Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/103639
Authors: 
Krause, Jochen
Paolella, Marc S.
Year of Publication: 
2014
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Publisher:] MDPI [Place:] Basel [Volume:] 2 [Year:] 2014 [Issue:] 2 [Pages:] 98-122
Abstract: 
A fast method is developed for value-at-risk and expected shortfall prediction for univariate asset return time series exhibiting leptokurtosis, asymmetry and conditional heteroskedasticity. It is based on a GARCH-type process driven by noncentral t innovations. While the method involves the use of several shortcuts for speed, it performs admirably in terms of accuracy and actually outperforms highly competitive models. Most remarkably, this is the case also for sample sizes as small as 250.
Subjects: 
GARCH
mixture-normal-GARCH
noncentral t
lookup table
JEL: 
C51
C53
G11
G17
Persistent Identifier of the first edition: 
Creative Commons License: 
http://creativecommons.org/licenses/by/3.0/
Document Type: 
Article
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