 Credit risk clustering in a business group: Which matters more, systematic or idiosyncratic risk?Feng Li () and Zhuojing He Cogent Economics & Finance, 2019, vol. 7, issue 1, 1632528 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. Date: 2019 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:taf:oaefxx:v:7:y:2019:i:1:p:1632528 Ordering information: This journal article can be ordered from DOI: 10.1080/23322039.2019.1632528 Access Statistics for this article Cogent Economics & Finance is currently edited by Steve Cook, Caroline Elliott, David McMillan, Duncan Watson and Xibin Zhang More articles in Cogent Economics & Finance from Taylor & Francis Journals |
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