This paper introduces a dominance test that allows to determine whether or not a financial institution can be classified as being more systemically important than another in a multivariate framework. The dominance test relies on a new risk measure, the ΔNetCoVaR that is specifically tailored to capture the joint extreme co-movements between institutions belonging to a network. The asymptotic theory for the statistical test is provided under mild regularity conditions concerning the joint distribution of asset returns which is assumed to be elliptically contoured. The proposed risk measure and risk measurement framework is used to analyse the US financial system during the recent Global Financial Crises. In the empirical analysis, the returns are assumed to be Elliptically Stable distributed and the estimation is carried out through the Sparse Multivariate Method of Simulated Quantiles, handling both the lack of an analytic expression for the probability density function and the potential high-dimensionality of the problem.

A dominance test for measuring financial connectedness

Bernardi M.
Membro del Collaboration Group
;
2020

Abstract

This paper introduces a dominance test that allows to determine whether or not a financial institution can be classified as being more systemically important than another in a multivariate framework. The dominance test relies on a new risk measure, the ΔNetCoVaR that is specifically tailored to capture the joint extreme co-movements between institutions belonging to a network. The asymptotic theory for the statistical test is provided under mild regularity conditions concerning the joint distribution of asset returns which is assumed to be elliptically contoured. The proposed risk measure and risk measurement framework is used to analyse the US financial system during the recent Global Financial Crises. In the empirical analysis, the returns are assumed to be Elliptically Stable distributed and the estimation is carried out through the Sparse Multivariate Method of Simulated Quantiles, handling both the lack of an analytic expression for the probability density function and the potential high-dimensionality of the problem.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3332206
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