Browsing by Author "Hedjazi Dellal, Badiâa"

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    Artificial financial market. Risk analysis approach
    (CERIST, 2015) Hedjazi Dellal, Badiâa; Aknine, Samir; Benatchba, Karima
    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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    Artificial financial market. Risk analysis approach
    (CERIST, 2015) Hedjazi Dellal, Badiâa; Aknine, Samir; Benatchba, Karima
    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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    Game theory for Initial Public Offering (IPO): A multi-agent approach
    (CERIST, 2012) Hedjazi Dellal, Badiâa; Ahmed-Nacer, Mohamed; Aknine, Samir; Benatchba, Karima
    This work consists in simulating a real time interbank gross payment system (RTGS) through a multi-agent model, to analyze the evolution of the liquidity brought by the banks to the system. In this model, each bank chooses the amount of a daily liquidity on the basis of costs minimization (costs of liquidity and delaying) by taking into account the liquidity brought by the other banks. Banks agents’ strategies are based on a liquidity game during several payment days where each bank plays against the others. For their adaptability, we integrate into bank agents learning classifier systems. We carry out several simulations to follow the system total liquidity evolution as that of each bank agent with varying costs coefficients. The question to answer is: what are the cash amounts that banks must provide and under what costs of liquidity and delaying, the system avoids the lack of liquidity? We find that liquidity depends on costs coefficients.
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    Interbank payment system (RTGS) simulation using multi-agent approach
    (CERIST, 2011-10) Hedjazi Dellal, Badiâa; Ahmed-Nacer, Mohamed; Aknine, Samir
    This work consists in simulating a real time interbank gross payment system (RTGS) through a multi-agent model, to analyze the evolution of the liquidity brought by the banks to the system. In this model, each bank chooses the amount of a daily liquidity on the basis of costs minimization (costs of liquidity and delaying) by taking into account the liquidity brought by the other banks. Banks agents’ strategies are based on a liquidity game during several payment days where each bank plays against the others. For their adaptability, we integrate into bank agents learning classifier systems. We carry out several simulations to follow the system total liquidity evolution as that of each bank agent with varying costs coefficients. The question to answer is: what are the cash amounts that banks must provide and under what costs of liquidity and delaying, the system avoids the lack of liquidity? We find that liquidity depends on costs coefficients.
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    Modèle de workflow orienté services pour une coopération flexible interentreprises. Application au marché des changes interbancaires
    (Université des Sciences et de la Technologie Houari Boumediene, 2012) Atik, Ali; Hedjazi Dellal, Badiâa
    Les systèmes de gestion de workflow traditionnels ne permettent pas la prise en charge des nouveaux besoins de coopération interentreprises, nécessitant une gestion décentralisée, flexible et répartie sur le web. Cette gestion ne peut se faire qu'au travers de la mise en place de processus transverses automatisés qui permettent entre autres, une amélioration des services rendus aux clients, la réduction des coûts et la mise en place de solutions décisionnelles pour le pilotage de la performance des processus. Le workflow est la manière de modéliser et d’exécuter des processus coopératifs et interentreprises. L’évolution de certains traitements durant le temps nécessite la modélisation par l’approche workflow flexible, dans le sens où il peut faire l’objet d’adaptations. La prise en charge de cette flexibilité (ou adaptabilité) du système est possible grâce à l'ouverture permise par les architectures orientées services et ceci par l'enrichissement du système avec de nouveaux web services. Aussi, l’automatisation de processus distribués sur des départements, ou autres structures qui peuvent être éloignées et disposant d’outils et systèmes hétérogènes, nécessite une approche orientée services. Le marché des changes interbancaire est un processus complexe, coopératif qui peut être grandement amélioré en utilisant la technologie workflow. L’objectif du projet est donc de développer un système de workflow flexible orienté services pour la gestion des changes interbancaires. Ce système doit permettre aux banques d’améliorer leurs processus du marché des changes et par conséquent d’augmenter leurs profitabilités et leurs services aux clients.
