The Performance of Hybrid ARIMA-GARCH Modeling in Forecasting Gold Price

In any type of investment, risk and return of the asset is very important to investors. Since 2000s, gold has been considered as a valuable precious metal. It is the most popular commodity and is categorized as a healthy return investment. Hence, the models that reflect the structure and pattern of...

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Main Authors:	Siti Roslindar, Yaziz, Noor Azlinna, Azizan, Roslinazairimah, Zakaria, Maizah Hura, Ahmad
Format:	Conference or Workshop Item
Language:	English
Published:	2013
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/4260/ http://umpir.ump.edu.my/id/eprint/4260/ http://umpir.ump.edu.my/id/eprint/4260/1/fist-2013-roslindar-the_performance_of.pdf

id	ump-4260
recordtype	eprints
spelling	ump-42602018-05-02T06:24:33Z http://umpir.ump.edu.my/id/eprint/4260/ The Performance of Hybrid ARIMA-GARCH Modeling in Forecasting Gold Price Siti Roslindar, Yaziz Noor Azlinna, Azizan Roslinazairimah, Zakaria Maizah Hura, Ahmad QA76 Computer software In any type of investment, risk and return of the asset is very important to investors. Since 2000s, gold has been considered as a valuable precious metal. It is the most popular commodity and is categorized as a healthy return investment. Hence, the models that reflect the structure and pattern of the gold price and its forecasting accuracy become very significant to investors. This study assesses the performance of hybridization of potential univariate time series specifically ARIMA models with the superior volatility model, GARCH incorporates with the formula of Box-Cox transformation in analyzing and forecasting gold price. The Box-Cox transformation is used as the data transformation due to its potential best practice in normalizing data, stabilizing variance and reducing heteroscedasticity. The performance of the proposed model is analyzed by employing the hybrid model using daily gold price data series. Empirical results indicate that the proposed hybrid model ARIMA-GARCH has effectively improved the estimating and forecasting accuracy and provide the optimum results compared to the previous studies. The findings suggest that the potential combination of powerful and flexibility of ARIMA and the strength of GARCH models in handling volatility and risk in the data series as well as to overcome the linear limitation in the ARIMA models made the hybridization of ARIMA-GARCH model as a new promising approach in modeling and forecasting gold price. 2013 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/4260/1/fist-2013-roslindar-the_performance_of.pdf Siti Roslindar, Yaziz and Noor Azlinna, Azizan and Roslinazairimah, Zakaria and Maizah Hura, Ahmad (2013) The Performance of Hybrid ARIMA-GARCH Modeling in Forecasting Gold Price. In: 20th International Congress on Modelling & Simulation 2013 (MODSIM2013), 1-6 December 2013 , Adelaide, Australia. pp. 1201-1207.. http://www.mssanz.org.au/modsim2013/F2/yaziz.pdf
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 Siti Roslindar, Yaziz Noor Azlinna, Azizan Roslinazairimah, Zakaria Maizah Hura, Ahmad The Performance of Hybrid ARIMA-GARCH Modeling in Forecasting Gold Price
description	In any type of investment, risk and return of the asset is very important to investors. Since 2000s, gold has been considered as a valuable precious metal. It is the most popular commodity and is categorized as a healthy return investment. Hence, the models that reflect the structure and pattern of the gold price and its forecasting accuracy become very significant to investors. This study assesses the performance of hybridization of potential univariate time series specifically ARIMA models with the superior volatility model, GARCH incorporates with the formula of Box-Cox transformation in analyzing and forecasting gold price. The Box-Cox transformation is used as the data transformation due to its potential best practice in normalizing data, stabilizing variance and reducing heteroscedasticity. The performance of the proposed model is analyzed by employing the hybrid model using daily gold price data series. Empirical results indicate that the proposed hybrid model ARIMA-GARCH has effectively improved the estimating and forecasting accuracy and provide the optimum results compared to the previous studies. The findings suggest that the potential combination of powerful and flexibility of ARIMA and the strength of GARCH models in handling volatility and risk in the data series as well as to overcome the linear limitation in the ARIMA models made the hybridization of ARIMA-GARCH model as a new promising approach in modeling and forecasting gold price.
format	Conference or Workshop Item
author	Siti Roslindar, Yaziz Noor Azlinna, Azizan Roslinazairimah, Zakaria Maizah Hura, Ahmad
author_facet	Siti Roslindar, Yaziz Noor Azlinna, Azizan Roslinazairimah, Zakaria Maizah Hura, Ahmad
author_sort	Siti Roslindar, Yaziz
title	The Performance of Hybrid ARIMA-GARCH Modeling in Forecasting Gold Price
title_short	The Performance of Hybrid ARIMA-GARCH Modeling in Forecasting Gold Price
title_full	The Performance of Hybrid ARIMA-GARCH Modeling in Forecasting Gold Price
title_fullStr	The Performance of Hybrid ARIMA-GARCH Modeling in Forecasting Gold Price
title_full_unstemmed	The Performance of Hybrid ARIMA-GARCH Modeling in Forecasting Gold Price
title_sort	performance of hybrid arima-garch modeling in forecasting gold price
publishDate	2013
url	http://umpir.ump.edu.my/id/eprint/4260/ http://umpir.ump.edu.my/id/eprint/4260/ http://umpir.ump.edu.my/id/eprint/4260/1/fist-2013-roslindar-the_performance_of.pdf
first_indexed	2023-09-18T21:58:45Z
last_indexed	2023-09-18T21:58:45Z
_version_	1777414256138911744

The Performance of Hybrid ARIMA-GARCH Modeling in Forecasting Gold Price

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