A multi-agent-based decision support system for bankruptcy contagion effects

With the increasing interdependence of marketing participants, distress experienced by a specific entity may cause other connecting firms to encounter financial difficulties, leading to a negative impact on their stock valuations. At the same time, individual investors have a great need to gain relevant information for portfolio risk management. The monitoring vision cannot be limited to investors' portfolios but must take into account any potential candidates affected. Based on the ontological knowledge model of inter-firm relationships, the proposed multi-agent decision support system continuously observes real-time news reports and forecasts their potential impact on the corresponding stock price. After identifying relating companies for which significant market reactions can be expected, a wireless push-based message service promptly supplies information. A case study is used to illustrate the multi-agent-based decision support system (MAB-DSS) implementation and its use. The example shows that the MAB-DSS can automate the solution for intricate and dynamic valuation effects among interdependent firms and provide constructive advice for individual investors.

[1]  Winfried Lamersdorf,et al.  Jadex: A BDI Reasoning Engine , 2005, Multi-Agent Programming.

[2]  Fausto Giunchiglia,et al.  Tropos: An Agent-Oriented Software Development Methodology , 2004, Autonomous Agents and Multi-Agent Systems.

[3]  B. Orgun,et al.  HL7 ontology and mobile agents for interoperability in heterogeneous medical information systems , 2006, Comput. Biol. Medicine.

[4]  João Leite,et al.  A Survey of Programming Languages and Platforms for Multi-Agent Systems , 2006, Informatica.

[5]  Diane Vanbergue,et al.  Conception de simulation multi-agents : application à la simulation des migrations intra-urbaines de la ville de Bogota , 2006, Quatre ans de recherche urbaine 2001-2004. Volume I.

[6]  K. Sycara,et al.  This Is a Publication of the American Association for Artificial Intelligence Multiagent Systems Multiagent System Issues and Challenges Individual Agent Reasoning Task Allocation Multiagent Planning Recognizing and Resolving Conflicts Managing Communication Modeling Other Agents Managing Resources , 2022 .

[7]  Dirk Krafzig,et al.  Enterprise SOA: Service-Oriented Architecture Best Practices , 2004 .

[8]  Robin G. Qiu.  Towards Ontology-driven Knowledge Synthesis for Heterogeneous Information Systems , 2006, J. Intell. Manuf..

[9]  Georgios Meditskos,et al.  A Rule-Based Object-Oriented OWL Reasoner , 2008, IEEE Transactions on Knowledge and Data Engineering.

[10]  Malay K. Dey,et al.  Who Trades Around Earnings Announcements? Evidence from Torq Data , 2007 .

[11]  Scott A. DeLoach,et al.  Multiagent Systems Engineering , 2001, Int. J. Softw. Eng. Knowl. Eng..

[12]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993 .

[13]  Frank S. C. Tseng,et al.  The concept of document warehousing for multi-dimensional modeling of textual-based business intelligence , 2006, Decis. Support Syst..

[14]  Jacques Ferber,et al.  Multi-agent systems - an introduction to distributed artificial intelligence , 1999 .

[15]  Michael Wooldridge,et al.  Intelligent agents: theory and practice The Knowledge Engineering Review , 1995 .

[16]  Y. Shoham.  Introduction to Multi-Agent Systems , 2002 .

[17]  Paul A. Fishwick,et al.  Computer Simulation: Growth Through Extension , 1997 .

[18]  Dipti Srinivasan,et al.  An Introduction to Multi-Agent Systems , 2010 .

[19]  Robert L. Axtell,et al.  WHY AGENTS? ON THE VARIED MOTIVATIONS FOR AGENT COMPUTING IN THE SOCIAL SCIENCES , 2000 .

[20]  Von-Wun Soo,et al.  A cooperative multi-agent platform for invention based on patent document analysis and ontology , 2006, Expert Syst. Appl..

[21]  Sveriges Riksbank.  Is Firm Interdependence within Industries Important for Portfolio Credit Risk? , 2004 .

[22]  José M. Molina López,et al.  Heterogeneous Domain Ontology for Location Based Information System in a Multi-agent Framework , 2006, IDEAL.

[23]  D. Foley,et al.  The economy needs agent-based modelling , 2009, Nature.

[24]  Katia P. Sycara,et al.  The RETSINA MAS Infrastructure , 2003, Autonomous Agents and Multi-Agent Systems.

[25]  Ron Weber,et al.  Conceptual Modeling and Ontology: Possibilities and Pitfalls , 2003, J. Database Manag..

[26]  Winfried Lamersdorf,et al.  Jadex: A Short Overview , 2004 .

[27]  Huaiqing Wang,et al.  Ontologies for crisis contagion management in financial institutions , 2009, J. Inf. Sci..

[28]  J. V. Rauff,et al.  Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence , 2005 .

[29]  Jürgen Dix,et al.  Multi-Agent Programming , 2009, Springer US.

[30]  Gerhard Weiss,et al.  Multi-Agent Systems , 2013 .

[31]  Blake LeBaron,et al.  Agent-based computational finance : Suggested readings and early research , 2000 .

[32]  Radu Popescu-Zeletin,et al.  Evolving biosciences in multi-agent systems , 2005, IEEE/WIC/ACM International Conference on Intelligent Agent Technology.

[33]  R. Litzenberger,et al.  Announcement effects of new equity issues and the use of intraday price data , 1988 .

[34]  Dirk Krafzig,et al.  Enterprise SOA: Service-Oriented Architecture Best Practices (The Coad Series) , 2004 .

[35]  Mauro Gallegati,et al.  Business fluctuations in a credit-network economy , 2006, 1006.3521.

[36]  Alexis Drogoul,et al.  Multi-agent Based Simulation: Where Are the Agents? , 2002, MABS.

[37]  Nobuhiro Kiyotaki,et al.  Balance-Sheet Contagion , 2002 .

[38]  Filip De Turck,et al.  Distributed Reasoning for Context-Aware Services through Design of an OWL Meta-Model , 2008, Fourth International Conference on Autonomic and Autonomous Systems (ICAS'08).

[39]  Gerhard Weiss,et al.  Multiagent systems: a modern approach to distributed artificial intelligence , 1999 .

[40]  Michael R. Genesereth,et al.  Software agents , 1994, CACM.

[41]  Agostino Poggi,et al.  Developing Multi-agent Systems with JADE , 2007, ATAL.

[42]  Elke Mentges.  Concepts for an agent-based framework for interdisciplinary social science simulation , 1999, J. Artif. Soc. Soc. Simul..

[43]  Olegas Vasilecas,et al.  Ontology-Based Information Systems Development: The Problem of Automation of Information Processing Rules , 2006, ADVIS.

[44]  Ron Weber,et al.  Research Commentary: Information Systems and Conceptual Modeling - A Research Agenda , 2002, Inf. Syst. Res..

[45]  Keith L. Clark,et al.  Ontology schema for an agent belief store , 2007, Int. J. Hum. Comput. Stud..

[46]  Nicholas R. Jennings,et al.  Intelligent agents: theory and practice , 1995, The Knowledge Engineering Review.

[47]  Hua-ping Chen,et al.  Conceptual model of valuation effects based on inter-firm relationship , 2010, 2010 International Conference on Electronics and Information Engineering.

[48]  A. Roadmapof.  A Roadmap of Agent Research and Development , 1995 .

[49]  Paolo Busetta,et al.  Jack intelligent agents - components for intelligent agents in java , 1998 .