Predicting Macroeconomic Time Series In Malaysia : Using Neural Network Approaches

In recent years, neural networks have received an increasing amount of intention among macroeconomic forecasters because of their potential to detect and reproduce linear and nonlinear relationship among a set of variables. This study provides an introduction to neural networks and its establishment...

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Main Author: Mohd. Zukime, Mat Junoh
Format: Thesis
Language:eng
eng
Published: 2001
Subjects:
Online Access:https://etd.uum.edu.my/353/1/Mohd._Zukime_Hj._Mat_Junoh%2C_2001.pdf
https://etd.uum.edu.my/353/2/1.Mohd._Zukime_Hj._Mat_Junoh%2C_2001.pdf
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id my-uum-etd.353
record_format uketd_dc
spelling my-uum-etd.3532013-07-24T12:06:51Z Predicting Macroeconomic Time Series In Malaysia : Using Neural Network Approaches 2001 Mohd. Zukime, Mat Junoh Sekolah Siswazah Sekolah Siswazah HC Economic History and Conditions In recent years, neural networks have received an increasing amount of intention among macroeconomic forecasters because of their potential to detect and reproduce linear and nonlinear relationship among a set of variables. This study provides an introduction to neural networks and its establishment to standard econometric techniques. An empirical results in forecasting macroeconomic variables to GDP growth in Malaysia was initially introduced. For both the in-sample and the out-of-sample periods, the forecasting accuracy of the neural network is found to be superior to a well established linear regression model, with the error reduction ranging 8 per cent to 57 per cent. A throughout review of the literature suggests that neural networks are generally more accurate than linear models for out-of-sample forecasting of economic output and various financial variables such as stock prices. However, the literature should still be considered inconclusive due to the relatively small number of reliable studies on the macroeconomic forecasting. The full potential of neural networks can probably be exploited by using them in conjunction with linear regression models. Hence, neural networks should be viewed as an additional tool to be included in the toolbox of macroeconomic forecasters. 2001 Thesis https://etd.uum.edu.my/353/ https://etd.uum.edu.my/353/1/Mohd._Zukime_Hj._Mat_Junoh%2C_2001.pdf application/pdf eng validuser https://etd.uum.edu.my/353/2/1.Mohd._Zukime_Hj._Mat_Junoh%2C_2001.pdf application/pdf eng public masters masters Universiti Utara Malaysia
institution Universiti Utara Malaysia
collection UUM ETD
language eng
eng
topic HC Economic History and Conditions
spellingShingle HC Economic History and Conditions
Mohd. Zukime, Mat Junoh
Predicting Macroeconomic Time Series In Malaysia : Using Neural Network Approaches
description In recent years, neural networks have received an increasing amount of intention among macroeconomic forecasters because of their potential to detect and reproduce linear and nonlinear relationship among a set of variables. This study provides an introduction to neural networks and its establishment to standard econometric techniques. An empirical results in forecasting macroeconomic variables to GDP growth in Malaysia was initially introduced. For both the in-sample and the out-of-sample periods, the forecasting accuracy of the neural network is found to be superior to a well established linear regression model, with the error reduction ranging 8 per cent to 57 per cent. A throughout review of the literature suggests that neural networks are generally more accurate than linear models for out-of-sample forecasting of economic output and various financial variables such as stock prices. However, the literature should still be considered inconclusive due to the relatively small number of reliable studies on the macroeconomic forecasting. The full potential of neural networks can probably be exploited by using them in conjunction with linear regression models. Hence, neural networks should be viewed as an additional tool to be included in the toolbox of macroeconomic forecasters.
format Thesis
qualification_name masters
qualification_level Master's degree
author Mohd. Zukime, Mat Junoh
author_facet Mohd. Zukime, Mat Junoh
author_sort Mohd. Zukime, Mat Junoh
title Predicting Macroeconomic Time Series In Malaysia : Using Neural Network Approaches
title_short Predicting Macroeconomic Time Series In Malaysia : Using Neural Network Approaches
title_full Predicting Macroeconomic Time Series In Malaysia : Using Neural Network Approaches
title_fullStr Predicting Macroeconomic Time Series In Malaysia : Using Neural Network Approaches
title_full_unstemmed Predicting Macroeconomic Time Series In Malaysia : Using Neural Network Approaches
title_sort predicting macroeconomic time series in malaysia : using neural network approaches
granting_institution Universiti Utara Malaysia
granting_department Sekolah Siswazah
publishDate 2001
url https://etd.uum.edu.my/353/1/Mohd._Zukime_Hj._Mat_Junoh%2C_2001.pdf
https://etd.uum.edu.my/353/2/1.Mohd._Zukime_Hj._Mat_Junoh%2C_2001.pdf
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