IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v270y2018i2p556-569.html
   My bibliography  Save this article

It takes all sorts: A heterogeneous agent explanation for prediction market mispricing

Author

Listed:
  • Restocchi, Valerio
  • McGroarty, Frank
  • Gerding, Enrico
  • Johnson, Johnnie E.V.

Abstract

Pricing anomalies threaten the value of prediction markets as a means of harnessing the ‘wisdom of the crowd’ to make accurate forecasts. The most persistent and puzzling pricing anomaly associated with price-implied prediction probabilities is the favourite-longshot bias (FLB). We demonstrate that existing models of the FLB fail to capture its full complexity, thereby preventing appropriate adjustments to market forecasts to improve their accuracy. We develop an agent-based model with heterogeneous agents in a fixed-odds market. Our agent-based simulations and comprehensive analysis using market data demonstrate that our model explains real market behaviour, including that of market makers, better than existing theories. Importantly, our results suggest that adequately complex models are necessary to describe complex phenomena such as pricing anomalies. We discuss how our model can be used to better understand the relation between market ecology and mispricing in contexts such as options and prediction markets, consequently enhancing their predictive power.

Suggested Citation

  • Restocchi, Valerio & McGroarty, Frank & Gerding, Enrico & Johnson, Johnnie E.V., 2018. "It takes all sorts: A heterogeneous agent explanation for prediction market mispricing," European Journal of Operational Research, Elsevier, vol. 270(2), pages 556-569.
  • Handle: RePEc:eee:ejores:v:270:y:2018:i:2:p:556-569
    DOI: 10.1016/j.ejor.2018.04.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037722171830314X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2018.04.011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Buckley, Winston S. & Brown, Garfield O. & Marshall, Mario, 2012. "A mispricing model of stocks under asymmetric information," European Journal of Operational Research, Elsevier, vol. 221(3), pages 584-592.
    3. David Forrest & Ian Mchale, 2007. "Anyone for Tennis (Betting)?," The European Journal of Finance, Taylor & Francis Journals, vol. 13(8), pages 751-768.
    4. Bruno Jullien & Bernard Salanie, 2000. "Estimating Preferences under Risk: The Case of Racetrack Bettors," Journal of Political Economy, University of Chicago Press, vol. 108(3), pages 503-530, June.
    5. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    6. Raymond D. Sauer, 1998. "The Economics of Wagering Markets," Journal of Economic Literature, American Economic Association, vol. 36(4), pages 2021-2064, December.
    7. Pierre‐André Chiappori & Bernard Salanié & François Salanié & Amit Gandhi, 2019. "From Aggregate Betting Data to Individual Risk Preferences," Econometrica, Econometric Society, vol. 87(1), pages 1-36, January.
    8. 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.
    9. Rhoda, Kenneth L & Olson, Gerard T & Rappaport, Jack M, 1999. "Risk Preferences and Information Flows in Racetrack Betting Markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 22(3), pages 265-285, Fall.
    10. David Forrest & Robert Simmons, 2008. "Sentiment in the betting market on Spanish football," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 119-126.
    11. Hyun Song Shin, 2008. "Prices Of State Contingent Claims With Insider Traders, And The Favourite-Longshot Bias," World Scientific Book Chapters, in: Donald B Hausch & Victor SY Lo & William T Ziemba (ed.), Efficiency Of Racetrack Betting Markets, chapter 34, pages 343-352, World Scientific Publishing Co. Pte. Ltd..
    12. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    13. Bruce, A.C. & Johnson, J.E.V. & Peirson, J., 2012. "Recreational versus professional bettors: Performance differences and efficiency implications," Economics Letters, Elsevier, vol. 114(2), pages 172-174.
    14. Linda M. Woodland & Bill M. Woodland, 2003. "The Reverse Favourite–longshot Bias and Market Efficiency in Major League Baseball: An Update," Bulletin of Economic Research, Wiley Blackwell, vol. 55(2), pages 113-123, April.
    15. Kenneth L. Rhoda & Gerard T. Olson & Jack M. Rappaport, 1999. "Risk Preferences And Information Flows In Racetrack Betting Markets," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 22(3), pages 265-285, September.
