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

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.

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Abstract

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.

Item Type: Conference or Workshop Item (Paper)
Additional Information: ISBN: 9789832078791 Organized by: Universiti Utara Malaysia
Uncontrolled Keywords: Forex Trading Prediction; Forex Trend Patterns; Artificial Neural Network; Linear Regression Line; Dynamic Time Warping
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: College of Arts and Sciences
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 24 Aug 2014 02:33
Last Modified: 24 Aug 2014 02:33
URI: https://repo.uum.edu.my/id/eprint/11971

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