IDEAS home Printed from https://ideas.repec.org/p/zur/econwp/072.html
   My bibliography  Save this paper

Inefficient markets

Author

Listed:
  • Jacob K. Goeree
  • Jingjing Zhang

Abstract

Traders' values and information typically consist of both private and common-value elements. In such environments, full allocative efficiency is impossible when the private rate of information substitution differs from the social rate (Jehiel and Moldovanu, 2001). We link this impossibility result to a failure of the efficient market hypothesis, which states that prices adequately reflect all available information (Fama, 1970, 1991). The intuition is that if prices were able to reveal all information then the common value would simply shift traders' private values by a known constant and full allocative efficiency would result. In a series of laboratory experiments we study price formation in markets with private and common values. Rational expectations, which form the basis for the efficient market hypothesis, predict that the introduction of common values has no adverse consequences for allocative and informational efficiency. In contrast, a "private" expectations model in which traders' optimal behavior depends on both their private and common-value information predicts that neither full allocative nor full informational efficiency is possible. We test these competing hypotheses and find that the introduction of common values lowers allocative efficiency by 28% on average, as predicted by the private expectations model, and that market prices differ significantly and substantially from their rational expectation levels. Finally, a comparison of observed and predicted payoffs suggests that observed behavior is close to the equilibrium predicted by the private expectations model.

Suggested Citation

  • Jacob K. Goeree & Jingjing Zhang, 2012. "Inefficient markets," ECON - Working Papers 072, Department of Economics - University of Zurich.
  • Handle: RePEc:zur:econwp:072
    as

