Modelling of crude oil prices using hybrid arima-garch model

Modelling of volatile data has become the area of interest in financial tim series recently. Volatility refers to the phenomenon where the conditional variance of the time series varies over time. The objective of this study is to compare the modelling performance of Generalized Autoregressive Condi...

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Main Author:	Hashim, Napishah
Format:	Thesis
Language:	English
Published:	2015
Subjects:	QA Mathematics
Online Access:	http://eprints.utm.my/id/eprint/54070/1/NapishahHashimMFS2015.pdf
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spelling	my-utm-ep.540702020-10-18T06:23:09Z Modelling of crude oil prices using hybrid arima-garch model 2015-06 Hashim, Napishah QA Mathematics Modelling of volatile data has become the area of interest in financial tim series recently. Volatility refers to the phenomenon where the conditional variance of the time series varies over time. The objective of this study is to compare the modelling performance of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and hybrid ARIMA-GARCH model for the prices of crude oil. Eviews and Minitab software are used to analyze the data. The models investigated are GARCH and hybrid ARIMA-GARCH model. In parameter estimation, Maximum Likelihood Estimation (MLE) is the preferred technique for GARCH models while Ordinary Least Squares Estimation (OLS) and MLE will be used for hybrid ARIMA-GARCH models. The goodness of fit of the model is measured using Akaike’s Information Criterion (AIC). The diagnostic checking is conducted to validate the goodness of fit of the model using Jarque-Bera test, Serial Correlation test and Heteroskedasticity test. Forecasting accuracies for both models are assessed using Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). The model which gives the lowest measure of error is considered to be the most appropriate model. Empirical results indicate that modelling using hybrid model has smaller AIC, MAE and MAPE values compared to GARCH model. It can be concluded that hybrid ARIMA-GARCH model is better in modelling crude oil prices data compared to GARCH model. 2015-06 Thesis http://eprints.utm.my/id/eprint/54070/ http://eprints.utm.my/id/eprint/54070/1/NapishahHashimMFS2015.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:86077 masters Universiti Teknologi Malaysia, Faculty of Science Faculty of Science
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA Mathematics
spellingShingle	QA Mathematics Hashim, Napishah Modelling of crude oil prices using hybrid arima-garch model
description	Modelling of volatile data has become the area of interest in financial tim series recently. Volatility refers to the phenomenon where the conditional variance of the time series varies over time. The objective of this study is to compare the modelling performance of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) and hybrid ARIMA-GARCH model for the prices of crude oil. Eviews and Minitab software are used to analyze the data. The models investigated are GARCH and hybrid ARIMA-GARCH model. In parameter estimation, Maximum Likelihood Estimation (MLE) is the preferred technique for GARCH models while Ordinary Least Squares Estimation (OLS) and MLE will be used for hybrid ARIMA-GARCH models. The goodness of fit of the model is measured using Akaike’s Information Criterion (AIC). The diagnostic checking is conducted to validate the goodness of fit of the model using Jarque-Bera test, Serial Correlation test and Heteroskedasticity test. Forecasting accuracies for both models are assessed using Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). The model which gives the lowest measure of error is considered to be the most appropriate model. Empirical results indicate that modelling using hybrid model has smaller AIC, MAE and MAPE values compared to GARCH model. It can be concluded that hybrid ARIMA-GARCH model is better in modelling crude oil prices data compared to GARCH model.
format	Thesis
qualification_level	Master's degree
author	Hashim, Napishah
author_facet	Hashim, Napishah
author_sort	Hashim, Napishah
title	Modelling of crude oil prices using hybrid arima-garch model
title_short	Modelling of crude oil prices using hybrid arima-garch model
title_full	Modelling of crude oil prices using hybrid arima-garch model
title_fullStr	Modelling of crude oil prices using hybrid arima-garch model
title_full_unstemmed	Modelling of crude oil prices using hybrid arima-garch model
title_sort	modelling of crude oil prices using hybrid arima-garch model
granting_institution	Universiti Teknologi Malaysia, Faculty of Science
granting_department	Faculty of Science
publishDate	2015
url	http://eprints.utm.my/id/eprint/54070/1/NapishahHashimMFS2015.pdf
_version_	1747817678447312896

Modelling of crude oil prices using hybrid arima-garch model

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