An Extreme Value Approach to Estimating Volatility and Value at Risk
AbstractThis 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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Bibliographic InfoArticle provided by University of Chicago Press in its journal Journal of Business.
Volume (Year): 76 (2003)
Issue (Month): 1 (January)
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Web page: http://www.journals.uchicago.edu/JB/
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