Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/25489 
Erscheinungsjahr: 
2006
Schriftenreihe/Nr.: 
CFS Working Paper No. 2006/23
Verlag: 
Goethe University Frankfurt, Center for Financial Studies (CFS), Frankfurt a. M.
Zusammenfassung: 
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.
Schlagwörter: 
Bootstrap
GARCH
Value-at-Risk
JEL: 
C22
C53
C63
G12
Persistent Identifier der Erstveröffentlichung: 
Dokumentart: 
Working Paper

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