Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/25489
Authors: 
Hartz, Christoph
Mittnik, Stefan
Paolella, Marc S.
Year of Publication: 
2006
Series/Report no.: 
CFS Working Paper 2006/23
Abstract: 
A resampling method based on the bootstrap and a bias-correction step is developed for improving the Value-at-Risk (VaR) forecasting ability of the normal-GARCH model. Compared to the use of more sophisticated GARCH models, the new method is fast, easy to implement, numerically reliable, and, except for having to choose a window length L for the bias-correction step, fully data driven. The results for several different financial asset returns over a long out-of-sample forecasting period, as well as use of simulated data, strongly support use of the new method, and the performance is not sensitive to the choice of L.
Subjects: 
Bootstrap
GARCH
Value-at-Risk
JEL: 
C22
C53
C63
G12
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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