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

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Listed:
  • Shareen Joshi
  • Jeffrey Parker
  • Mark A. Bedau
Abstract
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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    File URL: http://www.santafe.edu/sfi/publications/Working-Papers/98-12-115E.pdf
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    References listed on IDEAS

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    Cited by:

    1. Sunyoung Lee & Keun Lee, 2021. "3% rules the market: herding behavior of a group of investors, asset market volatility, and return to the group in an agent-based model," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(2), pages 359-380, April.
    2. Stephan Schulmeister, 2000. "Technical Analysis and Exchange Rate Dynamics," WIFO Studies, WIFO, number 25857.
    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.
    4. Jörn Dermietzel, 2008. "The Heterogeneous Agents Approach to Financial Markets – Development and Milestones," International Handbooks on Information Systems, in: Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), Handbook on Information Technology in Finance, chapter 19, pages 443-464, Springer.
    5. Norman Ehrentreich, 2002. "The Santa Fe Artificial Stock Market Re-Examined - Suggested Corrections," Computational Economics 0209001, University Library of Munich, Germany.
    6. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    7. Thomas Schuster, 2003. "Meta-Communication and Market Dynamics. Reflexive Interactions of Financial Markets and the Mass Media," Finance 0307014, University Library of Munich, Germany.

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