The main features are as follows. First, estimate and disentangle not only first-round effects(i.e. shock on external assets) and second-round effects (i.e. distress induced in the interbank network), but also a third-round effect induced by possible fire sales. Second, monitor at the same time the impact of shocks on individual or groups of financial institutions as well as their vulnerability to shocks on counterparties or certain asset classes. Third, estimate loss distributions, thus combining network effects with familiar risk measures such as VaR and CVaR. Fourth, in order to do robustness analyses and cope with incomplete data, generate sets of networks of interbank exposures coherent with the total lending and borrowing of each bank. As an illustration, we carry out a stress–test exercise on a dataset of listed European banks over the years 2008-2013. We find that second-round and third-round effects dominate first-round effects, therefore suggesting that most current stress-test frameworks might lead to a severe underestimation of systemic risk.
Leveraging the network: a stress-test framework based on DebtRank
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