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Price distortions and public information: theory, experiments and simulations

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  • Ruiz-Buforn, Alba
  • Alfarano, Simone
  • Camacho-Cuena, Eva

Abstract

This paper studies the effects on the asset price of the introduction of a public signal in the presence of asymmetric private information in a decentralized market. We introduce an artificial market model populated by boundedly rational agents with heterogeneous levels of reasoning: sophisticated and naive traders. The model captures the main impacts of public information analyzed in the laboratory experiments reported by Ruiz-Buforn et al. (2019). Public information, when correct, coordinates market activity, improving price convergence to the fundamentals. By contrast, unwarranted public information pushes prices away from fundamentals. This strong influence of public information on prices is primarily driven by its common knowledge property.

Suggested Citation

  • Ruiz-Buforn, Alba & Alfarano, Simone & Camacho-Cuena, Eva, 2019. "Price distortions and public information: theory, experiments and simulations," MPRA Paper 93288, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:93288
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    File URL: https://mpra.ub.uni-muenchen.de/93288/1/MPRA_paper_93288.pdf
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    References listed on IDEAS

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    1. Plott, Charles R & Sunder, Shyam, 1982. "Efficiency of Experimental Security Markets with Insider Information: An Application of Rational-Expectations Models," Journal of Political Economy, University of Chicago Press, vol. 90(4), pages 663-698, August.
    2. Plott, Charles R & Sunder, Shyam, 1988. "Rational Expectations and the Aggregation of Diverse Information in Laboratory Security Markets," Econometrica, Econometric Society, vol. 56(5), pages 1085-1118, September.
    3. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    4. Darrell Duffie, 2012. "Over-The-Counter Markets," Introductory Chapters,in: Dark Markets: Asset Pricing and Information Transmission in Over-the-Counter Markets Princeton University Press.
    5. Darrell Duffie & Gustavo Manso, 2007. "Information Percolation in Large Markets," American Economic Review, American Economic Association, vol. 97(2), pages 203-209, May.
    6. Duffie, Darrell & Malamud, Semyon & Manso, Gustavo, 2015. "Reprint of: Information percolation in segmented markets," Journal of Economic Theory, Elsevier, vol. 158(PB), pages 838-869.
    7. Camerer, Colin & Weigelt, Keith, 1991. "Information Mirages in Experimental Asset Markets," The Journal of Business, University of Chicago Press, vol. 64(4), pages 463-493, October.
    8. 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.
    9. Colin F. Camerer & Teck-Hua Ho & Juin-Kuan Chong, 2004. "A Cognitive Hierarchy Model of Games," The Quarterly Journal of Economics, Oxford University Press, vol. 119(3), pages 861-898.
    10. Stephen Morris & Hyun Song Shin, 2002. "Social Value of Public Information," American Economic Review, American Economic Association, vol. 92(5), pages 1521-1534, December.
    11. Ruiz-Buforn, Alba & Alfarano, Simone & Camacho-Cuena, Eva & Morone, Andrea, 2018. "Crowding out effect and traders' overreliance on public information in financial markets: a lesson from the lab," MPRA Paper 88866, University Library of Munich, Germany.
    12. Darrell Duffie, 2012. "Dark Markets: Asset Pricing and Information Transmission in Over-the-Counter Markets," Economics Books, Princeton University Press, edition 1, number 9623, March.
    13. Franklin Allen & Stephen Morris & Hyun Song Shin, 2006. "Beauty Contests and Iterated Expectations in Asset Markets," Review of Financial Studies, Society for Financial Studies, vol. 19(3), pages 719-752.
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    More about this item

    Keywords

    Public information; asset markets; asymmetric information;

    JEL classification:

    • C90 - Mathematical and Quantitative Methods - - Design of Experiments - - - General
    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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