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Technical Trading Creates a Prisoner's Dilemma: Results from an Agent-Based Model


  • Shareen Joshi
  • Jeffrey Parker
  • Mark A. Bedau


The widespread use and proven profitability of technical trading rules in financial markets has long been a puzzle in academic finance. In this paper we show, using an agent-based model of an evolving stock market, that widespread technical trading can arise due to a multi-person prisoners' dilemma in which the inclusion of techinical trading rules to a single agent's repertoire of rules is a dominant strategy. The use of this dominant strategy by all traders in the market creates a symmetric Nash equilibrium in which wealth earned is lower and the volatility of prices is higher than in the hypothetical case in which all agents rely only on fundamental rules. Our explanation of this lower wealth and higher volatility is that the use of technical trading rules worsens the accuracy of the predictions of all agents' market forecasts by contributing to the reinforcement of price trends, augmenting volatility, and increasing the amount of noise in the market. Submitted to Conference on Computational Finance 1999.

Suggested Citation

  • Shareen Joshi & Jeffrey Parker & Mark A. Bedau, 1998. "Technical Trading Creates a Prisoner's Dilemma: Results from an Agent-Based Model," Research in Economics 98-12-115e, Santa Fe Institute.
  • Handle: RePEc:wop:safire:98-12-115e

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    References listed on IDEAS

    1. 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.
    2. Blake LeBaron, "undated". "Technical Trading Rules and Regime Shifts in Foreign Exchange," Working papers _007, University of Wisconsin - Madison.
    3. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    4. LeBaron, Blake & Arthur, W. Brian & Palmer, Richard, 1999. "Time series properties of an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1487-1516, September.
    5. Roger E. A. Farmer, 1999. "Macroeconomics of Self-fulfilling Prophecies, 2nd Edition," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262062038, July.
    6. Diba, Behzad T & Grossman, Herschel I, 1988. "The Theory of Rational Bubbles in Stock Prices," Economic Journal, Royal Economic Society, vol. 98(392), pages 746-754, September.
    7. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. " Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
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    Cited by:

    1. Norman Ehrentreich, 2002. "The Santa Fe Artificial Stock Market Re-Examined - Suggested Corrections," Computational Economics 0209001, EconWPA.
    2. Thomas Schuster, 2003. "Meta-Communication and Market Dynamics. Reflexive Interactions of Financial Markets and the Mass Media," Finance 0307014, EconWPA.
    3. Shareen Joshi & Mark A. Bedau, 1998. "An Explanation of Generic Behavior in an Evolving Financial Market," Research in Economics 98-12-114e, Santa Fe Institute.


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