| Résumé | This study measures investment funds’ systemic credit risk in three forms: (1) credit risk common to all funds within each of the seven categories National Central Banks report
to the ECB; (2) credit risk in each category of investment fund conditional on distress on another category of investment fund and; (3) the build-up of investment funds’
vulnerabilities which may lead to a disorderly unraveling. The paper uses a novel framework which combines marginal probabilities of distress estimated from a structural
credit risk model with the consistent information multivariate density optimization (CIMDO) methodology and the generalized dynamic factor model (GDFM). The
framework models investment funds’ distress dependence explicitly and captures the time-varying non-linearities and feedback effects typical of financial markets. In addition,
the estimates of the common components of the investment funds’ distress measures may contain some early warning features, and identifying the macro and financial
variables most closely associated with them may serve to guide macro-prudential policy.
The relative importance of these variables differs from those associated with the common components of marginal measures of distress. Thus this framework can
contribute to the formulation of macro-prudential policy.
JEL Classification: C1, E5, F3, G1
Keywords: financial stability; investment funds; procyclicality, macro-prudential policy;
structural credit risk models; probability of distress; non-linearities; generalized dynamic
factor model; dynamic copulas. |
