.
    6. 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.
    7. Pope, Peter F & Peel, David A, 1989. "Information, Prices and Efficiency in a Fixed-Odds Betting Market," Economica, London School of Economics and Political Science, vol. 56(223), pages 323-341, August.
    8. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    9. 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.
    10. Thaler, Richard H & Ziemba, William T, 1988. "Parimutuel Betting Markets: Racetracks and Lotteries," Journal of Economic Perspectives, American Economic Association, vol. 2(2), pages 161-174, Spring.
    11. 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.
    12. 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)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. J. James Reade & Carl Singleton & Leighton Vaughan Williams, 2020. "Betting markets for English Premier League results and scorelines: evaluating a forecasting model," Economics Discussion Papers em-dp2020-03, Department of Economics, Reading University.

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rdg:emxxdp:em-dp2019-10. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Carl Singleton). General contact details of provider: http://edirc.repec.org/data/derdguk.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.