IDEAS home Printed from https://ideas.repec.org/a/eee/finmar/v68y2024ics1386418123000794.html
   My bibliography  Save this article

Price formation in field prediction markets: The wisdom in the crowd

Author

Listed:
  • Bossaerts, Frederik
  • Yadav, Nitin
  • Bossaerts, Peter
  • Nash, Chad
  • Todd, Torquil
  • Rudolf, Torsten
  • Hutchins, Rowena
  • Ponsonby, Anne-Louise
  • Mattingly, Karl

Abstract

Prediction markets are a successful information aggregation structure, however the exact mechanism by which private information is incorporated into the price remains poorly understood. We introduce a novel method based on the “Kyle model” to identify traders who contribute valuable information to the market price. Applied to a large field prediction market dataset, we identify traders whose trades have positive informational price impact. In contrast to others, these traders realize profit (on average) in excess of a theoretical expected informed lower bound. Results are replicated on other field prediction market datasets, providing strong evidence in favor of the Kyle model.

Suggested Citation

  • Bossaerts, Frederik & Yadav, Nitin & Bossaerts, Peter & Nash, Chad & Todd, Torquil & Rudolf, Torsten & Hutchins, Rowena & Ponsonby, Anne-Louise & Mattingly, Karl, 2024. "Price formation in field prediction markets: The wisdom in the crowd," Journal of Financial Markets, Elsevier, vol. 68(C).
  • Handle: RePEc:eee:finmar:v:68:y:2024:i:c:s1386418123000794
    DOI: 10.1016/j.finmar.2023.100881
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1386418123000794
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.finmar.2023.100881?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. Peter Bossaerts & Charles Plott, 2004. "Basic Principles of Asset Pricing Theory: Evidence from Large-Scale Experimental Financial Markets," Review of Finance, European Finance Association, vol. 8(2), pages 135-169.
    2. Peter Bossaerts & Cary Frydman & John Ledyard, 2014. "The Speed of Information Revelation and Eventual Price Quality in Markets with Insiders: Comparing Two Theories," Review of Finance, European Finance Association, vol. 18(1), pages 1-22.
    3. Elena Asparouhova & Peter Bossaerts & Jon Eguia & William Zame, 2015. "Asset Pricing and Asymmetric Reasoning," Journal of Political Economy, University of Chicago Press, vol. 123(1), pages 66-122.
    4. Brice Corgnet & Cary Deck & Mark Desantis & Kyle Hampton & Erik O Kimbrough, 2019. "Reconsidering Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets," Working Papers halshs-02146611, HAL.
    5. Vernon L. Smith, 1962. "An Experimental Study of Competitive Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 70(2), pages 111-111.
    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. Bernhardt, Dan & Hughson, Eric, 2002. "Intraday trade in dealership markets," European Economic Review, Elsevier, vol. 46(9), pages 1697-1732, October.
    8. Forsell, Eskil & Viganola, Domenico & Pfeiffer, Thomas & Almenberg, Johan & Wilson, Brad & Chen, Yiling & Nosek, Brian A. & Johannesson, Magnus & Dreber, Anna, 2019. "Predicting replication outcomes in the Many Labs 2 study," Journal of Economic Psychology, Elsevier, vol. 75(PA).
    9. Lionel Page & Christoph Siemroth, 2021. "How Much Information Is Incorporated into Financial Asset Prices? Experimental Evidence," The Review of Financial Studies, Society for Financial Studies, vol. 34(9), pages 4412-4449.
    10. Christoph Siemroth, 2021. "When Can Decision Makers Learn from Financial Market Prices?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(6), pages 1523-1552, September.
    11. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    12. Colin F. Camerer & Anna Dreber & Felix Holzmeister & Teck-Hua Ho & Jürgen Huber & Magnus Johannesson & Michael Kirchler & Gideon Nave & Brian A. Nosek & Thomas Pfeiffer & Adam Altmejd & Nick Buttrick , 2018. "Evaluating the replicability of social science experiments in Nature and Science between 2010 and 2015," Nature Human Behaviour, Nature, vol. 2(9), pages 637-644, September.
    13. Anat R. Admati, Paul Pfleiderer, 1988. "A Theory of Intraday Patterns: Volume and Price Variability," The Review of Financial Studies, Society for Financial Studies, vol. 1(1), pages 3-40.
    14. Camerer, Colin & Dreber, Anna & Forsell, Eskil & Ho, Teck-Hua & Huber, Jurgen & Johannesson, Magnus & Kirchler, Michael & Almenberg, Johan & Altmejd, Adam & Chan, Taizan & Heikensten, Emma & Holzmeist, 2016. "Evaluating replicability of laboratory experiments in Economics," MPRA Paper 75461, University Library of Munich, Germany.
    15. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
    16. Michael Gordon & Domenico Viganola & Anna Dreber & Magnus Johannesson & Thomas Pfeiffer, 2021. "Predicting replicability—Analysis of survey and prediction market data from large-scale forecasting projects," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-14, April.
    Full references (including those not matched with items on IDEAS)

