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Information Dissemination and Aggregation in Asset Markets with Simple Intelligent Traders

Author

Listed:
  • Andrew Lo

    (Massachusetts Institute of Technology)

  • Nicholas Chan

    (Massachusetts Institute of Technology)

  • Blake LeBaron

    (Brandeis University)

  • Tomaso Poggio

    (Massachusetts Institute of Technology)

Abstract

Various studies of asset markets have shown that traders are capable of learning and transmitting information through prices in many situations. In this paper we replace human traders with intelligent software agents in a series of simulated markets. Using these simple learning agents, we are able to replicate several features of the experiments with human subjects, specifically regarding (1) dissemination of information from informed to uninformed traders and (2) aggregation of information spread over different traders.

Suggested Citation

  • Andrew Lo & Nicholas Chan & Blake LeBaron & Tomaso Poggio, 1999. "Information Dissemination and Aggregation in Asset Markets with Simple Intelligent Traders," Computing in Economics and Finance 1999 653, Society for Computational Economics.
  • Handle: RePEc:sce:scecf9:653
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    References listed on IDEAS

    as
    1. Sunder, Shyam, 1992. "Market for Information: Experimental Evidence," Econometrica, Econometric Society, vol. 60(3), pages 667-695, May.
    2. Lettau, Martin, 1997. "Explaining the facts with adaptive agents: The case of mutual fund flows," Journal of Economic Dynamics and Control, Elsevier, vol. 21(7), pages 1117-1147, June.
    3. Arthur, W.B. & Holland, J.H. & LeBaron, B. & Palmer, R. & Tayler, P., 1996. "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Working papers 9625, Wisconsin Madison - Social Systems.
    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. Forsythe, Robert & Lundholm, Russell, 1990. "Information Aggregation in an Experimental Market," Econometrica, Econometric Society, vol. 58(2), pages 309-347, March.
    6. Arifovic, Jasmina, 1996. "The Behavior of the Exchange Rate in the Genetic Algorithm and Experimental Economies," Journal of Political Economy, University of Chicago Press, vol. 104(3), pages 510-541, June.
    7. 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.
    8. W. Brian Arthur & Paul Tayler, "undated". "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Computing in Economics and Finance 1997 57, Society for Computational Economics.
    9. 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.
    10. 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.
    11. Jamal, Karim & Sunder, Shyam, 1996. "Bayesian equilibrium in double auctions populated by biased heuristic traders," Journal of Economic Behavior & Organization, Elsevier, vol. 31(2), pages 273-291, November.
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    Cited by:

    1. Shu‐Heng Chen & Shu G. Wang, 2011. "Emergent Complexity In Agent‐Based Computational Economics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(3), pages 527-546, July.
    2. Shu-Heng Chan & Shu G. Wang, 2010. "Emergent Complexity in Agent-Based Computational Economics," ASSRU Discussion Papers 1017, ASSRU - Algorithmic Social Science Research Unit.

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