Overhearing in financial markets: a multi-agent approach markets: a multi-agent approach

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dc.contributor.authorHedjazi Dellal, Badiâa
dc.contributor.authorAhmed-Nacer, Mohamed
dc.contributor.authorAknine, Samir
dc.contributor.authorBenatchba, Karima
dc.date.accessioned2013-11-24T15:14:43Z
dc.date.available2013-11-24T15:14:43Z
dc.date.issued2010-11
dc.description.abstractOpen complex systems as financial markets evolve in a highly dynamic and uncertain environment. They are often subject to significant fluctuations due to unanticipated behaviours and information. Modelling and simulating these systems by means of agent systems, i.e., through artificial markets is a valuable approach. In this article, we present our model of asynchronous artificial market consisting of a set of adaptive and heterogeneous agents in interaction. These agents represent the various market participants (investors and institutions). Investor Agents have advanced mental models for ordinary investors which do not relay on fundamental or technical analysis methods. On one hand, these models are based on the risk tolerance and on the other hand on the information gathered by the agents. This information results from overhearing influential investors in the market or the order books. We model the system through investor agents using learning classifier systems as reasoning models. As a result, our artificial market allows the study of overhearing impacts on the market. We also present the experimental evaluation results of our model.fr_FR
dc.identifier.isrnCERIST-DSISM/RR--10-000000019--dzfr_FR
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/316
dc.publisherCERIST
dc.relation.ispartofRapports de recherche internes
dc.relation.ispartofseriesRapports de recherche internes
dc.relation.placeAlger
dc.subjectMulti-agent systemfr_FR
dc.subjectFinancial marketfr_FR
dc.subjectSimulationfr_FR
dc.subjectOverhearingfr_FR
dc.subjectSpeculationfr_FR
dc.subjectClassifier systemfr_FR
dc.titleOverhearing in financial markets: a multi-agent approach markets: a multi-agent approachfr_FR
dc.typeTechnical Report
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