Credit Risk Clustering in a Business Group : Which Matters More, Systematic or Idiosyncratic Risk?

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 dynamics of credit risk dependence and its driving forces based on an empirical study of a business group in China. Our empirical analysis shows that the tail dependence of credit risk varies over time and exhibits different patterns across pairwise firms. We also investigate the impacts of systematic and idiosyncratic factors on credit risk dependences. We find that the impacts of the money supply and short-term interest rates are positive, whereas those of exchange rates are negative. The impact of the CPI on credit risk dependence is ambiguous. Idiosyncratic factors are vital for predicting credit risk dependences. 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