Measuring Credit Risk in a Large Banking System: Econometric Modeling and Empirics

Two new measures for financial systemic risk are computed based on the time-varying conditional and unconditional probability of simultaneous failures of several financial institutions. These risk measures are derived from a multivariate model that allows for skewed and heavy-tailed changes in the market value of financial firms' equity. Our model can be interpreted as a Merton model with correlated Levy drivers. This model incorporates dynamic volatilities and dependence measures and uses the overall information on the shape of the multivariate distribution. Our correlation estimates are robust against possible outliers and influential observations. For very large cross-sectional dimensions, we propose an approximation based on a conditional Law of Large Numbers to compute extreme joint default probabilities. We apply the model to assess the risk of joint financial firm failure in the European Union during the financial crisis.