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Reconsidering Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets

Author

Listed:
  • Brice Corgnet

    (Emlyon Business School)

  • Cary Deck

    (University of Alabama
    Chapman University)

  • Mark DeSantis

    (Chapman University)

  • Kyle Hampton

    (Chapman University)

  • Erik O. Kimbrough

    (Chapman University)

Abstract

The ability of markets to aggregate dispersed information is a cornerstone of economics and finance. In a seminal experiment, Plott and Sunder (1988) offer support for the rational expectations hypothesis. However, recent laboratory experiments have called into question the robustness of those initial results. In this paper, we offer the first attempt to directly replicate key findings of the original study. Failing to replicate their results, the post-study probability that market performance is better described by rational expectations than the prior information (Walrasian) model is low. Given this result, we introduce a new treatment that implements a market structure consistent with naturally occurring prediction markets, which can be viewed as completing the original experimental design. In this new treatment, we find strong support for the rational expectations model. Thus, while the original paper showed conditions where markets can aggregate information, we attempt to identify sufficient conditions for such aggregation to be robust.

Suggested Citation

  • Brice Corgnet & Cary Deck & Mark DeSantis & Kyle Hampton & Erik O. Kimbrough, 2020. "Reconsidering Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets," Working Papers 20-03, Chapman University, Economic Science Institute.
    • Handle: RePEc:chu:wpaper:20-03
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    File URL: https://digitalcommons.chapman.edu/esi_working_papers/296/
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    Cited by:

    1. Andrea Albertazzi & Friederike Mengel & Ronald Peeters, 2021. "Benchmarking information aggregation in experimental markets," Economic Inquiry, Western Economic Association International, vol. 59(4), pages 1500-1516, October.
    2. 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).
    3. 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.
    4. 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.
    5. Corgnet, Brice & DeSantis, Mark & Porter, David, 2021. "Information aggregation and the cognitive make-up of market participants," European Economic Review, Elsevier, vol. 133(C).
    6. Zehao Liu & Chengbo Xie, 2023. "Haircuts, interest rates, and credit cycles," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 76(1), pages 69-109, July.
    7. Peeters, Ronald & Veiga, Helena & Vorsatz, Marc, 2025. "An experimental analysis of contagion in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 171(C).
    8. Brice Corgnet & Mark DeSantis & David Porter, 2020. "Information Aggregation and the Cognitive Make-up of Traders," Working Papers 20-18, Chapman University, Economic Science Institute.

    More about this item

    Keywords

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    JEL classification:

    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments

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