Varying the VaR for unconditional and conditional environments

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Show simple item record Cotter, John 2009-05-26T13:49:45Z 2009-05-26T13:49:45Z Centre for Financial Markets, 2004 en 2004
dc.description.abstract Accurate forecasting of risk is the key to successful risk management techniques. Using the largest stock index futures from twelve European bourses, this paper presents VaR measures based on their unconditional and conditional distributions for single and multi-period settings. These measures underpinned by extreme value theory are statistically robust explicitly allowing for fat-tailed densities. Conditional tail estimates are obtained by adjusting the unconditional extreme value procedure with GARCH filtered returns. The conditional modelling results in iid returns allowing for the use of a simple and efficient multi-period extreme value scaling law.The paper examines the properties of these distinct conditional and unconditional trading models. The paper finds that the biases inherent in unconditional single and multi-period estimates assuming normality extend to the conditional setting. en
dc.format.extent 207979 bytes
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher University College Dublin. School of Business. Centre for Financial Markets en
dc.relation.ispartofseries Centre for Financial Markets working paper series en
dc.relation.ispartofseries WP-04-06 en
dc.subject Value at Risk en
dc.subject GARCH filter en
dc.subject Extreme value theory en
dc.subject Conditional risk en
dc.subject.classification G1 en
dc.subject.classification G10 en
dc.subject.lcsh Risk--Econometric models en
dc.subject.lcsh Extreme value theory en
dc.subject.lcsh Econometric models en
dc.title Varying the VaR for unconditional and conditional environments en
dc.type Working Paper en
dc.internal.authorid UCD0043
dc.internal.availability Full text available en
dc.internal.webversions en
dc.status Not peer reviewed en
dc.neeo.contributor Cotter|John|aut|UCD0043

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