Incorporating artificial neural networks into a rule-based financial trading system

Author

Tan, Clarence N W

Author_Institution

Bond Univ., Gold Coast, Qld., Australia

fYear

1993

fDate

24-26 Nov 1993

Firstpage

292

Lastpage

293

Abstract

This paper discusses the incorporation of artificial neural networks (ANNs) into a rule-based financial trading system to enhance and improve trading profitability. It discusses the advantages of artificial neural nets over traditional rule-based-only systems. It also introduces an ideal ANN rule-based financial trading system that can incorporate technical, fundamental and chart analyses into the financial trading decision-making process, which may improve the probability of trading success. Each of the analysis methods is discussed in the context of its incorporation into an ANN-based system

Keywords

financial data processing; knowledge based systems; neural nets; probability; stock markets; artificial neural networks; chart analysis; decision-making process; fundamental analysis; rule-based financial trading system; technical analysis; trading profitability; trading success probability; Artificial neural networks; Bonding; Computer networks; Decision making; Engines; Game theory; Gold; Knowledge based systems; Knowledge engineering; Security;

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.1993.323004

Filename

323004