Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/153897 
Year of Publication: 
2012
Series/Report no.: 
ECB Working Paper No. 1464
Publisher: 
European Central Bank (ECB), Frankfurt a. M.
Abstract: 
Severe financial turbulences are driven by high impact and low probability events that are the characteristic hallmarks of systemic financial stress. These unlikely adverse events arise from the extreme tail of a probability distribution and are therefore very poorly captured by traditional econometric models that rely on the assumption of normality. In order to address the problem of extreme tail events, we adopt a mixture vector autoregressive (MVAR) model framework that allows for a multi-modal distribution of the residuals. A comparison between the respective results of a VAR and MVAR approach suggests that the mixture of distributions allows for a better assessment of the effect that adverse shocks have on counterparty credit risk, the real economy and banks’ capital requirements. Consequently, we argue that the MVAR provides a more accurate assessment of risk since it captures the fat tail events often observed in time series of default probabilities.
Subjects: 
Counterparty risk
Luxembourg banking sector
MVAR
stress testing
tier 1 capital ratio
JEL: 
C15
E44
G01
G21
Document Type: 
Working Paper

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