Hybrid Neural Network and Decision Tree for for Exchange Rates Forecasting

As the largest financial market in the world, foreign exchange (Forex) is becoming a very profitable market with a daily transaction of more than 3.0 trillion U.S. dollars. Therefore, predicting about it has been a challenge for many years. Artificial Neural Network (ANN) provides better performance...

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Main Authors:	Ardiansyah, Soleh, Mazlina, Abdul Majid, Jasni, Mohamad Zain
Format:	Conference or Workshop Item
Language:	English
Published:	2012
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/3518/ http://umpir.ump.edu.my/id/eprint/3518/1/6-ICoCSIM.pdf

id	ump-3518
recordtype	eprints
spelling	ump-35182018-05-21T01:53:43Z http://umpir.ump.edu.my/id/eprint/3518/ Hybrid Neural Network and Decision Tree for for Exchange Rates Forecasting Ardiansyah, Soleh Mazlina, Abdul Majid Jasni, Mohamad Zain QA76 Computer software As the largest financial market in the world, foreign exchange (Forex) is becoming a very profitable market with a daily transaction of more than 3.0 trillion U.S. dollars. Therefore, predicting about it has been a challenge for many years. Artificial Neural Network (ANN) provides better performance of forecasting but it tends to get stuck in local minima and there is no optimal way to determine the best classifier on it. Meanwhile, Decision Tree (DT) is able to generate classifier in the form of a tree. This paper proposes a hybrid prediction model by combining both ANN and DTalgorithm to predict exchange rates. The models are constructed by using the better of parameters and architectures based on related work such as filtering mechanism, number of hidden layers, number of hidden neurons, training algorithm, and error measurement, with the assumption that if the hybrid model is constructed by the better parameters and architectures, then the output of the model also produces better result 2012-12-03 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/3518/1/6-ICoCSIM.pdf Ardiansyah, Soleh and Mazlina, Abdul Majid and Jasni, Mohamad Zain (2012) Hybrid Neural Network and Decision Tree for for Exchange Rates Forecasting. In: Proceedings of the First International Conference on Computational Science and Information Management (ICoCSIM2012), 3-5 December 2012 , Toba Lake, North Sumatra, Indonesia. pp. 29-35., 1. ISBN 978-967-0120-60-7
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Ardiansyah, Soleh Mazlina, Abdul Majid Jasni, Mohamad Zain Hybrid Neural Network and Decision Tree for for Exchange Rates Forecasting
description	As the largest financial market in the world, foreign exchange (Forex) is becoming a very profitable market with a daily transaction of more than 3.0 trillion U.S. dollars. Therefore, predicting about it has been a challenge for many years. Artificial Neural Network (ANN) provides better performance of forecasting but it tends to get stuck in local minima and there is no optimal way to determine the best classifier on it. Meanwhile, Decision Tree (DT) is able to generate classifier in the form of a tree. This paper proposes a hybrid prediction model by combining both ANN and DTalgorithm to predict exchange rates. The models are constructed by using the better of parameters and architectures based on related work such as filtering mechanism, number of hidden layers, number of hidden neurons, training algorithm, and error measurement, with the assumption that if the hybrid model is constructed by the better parameters and architectures, then the output of the model also produces better result
format	Conference or Workshop Item
author	Ardiansyah, Soleh Mazlina, Abdul Majid Jasni, Mohamad Zain
author_facet	Ardiansyah, Soleh Mazlina, Abdul Majid Jasni, Mohamad Zain
author_sort	Ardiansyah, Soleh
title	Hybrid Neural Network and Decision Tree for for Exchange Rates Forecasting
title_short	Hybrid Neural Network and Decision Tree for for Exchange Rates Forecasting
title_full	Hybrid Neural Network and Decision Tree for for Exchange Rates Forecasting
title_fullStr	Hybrid Neural Network and Decision Tree for for Exchange Rates Forecasting
title_full_unstemmed	Hybrid Neural Network and Decision Tree for for Exchange Rates Forecasting
title_sort	hybrid neural network and decision tree for for exchange rates forecasting
publishDate	2012
url	http://umpir.ump.edu.my/id/eprint/3518/ http://umpir.ump.edu.my/id/eprint/3518/1/6-ICoCSIM.pdf
first_indexed	2023-09-18T21:57:54Z
last_indexed	2023-09-18T21:57:54Z
_version_	1777414202000932864

Hybrid Neural Network and Decision Tree for for Exchange Rates Forecasting

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