This paper is focused on the development of intelligent decision making model which is based on the application of artificial neural networks (ANN) and swarm intelligence technologies. The proposed model is used to generate one-step forward investment decisions. The ANN are used to make the analysis of historical stock returns and to calculate one day forward possible profit, which could be get while following the model proposed decisions, concerning the purchase of the stocks. Subsequently the Particle Swarm Optimization (PSO) algorithm is applied in order to select the „global best” ANNs for the future investment decisions and to adapt the weights of other networks towards the weights of the best network. The experimental investigations were made considering different number of neural networks, moving time intervals and commission fees. The experimental results presented in the paper show that the application of our proposed methodology lets to achieve better results than the average of the market.
DEVELOPMENT OF INTELLIGENT DECISION MAKING MODEL FOR STOCK MARKETS
