Information dissemination in an experimentally based agent-based stock market
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Information dissemination in an experimentally based agent-based stock market Jakob Grazzini
Received: 10 February 2012 / Accepted: 19 January 2013 / Published online: 17 February 2013 © Springer-Verlag Berlin Heidelberg 2013
Abstract This paper builds an agent-based model to reproduce the results of an experimental stock market that studies how the market aggregates private information. The aim is to use experiments and agent-based modeling to analyze the trading behavior in experimental stock markets. Using the experimental environment and results, it is possible to formulate a hypothesis about the subjects’ behavior and thereby formalize (algorithmically) the trading behavior in an agent-based model. This may lead to a better understanding of how the market converges to an equilibrium and of the mechanism that allows dissemination of private information in the market. Keywords Agent-based modeling · Experiments · Stock market · Asymmetric information · Learning
1 Introduction The aim of this paper is to use the flexibility of agent-based models to formalize the subjects’ behavior in an experimental stock market. Computational agents will trade in a realistic continuous double auction using simple strategies. The objective is to understand how experimental markets aggregate the traders’ private information.
The research leading to these results has received funding from the European Union, Seventh Framework Programme FP7/2007-2013 under grant agreement n CRISIS-ICT-2011-288501. The author wishes to thank the two anonymous referees for their stimulating comments. J. Grazzini (B) Institute of Economic Theory and Quantitative Methods, Catholic University of Milan, via Necchi 5, 20123 Milano, Italy e-mail: [email protected]
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Experiments and agent-based models are “natural allies” (Duffy 2006) and can complete each other in a prolific way (Contini et al. 2007). In experiments it is possible to control the economic environment and the market structure but not the motives and the subjects’ individual characteristics (Chan et al. 2001). A model can use the experimental environment and results to formalize the subjects’ behavior using the generative approach proposed by Epstein and Axtell (1996). The experiment provides the foundation and the results needed for the model, while the model provides the formalization of the subjects’ behavior. According to Smith (1982) it is possible to define a microeconomic system, S = (e, I ), as a microeconomic environment (e) and a microeconomic institution (I ). The microeconomic environment is defined by Smith (1982) as a list of N economic agents, K + 1 commodities and the characteristics of each agent i, e = (e1 , . . . , ei , . . . , e N ). The environment is thus a set of initial conditions that cannot be altered by the agents. The microeconomic institution defines the rules under which the agents act and interact. In a stock market the institution is represented by a trading mechanism, e.g. continuous double auction, that imposes a set of rules whi
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