ARIMA and symmetric GARCH-type models in forecasting Malaysia gold price

Gold price modelling is crucial in gold price pattern determination since the information can be used for investors to enter and exit the market. The model selection is important and corresponds to the gold price movement characteristics. This study examines the forecasting performance of autoregres...

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Main Authors: Siti Roslindar, Yaziz, Roslinazairimah, Zakaria, Suhartono, .
Format: Conference or Workshop Item
Language:English
Published: IOP Publishing 2019
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/27848/1/ARIMA%20and%20symmetric%20GARCH-type%20models%20in%20forecasting.pdf
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author Siti Roslindar, Yaziz
Roslinazairimah, Zakaria
Suhartono, .
author_facet Siti Roslindar, Yaziz
Roslinazairimah, Zakaria
Suhartono, .
author_sort Siti Roslindar, Yaziz
collection UMP
description Gold price modelling is crucial in gold price pattern determination since the information can be used for investors to enter and exit the market. The model selection is important and corresponds to the gold price movement characteristics. This study examines the forecasting performance of autoregressive integrated moving average (ARIMA) with symmetric generalised autoregressive conditional heteroscedastic (GARCH)-type models (standard GARCH, IGARCH and GARCH-M) under three types of innovations that are Gaussian, t and generalized error distributions to model gold price. The proposed models are employed to daily Malaysia gold price from year 2003 to 2014. The empirical results indicate that ARIMA(0,1,0) - standard GARCH(1,1) using t innovations is the most preferred ARIMA with symmetric GARCH-type model.
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spelling UMPir278482021-01-18T04:13:27Z http://umpir.ump.edu.my/id/eprint/27848/ ARIMA and symmetric GARCH-type models in forecasting Malaysia gold price Siti Roslindar, Yaziz Roslinazairimah, Zakaria Suhartono, . QA Mathematics Gold price modelling is crucial in gold price pattern determination since the information can be used for investors to enter and exit the market. The model selection is important and corresponds to the gold price movement characteristics. This study examines the forecasting performance of autoregressive integrated moving average (ARIMA) with symmetric generalised autoregressive conditional heteroscedastic (GARCH)-type models (standard GARCH, IGARCH and GARCH-M) under three types of innovations that are Gaussian, t and generalized error distributions to model gold price. The proposed models are employed to daily Malaysia gold price from year 2003 to 2014. The empirical results indicate that ARIMA(0,1,0) - standard GARCH(1,1) using t innovations is the most preferred ARIMA with symmetric GARCH-type model. IOP Publishing 2019-11-07 Conference or Workshop Item PeerReviewed pdf en cc_by http://umpir.ump.edu.my/id/eprint/27848/1/ARIMA%20and%20symmetric%20GARCH-type%20models%20in%20forecasting.pdf Siti Roslindar, Yaziz and Roslinazairimah, Zakaria and Suhartono, . (2019) ARIMA and symmetric GARCH-type models in forecasting Malaysia gold price. In: Journal of Physics: Conference Series, 2nd International Conference on Applied & Industrial Mathematics and Statistics (ICoAIMS 2019) , 23-25 July 2019 , Kuantan, Pahang, Malaysia. pp. 1-9., 1366 (012126). ISSN 1742-6588 (print); 1742-6596 (online) (Published) https://doi.org/10.1088/1742-6596/1366/1/012126
spellingShingle QA Mathematics
Siti Roslindar, Yaziz
Roslinazairimah, Zakaria
Suhartono, .
ARIMA and symmetric GARCH-type models in forecasting Malaysia gold price
title ARIMA and symmetric GARCH-type models in forecasting Malaysia gold price
title_full ARIMA and symmetric GARCH-type models in forecasting Malaysia gold price
title_fullStr ARIMA and symmetric GARCH-type models in forecasting Malaysia gold price
title_full_unstemmed ARIMA and symmetric GARCH-type models in forecasting Malaysia gold price
title_short ARIMA and symmetric GARCH-type models in forecasting Malaysia gold price
title_sort arima and symmetric garch type models in forecasting malaysia gold price
topic QA Mathematics
url http://umpir.ump.edu.my/id/eprint/27848/1/ARIMA%20and%20symmetric%20GARCH-type%20models%20in%20forecasting.pdf
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