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Improving the value at risk forecasts: Theory and evidence from the financial crisis

✍ Scribed by Roxana Halbleib; Winfried Pohlmeier

Book ID
116637063
Publisher
Elsevier Science
Year
2012
Tongue
English
Weight
462 KB
Volume
36
Category
Article
ISSN
0165-1889

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## ABSTRACT Value‐at‐risk (VaR) forecasting via a computational Bayesian framework is considered. A range of parametric models is compared, including standard, threshold nonlinear and Markov switching generalized autoregressive conditional heteroskedasticity (GARCH) specifications, plus standard an