Authors:
Bruce Vanstone
and
Gavin Finnie
Affiliation:
Faculty of Business and Bond University, Australia
Keyword(s):
Financial trading, Foreign currency, Artificial neural networks.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Computational Intelligence
;
Computer-Supported Education
;
Domain Applications and Case Studies
;
Fuzzy Systems
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Industrial, Financial and Medical Applications
;
Methodologies and Methods
;
Neural Networks
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Theory and Methods
Abstract:
The foreign exchange (FX) markets represent an enormous opportunity for traders. These markets have huge liquidity, trade 24 hours a day (except weekends), and allow the use of leverage. This paper takes a simple FX trading strategy and shows how to substantially improve it, using a neural network methodology originally developed by Vanstone & Finnie for creating and enhancing stockmarket trading systems. This result demonstrates the important role neural networks have to play within complex and noisy environments, such as that provided by the intraday FX markets.