Quantification of VaR: A Note on VaR Valuation in the South African Equity Market

The statistical distribution of financial returns plays a key role in evaluating Value-at-Risk using parametric methods. Traditionally, when evaluating parametric Value-at-Risk, the statistical distribution of the financial returns is assumed to be normally distributed. However, though simple to imp...

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Main Authors: Lesedi Mabitsela, Eben Maré, Rodwell Kufakunesu
Format: Article
Language:English
Published: MDPI AG 2015-02-01
Series:Journal of Risk and Financial Management
Subjects:
Online Access:http://www.mdpi.com/1911-8074/8/1/103
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spelling doaj-9737e23ccaa64e5b99c124695976d5302020-11-24T22:24:29ZengMDPI AGJournal of Risk and Financial Management1911-80742015-02-018110312610.3390/jrfm8010103jrfm8010103Quantification of VaR: A Note on VaR Valuation in the South African Equity MarketLesedi Mabitsela0Eben Maré1Rodwell Kufakunesu2Department of Mathematics and Applied Mathematics, University of Pretoria, Pretoria, 0002, South AfricaDepartment of Mathematics and Applied Mathematics, University of Pretoria, Pretoria, 0002, South AfricaDepartment of Mathematics and Applied Mathematics, University of Pretoria, Pretoria, 0002, South AfricaThe statistical distribution of financial returns plays a key role in evaluating Value-at-Risk using parametric methods. Traditionally, when evaluating parametric Value-at-Risk, the statistical distribution of the financial returns is assumed to be normally distributed. However, though simple to implement, the Normal distribution underestimates the kurtosis and skewness of the observed financial returns. This article focuses on the evaluation of the South African equity markets in a Value-at-Risk framework. Value-at-Risk is estimated on four equity stocks listed on the Johannesburg Stock Exchange, including the FTSE/JSE TOP40 index and the S & P 500 index. The statistical distribution of the financial returns is modelled using the Normal Inverse Gaussian and is compared to the financial returns modelled using the Normal, Skew t-distribution and Student t-distribution. We then estimate Value-at-Risk under the assumption that financial returns follow the Normal Inverse Gaussian, Normal, Skew t-distribution and Student t-distribution and backtesting was performed under each distribution assumption. The results of these distributions are compared and discussed.http://www.mdpi.com/1911-8074/8/1/103Value-at-RiskNormal Inverse Gaussian (NIG)FTSE/JSE TOP40 index
collection DOAJ
language English
format Article
sources DOAJ
author Lesedi Mabitsela
Eben Maré
Rodwell Kufakunesu
spellingShingle Lesedi Mabitsela
Eben Maré
Rodwell Kufakunesu
Quantification of VaR: A Note on VaR Valuation in the South African Equity Market
Journal of Risk and Financial Management
Value-at-Risk
Normal Inverse Gaussian (NIG)
FTSE/JSE TOP40 index
author_facet Lesedi Mabitsela
Eben Maré
Rodwell Kufakunesu
author_sort Lesedi Mabitsela
title Quantification of VaR: A Note on VaR Valuation in the South African Equity Market
title_short Quantification of VaR: A Note on VaR Valuation in the South African Equity Market
title_full Quantification of VaR: A Note on VaR Valuation in the South African Equity Market
title_fullStr Quantification of VaR: A Note on VaR Valuation in the South African Equity Market
title_full_unstemmed Quantification of VaR: A Note on VaR Valuation in the South African Equity Market
title_sort quantification of var: a note on var valuation in the south african equity market
publisher MDPI AG
series Journal of Risk and Financial Management
issn 1911-8074
publishDate 2015-02-01
description The statistical distribution of financial returns plays a key role in evaluating Value-at-Risk using parametric methods. Traditionally, when evaluating parametric Value-at-Risk, the statistical distribution of the financial returns is assumed to be normally distributed. However, though simple to implement, the Normal distribution underestimates the kurtosis and skewness of the observed financial returns. This article focuses on the evaluation of the South African equity markets in a Value-at-Risk framework. Value-at-Risk is estimated on four equity stocks listed on the Johannesburg Stock Exchange, including the FTSE/JSE TOP40 index and the S & P 500 index. The statistical distribution of the financial returns is modelled using the Normal Inverse Gaussian and is compared to the financial returns modelled using the Normal, Skew t-distribution and Student t-distribution. We then estimate Value-at-Risk under the assumption that financial returns follow the Normal Inverse Gaussian, Normal, Skew t-distribution and Student t-distribution and backtesting was performed under each distribution assumption. The results of these distributions are compared and discussed.
topic Value-at-Risk
Normal Inverse Gaussian (NIG)
FTSE/JSE TOP40 index
url http://www.mdpi.com/1911-8074/8/1/103
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