A structural framework for network-based default contagion in credit portfolios

Portfolio credit risk models typically incorporate the default dependence between obligors that arises from common risk factors. However, they often ignore obligor-to-obligor default contagion effects, which can propagate through economic networks. We present a structural framework that can be layered onto existing factor models to capture higher-order network-based default contagion. Our approach yields efficient and tractable computations that are applicable to heterogeneous singly connected networks, which can represent empirically observed dependence structures such as supply chains, corporate groups and hierarchical governments. As a key contribution, we develop an expectation-maximization algorithm that estimates default contagion parameters from historical creditworthiness information. Our simulation-based numerical results show that the impact of default contagion on risk measures is well estimated by our framework.