IDEAS home Printed from https://ideas.repec.org/p/chu/wpaper/15-15.html
   My bibliography  Save this paper

Revisiting Information Aggregation in Asset Markets: Reflective Learning & Market Efficiency

Author

Listed:
  • Brice Corgnet

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

  • Mark DeSantis

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

  • David Porter

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

Abstract

The ability of markets to aggregate disperse information leading to prices that reflect the fundamental value of an asset is key to assessing the often-debated efficiency of markets. We study information aggregation in the experimental environment originally created by Plott and Sunder (1988). Contrary to the current belief, we find that markets do not aggregate information. The model that best describes our data, as well as data on information aggregation subsequent to Plott and Sunder (1988), is prior information (Lintner, 1969). That is, traders use their private information but fail to use market prices to infer other traders’ information. We argue that reflecting on asset prices to infer others’ information requires specific skills related to the concept of cognitive reflection. We develop a learning model in which only a subset of the traders possess this reflective capacity. We show, using both simulations and laboratory experiments, that information aggregation can only be achieved when the market is populated by highly reflective traders and this high level of cognitive reflection is commonly known to all of the traders.

Suggested Citation

  • 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.
  • Handle: RePEc:chu:wpaper:15-15
    as

    Download full text from publisher

    File URL: http://www.chapman.edu/research-and-institutions/economic-science-institute/_files/WorkingPapers/revisiting-info-agg-in-asset-markets.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Oechssler, Jörg & Roider, Andreas & Schmitz, Patrick W., 2009. "Cognitive abilities and behavioral biases," Journal of Economic Behavior & Organization, Elsevier, vol. 72(1), pages 147-152, October.
    2. Eizo Akiyama & Nobuyuki Hanaki & Ryuichiro Ishikawa, 2013. "It is Not Just Confusion! Strategic Uncertainty in an Experimental Asset Market," Working Papers halshs-00854513, HAL.
    3. 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(04), pages 347-400, December.
    4. 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.
    5. Roger Guesnerie, 2005. "Assessing Rational Expectations 2: "Eductive" Stability in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262072580, March.
    6. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    7. Bruno Biais & Denis Hilton & Karine Mazurier & Sébastien Pouget, 2005. "Judgemental Overconfidence, Self-Monitoring, and Trading Performance in an Experimental Financial Market," Review of Economic Studies, Oxford University Press, vol. 72(2), pages 287-312.
    8. Helena Veiga & Marc Vorsatz, 2010. "Information aggregation in experimental asset markets in the presence of a manipulator," Experimental Economics, Springer;Economic Science Association, vol. 13(4), pages 379-398, December.
    9. Robert Bloomfield & Maureen O'Hara & Gideon Saar, 2009. "How Noise Trading Affects Markets: An Experimental Analysis," Review of Financial Studies, Society for Financial Studies, vol. 22(6), pages 2275-2302, June.
    10. 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.
    11. Isabelle Brocas & Juan D. Carrillo & Stephanie W. Wang & Colin F. Camerer, 2014. "Imperfect Choice or Imperfect Attention? Understanding Strategic Thinking in Private Information Games," Review of Economic Studies, Oxford University Press, vol. 81(3), pages 944-970.
    12. Kent D. Daniel, 2001. "Overconfidence, Arbitrage, and Equilibrium Asset Pricing," Journal of Finance, American Finance Association, vol. 56(3), pages 921-965, June.
    13. Edward T. Cokely & Colleen M. Kelley, 2009. "Cognitive abilities and superior decision making under risk: A protocol analysis and process model evaluation," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 4(1), pages 20-33, February.
