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Correlated Defaults of UK Banks: Dynamics and Asymmetries

Mario Cerrato, John Crosby, Minjoo Kim () and Yang Zhao

Working Papers from Business School - Economics, University of Glasgow

Abstract: We document asymmetric and time-varying features of dependence between the credit risks of global systemically important banks (G-SIBs) in the UK banking industry using a CDS dataset. We model the dependence of CDS spreads using a dynamic asymmetric cop- ula. Comparing our model with traditional copula models, we find that they usually under- estimate the probability of joint (or conditional) default in the UK G-SIBs. Furthermore, we show that dynamics and asymmetries between CDS spreads are closely associated with the probabilities of joint (or conditional) default through the extensive regression analysis. Especially, our regression analysis provides a policy implication that copula correlation or tail dependence coefficients are able to be leading indicators for the systemic credit event.

Keywords: Calibrated marginal default probability; probability of joint default; probability of conditional default; GAS-based GHST copula. (search for similar items in EconPapers)
JEL-codes: C32 G32 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ban, nep-ecm, nep-ifn and nep-rmg
Date: 2015-10
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Persistent link: https://EconPapers.repec.org/RePEc:gla:glaewp:2015_24

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