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The role of surprise: Understanding overreaction and underreaction to unanticipated events using in-play soccer betting market

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  • Choi, Darwin
  • Hui, Sam K.

Abstract

Previous research in finance has found evidences of both overreaction and underreaction to unanticipated events, but has yet to explain why investors overreact to certain events while underreacting to others. In this paper, we hypothesize that while market participants generally underreact to new events due to conservatism, the extent of underreaction is moderated by “surprise,” thus causing market participants to overreact to events that are highly surprising. We test our hypothesis using data from an in-play soccer betting market, where new events (goals) are clearly and exogenously defined, and the degree of “surprise” can be directly quantified (goals scored by underdogs are more surprising). We provide both statistical and economic evidences in support of our hypothesis.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:jeborg:v:107:y:2014:i:pb:p:614-629
    DOI: 10.1016/j.jebo.2014.02.009
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    3. Romain Gauriot Author e-mail: romain.gauriot@nyu.edu & Lionel Page Author e-mail: lionel.page@uts.edu.au, 2021. "How Market Prices React to Information: Evidence from Binary Options Markets," Working Papers 20200058, New York University Abu Dhabi, Department of Social Science, revised Oct 2021.
    4. Dave Cliff & James Hawkins & James Keen & Roberto Lau-Soto, 2021. "Implementing the BBE Agent-Based Model of a Sports-Betting Exchange," Papers 2108.02419, arXiv.org.
    5. 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.
    6. 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.
    7. Markus Jung & Mischa Seiter, 2021. "Towards a better understanding on mitigating algorithm aversion in forecasting: an experimental study," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 32(4), pages 495-516, December.
    8. 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.
    9. Angelini, Giovanni & De Angelis, Luca & Singleton, Carl, 2022. "Informational efficiency and behaviour within in-play prediction markets," International Journal of Forecasting, Elsevier, vol. 38(1), pages 282-299.
    10. Marius Otting & Christian Deutscher & Carl Singleton & Luca De Angelis, 2022. "Gambling on Momentum," Papers 2211.06052, arXiv.org.
    11. 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.
    12. Tim Pawlowski & Dooruj Rambaccussing & Philip Ramirez & James & Giambattista Rossi, 2023. "Exploring Entertainment Utility from Football Games," Economics Discussion Papers em-dp2023-13, Department of Economics, University of Reading.
    13. Michels, Rouven & Ötting, Marius & Langrock, Roland, 2023. "Bettors’ reaction to match dynamics: Evidence from in-game betting," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1118-1127.
    14. 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).
    15. 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.
    16. Piccoli, Pedro & Chaudhury, Mo & Souza, Alceu, 2017. "How do stocks react to extreme market events? Evidence from Brazil," Research in International Business and Finance, Elsevier, vol. 42(C), pages 275-284.
    17. Bizzozero, Paolo & Flepp, Raphael & Franck, Egon, 2018. "The effect of fast trading on price discovery and efficiency: Evidence from a betting exchange," Journal of Economic Behavior & Organization, Elsevier, vol. 156(C), pages 126-143.
    18. Michael Ehrmann & David‐Jan Jansen, 2017. "The Pitch Rather Than the Pit: Investor Inattention, Trading Activity, and FIFA World Cup Matches," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(4), pages 807-821, June.
    19. Borgards, Oliver & Czudaj, Robert L. & Hoang, Thi Hong Van, 2021. "Price overreactions in the commodity futures market: An intraday analysis of the Covid-19 pandemic impact," Resources Policy, Elsevier, vol. 71(C).
    20. Dave Cliff, 2021. "BBE: Simulating the Microstructural Dynamics of an In-Play Betting Exchange via Agent-Based Modelling," Papers 2105.08310, arXiv.org.
    21. Paolo Bizzozero & Raphael Flepp & Egon Franck, 2017. " Insider trading and price efficiency: Evidence from a betting exchange," Working Papers 368, University of Zurich, Department of Business Administration (IBW).
    22. 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.
    23. Alasdair Brown & Dooruj Rambaccussing & J. James Reade & Giambattista Rossi, 2018. "Forecasting With Social Media: Evidence From Tweets On Soccer Matches," Economic Inquiry, Western Economic Association International, vol. 56(3), pages 1748-1763, July.

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    More about this item

    Keywords

    Over/underreaction; Unanticipated events; Surprise; Conservatism; Prediction market; Bayesian dynamic model;
    All these keywords.

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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