Investment funds? vulnerabilities: A tail-risk dynamic CIMDO approach
Xisong Jin () and
Francisco Nadal De Simone ()
No 95, BCL working papers from Central Bank of Luxembourg
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.
Keywords: financial stability; investment funds; procyclicality, macro-prudential policy; structural credit risk models; probability of distress; non-linearities; generalized dynamic factor model; dynamic copulas (search for similar items in EconPapers)
JEL-codes: C1 E5 F3 G1 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-mac and nep-rmg
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