Reference : A Framework for Tracking Changes in the Intensity of Investment Funds’ Systemic Risk
Scientific journals : Article
Business & economic sciences : Finance
A Framework for Tracking Changes in the Intensity of Investment Funds’ Systemic Risk
Jin, Xisong mailto [University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > Luxembourg School of Finance (LSF) >]
Nadal de Simone, Francisco [Banque Centrale du Luxembourg]
Journal of Empirical Finance
[en] financial stability; investment funds; procyclicality, macroprudential policy; credit risk; early warning indicators; probability of distress, non-linearities, generalized dynamic factor model; dynamic copulas.
[en] This study applies to investment funds 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 of Segoviano, 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. It measures investment funds systemic credit risk in three forms: (1) credit risk common to all funds within each of the seven categories the Eurosystem reports to the ECB; (2) credit risk in each category of investment fund conditional on distress on another category of investment fund and; (3) the buildup of investment funds’ vulnerabilities over time which may unravel disorderly. In addition, the estimates of the common components of the investment funds’ distress measures contain early warning features, and the identification of their drivers is useful for macroprudential policy. As a result, this framework contributes to making macroprudential policy operational

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