Modelling and forecasting exchange rate of US dollar against Malaysian ringgit using hybrid ARIMA-GARCH and ARIMA-EGARCH models

Modelling and forecasting financial time series data has become the area of interest in financial world. However, the data exhibits certain stylized facts that must be handled by an appropriate models. Thus, this study was conducted to develop hybridization models between Autoregressive Integrated M...

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Main Author:	Mustafa, Asma’
Format:	Thesis
Language:	English
Published:	2017
Subjects:	QA Mathematics
Online Access:	http://eprints.utm.my/id/eprint/78489/1/AsmaMustafaMFS2017.pdf
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spelling	my-utm-ep.784892018-08-26T11:56:33Z Modelling and forecasting exchange rate of US dollar against Malaysian ringgit using hybrid ARIMA-GARCH and ARIMA-EGARCH models 2017-05 Mustafa, Asma’ QA Mathematics Modelling and forecasting financial time series data has become the area of interest in financial world. However, the data exhibits certain stylized facts that must be handled by an appropriate models. Thus, this study was conducted to develop hybridization models between Autoregressive Integrated Moving Average (ARIMA) model and Generalized Autoregressive Conditional Heterocedasticity (GARCH) family model for daily exchange rate data. Later, the performance of modelling and forecasting for the best models among them will be compared. GARCH family models are divided into two categories which are symmetric (GARCH) and asymmetric (EGARCH) models. In this study, daily data of U.S. Dollar exchange rate against Malaysia exchange rate (USD/MYR) is used from the period of 1st November 2010 until 30th August 2016 collected from the Central Bank of Malaysia. The data are divided into two parts where 90% of the data is used as in-sample period taken from 1st November 2010 until 3rd February 2016. Meanwhile, for another 10% is used for the out-sample period taken from 4th February 2016 until 30th August 2016. EViews software and Microsoft Excel are used in this study to analyze the data. The performance of the hybrid models are evaluated using AIC, MAE, RMSE and MAPE. Results showed that, hybrid ARIMA-EGARCH model is the best model in modelling and forecasting daily exchange rate data compared to hybrid ARIMA-GARCH model. 2017-05 Thesis http://eprints.utm.my/id/eprint/78489/ http://eprints.utm.my/id/eprint/78489/1/AsmaMustafaMFS2017.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:109757 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 Mustafa, Asma’ Modelling and forecasting exchange rate of US dollar against Malaysian ringgit using hybrid ARIMA-GARCH and ARIMA-EGARCH models
description	Modelling and forecasting financial time series data has become the area of interest in financial world. However, the data exhibits certain stylized facts that must be handled by an appropriate models. Thus, this study was conducted to develop hybridization models between Autoregressive Integrated Moving Average (ARIMA) model and Generalized Autoregressive Conditional Heterocedasticity (GARCH) family model for daily exchange rate data. Later, the performance of modelling and forecasting for the best models among them will be compared. GARCH family models are divided into two categories which are symmetric (GARCH) and asymmetric (EGARCH) models. In this study, daily data of U.S. Dollar exchange rate against Malaysia exchange rate (USD/MYR) is used from the period of 1st November 2010 until 30th August 2016 collected from the Central Bank of Malaysia. The data are divided into two parts where 90% of the data is used as in-sample period taken from 1st November 2010 until 3rd February 2016. Meanwhile, for another 10% is used for the out-sample period taken from 4th February 2016 until 30th August 2016. EViews software and Microsoft Excel are used in this study to analyze the data. The performance of the hybrid models are evaluated using AIC, MAE, RMSE and MAPE. Results showed that, hybrid ARIMA-EGARCH model is the best model in modelling and forecasting daily exchange rate data compared to hybrid ARIMA-GARCH model.
format	Thesis
qualification_level	Master's degree
author	Mustafa, Asma’
author_facet	Mustafa, Asma’
author_sort	Mustafa, Asma’
title	Modelling and forecasting exchange rate of US dollar against Malaysian ringgit using hybrid ARIMA-GARCH and ARIMA-EGARCH models
title_short	Modelling and forecasting exchange rate of US dollar against Malaysian ringgit using hybrid ARIMA-GARCH and ARIMA-EGARCH models
title_full	Modelling and forecasting exchange rate of US dollar against Malaysian ringgit using hybrid ARIMA-GARCH and ARIMA-EGARCH models
title_fullStr	Modelling and forecasting exchange rate of US dollar against Malaysian ringgit using hybrid ARIMA-GARCH and ARIMA-EGARCH models
title_full_unstemmed	Modelling and forecasting exchange rate of US dollar against Malaysian ringgit using hybrid ARIMA-GARCH and ARIMA-EGARCH models
title_sort	modelling and forecasting exchange rate of us dollar against malaysian ringgit using hybrid arima-garch and arima-egarch models
granting_institution	Universiti Teknologi Malaysia, Faculty of Science
granting_department	Faculty of Science
publishDate	2017
url	http://eprints.utm.my/id/eprint/78489/1/AsmaMustafaMFS2017.pdf
_version_	1747817997330808832

Modelling and forecasting exchange rate of US dollar against Malaysian ringgit using hybrid ARIMA-GARCH and ARIMA-EGARCH models

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