Artificial economic life: a simple model of a stockmarket

doi:10.1016/0167-2789(94)90287-9

Physica D: Nonlinear Phenomena

Volume 75, Issues 1–3, 1 August 1994, Pages 264-274

https://doi.org/10.1016/0167-2789(94)90287-9 Get rights and content

Abstract

We describe a model of a stockmarket in which independent adaptive agents can buy and sell stock on a central market. The overall market behavior, such as the stock price time series, is an emergent property of the agents' behavior. This approach to modelling a market is contrasted with conventional rational expectations approaches. Our model does not necessarily converge to an equilibrium, and can show bubbles, crashes, and continued high trading volume.

References (12)

L. Blume et al.
Evolution and market behavior
J. Econ. Theory
(1992)
R. Marimon et al.
Money as a medium of exchange in an economy with artificially intelligent agents
J. Econ. Dynamics & Control
(1990)
W. Brian Arthur
On learning and adaptation in the economy
Santa Fe Institute Working Paper 92-07-038
(1992)
W. Brian Arthur et al.
An evolutionary model of a stockmarket
(1994)
M.E. Blume et al.
The theory of security pricing and market structure
Financial Markets, Institutions and Instruments
(1992)
David E. Goldberg
Genetic Algorithms in Search, Optimization and Machine Learning
(1989)

There are more references available in the full text version of this article.

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Artificial economic life: a simple model of a stockmarket

Abstract

J. Econ. Theory

J. Econ. Dynamics & Control

On learning and adaptation in the economy

Santa Fe Institute Working Paper 92-07-038

An evolutionary model of a stockmarket

The theory of security pricing and market structure

Financial Markets, Institutions and Instruments

Genetic Algorithms in Search, Optimization and Machine Learning