IDEAS home Printed from https://ideas.repec.org/p/rdg/emxxdp/em-dp2019-20.html
   My bibliography  Save this paper

Informational efficiency and behaviour within in-play prediction markets

Author

Listed:
  • Giovanni Angelini

    () (Department of Economics, University of Bologna)

  • Luca De Angelis

    () (Department of Economics, University of Bologna)

  • Carl Singleton

    () (Department of Economics, University of Reading)

Abstract

We propose a practical framework to detect mispricing, test informational efficiency and evaluate the behavioural biases within high-frequency prediction markets, especially in how prices react to news. We show this using betting exchange data for association football, exploiting the moment when the first goal is scored in a match as major news that breaks cleanly. There is mispricing in these markets and inefficiency, explained by a reverse favourite-longshot bias. This is systematically absorbed or amplified after a goal, depending on the time elapsed in the match and whether the markets expect a close match before kick-off. We find that prices respond correctly when news is expected but overreact when it is a surprise. Price movements are consistent with market participants who interpret major news in a way which confirms their prior beliefs.

Suggested Citation

  • Giovanni Angelini & Luca De Angelis & Carl Singleton, 2019. "Informational efficiency and behaviour within in-play prediction markets," Economics Discussion Papers em-dp2019-20, Department of Economics, Reading University.
  • Handle: RePEc:rdg:emxxdp:em-dp2019-20
    as

