| dc.identifier.citation | Stankevicius, G. The Application of Self-Organizing Neural Networks in Financial Market Analysis / G. Stankevicius // International Conference on Neural Networks and Artificial Intelligence ICNNAI'99 = Международная конференция по нейронным сетям и искусственному интеллекту ICNNAI'99 : Proceedings, Brest, Belarus, 12–15 October 1999 / Brest Polytechnic Institute, Department of Computers and Laboratory of Artificial Neural Networks, Belarus Special Interest Group of International Neural NetWork Society, International Neural NetWork Society, Belarusian State University of Informatics and Radioelectronics (Belarus), Belarusian Academy of Sciences, Institute of Engineering Cybemetics (Belarus), Universidad Politechnica de Valencia (Spain), Institute of Computer Information Technologies (Ukraine, Ternopil) ; ed. V. Golovko. – Brest : BPI, 1999. – P. 161–165. | ru |
| dc.description.abstract | The problem of comparison of different companies is facing, when analyzing company's performance in stock exchange market. Due to many different fmancial ratios and parameters sometimes it is almost impossible to decide which company is a leader or not. One of the ways to solve this problem is the use of self-organizing (Kohonen's) neural networks. Using financial parameters as inputs, as an output we will have different groups of companies. Using the ranking, which is made before, results it is possible to determine which group consists of leading companies. By adding financial parameters of concrete company to the existing network, therefore, company will appear in one of earlier formed groups. Now it is possible to decide about mentioned company's price changing tendencies in the nearest future. | ru |
