Alternative distributed models for the comparative study of stock market phenomena

Benos, A; Tzafestas, E

dc.contributor.author	Benos, A	en
dc.contributor.author	Tzafestas, E	en
dc.date.accessioned	2014-03-01T01:45:53Z
dc.date.available	2014-03-01T01:45:53Z
dc.date.issued	1997	en
dc.identifier.issn	00200255	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/24770
dc.relation.uri	http://www.scopus.com/inward/record.url?eid=2-s2.0-0031191346&partnerID=40&md5=f58d0c4646df4a20ad760fab93267716	en
dc.subject.other	Artificial intelligence	en
dc.subject.other	Distributed computer systems	en
dc.subject.other	Knowledge representation	en
dc.subject.other	Distributed multiagent models	en
dc.subject.other	Stock market phenomena	en
dc.subject.other	Financial data processing	en
dc.title	Alternative distributed models for the comparative study of stock market phenomena	en
heal.type	journalArticle	en
heal.publicationDate	1997	en
heal.abstract	In this paper we present a methodology of studying the complex phenomena emerging in stock markets. This methodology is based on the use of distributed multi-agent models with minimal knowledge representation and reasoning capabilities that have proven to be a powerful modeling tool for complex biological systems. Unlike neural and ""neoconnectionist"" models, our models allow a comparative and incremental evaluation of their validity and relevance to the observed phenomena. The possibility of their application to the modeling and study of stock market phenomena is demonstrated on a simple example of a central agency that regulates the behavior of the investors: we show how a ""blind"" or myopic behavioral model reproduces results found in the literature and how the mutation of the model according to the parameters' values or the adaptation structures gives rise to a series of complex phenomena comparable to those observed in reality. © Elsevier Science Inc. 1997.	en
heal.journalName	Information Sciences	en
dc.identifier.volume	99	en
dc.identifier.issue	3-4	en
dc.identifier.spage	137	en
dc.identifier.epage	157	en