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A risk management tool based on forecasting using artificial neural networks is presented in this paper. The system is composed by two modules, each containing a sparsely connected feed forward network trained using a back propagation algorithm. The method is tested on real data from the BVB stock market. The presented results emphasise the high potential of using such a system in helping investors to detect the proper moments to exit the market in order to preserve their investments.

2010 Mathematics Subject Classification. 68T10, 68T05.1998 CR Categories and Descriptors. I.2.6 [ARTIFICIAL INTELLIGENCE ]: Subtopic – I.2.6 Learning; I.2.8 [ARTIFICIAL INTELLIGENCE]: Subtopic – I.2.8 Problem Solving, Control Methods, and Search.

Key words and phrases. forecasting, stock market, artificial neural networks.This paper has been presented at the International Conference KEPT2013: Knowledge Engineering Principles and Techniques, organized by Babeș-Bolyai University, Cluj-Napoca, July 5-7 2013.