A Frailty Cumulative Link Model for Enhanced Prediction of Loss Given Default Distribution

In this paper, the loss given default (LGD) distribution of defaulted debt is explored through the application of a cumulative link model that takes into account obligor-specific frailty. When constructing a model, it is important to recognize and address any correlations between LGD variables for defaulted debts from the same obligor. Our research highlights the significance of incorporating obligor-specific frailty into our proposed model, as it effectively captures the main characteristic of LGD variables. We demonstrate the use of our proposed frailty model through a real data example. Our empirical results support the significance of the obligor-specific frailty variable included in the proposed model. We further find that, in contrast to the independence alternatives, our proposed model achieves better out-of-time performance using an expanding rolling window approach, thereby enhancing the precision of LGD distribution predictions. The exceptional predictive accuracy of this model provides valuable insights for creditors and policymakers in assessing and managing credit risk.