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Informational efficiency and behaviour within in-play prediction markets

Author

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  • 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

Studies of financial market informational efficiency have proven burdensome in practice, because it is difficult to pinpoint when news breaks and is known by some or all the participants. We overcome this by designing a framework to detect mispricing, test informational efficiency and evaluate the behavioural biases within high-frequency prediction markets. We demonstrate 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 are pre-match and in-play mispricing and inefficiency in these markets, explained by reverse favourite-longshot bias (favourite bias). The mispricing tends to increase when the major news is a surprise, such as a goal scored by a longshot team late in a match, with the market underestimating their chances of going on to win. These results suggest that, even in prediction markets with large crowds of participants trading state-contingent claims, significant informational inefficiency and behavioural biases can be reflected in prices.

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, University of Reading, revised 01 Apr 2021.
  • Handle: RePEc:rdg:emxxdp:em-dp2019-20
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    References listed on IDEAS

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    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. Jacob A. Mincer & Victor Zarnowitz, 1969. "The Evaluation of Economic Forecasts," NBER Chapters, in: Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance, pages 3-46, National Bureau of Economic Research, Inc.
    4. Flepp, Raphael & Nüesch, Stephan & Franck, Egon, 2017. "The liquidity advantage of the quote-driven market: Evidence from the betting industry," The Quarterly Review of Economics and Finance, Elsevier, vol. 64(C), pages 306-317.
    5. 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.
    6. 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.
    7. repec:feb:framed:0081 is not listed on IDEAS
    8. Leighton Vaughan Williams & Ming‐Chien Sung & Peter A. F. Fraser‐Mackenzie & John Peirson & Johnnie E. V. Johnson, 2018. "Towards an Understanding of the Origins of the Favourite–Longshot Bias: Evidence from Online Poker Markets, a Real‐money Natural Laboratory," Economica, London School of Economics and Political Science, vol. 85(338), pages 360-382, April.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. Angelini, Giovanni & De Angelis, Luca, 2019. "Efficiency of online football betting markets," International Journal of Forecasting, Elsevier, vol. 35(2), pages 712-721.
    16. 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.
    17. 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.
    18. 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.
    19. Jacob A. Mincer, 1969. "Economic Forecasts and Expectations: Analysis of Forecasting Behavior and Performance," NBER Books, National Bureau of Economic Research, Inc, number minc69-1.
    20. Woodland, Linda M & Woodland, Bill M, 1994. "Market Efficiency and the Favorite-Longshot Bias: The Baseball Betting Market," Journal of Finance, American Finance Association, vol. 49(1), pages 269-279, March.
    21. 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.
    22. 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.
    23. Alistair C. Bruce & Johnnie E. V. Johnson & John D. Peirson & Jiejun Yu, 2009. "An Examination of the Determinants of Biased Behaviour in a Market for State Contingent Claims," Economica, London School of Economics and Political Science, vol. 76(302), pages 282-303, April.
    24. Matthew Rabin, 1998. "Psychology and Economics," Journal of Economic Literature, American Economic Association, vol. 36(1), pages 11-46, March.
    25. 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.
    26. Wolfers, Justin & Zitzewitz, Eric, 2006. "Interpreting Prediction Market Prices as Probabilities," IZA Discussion Papers 2092, Institute of Labor Economics (IZA).
    27. 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.
    28. Alasdair Brown, 2015. "Information Acquisition in Ostensibly Efficient Markets," Economica, London School of Economics and Political Science, vol. 82(327), pages 420-447, July.
    29. 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.
    30. Vaughan Williams,Leighton (ed.), 2005. "Information Efficiency in Financial and Betting Markets," Cambridge Books, Cambridge University Press, number 9780521816038, September.
    31. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    32. 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.
    33. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    34. 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.
    35. 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.
    36. Bo Cowgill & Eric Zitzewitz, 2015. "Corporate Prediction Markets: Evidence from Google, Ford, and Firm X," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(4), pages 1309-1341.
    37. 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.
    38. 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.
    39. 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.
    40. repec:pri:cepsud:91malkiel is not listed on IDEAS
    41. Michael A. Smith & David Paton & Leighton Vaughan Williams, 2006. "Market Efficiency in Person‐to‐Person Betting," Economica, London School of Economics and Political Science, vol. 73(292), pages 673-689, November.
    42. 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.
    43. repec:bla:econom:v:56:y:1989:i:223:p:323-41 is not listed on IDEAS
    44. Alasdair Brown, 2014. "Information Processing Constraints and Asset Mispricing," Economic Journal, Royal Economic Society, vol. 124(575), pages 245-268, March.
    45. 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.
    46. 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.
    47. 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.
    48. 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.
    49. 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.
    50. 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.
    51. 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.
    52. 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.
    53. 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.
    54. 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.
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    3. Pawlowski, Tim & Rambaccussing, Dooruj & Ramirez, Philip & Reade, J. James & Rossi, Giambattista, 2024. "Exploring entertainment utility from football games," Journal of Economic Behavior & Organization, Elsevier, vol. 223(C), pages 185-198.
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    5. 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.
    6. Raphael Flepp & Oliver Merz & Egon Franck, 2024. "When the league table lies: Does outcome bias lead to informationally inefficient markets?," Economic Inquiry, Western Economic Association International, vol. 62(1), pages 414-429, January.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. Aitazaz Ali Raja & Pierre Pinson & Jalal Kazempour & Sergio Grammatico, 2022. "A Market for Trading Forecasts: A Wagering Mechanism," Papers 2205.02668, arXiv.org, revised Oct 2022.
    13. 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.
    14. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Economics Discussion Papers em-dp2022-10, Department of Economics, University of Reading.
      • Marius Otting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Papers 2211.06052, arXiv.org.
    15. 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.
    16. Carl Singleton & Alex Bryson & Peter Dolton & James Reade & Dominik Schreyer, 2022. "Economics lessons from sports during the COVID-19 pandemic," Chapters, in: Paul M. Pedersen (ed.), Research Handbook on Sport and COVID-19, chapter 2, pages 9-18, Edward Elgar Publishing.
    17. Marius Ötting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2023. "Gambling on Momentum in Contests," Economics Discussion Papers em-dp2023-08, Department of Economics, University of Reading.

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    More about this item

    Keywords

    Market efficiency; Favourite-longshot bias; Mispricing; Sports forecasting; Probability forecasting; Behavioural bias; Betting strategy;
    All these keywords.

    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

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