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Market dynamics and agents behaviors: a computational approach

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Derveeuw, Julien

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Abstract

We explore market dynamics generated by the Santa-Fe Artificial Stock Market model. It allows to study how agents adapt themselves to a market dynamic without knowing its generation process. It was shown by Arthur and LeBaron, with the help of computer experiments, that agents in bounded rationality can make a rational global behavior emerge in this context. In the original model, agents do not ground their decision on an economic logic. Hence, we modify indicators used by agents to watch the market to give them more economic rationality. This leads us to divide agents in two groups: fundamentalists agents, who watch the market with classic economic indicators and speculator agents, who watch the market with technical indicators. This split allows us to study the influence of individual agents behaviors on global price dynamics. In this article, we show with the help of computational simulations that these two types of agents can generate classical market dynamics as well as perturbed ones (bubbles and kraches).

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Publisher Info
Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 4916.

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Date of creation: Apr 2005
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Handle: RePEc:pra:mprapa:4916

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Related research
Keywords: multi-agent; finance; financial market; simulation; bubbles; kraches;

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Find related papers by JEL classification:
D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
D40 - Microeconomics - - Market Structure and Pricing - - - General
D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets

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  1. Levy, Moshe & Levy, Haim & Solomon, Sorin, 1994. "A microscopic model of the stock market : Cycles, booms, and crashes," Economics Letters, Elsevier, vol. 45(1), pages 103-111, May. [Downloadable!] (restricted)
  2. Lux, Thomas, 1998. "The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 143-165, January. [Downloadable!] (restricted)
  3. Focardi, Sergio & Cincotti, Silvano & Marchesi, Michele, 2002. "Self-organization and market crashes," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 241-267, October. [Downloadable!] (restricted)
  4. N. F. Johnson & D. Lamper & P. Jefferies & M. L. Hart & S. Howison, 2001. "Application of multi-agent games to the prediction of financial time-series," Quantitative Finance Papers cond-mat/0105303, arXiv.org. [Downloadable!]
  5. Blake LeBaron, . "Experiments in Evolutionary Finance," Working papers _001, University of Wisconsin - Madison. [Downloadable!]
  6. Neil F. Johnson & David Lamper & Paul Jefferies & Michael L. Hart & Sam Howison, 2001. "Application of multi-agent games to the prediction of financial time-series," OFRC Working Papers Series 2001mf04, Oxford Financial Research Centre. [Downloadable!]
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