Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/245261 
Year of Publication: 
2019
Citation: 
[Journal:] Cogent Economics & Finance [ISSN:] 2332-2039 [Volume:] 7 [Issue:] 1 [Publisher:] Taylor & Francis [Place:] Abingdon [Year:] 2019 [Pages:] 1-23
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
Understanding how defaults correlate across firms is a persistent concern in risk management. In this paper, we apply covariate-dependent copula models to assess the dynamic nature of credit risk dependence, which we define as "credit risk clustering". We also study the driving forces of the credit risk clustering in CEC business group in China. Our empirical analysis shows that the credit risk clustering varies over time and exhibits different patterns across firm pairs in a business group. We also investigate the impacts of systematic and idiosyncratic factors on credit risk clustering. We find that the impacts of the money supply and the short-term interest rates are positive, whereas the impacts of exchange rates are negative. The roles of the CPI on credit risk clustering are ambiguous. Idiosyncratic factors are vital for predicting credit risk clustering. From a policy perspective, our results not only strengthen the results of previous research but also provide a possible approach to model and predict the extreme co-movement of credit risk in business groups with financial indicators.
Subjects: 
business groups
credit risk clustering
covariate-dependent copulas
MCMC
JEL: 
C11
C53
C58
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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