Predictive performance of conditional Extreme Value Theory in Value-at-Risk estimation
This paper conducts a comparative evaluation of the predictive performance of various Value-at-Risk (VaR) models. Special emphasis is paid to two methodologies related to the Extreme Value Theory (EVT): The Peaks Over Threshold (POT) and the Block Maxima (BM). We apply both unconditional and conditional EVT models to management of extreme market risks in stock markets. They are applied on daily returns of the BVMT and CAC 40 indices with the intention to compare the performance of various estimation methods on markets with different capitalisation and trading practices. The results we report demonstrate that conditional POT EVT method produces the most accurate forecasts of extreme losses both for standard and more extreme VaR quantiles. The conditional block maxima EVT method is less accurate.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. 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): 1 (2008)
Issue (Month): 2 ()
|Contact details of provider:|| Web page: http://www.inderscience.com/browse/index.php?journalID=218|