IDEAS home Printed from
   My bibliography  Save this paper

Information Aggregation with Heterogeneous Traders


  • Cary Deck

    (Department of Economics, Finance and Legal Studies, University of Alabama and Economic Science Institute, Chapman University)

  • Tae In Jun

    (Department of Economics, Finance and Legal Studies, University of Alabama)

  • Laura Razzolini

    (Department of Economics, Finance and Legal Studies, University of Alabama)

  • Tavoy Reid

    (Department of Economics, Finance and Legal Studies, University of Alabama)


The efficient market hypothesis predicts that asset prices reflect all available information. A seminal experiment reported that contingent claim markets could yield market outcomes consistent with information aggregation when traders hold heterogeneous state-contingent values. However, a recent experiment found the rational expectation model outperformed the prior information and maxi-min models in contingent claim markets when traders hold homogeneous values despite the no trade equilibrium in that setting. But that same study failed to replicate the original result calling into question when, if ever, prices reliably reflect the aggregate information of traders with heterogeneous values. In this paper, we show contingent claim markets can robustly yield prices consistent with the efficient market hypothesis when traders hold heterogeneous values in certain circumstances. The key distinction between our environment and that of the previous studies is that we consider trader values that are correlated and not too dissimilar.

Suggested Citation

  • Cary Deck & Tae In Jun & Laura Razzolini & Tavoy Reid, 2022. "Information Aggregation with Heterogeneous Traders," Working Papers 22-13, Chapman University, Economic Science Institute.
  • Handle: RePEc:chu:wpaper:22-13

    Download full text from publisher

    File URL:
    Download Restriction: no

    More about this item


    Information Aggregation; Rational Expectations; Laboratory Experiments;
    All these keywords.

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • G1 - Financial Economics - - General Financial Markets

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:chu:wpaper:22-13. 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: Megan Luetje (email available below). General contact details of provider: .

    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.