IDEAS home Printed from https://ideas.repec.org/a/bla/popmgt/v29y2020i9p2077-2095.html
   My bibliography  Save this article

Anomalies in Probability Estimates for Event Forecasting on Prediction Markets

Author

Listed:
  • Ho Cheung Brian Lee
  • Jan Stallaert
  • Ming Fan

Abstract

Innovative forecasting methods using new data sources have been developed to address various problems in operations management, such as demand, sales, and event forecasts. One of the methods for forecasting events consists of prediction markets where participants can take financial positions that may generate returns depending on whether certain events occur or not. Results in experimental psychology and behavioral economics have shown that individuals, including experts, can be subject to judgment bias when making probability estimates for future events. We examine, in this study, whether prediction markets are immune to such bias in estimating event probability. We find that even when there are large numbers of transactions and high volumes of trades, probabilistic fallacies still occur. Moreover, when they occur, they tend to be persistent over a certain period of time, and they tend to happen in situations similar to the ones where individual probabilistic fallacies are reported to occur. Our results have implications for the design of prediction markets and at the same time call for caution when using forecasts generated this way.

Suggested Citation

  • Ho Cheung Brian Lee & Jan Stallaert & Ming Fan, 2020. "Anomalies in Probability Estimates for Event Forecasting on Prediction Markets," Production and Operations Management, Production and Operations Management Society, vol. 29(9), pages 2077-2095, September.
  • Handle: RePEc:bla:popmgt:v:29:y:2020:i:9:p:2077-2095
    DOI: 10.1111/poms.13175
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/poms.13175
    Download Restriction: no

    File URL: https://libkey.io/10.1111/poms.13175?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
    ---><---

