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The Distribution of Information and the Price Efficiency of Markets

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  • Brice Corgnet

    (EMLYON Business School)

  • Mark DeSantis

    (Argyros School of Business and Economics & Economic Science Institute, Chapman University)

  • David Porter

    (Argyros School of Business and Economics & Economic Science Institute, Chapman University)

Abstract

Apparently contradictory evidence has accumulated regarding the extent to which financial markets are informationally efficient. Shedding new light on this old debate, we show that differences in the distribution of private information may explain why informational efficiency can vary greatly across markets. We find that markets are informationally efficient when complete information is concentrated in the hands of competing insiders whereas they are less efficient when private information is dispersed across traders. A learning model helps to illustrate why inferring others’ private information from prices takes more time when information is more dispersed. We discuss the implications of our findings for understanding the potential consequences of lowering the cost of information on the informational efficiency of markets.

Suggested Citation

  • Brice Corgnet & Mark DeSantis & David Porter, 2018. "The Distribution of Information and the Price Efficiency of Markets," Working Papers 18-09, Chapman University, Economic Science Institute.
    • Handle: RePEc:chu:wpaper:18-09
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    Cited by:

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    2. Brice Corgnet & Cary Deck & Mark DeSantis & David Porter, 2022. "Forecasting Skills in Experimental Markets: Illusion or Reality?," Management Science, INFORMS, vol. 68(7), pages 5216-5232, July.
    3. Brice Corgnet & Cary Deck & Mark DeSantis & Kyle Hampton & Erik O. Kimbrough, 2023. "When Do Security Markets Aggregate Dispersed Information?," Management Science, INFORMS, vol. 69(6), pages 3697-3729, June.
    4. 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.
    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. 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. Merl, Robert, 2022. "Literature review of experimental asset markets with insiders," Journal of Behavioral and Experimental Finance, Elsevier, vol. 33(C).
    8. Artem Stopochkin & Inessa Sytnik & Janusz Wielki & Nataliia Zemlianska, 2021. "Methodology for Building Trader's Investment Strategy Based on Assessment of the Market Value of the Company," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 913-935.
    9. Ahrash Dianat & Christoph Siemroth, 2021. "Improving decisions with market information: an experiment on corporate prediction markets," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 143-176, March.
    10. repec:grz:wpsses:2021-04 is not listed on IDEAS
    11. 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

    Information aggregation; information dispersion; market efficiency; experimental asset markets; learning models; cognitive finance;
    All these keywords.

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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