Quantifying Systemic Risk in the Presence of Unlisted Banks: Application to the European Banking Sector

We propose a credit portfolio approach for evaluating systemic risk and attributing it across institutions. We construct a model that can be estimated from high-frequency CDS data. This captures risks from publicly traded banks, privately held institutions, and cooperative banks, extending approaches that rely on information from the public equity market only. We account for correlated losses between the institutions, overcoming a modeling weakness in earlier studies. We also offer a modeling extension to account for fat tails and skewness of asset returns. The model is applied to a universe of banks where we find discrepancies between the capital adequacy of the largest contributors to systemic risk relative to less systemically important banks on a European scale.