The systemic risk measure (SRISK) by V-Lab provides a market view of the vulnerability of financial institutions to a sudden downturn in the economy. To overcome the shortcoming that it cannot be applied to non-listed banks, SRISK characteristics of listed banks are mapped on balance sheet...

We introduce a structural quantile vector autoregressive (VAR) model. Unlike standard VAR which models only the average interaction of the endogenous variables, quantile VAR models their interaction at any quantile. We show how to estimate and forecast multivariate quantiles within a recursive...

We study the functioning and possible breakdown of the interbank market in the presence of counterparty risk. We allow banks to have private information about the risk of their assets. We show how banks’ asset risk affects funding liquidity in the interbank market. Several interbank market...

We study the functioning of secured and unsecured interbank markets in the presence of credit risk. The model generates empirical predictions that are in line with developments during the 2007-2009 financial crises. Interest rates decouple across secured and unsecured markets following an...

Macro-prudential authorities need to assess medium-term downside risks to the real economy, caused by severe financial shocks. Before activating policy measures, they also need to consider their short-term negative impact. This gives rise to a risk management problem, an inter-temporal trade-off...

We study how banks manage their liquidity among the various assets at their disposal. We exploit the introduction of the ECB's two-tier system which heterogeneously reduced the cost of additional reserves holdings. We find that the treated banks increase reserve holdings by borrowing on the...

A decision maker tests whether the gradient of the loss function evaluated at a judgmental decision is zero. If the test does not reject, the action is the judgmental decision. If the test rejects, the action sets the gradient equal to the boundary of the rejection region. This statistical...

Engle and Manganelli (2004) propose CAViaR, a class of models suitable for estimating conditional quantiles in dynamic settings. Engle and Manganelli apply their approach to the estimation of Value at Risk, but this is only one of many possible applications. Here we extend CAViaR models to...