Applying a copula to the estimation of value-at-risk

Value-at-Risk (VaR) is a common tool employed in the estimation of market risk. Traditionally, VaR of a portfolio is estimated through an assumption of normally distributed portfolio returns. Yet, as we delve further into the estimation of VaR, we believe that returns are not always normally distrib...

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Main Authors: Ang, Fang Ting, Shen, Angela Xiao'Ou, Khoo, Isabella Hui Ling
Other Authors: Wu Yuan
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/51305
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-513052023-05-19T06:16:18Z Applying a copula to the estimation of value-at-risk Ang, Fang Ting Shen, Angela Xiao'Ou Khoo, Isabella Hui Ling Wu Yuan Nanyang Business School DRNTU::Business Value-at-Risk (VaR) is a common tool employed in the estimation of market risk. Traditionally, VaR of a portfolio is estimated through an assumption of normally distributed portfolio returns. Yet, as we delve further into the estimation of VaR, we believe that returns are not always normally distributed, and there are lapses in this assumption resulting in the underestimation of VaR. Hence, recognizing the importance of the accurate estimation of market risk, this paper seeks to introduce the theory of copula into the estimation of VaR to present a case where the use of copula in the Monte Carlo simulations of VaR results in a better estimation of VaR compared to the traditional assumption of normal distributions. In view of this, we simulate a portfolio containing two market risk factors, the foreign exchange rates of USD against JPY and GBP against JPY, and in particular chose to describe their dependence structure using the Clayton copula. Through the generation of pseudo random numbers making use of MATLAB, back-testing results have shown that using a copula provides a more reliable estimation of the VaR. BUSINESS 2013-03-28T03:18:55Z 2013-03-28T03:18:55Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/51305 en Nanyang Technological University 47 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Business
spellingShingle DRNTU::Business
Ang, Fang Ting
Shen, Angela Xiao'Ou
Khoo, Isabella Hui Ling
Applying a copula to the estimation of value-at-risk
description Value-at-Risk (VaR) is a common tool employed in the estimation of market risk. Traditionally, VaR of a portfolio is estimated through an assumption of normally distributed portfolio returns. Yet, as we delve further into the estimation of VaR, we believe that returns are not always normally distributed, and there are lapses in this assumption resulting in the underestimation of VaR. Hence, recognizing the importance of the accurate estimation of market risk, this paper seeks to introduce the theory of copula into the estimation of VaR to present a case where the use of copula in the Monte Carlo simulations of VaR results in a better estimation of VaR compared to the traditional assumption of normal distributions. In view of this, we simulate a portfolio containing two market risk factors, the foreign exchange rates of USD against JPY and GBP against JPY, and in particular chose to describe their dependence structure using the Clayton copula. Through the generation of pseudo random numbers making use of MATLAB, back-testing results have shown that using a copula provides a more reliable estimation of the VaR.
author2 Wu Yuan
author_facet Wu Yuan
Ang, Fang Ting
Shen, Angela Xiao'Ou
Khoo, Isabella Hui Ling
format Final Year Project
author Ang, Fang Ting
Shen, Angela Xiao'Ou
Khoo, Isabella Hui Ling
author_sort Ang, Fang Ting
title Applying a copula to the estimation of value-at-risk
title_short Applying a copula to the estimation of value-at-risk
title_full Applying a copula to the estimation of value-at-risk
title_fullStr Applying a copula to the estimation of value-at-risk
title_full_unstemmed Applying a copula to the estimation of value-at-risk
title_sort applying a copula to the estimation of value-at-risk
publishDate 2013
url http://hdl.handle.net/10356/51305
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