%0 Conference Proceedings
%T Stock Market Multi-Agent Recommendation System Based on the Elliott Wave Principle
%+ Universitatea de Vest din Timișoara [România] = West University of Timișoara [Romania] = Université Ouest de Timișoara [Roumanie] (UVT)
%+ Green Mountain Analytics
%A Tirea, Monica
%A Tandau, Ioan
%A Negru, Viorel
%Z Part 1: Conference
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B International Cross-Domain Conference and Workshop on Availability, Reliability, and Security (CD-ARES)
%C Prague, Czech Republic
%Y Gerald Quirchmayr
%Y Josef Basl
%Y Ilsun You
%Y Lida Xu
%Y Edgar Weippl
%I Springer
%3 Multidisciplinary Research and Practice for Information Systems
%V LNCS-7465
%P 332-346
%8 2012-08-20
%D 2012
%R 10.1007/978-3-642-32498-7_25
%K Multi-Agent Systems
%K Elliott Wave Theory
%K Technical Analysis Methods
%K Neural Networks
%K Fibonacci Series
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X The goal of this paper is to create a hybrid recommendation system based on a Multi-Agent Architecture that will inform the trader about the future stock trend in order to improve the profitability of a short or medium time period investment.We proposed a Multi-Agent Architecture that uses the numbers of the Fibonacci Series and the Elliott Wave Theory, along with some special Technical Analysis Methods (namely Gap Analysis, Breakout System, Market Modes and Momentum Precedes Price) and Neural Networks (Multi-Layer Perceptron) and tries to combine and / or compare the result given by part / all of them in order to forecast trends in the financial market. In order to validate our model a prototype was developed.
%G English
%Z TC 5
%Z TC 8
%Z WG 8.4
%Z WG 8.9
%2 https://inria.hal.science/hal-01542446/document
%2 https://inria.hal.science/hal-01542446/file/978-3-642-32498-7_25_Chapter.pdf
%L hal-01542446
%U https://inria.hal.science/hal-01542446
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG
%~ IFIP-TC8
%~ IFIP-CD-ARES
%~ IFIP-WG8-4
%~ IFIP-WG8-9
%~ IFIP-LNCS-7465