    16. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    17. del Corral, Julio & Prieto-Rodríguez, Juan, 2010. "Are differences in ranks good predictors for Grand Slam tennis matches?," International Journal of Forecasting, Elsevier, vol. 26(3), pages 551-563, July.
    18. Ian Crawford & Krishna Pendakur, 2013. "How many types are there?," Economic Journal, Royal Economic Society, vol. 123, pages 77-95, March.
    19. Busche, Kelly & Hall, Christopher D, 1988. "An Exception to the Risk Preference Anomaly," The Journal of Business, University of Chicago Press, vol. 61(3), pages 337-346, July.
    20. James J. Heckman, 2001. "Micro Data, Heterogeneity, and the Evaluation of Public Policy: Nobel Lecture," Journal of Political Economy, University of Chicago Press, vol. 109(4), pages 673-748, August.
    21. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    22. Sveinung Arnesen & Ole Bergfjord, 2014. "Prediction markets vs polls – an examination of accuracy for the 2008 and 2012 elections," Journal of Prediction Markets, University of Buckingham Press, vol. 8(3), pages 24-33.
    23. Buckley, Winston S. & Long, Hongwei, 2015. "A discontinuous mispricing model under asymmetric information," European Journal of Operational Research, Elsevier, vol. 243(3), pages 944-955.
    24. Alan P. Kirman, 1992. "Whom or What Does the Representative Individual Represent?," Journal of Economic Perspectives, American Economic Association, vol. 6(2), pages 117-136, Spring.
    25. 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.
    26. 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.
    27. Drazen Prelec, 1998. "The Probability Weighting Function," Econometrica, Econometric Society, vol. 66(3), pages 497-528, May.
    28. Joseph Golec & Maurry Tamarkin, 1998. "Bettors Love Skewness, Not Risk, at the Horse Track," Journal of Political Economy, University of Chicago Press, vol. 106(1), pages 205-225, February.
    29. Shin, Hyun Song, 1991. "Optimal Betting Odds against Insider Traders," Economic Journal, Royal Economic Society, vol. 101(408), pages 1179-1185, September.
    30. Shin, Hyun Song, 1993. "Measuring the Incidence of Insider Trading in a Market for State-Contingent Claims," Economic Journal, Royal Economic Society, vol. 103(420), pages 1141-1153, September.
    31. Ma, Tiejun & Tang, Leilei & McGroarty, Frank & Sung, Ming-Chien & Johnson, Johnnie E. V, 2016. "Time is money: Costing the impact of duration misperception in market prices," European Journal of Operational Research, Elsevier, vol. 255(2), pages 397-410.
    32. David A. Malueg & Andrew J. Yates, 2010. "Testing Contest Theory: Evidence from Best-of-Three Tennis Matches," The Review of Economics and Statistics, MIT Press, vol. 92(3), pages 689-692, August.
    33. 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.
    34. Feess, Eberhard & Müller, Helge & Schumacher, Christoph, 2016. "Estimating risk preferences of bettors with different bet sizes," European Journal of Operational Research, Elsevier, vol. 249(3), pages 1102-1112.
    35. Michael Cain & David Law & David Peel, 2003. "The Favourite‐Longshot Bias, Bookmaker Margins and Insider Trading in a Variety of Betting Markets," Bulletin of Economic Research, Wiley Blackwell, vol. 55(3), pages 263-273, July.
    36. Berg, Joyce E. & Nelson, Forrest D. & Rietz, Thomas A., 2008. "Prediction market accuracy in the long run," International Journal of Forecasting, Elsevier, vol. 24(2), pages 285-300.
    37. 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.
    38. V. Armatas & A. Yiannakos & P. Sileloglou, 2007. "Relationship between time and goal scoring in soccer games: Analysis of three World Cups," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 7(2), pages 48-58, May.
    39. Amit Gandhi & Ricardo Serrano-Padial, 2015. "Does Belief Heterogeneity Explain Asset Prices: The Case of the Longshot Bias," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 82(1), pages 156-186.
    40. Hvattum, Lars Magnus & Arntzen, Halvard, 2010. "Using ELO ratings for match result prediction in association football," International Journal of Forecasting, Elsevier, vol. 26(3), pages 460-470, July.
    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. Emanuele Borgonovo & Marco Pangallo & Jan Rivkin & Leonardo Rizzo & Nicolaj Siggelkow, 2022. "Sensitivity analysis of agent-based models: a new protocol," Computational and Mathematical Organization Theory, Springer, vol. 28(1), pages 52-94, March.
    2. 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.
