Modelling and forecasting the predictability of stock market return in asian countries by using hybrid arima-garch models

Predictability of the stock market return has been a crucial topic over a decade. The ability to forecast and predict the stock market price allows investors to make investment decisions at the lowest risk and also allows policy makers to evaluate development of stock markets as to design rules and...

Full description

Saved in:

Bibliographic Details
Main Author:	Siow, Kent Woh
Format:	Thesis
Language:	English
Published:	2020
Subjects:	Q Science (General)
Online Access:	http://eprints.utm.my/id/eprint/102404/1/SiowKentWohMFS2020.pdf.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-utm-ep.102404
record_format	uketd_dc
spelling	my-utm-ep.1024042023-08-21T08:28:50Z Modelling and forecasting the predictability of stock market return in asian countries by using hybrid arima-garch models 2020 Siow, Kent Woh Q Science (General) Predictability of the stock market return has been a crucial topic over a decade. The ability to forecast and predict the stock market price allows investors to make investment decisions at the lowest risk and also allows policy makers to evaluate development of stock markets as to design rules and regulations. Thus, this study was conducted to serve two main purposes. First of all, hybrid models was developed between Autoregressive Integrated Moving Average (ARIMA) model and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family model for daily stock market data. In GARCH family models, there are GARCH, EGARCH and TGARCH where GARCH is symmetric model and EGARCH and TGARCH are asymmetric models. As hybridization of ARIMA model with different GARCH family models have different level of performances, each of the established hybrid models are evaluated using AIC, MAE, RMSE as well as MAPE to identify the outperformed model. In this study, daily stock prices of nine Asian countries (China, Hong Kong, India, Indonesia, Korea, Malaysia, Philippines, Singapore, and Thailand) are being used. EViews and R studio software act as the tools to perform the analysis. Results show that hybrid ARIMA-EGARCH model outperformed. On the other hand, identification of the calendar effects of all the nine Asian countries is the second concern of this study. The results show that each of the Asian countries have different calendar effects. 2020 Thesis http://eprints.utm.my/id/eprint/102404/ http://eprints.utm.my/id/eprint/102404/1/SiowKentWohMFS2020.pdf.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:146098 masters Universiti Teknologi Malaysia Faculty of Science
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	Q Science (General)
spellingShingle	Q Science (General) Siow, Kent Woh Modelling and forecasting the predictability of stock market return in asian countries by using hybrid arima-garch models
description	Predictability of the stock market return has been a crucial topic over a decade. The ability to forecast and predict the stock market price allows investors to make investment decisions at the lowest risk and also allows policy makers to evaluate development of stock markets as to design rules and regulations. Thus, this study was conducted to serve two main purposes. First of all, hybrid models was developed between Autoregressive Integrated Moving Average (ARIMA) model and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family model for daily stock market data. In GARCH family models, there are GARCH, EGARCH and TGARCH where GARCH is symmetric model and EGARCH and TGARCH are asymmetric models. As hybridization of ARIMA model with different GARCH family models have different level of performances, each of the established hybrid models are evaluated using AIC, MAE, RMSE as well as MAPE to identify the outperformed model. In this study, daily stock prices of nine Asian countries (China, Hong Kong, India, Indonesia, Korea, Malaysia, Philippines, Singapore, and Thailand) are being used. EViews and R studio software act as the tools to perform the analysis. Results show that hybrid ARIMA-EGARCH model outperformed. On the other hand, identification of the calendar effects of all the nine Asian countries is the second concern of this study. The results show that each of the Asian countries have different calendar effects.
format	Thesis
qualification_level	Master's degree
author	Siow, Kent Woh
author_facet	Siow, Kent Woh
author_sort	Siow, Kent Woh
title	Modelling and forecasting the predictability of stock market return in asian countries by using hybrid arima-garch models
title_short	Modelling and forecasting the predictability of stock market return in asian countries by using hybrid arima-garch models
title_full	Modelling and forecasting the predictability of stock market return in asian countries by using hybrid arima-garch models
title_fullStr	Modelling and forecasting the predictability of stock market return in asian countries by using hybrid arima-garch models
title_full_unstemmed	Modelling and forecasting the predictability of stock market return in asian countries by using hybrid arima-garch models
title_sort	modelling and forecasting the predictability of stock market return in asian countries by using hybrid arima-garch models
granting_institution	Universiti Teknologi Malaysia
granting_department	Faculty of Science
publishDate	2020
url	http://eprints.utm.my/id/eprint/102404/1/SiowKentWohMFS2020.pdf.pdf
_version_	1776100915143507968

Modelling and forecasting the predictability of stock market return in asian countries by using hybrid arima-garch models

Similar Items