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On the Design of Agent-based Artificial Stock Markets

Olivier Brandouy (), Philippe Mathieu () and Iryna Veryzhenko
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Philippe Mathieu: LIFL - Laboratoire d'Informatique Fondamentale de Lille - Université de Lille, Sciences et Technologies - Inria - Institut National de Recherche en Informatique et en Automatique - Université de Lille, Sciences Humaines et Sociales - CNRS - Centre National de la Recherche Scientifique, SMAC - Systèmes Multi-Agents et Comportements - CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 - Centrale Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique
Iryna Veryzhenko: LIFL - Laboratoire d'Informatique Fondamentale de Lille - Université de Lille, Sciences et Technologies - Inria - Institut National de Recherche en Informatique et en Automatique - Université de Lille, Sciences Humaines et Sociales - CNRS - Centre National de la Recherche Scientifique, SMAC - Systèmes Multi-Agents et Comportements - CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 - Centrale Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique

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Abstract: The purpose of this paper is to define software engineering abstractions that provide a generic framework for stock market simulations. We demonstrate a series of key points and principles that has governed the development of an Agent-Based financial market application programming interface (API). The simulator architecture is presented. During artificial market construction we have faced the whole variety of agent-based modelling issues : local interaction, distributed knowledge and resources, heterogeneous environments, agents autonomy, artificial intelligence, speech acts, discrete or continuous scheduling and simulation. Our study demonstrates that the choices made for agent-based modelling in this context deeply impact the resulting market dynamics and proposes a series of advances regarding the main limits the existing platforms actually meet.

Date: 2013
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Citations: View citations in EconPapers (11)

Published in Agents and Artificial Intelligence, Springer, pp.350-364, 2013, 978-3-642-29966-7. ⟨10.1007/978-3-642-29966-7_23⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00826419

DOI: 10.1007/978-3-642-29966-7_23

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