    Download full text from publisher

    File URL: http://www.reading.ac.uk/web/FILES/economics/emdp201920.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Manski, Charles F., 2006. "Interpreting the predictions of prediction markets," Economics Letters, Elsevier, vol. 91(3), pages 425-429, June.
    2. Alexis Direr, 2013. "Are betting markets efficient? Evidence from European Football Championships," Applied Economics, Taylor & Francis Journals, vol. 45(3), pages 343-356, January.
    3. Erik Snowberg & Justin Wolfers, 2010. "Explaining the Favorite-Long Shot Bias: Is it Risk-Love or Misperceptions?," Journal of Political Economy, University of Chicago Press, vol. 118(4), pages 723-746, August.
    4. Plott, Charles R & Sunder, Shyam, 1988. "Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets," Econometrica, Econometric Society, vol. 56(5), pages 1085-1118, September.
    5. 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.
    6. Marco Ottaviani & Peter Norman Sørensen, 2015. "Price Reaction to Information with Heterogeneous Beliefs and Wealth Effects: Underreaction, Momentum, and Reversal," American Economic Review, American Economic Association, vol. 105(1), pages 1-34, January.
    7. John A. List, 2004. "Testing Neoclassical Competitive Theory in Multilateral Decentralized Markets," Journal of Political Economy, University of Chicago Press, vol. 112(5), pages 1131-1156, October.
    8. 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.
    9. Koessler, Frédéric & Noussair, Charles & Ziegelmeyer, Anthony, 2012. "Information aggregation and belief elicitation in experimental parimutuel betting markets," Journal of Economic Behavior & Organization, Elsevier, vol. 83(2), pages 195-208.
    10. De Bondt, Werner F M & Thaler, Richard H, 1990. "Do Security Analysts Overreact?," American Economic Review, American Economic Association, vol. 80(2), pages 52-57, May.
    11. Angelini, Giovanni & De Angelis, Luca, 2019. "Efficiency of online football betting markets," International Journal of Forecasting, Elsevier, vol. 35(2), pages 712-721.
    12. Choi, Darwin & Hui, Sam K., 2014. "The role of surprise: Understanding overreaction and underreaction to unanticipated events using in-play soccer betting market," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 614-629.
    13. Karen Croxson & J. James Reade, 2014. "Information and Efficiency: Goal Arrival in Soccer Betting," Economic Journal, Royal Economic Society, vol. 124(575), pages 62-91, March.
    14. 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.
    15. Christian Deutscher & Bernd Frick & Marius Ötting, 2018. "Betting market inefficiencies are short-lived in German professional football," Applied Economics, Taylor & Francis Journals, vol. 50(30), pages 3240-3246, June.
    16. Ioannidis, C. & Peel, D.A., 2005. "Testing for market efficiency in gambling markets when the errors are non-normal and heteroskedastic an application of the wild bootstrap," Economics Letters, Elsevier, vol. 87(2), pages 221-226, May.
    17. Matthew Rabin, 1998. "Psychology and Economics," Journal of Economic Literature, American Economic Association, vol. 36(1), pages 11-46, March.
    18. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    19. Wolfers, Justin & Zitzewitz, Eric, 2006. "Interpreting Prediction Market Prices as Probabilities," IZA Discussion Papers 2092, Institute of Labor Economics (IZA).
    20. Charles R. Plott & Jorgen Wit & Winston C. Yang, 2003. "Parimutuel betting markets as information aggregation devices: experimental results," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 22(2), pages 311-351, September.
    21. Smith, Michael A. & Paton, David & Williams, Leighton Vaughan, 2009. "Do bookmakers possess superior skills to bettors in predicting outcomes?," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 539-549, August.
    22. Michael Cain & David Law & David Peel, 2000. "The Favourite‐Longshot Bias and Market Efficiency in UK Football betting," Scottish Journal of Political Economy, Scottish Economic Society, vol. 47(1), pages 25-36, February.
    23. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    24. Franck, Egon & Verbeek, Erwin & Nüesch, Stephan, 2010. "Prediction accuracy of different market structures -- bookmakers versus a betting exchange," International Journal of Forecasting, Elsevier, vol. 26(3), pages 448-459, July.
    25. Raymond M. Brooks & Ajay Patel & Tie Su, 2003. "How the Equity Market Responds to Unanticipated Events," The Journal of Business, University of Chicago Press, vol. 76(1), pages 109-134, January.
    26. Bo Cowgill & Eric Zitzewitz, 2015. "Corporate Prediction Markets: Evidence from Google, Ford, and Firm X," Review of Economic Studies, Oxford University Press, vol. 82(4), pages 1309-1341.
    27. Ali, Mukhtar M, 1977. "Probability and Utility Estimates for Racetrack Bettors," Journal of Political Economy, University of Chicago Press, vol. 85(4), pages 803-815, August.
    28. 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.
    29. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    30. repec:pri:cepsud:91malkiel is not listed on IDEAS
    31. Erik Snowberg & Justin Wolfers, 2010. "Explaining the Favorite-Longshot Bias: Is it Risk-Love or Misperceptions?," CESifo Working Paper Series 3029, CESifo.
    32. Chan, Wesley S., 2003. "Stock price reaction to news and no-news: drift and reversal after headlines," Journal of Financial Economics, Elsevier, vol. 70(2), pages 223-260, November.
    33. 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.
    34. Alasdair Brown, 2014. "Information Processing Constraints and Asset Mispricing," Economic Journal, Royal Economic Society, vol. 124(575), pages 245-268, March.
    35. 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.
    36. 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.
    37. 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.
    38. Kian‐Ping Lim & Robert Brooks, 2011. "The Evolution Of Stock Market Efficiency Over Time: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 69-108, February.
    39. Bruno Deschamps & Olivier Gergaud, 2007. "Efficiency in Betting Markets: Evidence from English Football," Journal of Prediction Markets, University of Buckingham Press, vol. 1(1), pages 61-73, February.
    40. 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.
    41. 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.
    42. Golec, Joseph & Tamarkin, Maurry, 1991. "The degree of inefficiency in the football betting market : Statistical tests," Journal of Financial Economics, Elsevier, vol. 30(2), pages 311-323, December.
    43. Lionel Page & Robert T. Clemen, 2013. "Do Prediction Markets Produce Well‐Calibrated Probability Forecasts?-super-," Economic Journal, Royal Economic Society, vol. 123(568), pages 491-513, May.
    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. 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.
    2. 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

    Market efficiency; Favourite-longshot bias; Mispricing; Sports forecasting; Probability forecasting; Behavioural bias; Betting strategy;

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism
    • Z2 - Other Special Topics - - Sports Economics

    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-dp2019-20. 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.