    3. Simon Kloker & Tim Straub & Christof Weinhardt, 2019. "Moderators for Partition Dependence in Prediction Markets," Group Decision and Negotiation, Springer, vol. 28(4), pages 723-756, August.
    4. Jaspersen, Johannes G., 2022. "Convex combinations in judgment aggregation," European Journal of Operational Research, Elsevier, vol. 299(2), pages 780-794.
    5. Costa Sperb, L.F. & Sung, M.-C. & Ma, T. & Johnson, J.E.V., 2022. "Turning the heat on financial decisions: Examining the role temperature plays in the incidence of bias in a time-limited financial market," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1142-1157.
    6. Dave Cliff, 2021. "BBE: Simulating the Microstructural Dynamics of an In-Play Betting Exchange via Agent-Based Modelling," Papers 2105.08310, arXiv.org.
    7. Yu, Dian & Gao, Jianjun & Wang, Tongyao, 2022. "Betting market equilibrium with heterogeneous beliefs: A prospect theory-based model," European Journal of Operational Research, Elsevier, vol. 298(1), pages 137-151.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Yu, Dian & Gao, Jianjun & Wang, Tongyao, 2022. "Betting market equilibrium with heterogeneous beliefs: A prospect theory-based model," European Journal of Operational Research, Elsevier, vol. 298(1), pages 137-151.
    3. Martin Kukuk & Stefan Winter, 2008. "An Alternative Explanation of the Favorite-Longshot Bias," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 2(2), pages 79-96, September.
    4. Stefan Winter & Martin Kukuk, 2008. "Do horses like vodka and sponging? - On market manipulation and the favourite-longshot bias," Applied Economics, Taylor & Francis Journals, vol. 40(1), pages 75-87.
    5. 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.
    6. Rebeggiani, Luca & Gross, Johannes, 2018. "Chance or Ability? The Efficiency of the Football Betting Market Revisited," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181563, Verein für Socialpolitik / German Economic Association.
    7. 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.
    8. Sung, Ming-Chien & McDonald, David C.J. & Johnson, Johnnie E.V. & Tai, Chung-Ching & Cheah, Eng-Tuck, 2019. "Improving prediction market forecasts by detecting and correcting possible over-reaction to price movements," European Journal of Operational Research, Elsevier, vol. 272(1), pages 389-405.
    9. John Peirson & Michael A. Smith, 2010. "Expert Analysis and Insider Information in Horse Race Betting: Regulating Informed Market Behavior," Southern Economic Journal, John Wiley & Sons, vol. 76(4), pages 976-992, April.
    10. Jinook Jeong & Jee Young Kim & Yoon Jae Ro, 2019. "On the efficiency of racetrack betting market: a new test for the favourite-longshot bias," Applied Economics, Taylor & Francis Journals, vol. 51(54), pages 5817-5828, November.
    11. Franke, Maximilian, 2020. "Do market participants misprice lottery-type assets? Evidence from the European soccer betting market," The Quarterly Review of Economics and Finance, Elsevier, vol. 75(C), pages 1-18.
    12. Jullien, Bruno & Salanié, Bernard, 2005. "Empirical Evidence on the Preferences of Racetrack Bettors," IDEI Working Papers 178, Institut d'Économie Industrielle (IDEI), Toulouse.
    13. Egon Franck & Erwin Verbeek & Stephan Nüesch, 2011. "Sentimental Preferences and the Organizational Regime of Betting Markets," Southern Economic Journal, John Wiley & Sons, vol. 78(2), pages 502-518, October.
    14. 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.
    15. Oliver Merz & Raphael Flepp & Egon Franck, 2019. "Does sentiment harm market efficiency? An empirical analysis using a betting exchange setting," Working Papers 381, University of Zurich, Department of Business Administration (IBW).
    16. 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.
    17. Niko Suhonen & Jani Saastamoinen & Mika Linden, 2018. "A dual theory approach to estimating risk preferences in the parimutuel betting market," Empirical Economics, Springer, vol. 54(3), pages 1335-1351, May.
    18. 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.
    19. Montone, Maurizio, 2021. "Optimal pricing in the online betting market," Journal of Economic Behavior & Organization, Elsevier, vol. 186(C), pages 344-363.
    20. Zhang, Chi & Thijssen, Jacco, 2022. "On sticky bookmaking as a learning device in horse-racing betting markets," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).

    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:eee:ejores:v:270:y:2018:i:2:p:556-569. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.