Hierarchical copula in credit risk modeling
<b>Importance </b>This research outlines an economic and mathematical model of the overdue loan debt. The model is based on copula functions allowing to simulate the non-Gaussian allocation of financial risks and credit risk, in particular. <br></br> <b>Objectives </b>The research models the joint allocation of overdue debt series in order to forecast the credit risk exposure. Relying upon the forecasting results, we intend to evaluate the efficiency of methods used to make provisions for possible losses and subsequently determine a reasonable approach to accruing the provision. <br></br> <b>Methods </b>We examine whether hierarchical copula models can be applied to build the joint allocation of overdue loan debt series in relation to banking institutions. It is considered as the basis for making further estimates of the overdue loan debt. <br></br> <b>Results </b>We build and evaluate a multivariate copula model of overdue loan indebtedness with the hierarchical structure. Based on the modeled multivariate correlation, we forecasted indicators of the overdue loan debt, which could be used as estimated provisions for credit losses. The estimated provisions turn to be sufficient for covering the real amount of overdue debt, being, in most cases, much less that that indicated in Regulation of the Central Bank of the Russian Federation № 254-П <i>On Rates of Provisions for Loan Losses</i>. <br></br> <b>Conclusions and Relevance</b> The multivariate copula model of the overdue loan debt can underlie effective risk management systems in credit institutions.