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Noise Trading in a Laboratory Financial Market: A Maximum Likelihood Approach

Author

Listed:
  • Marco Cipriani

    (George Washington University,)

  • Antonio Guarino

    (University College London and University of Venice,)

Abstract

We study the extent to which, in a laboratory financial market, noise trading can stem from subjects' irrationality. We estimate a structural model of sequential trading by using experimental data. In the experiment, subjects receive private information on the value of an asset and trade it in sequence with a market maker. We find that, in the laboratory, the noise due to the irrational use of private information accounts for 35% of the decisions. When subjects act as noise traders, they abstain from trading 67% of the time. When they trade, the probability that they buy is significantly higher than the probability that they sell. (JEL: C92, D8, G14) Copyright (c) 2005 The European Economic Association.

Suggested Citation

  • Marco Cipriani & Antonio Guarino, 2005. "Noise Trading in a Laboratory Financial Market: A Maximum Likelihood Approach," Journal of the European Economic Association, MIT Press, vol. 3(2-3), pages 315-321, 04/05.
  • Handle: RePEc:tpr:jeurec:v:3:y:2005:i:2-3:p:315-321
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    Citations

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    Cited by:

    1. Marco Cipriani & Antonio Guarino, 2009. "Herd Behavior in Financial Markets: An Experiment with Financial Market Professionals," Journal of the European Economic Association, MIT Press, vol. 7(1), pages 206-233, March.
    2. Cipriani, Marco & Guarino, Antonio, 2008. "Transaction costs and informational cascades in financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 68(3-4), pages 581-592, December.

    More about this item

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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