    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. Forsythe, Robert & Forrest Nelson & George R. Neumann & Jack Wright, 1992. "Anatomy of an Experimental Political Stock Market," American Economic Review, American Economic Association, vol. 82(5), pages 1142-1161, December.
    3. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    4. Yates, J. Frank & Carlson, Bruce W., 1986. "Conjunction errors: Evidence for multiple judgment procedures, including "signed summation"," Organizational Behavior and Human Decision Processes, Elsevier, vol. 37(2), pages 230-253, April.
    5. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    6. 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.
    7. Carlson, Bruce W. & Yates, J. Frank, 1989. "Disjunction errors in qualitative likelihood judgment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 44(3), pages 368-379, December.
    8. 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.
    9. Ruomeng Cui & Santiago Gallino & Antonio Moreno & Dennis J. Zhang, 2018. "The Operational Value of Social Media Information," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1749-1769, October.
    10. Ethan Mollick & Ramana Nanda, 2016. "Wisdom or Madness? Comparing Crowds with Expert Evaluation in Funding the Arts," Management Science, INFORMS, vol. 62(6), pages 1533-1553, June.
    11. Charness, Gary & Karni, Edi & Levin, Dan, 2010. "On the conjunction fallacy in probability judgment: New experimental evidence regarding Linda," Games and Economic Behavior, Elsevier, vol. 68(2), pages 551-556, March.
    12. Robin Hanson & Ryan Oprea, 2009. "A Manipulator Can Aid Prediction Market Accuracy," Economica, London School of Economics and Political Science, vol. 76(302), pages 304-314, April.
    13. Samayita Guha & Subodha Kumar, 2018. "Emergence of Big Data Research in Operations Management, Information Systems, and Healthcare: Past Contributions and Future Roadmap," Production and Operations Management, Production and Operations Management Society, vol. 27(9), pages 1724-1735, September.
    14. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    15. Martin Spann & Bernd Skiera, 2003. "Internet-Based Virtual Stock Markets for Business Forecasting," Management Science, INFORMS, vol. 49(10), pages 1310-1326, October.
    16. Michael Ostrovsky, 2012. "Information Aggregation in Dynamic Markets With Strategic Traders," Econometrica, Econometric Society, vol. 80(6), pages 2595-2647, November.
    17. Michael Kaestner, 2006. "Anomalous Price Behavior Following Earnings Surprises: Does Representativeness Cause Overreaction?," Post-Print halshs-03035865, HAL.
    18. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    19. Donald B. Hausch & William T. Ziemba & Mark Rubinstein, 1981. "Efficiency of the Market for Racetrack Betting," Management Science, INFORMS, vol. 27(12), pages 1435-1452, December.
    20. Kenneth Oliven & Thomas A. Rietz, 2004. "Suckers Are Born but Markets Are Made: Individual Rationality, Arbitrage, and Market Efficiency on an Electronic Futures Market," Management Science, INFORMS, vol. 50(3), pages 336-351, March.
    21. Asa B. Palley & Jack B. Soll, 2019. "Extracting the Wisdom of Crowds When Information Is Shared," Management Science, INFORMS, vol. 67(5), pages 2291-2309, May.
    22. Frank Chen & Zvi Drezner & Jennifer K. Ryan & David Simchi-Levi, 2000. "Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information," Management Science, INFORMS, vol. 46(3), pages 436-443, March.
    23. Kenneth C. Lichtendahl & Yael Grushka-Cockayne & Phillip E. Pfeifer, 2013. "The Wisdom of Competitive Crowds," Operations Research, INFORMS, vol. 61(6), pages 1383-1398, December.
    24. 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.
    25. Yossi Aviv, 2001. "The Effect of Collaborative Forecasting on Supply Chain Performance," Management Science, INFORMS, vol. 47(10), pages 1326-1343, October.
    26. Michael Kaestner, 2006. "Anomalous Price Behavior Following Earnings Surprises: Does Representativeness Cause Overreaction?," Finance, Presses universitaires de Grenoble, vol. 27(2), pages 5-31.
    27. Joyce E. Berg & Thomas A. Rietz, 2003. "Prediction Markets as Decision Support Systems," Information Systems Frontiers, Springer, vol. 5(1), pages 79-93, January.
    28. Joyce E. Berg & George R. Neumann & Thomas A. Rietz, 2009. "Searching for Google's Value: Using Prediction Markets to Forecast Market Capitalization Prior to an Initial Public Offering," Management Science, INFORMS, vol. 55(3), pages 348-361, March.
    29. 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.
    30. Ivo Blohm & Christoph Riedl & Johann Füller & Jan Marco Leimeister, 2016. "Rate or Trade? Identifying Winning Ideas in Open Idea Sourcing," Information Systems Research, INFORMS, vol. 27(1), pages 27-48, March.
    31. Justin Wolfers & Eric Zitzewitz, 2009. "Using Markets to Inform Policy: The Case of the Iraq War," Economica, London School of Economics and Political Science, vol. 76(302), pages 225-250, April.
    32. Jordan Tong & Daniel Feiler & Richard Larrick, 2018. "A Behavioral Remedy for the Censorship Bias," Production and Operations Management, Production and Operations Management Society, vol. 27(4), pages 624-643, April.
    33. Eva Regnier, 2018. "Probability Forecasts Made at Multiple Lead Times," Management Science, INFORMS, vol. 64(5), pages 2407-2426, May.
    34. Gerardine DeSanctis & R. Brent Gallupe, 1987. "A Foundation for the Study of Group Decision Support Systems," Management Science, INFORMS, vol. 33(5), pages 589-609, May.
    35. Ayse Kocabiyikoglu & Celile Itir Gogus & M. Sinan Gonul, 2015. "Revenue Management vs. Newsvendor Decisions: Does Behavioral Response Mirror Normative Equivalence?," Production and Operations Management, Production and Operations Management Society, vol. 24(5), pages 750-761, May.
    36. Richard H. Thaler, 2016. "Behavioral Economics: Past, Present, and Future," American Economic Review, American Economic Association, vol. 106(7), pages 1577-1600, July.
    37. Lian Jian & Rahul Sami, 2012. "Aggregation and Manipulation in Prediction Markets: Effects of Trading Mechanism and Information Distribution," Management Science, INFORMS, vol. 58(1), pages 123-140, January.
    38. Smith, Vernon L, 1991. "Rational Choice: The Contrast between Economics and Psychology," Journal of Political Economy, University of Chicago Press, vol. 99(4), pages 877-897, August.
    39. Tonya Boone & Ram Ganeshan & Robert L. Hicks & Nada R. Sanders, 2018. "Can Google Trends Improve Your Sales Forecast?," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1770-1774, October.
    40. Raymond Yiu Keung Lau & Wenping Zhang & Wei Xu, 2018. "Parallel Aspect‐Oriented Sentiment Analysis for Sales Forecasting with Big Data," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1775-1794, October.
    41. 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.
    42. Anthony, Joseph H, 1988. " The Interrelation of Stock and Options Market Trading-Volume Data," Journal of Finance, American Finance Association, vol. 43(4), pages 949-964, September.
    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. Karimi, Majid & Zaerpour, Nima, 2022. "Put your money where your forecast is: Supply chain collaborative forecasting with cost-function-based prediction markets," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1035-1049.

