Authors:
Hedjazi Badiâa
1
;
Aknine Samir
2
;
Ahmed-Nacer Mohamed
3
and
Benatchba Karima
4
Affiliations:
1
CERIST Research Center on Scientific and Technical Information, Algeria
;
2
Lyon 1 University, France
;
3
USTHB University of Science and Technology Houari Boumediene, Algeria
;
4
ESI and National High School of Computer Science, Algeria
Keyword(s):
Multi-agent system, Financial market, Simulation, Overhearing, Speculation, Classifier system.
Related
Ontology
Subjects/Areas/Topics:
Agent Models and Architectures
;
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bioinformatics
;
Biomedical Engineering
;
Distributed and Mobile Software Systems
;
Economic Agent Models
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Methodologies and Technologies
;
Multi-Agent Systems
;
Operational Research
;
Simulation
;
Software Engineering
;
Symbolic Systems
Abstract:
Open 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 model
s. 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.
(More)