Network Tail Risk Estimation in the European Banking System

Abstract Measuring interconnectedness in a banking system to identify the potential transmission channels of systemic risk is a main issue for the analysis of financial stability. We develop a methodology based on conditional tail risk networks to assess the channels of transmission in a banking system and to identify the most relevant and/or fragile institutions. The networks are constructed using quantile graphical models and the proposed framework can be considered as a network extension of the Δ CoVaR approach by Adrian and Brunnermeier (2016). From the conditional tail risk networks we can then compute synthetic indices of systemic risk for each bank. An additional set of systemic risk indicators is computed by considering together the network of conditional tail risk and bank-specific indicators of credit risk (as an example we use the ratio of non-performing loans, NPL). The empirical analysis focuses on the European banking system and considers a panel of 36 representative banks. Among the main findings, we found evidence of regional clusters of interconnected banks, especially in crisis period. Moreover, in terms of interconnectedness alone, systemic risk is diffused relatively evenly across European banks, while the set of systemic indicators built using also NPL highlighted a concentration of risk in southern European countries.