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Asset Price Dynamics among Heterogeneous Interacting Agents

  • Carl Chiarella

    ()

  • Mauro Gallegati
  • Roberto Leombruni
  • Antonio Palestrini

In this paper, we investigate the presence of rationalherding on asset price dynamics during the intra-day trading withheterogeneous interacting agents, whose information set is notcomplete. In the model, individual probability measures offinancial investment strategies are defined using statisticalmechanics concepts. In addition, there is a learning processtoward the best strategy, implemented as a geneticalgorithm. Simulations show that imitative behavior can be arational strategy, since it allows an investor to gain excessreturns on an asset by exploiting information regarding pricedynamics not strictly contained in the fundamental solution. Herdbehavior is rational in the sense that it produces profits at theexpense of increasing the complexity of the system. Copyright Kluwer Academic Publishers 2003

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File URL: http://hdl.handle.net/10.1023/A:1026137931041
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Article provided by Society for Computational Economics in its journal Computational Economics.

Volume (Year): 22 (2003)
Issue (Month): 2 (October)
Pages: 213-223

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Handle: RePEc:kap:compec:v:22:y:2003:i:2:p:213-223
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  1. Routledge, Bryan R, 1999. "Adaptive Learning in Financial Markets," Review of Financial Studies, Society for Financial Studies, vol. 12(5), pages 1165-1202.
  2. W. Brian Arthur, 1992. "On Learning and Adaptation in the Economy," Working Papers 854, Queen's University, Department of Economics.
  3. Lux, T. & M. Marchesi, . "Scaling and Criticality in a Stochastic Multi-Agent Model of a Financial Market," Discussion Paper Serie B 438, University of Bonn, Germany, revised Jul 1998.
  4. Carl Chiarella & Xue-Zhong He, 1999. "Heterogeneous Beliefs, Risks and Learning in a Simple Asset Pricing Model," Research Paper Series 18, Quantitative Finance Research Centre, University of Technology, Sydney.
  5. Carl Chiarella & Xue-Zhong He, 2001. "Asset Price and Wealth Dynamics Under Heterogeneous Expectations," Research Paper Series 56, Quantitative Finance Research Centre, University of Technology, Sydney.
  6. Brock, W.A. & Hommes, C.H., 1996. "A Rational Route to Randomness," Working papers 9530r, Wisconsin Madison - Social Systems.
  7. Kirman Alan & Teyssière Gilles, 2002. "Microeconomic Models for Long Memory in the Volatility of Financial Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(4), pages 1-23, January.
  8. Arthur, W Brian, 1994. "Inductive Reasoning and Bounded Rationality," American Economic Review, American Economic Association, vol. 84(2), pages 406-11, May.
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