Skip to Main content Skip to Navigation
Conference papers

Stock Market Multi-Agent Recommendation System Based on the Elliott Wave Principle

Abstract : 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.
Complete list of metadata

Cited literature [13 references]  Display  Hide  Download
Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Monday, June 19, 2017 - 5:01:25 PM
Last modification on : Monday, February 1, 2021 - 11:48:02 AM
Long-term archiving on: : Friday, December 15, 2017 - 9:52:09 PM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License



Monica Tirea, Ioan Tandau, Viorel Negru. Stock Market Multi-Agent Recommendation System Based on the Elliott Wave Principle. International Cross-Domain Conference and Workshop on Availability, Reliability, and Security (CD-ARES), Aug 2012, Prague, Czech Republic. pp.332-346, ⟨10.1007/978-3-642-32498-7_25⟩. ⟨hal-01542446⟩



Record views


Files downloads