Behavioral Trading System - Detecting Crisis, Risk and Stability in Financial Markets

Abstract

The goal of this paper is to create a hybrid system based on a Multi-Agent Architecture that will investigate the evolution of some prediction strategies (Elliott Wave, Lucas, GANN) along with technical, fundamental and macro-economical analysis methods on stock market indexes and how this information influences the stock market behavior in order to improve the profitability on a short or medium time period investment. The proposed system correlates the results from Elliott Wave, GANN and Lucas methods in order to determine a better prediction of the stock price position on the trend and based on this to determine which will be its future direction. The system also finds correlations between the pattern recognition methods and technical and fundamental methods results in order to find the direction of the market trend, to predict the next day price of a stock and to trigger a useful buy/sell signal. In order to validate our model a prototype was developed and applied to the Bucharest Stock Exchange Market indexes.