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...

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Main Author: Siow, Kent Woh
Format: Thesis
Language:English
Published: 2020
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Online Access:http://eprints.utm.my/id/eprint/102404/1/SiowKentWohMFS2020.pdf.pdf
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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
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