This paper proposes a #credit #portfolio approach for evaluating #systemicrisk and attributing it across #financialinstitutions. The proposed model can be estimated from high-frequency credit default swap (#cds) data and captures risks from publicly traded #banks, privately held institutions, and coöperative banks. The approach overcomes limitations of earlier studies by accounting for correlated losses between institutions and also offers a modeling extension to account for #fattails and #skewness of #assetreturns. The model is applied to a universe of banks in #europe, highlighting discrepancies between the #capitaldequacy of the largest contributors to systemic risk and less systemically important banks.
Quantifying Systemic Risk in the Presence of Unlisted Banks: Application to the European Banking Sector
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