    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. Karimi, Majid & Zaerpour, Nima, 2022. "Put your money where your forecast is: Supply chain collaborative forecasting with cost-function-based prediction markets," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1035-1049.
    2. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, November.
    3. Pavel Atanasov & Phillip Rescober & Eric Stone & Samuel A. Swift & Emile Servan-Schreiber & Philip Tetlock & Lyle Ungar & Barbara Mellers, 2017. "Distilling the Wisdom of Crowds: Prediction Markets vs. Prediction Polls," Management Science, INFORMS, vol. 63(3), pages 691-706, March.
    4. Siemroth, Christoph, 2014. "Why prediction markets work : The role of information acquisition and endogenous weighting," Working Papers 14-02, University of Mannheim, Department of Economics.
    5. 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.
    6. Patrick Buckley & Fergal O’Brien, 0. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 0, pages 1-13.
    7. Stefan Palan & Jürgen Huber & Larissa Senninger, 2020. "Aggregation mechanisms for crowd predictions," Experimental Economics, Springer;Economic Science Association, vol. 23(3), pages 788-814, September.
    8. Patrick Buckley & Fergal O’Brien, 2017. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 19(3), pages 611-623, June.
    9. Boussaidi, Ramzi & AlSaggaf, Majid Ibrahim, 2022. "Contrarian profits and representativeness heuristic in the MENA stock markets," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 97(C).
    10. Edoardo Gaffeo, 2013. "Using information markets in grantmaking. An assessment of the issues involved and an application to Italian banking foundations," DEM Discussion Papers 2013/08, Department of Economics and Management.
    11. Joyce E. Berg & John Geweke & Thomas A. Rietz, 2010. "Memoirs of an indifferent trader: Estimating forecast distributions from prediction markets," Quantitative Economics, Econometric Society, vol. 1(1), pages 163-186, July.
    12. Ahrash Dianat & Christoph Siemroth, 2021. "Improving decisions with market information: an experiment on corporate prediction markets," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 143-176, March.
    13. 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.
    14. Zhao, Yang & Yu, Min-Teh, 2020. "Predicting catastrophe risk: Evidence from catastrophe bond markets," Journal of Banking & Finance, Elsevier, vol. 121(C).
    15. Lawrence Choo & Todd R. Kaplan & Ro’i Zultan, 2019. "Information aggregation in Arrow–Debreu markets: an experiment," Experimental Economics, Springer;Economic Science Association, vol. 22(3), pages 625-652, September.
    16. Bergemann, Dirk & Ottaviani, Marco, 2021. "Information Markets and Nonmarkets," CEPR Discussion Papers 16459, C.E.P.R. Discussion Papers.
    17. Xiangyu Chang & Yinghui Huang & Mei Li & Xin Bo & Subodha Kumar, 2021. "Efficient Detection of Environmental Violators: A Big Data Approach," Production and Operations Management, Production and Operations Management Society, vol. 30(5), pages 1246-1270, May.
    18. Victor Tiberius & Christoph Rasche, 2011. "Prognosemärkte," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 21(4), pages 467-472, April.
    19. Snowberg, Erik & Wolfers, Justin & Zitzewitz, Eric, 2013. "Prediction Markets for Economic Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 657-687, Elsevier.
    20. Dilger, Alexander, 2016. "Bedingte Aktiengeschäfte," Discussion Papers of the Institute for Organisational Economics 08/2016, University of Münster, Institute for Organisational Economics.

    More about this item

    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:bla:popmgt:v:29:y:2020:i:9:p:2077-2095. 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: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1937-5956 .

    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.