Beyond the Sample: Extreme Quantile and Probability Estimation

Jon Danielsson () and Casper G. de Vries ()

No 98-016/2, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: Economic problems such as large claims analysis in insurance and value-at-risk in finance, require assessment of the probability P of extreme realizations Q. This paper provided a semi-parametric method for estimation of extreme (P, Q) combinations for data with heavy tails. We solve the long standing problem of estimating the sample treshold of where the tail of the distribution starts. This is accomplished by the combination of a control variate type device and a subsample bootstrap technique. The subsample bootstrap attains convergence in probability, whereas the full sample bootstrap would only provide convergence in distribution. This permits a complete and comprehensive treatment of extreme (P, Q) estimation.

Keywords: Extreme value theory; tail estimation; risk analysis (search for similar items in EconPapers)
Date: 1998-02-16
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Related works:
Working Paper: Beyond the Sample: Extreme Quantile and Probability Estimation (1998)
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Persistent link: http://EconPapers.repec.org/RePEc:dgr:uvatin:19980016

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