Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/20767
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dc.contributor.advisorPandey, Ajay
dc.contributor.authorChandna, Charulata
dc.date.accessioned2018-05-29T05:46:21Z
dc.date.available2018-05-29T05:46:21Z
dc.date.copyright2004
dc.date.issued2004
dc.identifier.urihttp://hdl.handle.net/11718/20767
dc.description.abstractThe paper present a new method for computing the VaR for a set of fixed income securities based on extreme value theory that models the tail probabilities directly without making any assumption about the distribution of entire return process. If compares the estimates of VaR for a portfolio of fixed income securities across three methods: Variance-Covariance method. Historical Simulation method and Extreme Value method and finds that extreme value method solves the problem of fatter tails and provides the best VaR estimator in terms of correct failure ratio and the size of VaR.en_US
dc.language.isoenen_US
dc.publisherIndian Institute of Management Ahmedabaden_US
dc.relation.ispartofseriesSP;001109
dc.subjectRisk Managementen_US
dc.subjectValue at risk (VaR)en_US
dc.subjectVariance-Covariance methoden_US
dc.titleValue at risk for non normally distributed market variables and incorporating event risken_US
dc.typeStudent Projecten_US
Appears in Collections:Student Projects

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