Modelling and forecasting gold price return and its volatility

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Main Authors: Nurul Nisa’, Khairol Azmi, Izzah Nazatul Nazihah, Ejap, Nur Hamizah, Mohd Ariff, Nur Huda Athirah, Abdullah
Other Authors: nurulnisa@uitm.edu.my
Format: Article
Language:English
Published: Institute of Engineering Mathematics, Universiti Malaysia Perlis 2023
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Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77709
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Institution: Universiti Malaysia Perlis
Language: English
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spelling my.unimap-777092023-01-24T13:08:12Z Modelling and forecasting gold price return and its volatility Nurul Nisa’, Khairol Azmi Izzah Nazatul Nazihah, Ejap Nur Hamizah, Mohd Ariff Nur Huda Athirah, Abdullah Nurul Nisa’, Khairol Azmi nurulnisa@uitm.edu.my Faculty Of Computer and Mathematical Sciences, Universiti Teknologi MARA (UiTM) GARCH Gold price Price return Forecasting Volatility Link to publisher's homepage at https://amci.unimap.edu.my/ In the financial industry, forecasting gold price return and its volatility are crucial. Even tiny improvements in prediction performance can add up to a significant sum of money. One strategy for anticipating gold price volatility is the GARCH family of models. The GARCH process provides a more realistic background for estimating financial instrument values and rates than other models. The aim of this research is to model the volatility and price of gold via GARCH(1,1), EGARCH(1,1) and TGARCH(1,1) models. The data was employed from 4th January 2016 until 29th October 2021 retrieved from Yahoo Finance website. The data was converted into return price to make it stationary. The performance of the estimated models was compared by using information criterion. The best model is the one that has the lowest values of information criterion. TGARCH(1,1) is outperformed other proposed models where it has an ability to capture the bad and good news that exist in the data series. The best model is used to forecast the volatility and return of gold price. The return is expected to be constant with high risk for the next 5 days from the point origin in this study. 2023-01-24T13:08:12Z 2023-01-24T13:08:12Z 2022-12 Article Applied Mathematics and Computational Intelligence (AMCI), vol.11(1), 2022, pages 399-411 2289-1315 (print) 2289-1323 (online) http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77709 https://amci.unimap.edu.my/ en Institute of Engineering Mathematics, Universiti Malaysia Perlis
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic GARCH
Gold price
Price return
Forecasting
Volatility
spellingShingle GARCH
Gold price
Price return
Forecasting
Volatility
Nurul Nisa’, Khairol Azmi
Izzah Nazatul Nazihah, Ejap
Nur Hamizah, Mohd Ariff
Nur Huda Athirah, Abdullah
Nurul Nisa’, Khairol Azmi
Modelling and forecasting gold price return and its volatility
description Link to publisher's homepage at https://amci.unimap.edu.my/
author2 nurulnisa@uitm.edu.my
author_facet nurulnisa@uitm.edu.my
Nurul Nisa’, Khairol Azmi
Izzah Nazatul Nazihah, Ejap
Nur Hamizah, Mohd Ariff
Nur Huda Athirah, Abdullah
Nurul Nisa’, Khairol Azmi
format Article
author Nurul Nisa’, Khairol Azmi
Izzah Nazatul Nazihah, Ejap
Nur Hamizah, Mohd Ariff
Nur Huda Athirah, Abdullah
Nurul Nisa’, Khairol Azmi
author_sort Nurul Nisa’, Khairol Azmi
title Modelling and forecasting gold price return and its volatility
title_short Modelling and forecasting gold price return and its volatility
title_full Modelling and forecasting gold price return and its volatility
title_fullStr Modelling and forecasting gold price return and its volatility
title_full_unstemmed Modelling and forecasting gold price return and its volatility
title_sort modelling and forecasting gold price return and its volatility
publisher Institute of Engineering Mathematics, Universiti Malaysia Perlis
publishDate 2023
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77709
_version_ 1772813099535958016