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An Extreme Value Approach to Estimating Volatility and Value at Risk

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Author Info
Turan G. Bali (Baruch College)
Abstract

This article determines the type of asymptotic distribution for the extreme changes in U.S. Treasury yields. The thin-tailed Gumbel and exponential distributions are strongly rejected against the fat-tailed Frechet and Pareto distributions. The empirical results indicate that the volatility of maximal and minimal changes in interest rates declines as time-to-maturity rises, yielding a downward-sloping volatility curve for the extremes. The article proposes an extreme value approach to estimating value at risk and shows that the statistical theory of extremes provides a more accurate approach for risk management and value at risk (VaR) calculations than the standard models.

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File URL: http://www.journals.uchicago.edu/cgi-bin/resolve?JB760111
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Publisher Info
Article provided by University of Chicago Press in its journal Journal of Business.

Volume (Year): 76 (2003)
Issue (Month): 1 (January)
Pages: 83-108
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Handle: RePEc:ucp:jnlbus:v:76:y:2003:i:1:p:83-108

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  1. Ozun, Alper & Cifter, Atilla & Yilmazer, Sait, 2007. "Filtered Extreme Value Theory for Value-At-Risk Estimation," MPRA Paper 3302, University Library of Munich, Germany. [Downloadable!]
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This page was last updated on 2008-8-11.


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