Symmetric and asymmetric garch models for forecasting the prices of gold

Gold prices forecasts are of interest to many people. Gold prices however, change rapidly from period to period. In short, they are not constant. The change is not only in the mean, but also in the variability of the gold prices series. Daily gold prices per ounce, from January 3, 2000 to December 3...

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Main Author:	Pung, Yean Ping
Format:	Thesis
Language:	English
Published:	2013
Subjects:	Q Science (General)
Online Access:	http://eprints.utm.my/id/eprint/47930/25/PungYeanPingMFS2013.pdf
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spelling	my-utm-ep.479302017-06-22T03:09:49Z Symmetric and asymmetric garch models for forecasting the prices of gold 2013-09 Pung, Yean Ping Q Science (General) Gold prices forecasts are of interest to many people. Gold prices however, change rapidly from period to period. In short, they are not constant. The change is not only in the mean, but also in the variability of the gold prices series. Daily gold prices per ounce, from January 3, 2000 to December 31, 2010 is used in this study with the Schwarz Information Criterion (SIC), Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) as the forecasting accuracy measures. For the purpose of this study, gold prices from ten major consumer countries are examined. The currencies are American dollar, Australian dollar, Canadian dollar, Swiss franc, Chinese renmimbi, Egyptian pound, Euro, Japanese yen, Turkish lira and South African rand. This study considers five models from the GARCH-family namely the Generalized Autoregressive Conditional Heteroscedasticity (GARCH (p, q)), GARCH-M, Power of GARCH (PGARCH), Threshold GARCH (TGARCH) and Exponential GARCH (EGARCH). These models are analyzed by using the E-Views 6.0 software. Several combinations of p and q values are considered to develop several GARCH (p, q) models. Using the maximum likelihood method to estimate the coefficients in the models, followed by model validation and model selection criteria, it is concluded that EGARCH (1, 1) and TGARCH (1, 1) are the best models for eight of the currencies understudied. 2013-09 Thesis http://eprints.utm.my/id/eprint/47930/ http://eprints.utm.my/id/eprint/47930/25/PungYeanPingMFS2013.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Science Faculty of Science
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	Q Science (General)
spellingShingle	Q Science (General) Pung, Yean Ping Symmetric and asymmetric garch models for forecasting the prices of gold
description	Gold prices forecasts are of interest to many people. Gold prices however, change rapidly from period to period. In short, they are not constant. The change is not only in the mean, but also in the variability of the gold prices series. Daily gold prices per ounce, from January 3, 2000 to December 31, 2010 is used in this study with the Schwarz Information Criterion (SIC), Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) as the forecasting accuracy measures. For the purpose of this study, gold prices from ten major consumer countries are examined. The currencies are American dollar, Australian dollar, Canadian dollar, Swiss franc, Chinese renmimbi, Egyptian pound, Euro, Japanese yen, Turkish lira and South African rand. This study considers five models from the GARCH-family namely the Generalized Autoregressive Conditional Heteroscedasticity (GARCH (p, q)), GARCH-M, Power of GARCH (PGARCH), Threshold GARCH (TGARCH) and Exponential GARCH (EGARCH). These models are analyzed by using the E-Views 6.0 software. Several combinations of p and q values are considered to develop several GARCH (p, q) models. Using the maximum likelihood method to estimate the coefficients in the models, followed by model validation and model selection criteria, it is concluded that EGARCH (1, 1) and TGARCH (1, 1) are the best models for eight of the currencies understudied.
format	Thesis
qualification_level	Master's degree
author	Pung, Yean Ping
author_facet	Pung, Yean Ping
author_sort	Pung, Yean Ping
title	Symmetric and asymmetric garch models for forecasting the prices of gold
title_short	Symmetric and asymmetric garch models for forecasting the prices of gold
title_full	Symmetric and asymmetric garch models for forecasting the prices of gold
title_fullStr	Symmetric and asymmetric garch models for forecasting the prices of gold
title_full_unstemmed	Symmetric and asymmetric garch models for forecasting the prices of gold
title_sort	symmetric and asymmetric garch models for forecasting the prices of gold
granting_institution	Universiti Teknologi Malaysia, Faculty of Science
granting_department	Faculty of Science
publishDate	2013
url	http://eprints.utm.my/id/eprint/47930/25/PungYeanPingMFS2013.pdf
_version_	1747817266229018624

Symmetric and asymmetric garch models for forecasting the prices of gold

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