Value-at-risk modelling for the Malaysian stock exchange based on Monte Carlo simulation / Zatul Karamah Haji Ahmad Baharul-Ulum

This study puts forward Value-at-Risk (VaR) models based on Monte Carlo Simulation (MCS) that are integrated with several volatility representations to estimate the market risk for seven non-financial sectors traded on the first board of the Malaysian stock exchange which is now known as Bursa Malay...

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Main Author:	Haji Ahmad Baharul-Ulum, Zatul Karamah
Format:	Thesis
Language:	English
Published:	2008
Subjects:	Financial management Business finance Corporation finance
Online Access:	https://ir.uitm.edu.my/id/eprint/15518/1/TP_ZATUL%20KARAMAH%20AHMAD%20BAHARUL-ULUM%20BM%2008_5.PDF
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id	my-uitm-ir.15518
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spelling	my-uitm-ir.155182016-11-18T04:33:45Z Value-at-risk modelling for the Malaysian stock exchange based on Monte Carlo simulation / Zatul Karamah Haji Ahmad Baharul-Ulum 2008 Haji Ahmad Baharul-Ulum, Zatul Karamah Financial management. Business finance. Corporation finance This study puts forward Value-at-Risk (VaR) models based on Monte Carlo Simulation (MCS) that are integrated with several volatility representations to estimate the market risk for seven non-financial sectors traded on the first board of the Malaysian stock exchange which is now known as Bursa Malaysia. In a sample over the years from 1993 until 2004 for construction, consumer product, industrial product, plantation, property, trade and services and mining sectors, the expected maximum losses were quantified for 1-day, 10-days and 25-days at 95% and 99% confidence levels. While the mining sector gave the highest expected value of VaR in all parameter settings, the plantation sector delivered the minimum value of VaR in most circumstances. Next, in a two-year out-of-sample group covering 2005 to 2006, the performance of the RiskMetrics EWMA and GARCH-based models was assessed from three different perspectives; conservatism, accuracy and efficiency. Although mixed results were observed, the study provides some indications of the applicability of some VaR models for the sectors involved besides confirming that data and computational choices affect risk measurement qualities. Under conservatism tests, the GARCH-based models were the most conservative model at both the 95% and 99% levels of confidence of Mean Relative Bias and Root Mean Squared Relative Bias in the single variable cases, while the t-distributed EGARCH delivered good results in multiple variables circumstances. For accuracy performances, tests conducted using Kupiec’s and Christoffersen’s provided evidence that almost every model was found to be accurate for all sets of occurrence. However, using Lopez test, which takes into consideration the magnitude of the impact of exceptions, models with the highest accuracy rate for multiple variables and most of the sectors studied under single variable were the MCS2+EGARCHn and MCSi+GARCHt respectively. In measuring efficiency, restricted to the confidence levels, the t-distributed models were identified as the best representative to track movements in true risk exposure for single variable while MCS2+EGARCHn for multiple variables conditions. As such, this study indicates that a consideration of fat-tails and asymmetries are crucial issues when deciding to estimate VaR in managing financial risk. 2008 Thesis https://ir.uitm.edu.my/id/eprint/15518/ https://ir.uitm.edu.my/id/eprint/15518/1/TP_ZATUL%20KARAMAH%20AHMAD%20BAHARUL-ULUM%20BM%2008_5.PDF text en public phd doctoral Universiti Teknologi MARA Faculty of Business Management
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Financial management Business finance Corporation finance
spellingShingle	Financial management Business finance Corporation finance Haji Ahmad Baharul-Ulum, Zatul Karamah Value-at-risk modelling for the Malaysian stock exchange based on Monte Carlo simulation / Zatul Karamah Haji Ahmad Baharul-Ulum
description	This study puts forward Value-at-Risk (VaR) models based on Monte Carlo Simulation (MCS) that are integrated with several volatility representations to estimate the market risk for seven non-financial sectors traded on the first board of the Malaysian stock exchange which is now known as Bursa Malaysia. In a sample over the years from 1993 until 2004 for construction, consumer product, industrial product, plantation, property, trade and services and mining sectors, the expected maximum losses were quantified for 1-day, 10-days and 25-days at 95% and 99% confidence levels. While the mining sector gave the highest expected value of VaR in all parameter settings, the plantation sector delivered the minimum value of VaR in most circumstances. Next, in a two-year out-of-sample group covering 2005 to 2006, the performance of the RiskMetrics EWMA and GARCH-based models was assessed from three different perspectives; conservatism, accuracy and efficiency. Although mixed results were observed, the study provides some indications of the applicability of some VaR models for the sectors involved besides confirming that data and computational choices affect risk measurement qualities. Under conservatism tests, the GARCH-based models were the most conservative model at both the 95% and 99% levels of confidence of Mean Relative Bias and Root Mean Squared Relative Bias in the single variable cases, while the t-distributed EGARCH delivered good results in multiple variables circumstances. For accuracy performances, tests conducted using Kupiec’s and Christoffersen’s provided evidence that almost every model was found to be accurate for all sets of occurrence. However, using Lopez test, which takes into consideration the magnitude of the impact of exceptions, models with the highest accuracy rate for multiple variables and most of the sectors studied under single variable were the MCS2+EGARCHn and MCSi+GARCHt respectively. In measuring efficiency, restricted to the confidence levels, the t-distributed models were identified as the best representative to track movements in true risk exposure for single variable while MCS2+EGARCHn for multiple variables conditions. As such, this study indicates that a consideration of fat-tails and asymmetries are crucial issues when deciding to estimate VaR in managing financial risk.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Haji Ahmad Baharul-Ulum, Zatul Karamah
author_facet	Haji Ahmad Baharul-Ulum, Zatul Karamah
author_sort	Haji Ahmad Baharul-Ulum, Zatul Karamah
title	Value-at-risk modelling for the Malaysian stock exchange based on Monte Carlo simulation / Zatul Karamah Haji Ahmad Baharul-Ulum
title_short	Value-at-risk modelling for the Malaysian stock exchange based on Monte Carlo simulation / Zatul Karamah Haji Ahmad Baharul-Ulum
title_full	Value-at-risk modelling for the Malaysian stock exchange based on Monte Carlo simulation / Zatul Karamah Haji Ahmad Baharul-Ulum
title_fullStr	Value-at-risk modelling for the Malaysian stock exchange based on Monte Carlo simulation / Zatul Karamah Haji Ahmad Baharul-Ulum
title_full_unstemmed	Value-at-risk modelling for the Malaysian stock exchange based on Monte Carlo simulation / Zatul Karamah Haji Ahmad Baharul-Ulum
title_sort	value-at-risk modelling for the malaysian stock exchange based on monte carlo simulation / zatul karamah haji ahmad baharul-ulum
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Business Management
publishDate	2008
url	https://ir.uitm.edu.my/id/eprint/15518/1/TP_ZATUL%20KARAMAH%20AHMAD%20BAHARUL-ULUM%20BM%2008_5.PDF
_version_	1783733413265539072

Value-at-risk modelling for the Malaysian stock exchange based on Monte Carlo simulation / Zatul Karamah Haji Ahmad Baharul-Ulum

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