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Extreme value approach value approach for estimating value at risk metrics with respect to Basel II

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dc.title Extreme value approach value approach for estimating value at risk metrics with respect to Basel II en
dc.contributor.author Homolka, Lubor
dc.relation.ispartof International Journal of Mathematics and Computers in Simulation
dc.identifier.issn 1998-0159 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2013
utb.relation.volume 7
utb.relation.issue 2
dc.citation.spage 171
dc.citation.epage 178
dc.type article
dc.language.iso en
dc.publisher North Atlantic University Union (NAUN) en
dc.relation.uri http://www.naun.org/multimedia/NAUN/mcs/2002-110.pdf
dc.subject Basel II en
dc.subject Bootstrap en
dc.subject Extreme value theory en
dc.subject Historical simulation en
dc.subject Value at risk en
dc.description.abstract A large number of articles have been written about methods designed to assess easily interpretable value reflecting risk taken from a (not exclusively financial) process. In the financial environment, prevailing concepts include Value at Risk (VaR) and its derivatives, such as Conditional Value at Risk. The purpose of this paper is to describe appropriateness of the VaR metrics under Basel II legislative framework and to stress VaR estimation techniques. A relatively new approach titled Extreme Value Theory and methods allowed by Basel II are compared on illustrative example of a skewed distribution with presence of outliers. Our findings suggest alternative methods assess higher VaR than the classical ones (historical simulation, mean-variance model and Monte Carlo simulation) and are more precise in terms of variance. en
utb.faculty Faculty of Management and Economics
dc.identifier.uri http://hdl.handle.net/10563/1003270
utb.identifier.obdid 43870117
utb.identifier.scopus 2-s2.0-84877986445
utb.source j-scopus
dc.date.accessioned 2013-07-27T14:54:38Z
dc.date.available 2013-07-27T14:54:38Z
utb.contributor.internalauthor Homolka, Lubor
utb.fulltext.affiliation Lubor Homolka Lubor Homolka, Tomas Bata University in Zlín, FaME CZ, Department of Statistics and Quantitative Methods (e-mail: homolka@ fame.utb.cz)
utb.fulltext.dates -
utb.fulltext.sponsorship This paper was supported by Project No. IGA/FaME/2012/12: Optimization of internal rating model parameters of commercial banks in the small and medium enterprises.
utb.fulltext.faculty Faculty of Management and Economics
utb.fulltext.ou Department of Statistics and Quantitative Methods
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