    14. Shane Frederick, 2005. "Cognitive Reflection and Decision Making," Journal of Economic Perspectives, American Economic Association, vol. 19(4), pages 25-42, Fall.
    15. Brice Corgnet & Roberto Hernán-González & Praveen Kujal & David Porter, 2015. "The Effect of Earned Versus House Money on Price Bubble Formation in Experimental Asset Markets," Review of Finance, European Finance Association, vol. 19(4), pages 1455-1488.
    16. Grinblatt, Mark & Keloharju, Matti & Linnainmaa, Juhani T., 2012. "IQ, trading behavior, and performance," Journal of Financial Economics, Elsevier, vol. 104(2), pages 339-362.
    17. Andersen, Steffen & Campbell, John Y. & Meisner-Nielsen, Kasper & Ramadorai, Tarun, 2014. "Inattention and Inertia in Household Finance: Evidence from the Danish Mortgage Market," Scholarly Articles 17492179, Harvard University Department of Economics.
    18. Cheung, Stephen L. & Hedegaard, Morten & Palan, Stefan, 2014. "To see is to believe: Common expectations in experimental asset markets," European Economic Review, Elsevier, vol. 66(C), pages 84-96.
    19. Sanford J. Grossman, 1977. "The Existence of Futures Markets, Noisy Rational Expectations and Informational Externalities," Review of Economic Studies, Oxford University Press, vol. 44(3), pages 431-449.
    20. 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.
    21. 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.
    22. Jan Krahnen & Martin Weber, 2001. "Marketmaking in the Laboratory: Does Competition Matter?," Experimental Economics, Springer;Economic Science Association, vol. 4(1), pages 55-85, June.
    23. Guillermo Campitelli & Martin Labollita, 2010. "Correlations of cognitive reflection with judgments and choices," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 5(3), pages 182-191, June.
    24. Julie Agnew & Pierluigi Balduzzi & Annika Sundén, 2003. "Portfolio Choice and Trading in a Large 401(k) Plan," American Economic Review, American Economic Association, vol. 93(1), pages 193-215, March.
    25. Kent Daniel & David Hirshleifer & Avanidhar Subrahmanyam, 1998. "Investor Psychology and Security Market Under- and Overreactions," Journal of Finance, American Finance Association, vol. 53(6), pages 1839-1885, December.
    26. Diamond, Douglas W. & Verrecchia, Robert E., 1981. "Information aggregation in a noisy rational expectations economy," Journal of Financial Economics, Elsevier, vol. 9(3), pages 221-235, September.
    27. Mark Grinblatt & Matti Keloharju & Juhani Linnainmaa, 2011. "IQ and Stock Market Participation," Journal of Finance, American Finance Association, vol. 66(6), pages 2121-2164, December.
    28. Desgranges, G. & Guesnerie, R., 1996. "Common knowledge and the information revealed through prices: some conjectures," DELTA Working Papers 96-22, DELTA (Ecole normale supérieure).
    29. Bogan, Vicki, 2008. "Stock Market Participation and the Internet," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(01), pages 191-211, March.
    30. Fama, Eugene F, 1991. " Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Brice Corgnet & Cary Deck & Mark Desantis & David Porter, 2017. "Information (Non)Aggregation in Markets with Costly Signal Acquisition," Working Papers halshs-01686493, HAL.
    2. Lionel Page & Christoph Siemroth, 2018. "How much information is incorporated in financial asset prices? Experimental Evidence," QuBE Working Papers 054, QUT Business School.
    3. Mark Schneider, 2016. "Dual Process Utility Theory: A Model of Decisions Under Risk and Over Time," Working Papers 16-23, Chapman University, Economic Science Institute.
    4. Utz Weitzel & Christoph Huber & Florian Lindner & Jürgen Huber & Julia Rose & Michael Kirchler, 2018. "Bubbles and financial professionals," Working Papers 2018-04, Faculty of Economics and Statistics, University of Innsbruck, revised Jun 2018.

    More about this item

    Keywords

    Information aggregation; market efficiency; experimental asset markets; behavioral finance;

    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

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:chu:wpaper:15-15. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Megan Luetje). General contact details of provider: http://edirc.repec.org/data/esichus.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.