Market dynamics and agents behaviors: a computational approach
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).
|Date of creation:||Apr 2005|
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- 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.
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- repec:att:wimass:9528 is not listed on IDEAS
- 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," Papers cond-mat/0105303, arXiv.org.
- Blake LeBaron, .
"Experiments in Evolutionary Finance,"
_001, University of Wisconsin - Madison.
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