Cover Image

Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms

Forex prediction has become a challenging task in the Forex market since the late 1970s due to uncertainty movement of exchange rates.In this paper, we utilised linear regression equation to analyse the historical data and discover the trends patterns in Forex.These trends patterns are modeled and l...

Full description

Saved in:
Bibliographic Details
Main Authors: Tiong, Leslie C.O., Ngo, David C.L., Lee, Yunli
Format: Conference or Workshop Item
Language:English
Published: 2013
Subjects:
QA76 Computer software
Online Access:http://repo.uum.edu.my/11971/1/PID92.pdf
http://repo.uum.edu.my/11971/
http://www.icoci.cms.net.my/proceedings/2013/TOC.html
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uum.repo.11971
record_format eprints
spelling my.uum.repo.119712014-08-24T02:33:57Z http://repo.uum.edu.my/11971/ Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms Tiong, Leslie C.O. Ngo, David C.L. Lee, Yunli QA76 Computer software Forex prediction has become a challenging task in the Forex market since the late 1970s due to uncertainty movement of exchange rates.In this paper, we utilised linear regression equation to analyse the historical data and discover the trends patterns in Forex.These trends patterns are modeled and learned by Artificial Neural Network algorithm, and Dynamic Time Warping algorithm is used to predict the near future trends.Our experiment result shows a satisfactory result using the proposed approach. 2013-08-28 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/11971/1/PID92.pdf Tiong, Leslie C.O. and Ngo, David C.L. and Lee, Yunli (2013) Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms. In: 4th International Conference on Computing and Informatics (ICOCI 2013), 28 -30 August 2013, Kuching, Sarawak, Malaysia. http://www.icoci.cms.net.my/proceedings/2013/TOC.html
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA76 Computer software
spellingShingle QA76 Computer software
Tiong, Leslie C.O.
Ngo, David C.L.
Lee, Yunli
Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms
description Forex prediction has become a challenging task in the Forex market since the late 1970s due to uncertainty movement of exchange rates.In this paper, we utilised linear regression equation to analyse the historical data and discover the trends patterns in Forex.These trends patterns are modeled and learned by Artificial Neural Network algorithm, and Dynamic Time Warping algorithm is used to predict the near future trends.Our experiment result shows a satisfactory result using the proposed approach.
format Conference or Workshop Item
author Tiong, Leslie C.O.
Ngo, David C.L.
Lee, Yunli
author_facet Tiong, Leslie C.O.
Ngo, David C.L.
Lee, Yunli
author_sort Tiong, Leslie C.O.
title Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms
title_short Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms
title_full Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms
title_fullStr Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms
title_full_unstemmed Forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms
title_sort forex trading prediction using linear regression line, artificial neural network and dynamic time warping algorithms
publishDate 2013
url http://repo.uum.edu.my/11971/1/PID92.pdf
http://repo.uum.edu.my/11971/
http://www.icoci.cms.net.my/proceedings/2013/TOC.html
_version_ 1644280786725109760
score 13.211869

Similar Items