Title :
Trading a NYSE-stock with a simple artificial neural network-based financial trading system
Author :
Tan, Clarence N W
Author_Institution :
School of Inf. Technol., Bond Univ., Gold Coast, Qld., Australia
Abstract :
Reports hypothetical trading results of a New York Stock Exchange (NYSE) listed stock over a period of two years using an artificial neural network (ANN) based financial trading system. The system was designed, constructed and tested for its ability to predict stock prices and more importantly increase trading profit. This system is still at a preliminary stage and many of the parameters effect on the ANN have not been fully explored yet. However, this simple system has provided insight into the design of a successful ANN-based financial trading system, as the results have been quite encouraging
Keywords :
financial data processing; neural nets; stock markets; NYSE listed stock; New York Stock Exchange; artificial neural network-based financial trading system; hypothetical trading results; stock price prediction; trading profit; Artificial neural networks; Backpropagation; Bonding; Computer networks; Economic forecasting; Information technology; Neurons; Predictive models; Stock markets; Testing;
Conference_Titel :
Artificial Neural Networks and Expert Systems, 1993. Proceedings., First New Zealand International Two-Stream Conference on
Conference_Location :
Dunedin
Print_ISBN :
0-8186-4260-2
DOI :
10.1109/ANNES.1993.323022
