Evaluating Systemic Risk using Bank Default Probabilities in Financial Networks

In this paper, we propose a novel methodology to measure systemic risk in networks composed of financial institutions. Our procedure combines the impact effects obtained from stress measures that rely on feedback centrality properties with default probabilities of institutions. We also present new heuristics for designing feasible and relevant stress-testing scenarios that can subside regulators in financial system surveillance tasks. We develop a methodology to extract banking communities and show that these communities are mostly composed of non-large banks and have a relevant effect on systemic risk. This finding renders these communities objects of interest for supervisory activities besides SIFIs and large banks. Finally, our results provide insights and guidelines that can be useful for policymaking.