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    Multi-Agent Liquidity Risk Management in an Interbank Net Settlement System
    (Springer Berlin Heidelberg, 2012) Hedjazi Dellal, Badiâa; Ahmed-Nacer, Mohamed; Aknine, Samir; Benatchba, Karima
    A net settlement system is a payment system between banks, where a large number of transactions are accumulated, usually waiting until the end of each day to be settled through payment instruments like: wire transfers, direct debits, cheques, .... These systems also provide clearing functions to reduce interbank payments but are sometimes exposed to liquidity risks. Monitoring, and optimizing the interbank exchanges through suitable tools is useful for the proper functioning of these systems. The goal is to add to these systems an intelligent software layer integrated with the existing system for the improvement of transactions processing and consequently avoid deadlock situations, deficiencies and improve system efficiency. We model and develop by multi-agent an intelligent tracking system of the interbank exchanged transactions to optimize payments settlement and minimize liquidity risks.
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    Multi-agent liquidity risk management in an interbank net settlement system
    (CERIST, 2012-09) Hedjazi Dellal, Badiâa; Ahmed-Nacer, Mohamed; Aknine, Samir; Benatchba, Karima
    A net settlement system is a payment system between banks, where a large number of transactions between the banks are accumulated, usually waiting until the end of each day to be settled trough payment instruments like: wire transfers, direct debits, cheques, bank cards... These systems also provide clearing functions to reduce the number of interbank payments to achieve but are sometimes exposed to liquidity risks. Monitoring, controlling and optimizing the interbank exchanges through suitable tools is useful for the proper functioning of these systems. The goal is to add to these systems an intelligent software layer integrated with the existing system for the improvement and multilateral optimization of transactions and consequently avoid deadlock situations, bypass certain deficiencies and improve system efficiency. We model and develop by multi-agent an intelligent tracking system of the exchanged transactions through an interbank clearing system, to optimize payments settlement and minimize liquidity risks.
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    OVERHEARING IN FINANCIAL MARKETS: A Multi-agent Approach
    (SciTePress Science and Technology Publications, 2011) Hedjazi Dellal, Badiâa; Aknine, Samir; Ahmed-Nacer, Mohamed; Benatchba, Karima
    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 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.
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    Overhearing in financial markets: a multi-agent approach markets: a multi-agent approach
    (CERIST, 2010-11) Hedjazi Dellal, Badiâa; Ahmed-Nacer, Mohamed; Aknine, Samir; Benatchba, Karima
    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 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.
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    Workflow de décision coopérative à base de système multi-agent -- Cas de processus de décision spatial
    (2007) Hedjazi Dellal, Badiâa; Admane, Farida; Alquier, Anne-Marie
    Cet article porte sur la modélisation, sous forme de workflow, d’un processus de prise de décision spatiale (ou territoriale) et coopérative. Ce processus est distribué, coopératif et coordonné et est caractérisé par une certaine complexité. Il présente un outil d’aide à la décision basé sur des méthodes multicritères pour la simplification du problème décisionnel par la réduction et l'ordonnancement des solutions. Il met en œuvre un système multi-agent qui utilise le principe de la négociation pour la résolution de conflits afin d’aboutir à un compromis. Pour la validation de l'outil, un Système d'Information Géographique est exploité comme source d’information spatiale. Le problème décisionnel auquel on s’intéresse est le choix d’une localisation de moindre impact sur l’environnement qui est un problème décisionnel émergent.
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    Workflow de décision coopérative à base de système multi-agent. Cas de processus de décision spatial
    (Ecole Nationale Supérieure d'Informatique ESI (ex. INI), 2006) Hedjazi Dellal, Badiâa; Khelladi, Abdelkader
    Cette thèse porte sur l’utilisation de la technologie workflow et des systèmes multi-agents dans un processus d’aide à la décision spatiale coopérative. Le processus d’aide à la décision coopérative sera modélisé sous forme de workflow. La première phase du processus consiste à exploiter des méthodes multicritères appropriées pour le problème spatial posé. Une fois le rangement des solutions obtenu et suite aux conflits qui peuvent surgir entre les différents acteurs du système pour choisir l’une ou l’autre solution, le processus de décision sera poursuivi par une négociation entre les différents acteurs du système afin d’aboutir à un compromis. La négociation sera réalisée en utilisant un système multi-agents (SMA). Les agents du SMA seront du type cognitif et auront comme tache principale d’assister les acteurs dans leur négociation. La négociation sera par argumentation vu qu’elle simule un processus entre des humains qui chacun d’eux essaie de persuader les autres intervenants en utilisant des arguments. Le problème spatial choisi pour l’étude de cas sera « le choix d’une localisation de moindre impact sur l’environnement pour la construction d’un barrage ».