Artificial financial market. Risk analysis approach

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Date
2015
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CERIST
Abstract
Financial market is in constant confrontation with various financial risks. These contribute to market instabilities, financial crises and substantial losses for investors. To effectively manage these risks, we should understand the complexity of the market due to its evolution in an uncertain environment. This is possible through multi-agent modeling and simulation while taking into consideration risk indicators. We, propose, in this paper, to model a financial market simulation system using a multi-agent model, where agents represent the different market participants. The reasoning model of our agents is based on different risk indicators. We use the classifier systems as reasoning and learning model for the cognitive agents of our system. This system is a decision tool dedicated to managers or experts wanting to analyze and understand through the behaviour of the different participants, the evolution of the global dynamics of the market and the influence of the different risk factors on the market and on the various categories of market participants.
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Keywords
Financial Market, Financial Risk, Multi-Agent System, Classifier System, Modeling, Simulation
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