    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. Frederik Bossaerts & Nitin Yadav & Peter Bossaerts & Chad Nash & Torquil Todd & Torsten Rudolf & Rowena Hutchins & Anne-Louise Ponsonby & Karl Mattingly, 2022. "Price Formation in Field Prediction Markets: the Wisdom in the Crowd," Papers 2209.08778, arXiv.org.
    2. Brice Corgnet & Cary Deck & Mark DeSantis & Kyle Hampton & Erik O. Kimbrough, 2023. "When Do Security Markets Aggregate Dispersed Information?," Management Science, INFORMS, vol. 69(6), pages 3697-3729, June.
    3. Bergemann, Dirk & Ottaviani, Marco, 2021. "Information Markets and Nonmarkets," CEPR Discussion Papers 16459, C.E.P.R. Discussion Papers.
    4. Forsell, Eskil & Viganola, Domenico & Pfeiffer, Thomas & Almenberg, Johan & Wilson, Brad & Chen, Yiling & Nosek, Brian A. & Johannesson, Magnus & Dreber, Anna, 2019. "Predicting replication outcomes in the Many Labs 2 study," Journal of Economic Psychology, Elsevier, vol. 75(PA).
    5. Huber, Christoph & Kirchler, Michael, 2023. "Experiments in finance: A survey of historical trends," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    6. Charles N. Noussair & Steven Tucker, 2013. "Experimental Research On Asset Pricing," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 554-569, July.
    7. Arturo Macias, 2022. "Capital structure irrelevance in the laboratory: an experiment with complete and asymmetric information," Experimental Economics, Springer;Economic Science Association, vol. 25(5), pages 1418-1440, November.
    8. Fanelli, Daniele, 2020. "Metascientific reproducibility patterns revealed by informatic measure of knowledge," MetaArXiv 5vnhj, Center for Open Science.
    9. Corgnet, Brice & Deck, Cary & DeSantis, Mark & Porter, David, 2018. "Information (non)aggregation in markets with costly signal acquisition," Journal of Economic Behavior & Organization, Elsevier, vol. 154(C), pages 286-320.
    10. Jakob Grazzini, 2013. "Information dissemination in an experimentally based agent-based stock market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 179-209, April.
    11. Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2022. "Forecasting Skills in Experimental Markets: Illusion or Reality?," Management Science, INFORMS, vol. 68(7), pages 5216-5232, July.
    12. Merl, Robert & Stöckl, Thomas & Palan, Stefan, 2023. "Insider trading regulation and shorting constraints. Evaluating the joint effects of two market interventions," Journal of Banking & Finance, Elsevier, vol. 154(C).
    13. Edward Halim & Yohanes E. Riyanto & Nilanjan Roy, 2019. "Costly Information Acquisition, Social Networks, and Asset Prices: Experimental Evidence," Journal of Finance, American Finance Association, vol. 74(4), pages 1975-2010, August.
    14. Martin Barner & Francesco Feri & Charles R. Plott, 2005. "On the microstructure of price determination and information aggregation with sequential and asymmetric information arrival in an experimental asset market," Annals of Finance, Springer, vol. 1(1), pages 73-107, January.
    15. Marco Mantovani & Antonio Filippin, 2024. "When do prediction markets return average beliefs? Experimental evidence," Working Papers 532, University of Milano-Bicocca, Department of Economics.
    16. Simone Alfarano & Albert Banal-Estañol & Eva Camacho & Giulia Iori & Burcu Kapar & Rohit Rahi, 2024. "Centralized vs decentralized markets: The role of connectivity," Economics Working Papers 1877, Department of Economics and Business, Universitat Pompeu Fabra.
    17. Reitz, Stefan & Schmidt, Markus A. & Taylor, Mark P., 2009. "Financial intermediation and the role of price discrimination in a two-tier market," Discussion Paper Series 1: Economic Studies 2009,13, Deutsche Bundesbank.
    18. Biais, Bruno & Mariotti, Thomas & Moinas, Sophie & Pouget, Sébastien, 2017. "Asset Pricing and Risk Sharing in Complete Markets: An Experimental Investigation," TSE Working Papers 17-798, Toulouse School of Economics (TSE), revised Aug 2024.
    19. So, Tony, 2020. "Classroom experiments as a replication device," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 86(C).
    20. Zhou, Deqing, 2013. "Irrational confidence, imperfect and long-lived information," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 383-405.

    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:finmar:v:68:y:2024:i:c:s1386418123000794. 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/finmar .

    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.
    pFad - Phonifier reborn

    Pfad - The Proxy pFad of © 2024 Garber Painting. All rights reserved.

    Note: This service is not intended for secure transactions such as banking, social media, email, or purchasing. Use at your own risk. We assume no liability whatsoever for broken pages.


    Alternative Proxies:

    Alternative Proxy

    pFad Proxy

    pFad v3 Proxy

    pFad v4 Proxy