Hakman, A. Wan and Hunter, Andrew and Dunne, Peter (2002) Autonomous agent models of stock markets. Artificial Intelligence Review, 17 (2). pp. 87-128. ISSN 1573-7462

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Abstract

The use of artificial agents in the study of stock markets has aroused much interest in the past two decades. Models of markets consisting of agents were built to reinforce or question theories in economics – including the principle of “negative feedback”, the Efficient Market Hypothesis, and chaos theory. In this article, we review the development of these agent models, highlight key design issues and problems, and suggest some directions for future research.

Item Type:	Article
Additional Information:	The use of artificial agents in the study of stock markets has aroused much interest in the past two decades. Models of markets consisting of agents were built to reinforce or question theories in economics – including the principle of “negative feedback”, the Efficient Market Hypothesis, and chaos theory. In this article, we review the development of these agent models, highlight key design issues and problems, and suggest some directions for future research.
Keywords:	Economic models, Markets
Subjects:	L Social studies > L100 Economics
Divisions:	College of Sciences > Faculty of Science > Lincoln School of Computer Science
Depositing User:	Bev Jones
Date Deposited:	21 Sep 2007
Last Modified:	18 Jul 2011 16:12
URI:	http://eprints.lincoln.ac.uk/id/eprint/664

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