Heavy-tailed value-at-risk analysis for Malaysian stock exchange

This article investigates the comparison of power-law value-at-risk (VaR) evaluation with quantile and non-linear time-varying volatility approaches. A simple Pareto distribution is proposed to account the heavy-tailed property in the empirical distribution of returns. Alternative VaR measurement su...

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Main Author: CHIN, W
Format: Article
Published: ELSEVIER SCIENCE BV 2008
Subjects:
Online Access:http://shdl.mmu.edu.my/2656/
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author CHIN, W
author_facet CHIN, W
author_sort CHIN, W
building MMU Institutional Repository
collection Online Access
description This article investigates the comparison of power-law value-at-risk (VaR) evaluation with quantile and non-linear time-varying volatility approaches. A simple Pareto distribution is proposed to account the heavy-tailed property in the empirical distribution of returns. Alternative VaR measurement such as non-parametric quantile estimate is implemented using interpolation method. In addition, we also used the well-known two components ARCH modelling technique under the assumptions of normality and heavy-tailed (student-t distribution) for the innovations. Our results evidenced that the predicted VaR under the Pareto distribution exhibited similar results with the symmetric heavy-tailed long-memory ARCH model. However, it is found that only the Pareto distribution is able to provide a convenient framework for asymmetric properties in both the lower and upper tails. (c) 2008 Elsevier B.V. All rights reserved.
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spelling mmu-26562011-09-08T03:15:56Z http://shdl.mmu.edu.my/2656/ Heavy-tailed value-at-risk analysis for Malaysian stock exchange CHIN, W T Technology (General) QA75.5-76.95 Electronic computers. Computer science This article investigates the comparison of power-law value-at-risk (VaR) evaluation with quantile and non-linear time-varying volatility approaches. A simple Pareto distribution is proposed to account the heavy-tailed property in the empirical distribution of returns. Alternative VaR measurement such as non-parametric quantile estimate is implemented using interpolation method. In addition, we also used the well-known two components ARCH modelling technique under the assumptions of normality and heavy-tailed (student-t distribution) for the innovations. Our results evidenced that the predicted VaR under the Pareto distribution exhibited similar results with the symmetric heavy-tailed long-memory ARCH model. However, it is found that only the Pareto distribution is able to provide a convenient framework for asymmetric properties in both the lower and upper tails. (c) 2008 Elsevier B.V. All rights reserved. ELSEVIER SCIENCE BV 2008-07 Article NonPeerReviewed CHIN, W (2008) Heavy-tailed value-at-risk analysis for Malaysian stock exchange. Physica A: Statistical Mechanics and its Applications, 387 (16-17). pp. 4285-4298. ISSN 03784371 http://dx.doi.org/10.1016/j.physa.2008.01.075 doi:10.1016/j.physa.2008.01.075 doi:10.1016/j.physa.2008.01.075
spellingShingle T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
CHIN, W
Heavy-tailed value-at-risk analysis for Malaysian stock exchange
title Heavy-tailed value-at-risk analysis for Malaysian stock exchange
title_full Heavy-tailed value-at-risk analysis for Malaysian stock exchange
title_fullStr Heavy-tailed value-at-risk analysis for Malaysian stock exchange
title_full_unstemmed Heavy-tailed value-at-risk analysis for Malaysian stock exchange
title_short Heavy-tailed value-at-risk analysis for Malaysian stock exchange
title_sort heavy-tailed value-at-risk analysis for malaysian stock exchange
topic T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
url http://shdl.mmu.edu.my/2656/
http://shdl.mmu.edu.my/2656/
http://shdl.mmu.edu.my/2656/