A Modular Agent-Based Environment for Studying Stock Markets
AbstractArtificial stock markets are built with diffuse priors in mind regarding trading strategiesand price formation mechanisms. Diffuse priors are a natural consequence of theunknown relation between the various elements that drive market dynamics and the largevariety of market organizations, findings, however, might hold only within the specific marketsettings. In this paper we propose a framework for building agent-based artificial stockmarkets. We present the mechanism of the framework based on a previously identified listof organizational and behavioural aspects. Within the framework experiments with arbitrarymany trading strategies, acting in various market organizations can be conducted in aflexible way, without changing its architecture. In this way experiments of other artificialstock markets, as well as theoretical models can be replicated and their findings compared.Comparisons of the different experimental results might indicate whether findings are dueto tradersâ€™ behaviour or to the chosen market structure and could suggest how to improvemarket quality.
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Bibliographic InfoPaper provided by Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam. in its series Research Paper with number ERS-2005-017-LIS.
Date of creation: 03 Apr 2005
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simulatiemodellen; artificial stock markets; agent-based modelling; behavioural finance; computational economics;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-09-29 (All new papers)
- NEP-CBE-2005-09-29 (Cognitive & Behavioural Economics)
- NEP-CMP-2005-09-29 (Computational Economics)
- NEP-GTH-2005-09-29 (Game Theory)
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