Title :
An investment strategy for the Stock Exchange using neural networks
Author :
Wysocki, Antoni ; Lawrynczuk, Maciej
Author_Institution :
Inst. of Control & Comput. Eng., Warsaw Univ. of Technol., Warsaw, Poland
Abstract :
This paper describes a neural system which helps to make the current investment decisions. Some well known financial indicators usually considered by investors are inputs of the system. The basic problem is to select appropriately the indicators which would give the best predictor. Two methods are used and compared: the combination method and the correlation method. To analyze the problem daily quotations of companies included in the Warsaw Stock Exchange Index (WIG20) are used.
Keywords :
combinatorial mathematics; correlation methods; investment; neural nets; stock markets; WIG20; Warsaw Stock Exchange Index; combination method; correlation method; daily quotations; financial indicators; investment decisions; neural networks; Biological neural networks; Indexes; Investment; Oscillators; Share prices; Stock markets; Stock exchange; neural networks; nonlinear modeling; prediction; soft computing;
Conference_Titel :
Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on
