Varying the VaR for Unconditional and Conditional Environments

John Cotter

No 200419, Working Papers from Geary Institute, University College Dublin

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.

Keywords: extreme value theory; GARCH filter; conditional risk (search for similar items in EconPapers)
JEL-codes: G1 G10 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2011
New Economics Papers: this item is included in nep-ban, nep-for and nep-rmg
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http://www.ucd.ie/geary/static/publications/workingpapers/gearywp200419.pdf First version, 2004 (application/pdf)

Related works:
Working Paper: Varying the VaR for Unconditional and Conditional Environments (2011)
Journal Article: Varying the VaR for unconditional and conditional environments (2007)
Working Paper: Varying the VaR for Unconditional and Conditional Environments (2004)
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Persistent link: https://EconPapers.repec.org/RePEc:ucd:wpaper:200419

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