The effects of risk modelling: Assessing value-at-risk accuracy
This study examines Value-at-Risk (VaR) models that are integrated with several volatility representations to estimate the market risk for seven nonfinancial sectors traded on the first board of the Malaysian stock exchange. In a sample that spanned 19 years from1993 until 2012 for construction, con...
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Faculty of Economics and Administration
2015
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2-s2.0-84938689976 Baharul-Ulum Z.K.A.; Ahmad I.; Salamudin N.; Daud N.M. The effects of risk modelling: Assessing value-at-risk accuracy 2015 Institutions and Economies 7 2 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938689976&partnerID=40&md5=0505624fcb551a05228a8760ceec50d4 This study examines Value-at-Risk (VaR) models that are integrated with several volatility representations to estimate the market risk for seven nonfinancial sectors traded on the first board of the Malaysian stock exchange. In a sample that spanned 19 years from1993 until 2012 for construction, consumer product, industrial product, plantation, property, trade and services and mining sectors, the expected maximum losses are quantified at 95% confidence level. For accuracy determination, assessments using Kupiec test and Christoffersen test have provided evidence that almost every model are found to be accurate for all sets of occurrence. However, using the Lopez test which takes into consideration the magnitude of the impact of exceptions, the most accurate model is the VaR which is integrated with GARCHt. This study found that fat tails and asymmetries are important issues that need to be considered when estimating VaR in managing financial risks. © 2015, Faculty of Economics and Administration. All rights reserved. Faculty of Economics and Administration 22321640 English Article |
author |
Baharul-Ulum Z.K.A.; Ahmad I.; Salamudin N.; Daud N.M. |
spellingShingle |
Baharul-Ulum Z.K.A.; Ahmad I.; Salamudin N.; Daud N.M. The effects of risk modelling: Assessing value-at-risk accuracy |
author_facet |
Baharul-Ulum Z.K.A.; Ahmad I.; Salamudin N.; Daud N.M. |
author_sort |
Baharul-Ulum Z.K.A.; Ahmad I.; Salamudin N.; Daud N.M. |
title |
The effects of risk modelling: Assessing value-at-risk accuracy |
title_short |
The effects of risk modelling: Assessing value-at-risk accuracy |
title_full |
The effects of risk modelling: Assessing value-at-risk accuracy |
title_fullStr |
The effects of risk modelling: Assessing value-at-risk accuracy |
title_full_unstemmed |
The effects of risk modelling: Assessing value-at-risk accuracy |
title_sort |
The effects of risk modelling: Assessing value-at-risk accuracy |
publishDate |
2015 |
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Institutions and Economies |
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7 |
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2 |
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url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84938689976&partnerID=40&md5=0505624fcb551a05228a8760ceec50d4 |
description |
This study examines Value-at-Risk (VaR) models that are integrated with several volatility representations to estimate the market risk for seven nonfinancial sectors traded on the first board of the Malaysian stock exchange. In a sample that spanned 19 years from1993 until 2012 for construction, consumer product, industrial product, plantation, property, trade and services and mining sectors, the expected maximum losses are quantified at 95% confidence level. For accuracy determination, assessments using Kupiec test and Christoffersen test have provided evidence that almost every model are found to be accurate for all sets of occurrence. However, using the Lopez test which takes into consideration the magnitude of the impact of exceptions, the most accurate model is the VaR which is integrated with GARCHt. This study found that fat tails and asymmetries are important issues that need to be considered when estimating VaR in managing financial risks. © 2015, Faculty of Economics and Administration. All rights reserved. |
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Faculty of Economics and Administration |
issn |
22321640 |
language |
English |
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Article |
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scopus |
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Scopus |
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1823296165742903296 |