We define the extreme values of any random sample of size n from a distribution function F as the observations exceeding a threshold and following a type of generalized Pareto distribution (GPD) involving the tail index of F. The threshold is the order statistic that minimizes a Kolmogorov-Smirnov statistic between the empirical distribution of the corresponding largest observations and the corresponding GPD. To formalize the definition we use a semiparametric bootstrap to test the corresponding GPD approximation. Finally, we use our methodology to estimate the tail index and value at risk (VaR) of some financial indexes of major stock markets. Copyright 2004, Oxford University Press.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
file. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 2 (2004) Issue (Month): 3 () Pages: 349-369 Download reference. The following formats are available: HTML,
plain text,
BibTeX,
RIS (EndNote),
ReDIF
Handle: RePEc:oup:jfinec:v:2:y:2004:i:3:p:349-369
Contact details of provider: Postal: Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK Fax: 01865 267 985 Email: Web page: http://jfec.oxfordjournals.org/