Trading foreign currency using artificial neural network strategies

Bruce Vanstone*, Gavin Finnie

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Neural Computation Theory and Applications
Subtitle of host publicationNCTA 2011
EditorsK Madani
Place of PublicationFrance
PublisherSpringer
Pages163-167
Number of pages5
ISBN (Print)9789898425843
Publication statusPublished - 2011
EventInternational Conference on Neural Computation Theory and Applications - Paris, Paris, France
Duration: 24 Oct 201126 Oct 2011
http://www.ncta.ijcci.org/NCTA2011/

Conference

ConferenceInternational Conference on Neural Computation Theory and Applications
Abbreviated titleNCTA 2011
CountryFrance
CityParis
Period24/10/1126/10/11
Internet address

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Cite this

Vanstone, B., & Finnie, G. (2011). Trading foreign currency using artificial neural network strategies. In K. Madani (Ed.), Proceedings of the International Conference on Neural Computation Theory and Applications: NCTA 2011 (pp. 163-167). France: Springer.