IDEAS home Printed from https://ideas.repec.org/a/buc/jpredm/v1y2007i3p219-231.html
   My bibliography  Save this article

Public Information Bias and Prediction Market Accuracy

Author

Listed:
  • Thomas S. Gruca
  • Joyce E. Berg

Abstract

How do prediction markets achieve high levels of accuracy? We propose that, in some situations, traders in prediction markets improve upon publicly available information. Specifically, when there is a known bias in publicly available information, markets provide an incentive for traders to "de-bias" this information. In such a situation, a prediction market will provide a more accurate forecast than the public information available to traders. We test our conjecture using real-money prediction markets for seven local elections in the United States. We find that the prediction market forecasts are significantly more accurate than those generated using the pre-election polls.

Suggested Citation

  • Thomas S. Gruca & Joyce E. Berg, 2007. "Public Information Bias and Prediction Market Accuracy," Journal of Prediction Markets, University of Buckingham Press, vol. 1(3), pages 219-231, December.
  • Handle: RePEc:buc:jpredm:v:1:y:2007:i:3:p:219-231
    as

    Download full text from publisher

    File URL: http://www.ingentaconnect.com/content/ubpl/jpm/2007/00000001/00000003/art00004
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Smith, Michael A. & Paton, David & Williams, Leighton Vaughan, 2009. "Do bookmakers possess superior skills to bettors in predicting outcomes?," Journal of Economic Behavior & Organization, Elsevier, vol. 71(2), pages 539-549, August.
    2. Patrick Buckley & Fergal O’Brien, 0. "The effect of malicious manipulations on prediction market accuracy," Information Systems Frontiers, Springer, vol. 0, pages 1-13.
    3. Lennart Sjöberg, 2009. "Are all crowds equally wise? a comparison of political election forecasts by experts and the public," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(1), pages 1-18.
    4. Buckley, Patrick, 2016. "Harnessing the wisdom of crowds: Decision spaces for prediction markets," Business Horizons, Elsevier, vol. 59(1), pages 85-94.
    5. 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.

    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:buc:jpredm:v:1:y:2007:i:3:p:219-231. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Dominic Cortis, University of Malta (email available below). General contact details of provider: http://www.ubpl.co.uk/ .

    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.