Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/27671 
Year of Publication: 
2008
Series/Report no.: 
Economics Working Paper No. 2008-16
Publisher: 
Kiel University, Department of Economics, Kiel
Abstract: 
In this note a Monte Carlo approach is suggested to determine critical values for diagnostic tests of Value-at-Risk models that rely on binary random variables. Monte Carlo testing offers exact significance levels in finite samples. Conditional on exact critical values the dynamic quantile test suggested by Engle and Manganelli (2004) turns out more powerful than a recently proposed Portmanteau type test (Hurlin and Tokpavi 2006).
Subjects: 
Value-at-Risk
Monte Carlo test
JEL: 
G28
C52
C22
Document Type: 
Working Paper

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