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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 diverse information is a cornerstone of economics and finance, and empirical evidence for such aggregation has been demonstrated in previous laboratory experiments. Most notably Plott and Sunder (1988) find clear support for the rational expectations hypothesis in their Series B and C markets. However, recent studies have called into question the robustness of these findings. In this paper, we report the result of a direct replication of the key information aggregation results presented in Plott and Sunder. We do not find the same strong evidence in support of rational expectations that Plott and Sunder report suggesting information aggregation is a fragile property of markets.

Suggested Citation

  • 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 19-11, Chapman University, Economic Science Institute.
    • Handle: RePEc:chu:wpaper:19-11
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    File URL: https://digitalcommons.chapman.edu/esi_working_papers/269/
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    References listed on IDEAS

    as
    1. Lintner, John, 1969. "The Aggregation of Investor's Diverse Judgments and Preferences in Purely Competitive Security Markets," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 4(4), pages 347-400, December.
    2. 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.
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    6. Brice Corgnet & Mark DeSantis & David Porter, 2015. "Revisiting Information Aggregation in Asset Markets: Reflective Learning & Market Efficiency," Working Papers 15-15, Chapman University, Economic Science Institute.
    7. Jürgen Huber & Martin Angerer & Michael Kirchler, 2011. "Experimental asset markets with endogenous choice of costly asymmetric information," Experimental Economics, Springer;Economic Science Association, vol. 14(2), pages 223-240, May.
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    9. Page, Lionel & Siemroth, Christoph, 2017. "An experimental analysis of information acquisition in prediction markets," Games and Economic Behavior, Elsevier, vol. 101(C), pages 354-378.
    10. 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.
    11. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    12. Peter Bossaerts, 2009. "What Decision Neuroscience Teaches Us About Financial Decision Making," Annual Review of Financial Economics, Annual Reviews, vol. 1(1), pages 383-404, November.
    13. Hanson, Robin & Oprea, Ryan & Porter, David, 2006. "Information aggregation and manipulation in an experimental market," Journal of Economic Behavior & Organization, Elsevier, vol. 60(4), pages 449-459, August.
    14. Lionel Page & Christoph Siemroth, 2021. "How Much Information Is Incorporated into Financial Asset Prices? Experimental Evidence," Review of Financial Studies, Society for Financial Studies, vol. 34(9), pages 4412-4449.
    15. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
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    Citations

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    Cited by:

    1. 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.
    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. Corgnet, Brice & DeSantis, Mark & Porter, David, 2021. "Information aggregation and the cognitive make-up of market participants," European Economic Review, Elsevier, vol. 133(C).
    4. 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.
    5. 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.
    6. 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.
    7. Peeters, Ronald & Vorstaz, Marc, 2022. "An experimental analysis of contagion in financial markets," DES - Working Papers. Statistics and Econometrics. WS 31230, Universidad Carlos III de Madrid. Departamento de Estadística.

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    More about this item

    Keywords

    Aggregation; Efficient Markets; Rational Expectations; Experiments; Replication;
    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

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