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. © 2012 IFIP International Federation for Information Processing.
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CITATION STYLE
Tirea, M., Tandau, I., & Negru, V. (2012). Stock market multi-agent recommendation system based on the Elliott Wave Principle. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7465 LNCS, pp. 332–346). https://doi.org/10.1007/978-3-642-32498-7_25
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