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The distribution of information and the price efficiency of markets

Author

Listed:
  • Brice Corgnet

    (EM - EMLyon Business School, GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - ENS de Lyon - École normale supérieure de Lyon - Université de Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet - Saint-Étienne - CNRS - Centre National de la Recherche Scientifique)

  • Mark Desantis

    (Chapman University)

  • David Porter

    (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.

Suggested Citation

  • Brice Corgnet & Mark Desantis & David Porter, 2019. "The distribution of information and the price efficiency of markets," Post-Print halshs-02393564, HAL.
    • Handle: RePEc:hal:journl:halshs-02393564
    DOI: 10.1016/j.jedc.2019.02.006
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    Citations

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    Cited by:

    1. Sattarhoff, Cristina & Gronwald, Marc, 2022. "Measuring informational efficiency of the European carbon market — A quantitative evaluation of higher order dependence," International Review of Financial Analysis, Elsevier, vol. 84(C).
    2. Deck, Cary & Jun, Tae In & Razzolini, Laura & Reid, Tavoy, 2024. "Information aggregation with heterogeneous traders," Journal of Behavioral and Experimental Finance, Elsevier, vol. 43(C).
    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. 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).
    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. Corgnet, Brice & DeSantis, Mark & Porter, David, 2021. "Information aggregation and the cognitive make-up of market participants," European Economic Review, Elsevier, vol. 133(C).
    10. Ahrash Dianat & Christoph Siemroth, 2021. "Correction to: Improving decisions with market information: an experiment on corporate prediction markets," Experimental Economics, Springer;Economic Science Association, vol. 24(3), pages 1074-1074, September.
    11. repec:grz:wpsses:2021-04 is not listed on IDEAS
    12. 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.

    More about this item

    Keywords

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    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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