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

fYear

1993

fDate

24-26 Nov 1993

Firstpage

294

Lastpage

295

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ANNES.1993.323022

Filename

323022