IDEAS home Printed from https://ideas.repec.org/p/rdg/emxxdp/em-dp2018-02.html
   My bibliography  Save this paper

Prediction Markets and Poll Releases: When Are Prices Most Informative?

Author

Listed:
  • Alasdair Brown

    (University of East Anglia)

  • James Reade

    (Department of Economics, University of Reading)

  • Leighton Vaughan Williams

    (Nottingham Business School)

Abstract

Prediction markets are a popular platform for eliciting incentivised crowd predictions. In this paper, we examine variation in the information contained in prediction market prices by studying Intrade prices on U.S. elections around the release of opinion polls. We find that poll releases stimulate an immediate uptick in trading activity. However, much of this activity involves relatively inexperienced traders and, as a result, price efficiency declines in the immediate aftermath of a poll release. It is not until more experienced traders enter the market in the following ours that price efficiency recovers. More generally, this suggests that information releases do not necessarily improve prediction market forecasts, but may instead attract noise traders who temporarily reduce price efficiency.

Suggested Citation

  • Alasdair Brown & James Reade & Leighton Vaughan Williams, 2018. "Prediction Markets and Poll Releases: When Are Prices Most Informative?," Economics Discussion Papers em-dp2018-02, Department of Economics, University of Reading.
  • Handle: RePEc:rdg:emxxdp:em-dp2018-02
    as

    Download full text from publisher

    File URL: http://www.reading.ac.uk/web/FILES/economics/emdp2018134.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. De Long, J Bradford, et al, 1990. "Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Journal of Finance, American Finance Association, vol. 45(2), pages 379-395, June.
    2. Alasdair Brown & Dooruj Rambaccussing & J. James Reade & Giambattista Rossi, 2016. "Using Social Media to Identify Market Inefficiencies: Evidence from Twitter and Betfair," Dundee Discussion Papers in Economics 293, Economic Studies, University of Dundee.
    3. 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.
    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. Tai, Chung-Ching & Lin, Hung-Wen & Chie, Bin-Tzong & Tung, Chen-Yuan, 2019. "Predicting the failures of prediction markets: A procedure of decision making using classification models," International Journal of Forecasting, Elsevier, vol. 35(1), pages 297-312.
    2. Brown, Alasdair & Reade, J. James & Vaughan Williams, Leighton, 2019. "When are prediction market prices most informative?," International Journal of Forecasting, Elsevier, vol. 35(1), pages 420-428.
    3. Dmitry Dagaev & Egor Stoyan, 2019. "Parimutuel Betting On The Esports Duels: Reverse Favourite-Longshot Bias And Its Determinants," HSE Working papers WP BRP 216/EC/2019, National Research University Higher School of Economics.
    4. Harrison Hong & Terence Lim & Jeremy C. Stein, 2000. "Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies," Journal of Finance, American Finance Association, vol. 55(1), pages 265-295, February.
    5. Angelidis, Dimitrios & Koulakiotis Athanasios & Kiohos Apostolos, 2018. "Feedback Trading Strategies: The Case of Greece and Cyprus," South East European Journal of Economics and Business, Sciendo, vol. 13(1), pages 93-99, June.
    6. Lo, Andrew W & MacKinlay, A Craig, 1990. "When Are Contrarian Profits Due to Stock Market Overreaction?," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 175-205.
    7. 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.
    8. Seungwook Bahng, 2003. "Do Psychological Barriers Exist in the Stock Price Indices? Evidence from Asia's Emerging Markets," International Area Studies Review, Center for International Area Studies, Hankuk University of Foreign Studies, vol. 6(1), pages 35-52, March.
    9. Giusti, G. & Noussair, C.N. & Voth, H-J., 2013. "Recreating the South Sea Bubble : Lessons from an Experiment in Financial History," Discussion Paper 2013-042, Tilburg University, Center for Economic Research.
    10. Barge-Gil, Andrés & García-Hiernaux, Alfredo, 2019. "Staking plans in sports betting under unknown true probabilities of the event," MPRA Paper 92196, University Library of Munich, Germany.
    11. Sheridan Titman & Chishen Wei. Wei & Bin Zhao, 2021. "Corporate Actions and the Manipulation of Retail Investors in China: An Analysis of Stock Splits," NBER Working Papers 29212, National Bureau of Economic Research, Inc.
    12. Berna Kirkulak & Çagnur Kaytmaz Balsari, 2009. "Inflation Accounting and Stock Returns: Evidence From Istanbul Stock Exchange (ISE)," Istanbul Stock Exchange Review, Research and Business Development Department, Borsa Istanbul, vol. 11(42), pages 19-34.
    13. Brian Aitken, 1998. "Have Institutional Investors Destabilized Emerging Markets?," Contemporary Economic Policy, Western Economic Association International, vol. 16(2), pages 173-184, April.
    14. Bernardina Algieri, 2014. "A roller coaster ride: an empirical investigation of the main drivers of the international wheat price," Agricultural Economics, International Association of Agricultural Economists, vol. 45(4), pages 459-475, July.
    15. Klein, A. & Urbig, D. & Kirn, S., 2008. "Who Drives the Market? Estimating a Heterogeneous Agent-based Financial Market Model Using a Neural Network Approach," MPRA Paper 14433, University Library of Munich, Germany.
    16. Enders, Zeno & Hakenes, Hendrik Hakenes, 2014. "On the Existence and Prevention of Speculative Bubbles," Working Papers 0567, University of Heidelberg, Department of Economics.
    17. Huan Xie & Jipeng Zhang, 2016. "Bubbles and experience: An experiment with a steady inflow of new traders," Southern Economic Journal, John Wiley & Sons, vol. 82(4), pages 1349-1373, April.
    18. Damir Tokic, 2014. "Legitimate speculation versus excessive speculation," Journal of Asset Management, Palgrave Macmillan, vol. 15(6), pages 378-391, December.
    19. Mark Richard & Jan Vecer, 2021. "Efficiency Testing of Prediction Markets: Martingale Approach, Likelihood Ratio and Bayes Factor Analysis," Risks, MDPI, vol. 9(2), pages 1-20, February.
    20. Assaf, Ata & Demir, Ender & Ersan, Oguz, 2024. "Detecting and date-stamping bubbles in fan tokens," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 98-113.

    More about this item

    Keywords

    prediction markets; opinion polls; price efficiency; information efficiency;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:rdg:emxxdp:em-dp2018-02. 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: Alexander Mihailov (email available below). General contact details of provider: https://edirc.repec.org/data/derdguk.html .

    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.