    Download full text from publisher

    File URL: https://www.zora.uzh.ch/id/eprint/62216/1/econwp072.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kjell G. Nyborg, 2004. "Multiple Unit Auctions and Short Squeezes," Review of Financial Studies, Society for Financial Studies, vol. 17(2), pages 545-580.
    2. 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.
    3. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    4. Smith, Vernon L., 2010. "Theory and experiment: What are the questions?," Journal of Economic Behavior & Organization, Elsevier, vol. 73(1), pages 3-15, January.
    5. 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.
    6. Forsythe, Robert & Lundholm, Russell, 1990. "Information Aggregation in an Experimental Market," Econometrica, Econometric Society, vol. 58(2), pages 309-347, March.
    7. Vernon L. Smith, 1962. "An Experimental Study of Competitive Market Behavior," Journal of Political Economy, University of Chicago Press, vol. 70, pages 111-111.
    8. 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.
    9. Friedman, Daniel, 2010. "Preferences, beliefs and equilibrium: What have experiments taught us?," Journal of Economic Behavior & Organization, Elsevier, vol. 73(1), pages 29-33, January.
    10. Forsythe, Robert & Palfrey, Thomas R & Plott, Charles R, 1982. "Asset Valuation in an Experimental Market," Econometrica, Econometric Society, vol. 50(3), pages 537-567, May.
    11. 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.
    12. O'Brien, John & Srivastava, Sanjay, 1991. "Dynamic Stock Markets with Multiple Assets: An Experimental Analysis," Journal of Finance, American Finance Association, vol. 46(5), pages 1811-1838, December.
    13. Cason, Timothy N. & Friedman, Daniel, 1996. "Price formation in double auction markets," Journal of Economic Dynamics and Control, Elsevier, vol. 20(8), pages 1307-1337, August.
    14. John H. Kagel, 2004. "Double Auction Markets with Stochastic Supply and Demand Schedules: Call Markets and Continuous Auction Trading Mechanisms," Palgrave Macmillan Books, in: Steffen Huck (ed.), Advances in Understanding Strategic Behaviour, chapter 9, pages 181-208, Palgrave Macmillan.
    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. Großer, Jens & Reuben, Ernesto, 2013. "Redistribution and market efficiency: An experimental study," Journal of Public Economics, Elsevier, vol. 101(C), pages 39-52.
    2. Trianti, Nikoletta, 2015. "Portfolio Management in Public Pension Reserve Funds/Gestión de carteras en los Fondos de Reserva de las Pensiones Públicas," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 33, pages 985-1008, Septiembr.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nuzzo, Simone & Morone, Andrea, 2017. "Asset markets in the lab: A literature review," Journal of Behavioral and Experimental Finance, Elsevier, vol. 13(C), pages 42-50.
    2. Martin Barner & Francesco Feri & Charles R. Plott, 2005. "On the microstructure of price determination and information aggregation with sequential and asymmetric information arrival in an experimental asset market," Annals of Finance, Springer, vol. 1(1), pages 73-107, January.
    3. Eric M. Aldrich & Kristian López Vargas, 2020. "Experiments in high-frequency trading: comparing two market institutions," Experimental Economics, Springer;Economic Science Association, vol. 23(2), pages 322-352, June.
    4. Lawrence Choo & Todd R. Kaplan & Ro’i Zultan, 2019. "Information aggregation in Arrow–Debreu markets: an experiment," Experimental Economics, Springer;Economic Science Association, vol. 22(3), pages 625-652, September.
    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. Edward Halim & Yohanes E. Riyanto & Nilanjan Roy, 2019. "Costly Information Acquisition, Social Networks, and Asset Prices: Experimental Evidence," Journal of Finance, American Finance Association, vol. 74(4), pages 1975-2010, August.
    7. Kay-Yut Chen & Leslie R. Fine & Bernardo A. Huberman, 2004. "Eliminating Public Knowledge Biases in Information-Aggregation Mechanisms," Management Science, INFORMS, vol. 50(7), pages 983-994, July.
    8. Charles N. Noussair & Steven Tucker, 2013. "Experimental Research On Asset Pricing," Journal of Economic Surveys, Wiley Blackwell, vol. 27(3), pages 554-569, July.
    9. Kay-Yut Chen & Leslie R. Fine & Bernardo A. Huberman, 2001. "Forecasting Uncertain Events with Small Groups," Papers cond-mat/0108028, arXiv.org.
    10. Veiga, Helena & Vorsatz, Marc, 2009. "Price manipulation in an experimental asset market," European Economic Review, Elsevier, vol. 53(3), pages 327-342, April.
    11. Jason Shachat & Anand Srinivasan, 2022. "Informational Price Cascades and Non-Aggregation of Asymmetric Information in Experimental Asset Markets," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 23(4), pages 388-407, November.
    12. Corgnet, Brice & DeSantis, Mark & Porter, David, 2020. "The distribution of information and the price efficiency of markets," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    13. 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.
    14. Paul J. Healy & Sera Linardi & J. Richard Lowery & John O. Ledyard, 2010. "Prediction Markets: Alternative Mechanisms for Complex Environments with Few Traders," Management Science, INFORMS, vol. 56(11), pages 1977-1996, November.
    15. Morone, Andrea & Nuzzo, Simone, 2015. "Market Efficiency, Trading Institutions and Information Mirages: evidence from an experimental asset market," MPRA Paper 67448, University Library of Munich, Germany.
    16. Choo, Lawrence, 2016. "Market competition for decision rights: An experiment based on the “Hat Puzzle Problem”," MPRA Paper 73408, University Library of Munich, Germany.
    17. Keser, Claudia & Markstädter, Andreas, 2014. "Informational asymmetries in laboratory asset markets with state-dependent fundamentals," University of Göttingen Working Papers in Economics 207, University of Goettingen, Department of Economics.
    18. Alex Richardson & Shirley Gregor & Richard Heaney, 2012. "Using decision support to manage the influence of cognitive abilities on share trading performance," Australian Journal of Management, Australian School of Business, vol. 37(3), pages 523-541, December.
    19. Jakob Grazzini, 2013. "Information dissemination in an experimentally based agent-based stock market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 8(1), pages 179-209, April.
    20. 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.

    More about this item

    Keywords

    Efficient market hypothesis; informational and allocative efficiency; experiments;
    All these keywords.

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior

    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:zur:econwp:072. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Severin Oswald (email available below). General contact details of provider: https://edirc.repec.org/data/seizhch.html .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.