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Identifying SIFIs: Toward the Simpler Approach

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Date
2013
Collection title
SSRN Working Paper Series
Dewey
Economie financière
Sujet
Régulation bancaire et financière; Banking Regulation; Systemic Risk
JEL code
G.G0.G01; G.G3.G32
URI
https://basepub.dauphine.fr/handle/123456789/13727
Collections
  • DRM : Publications
Metadata
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Author
Benoit, Sylvain
559342 Laboratoire d'Economie de Dauphine [LEDa]
Dudek, Jérémy
2579 Centre de Recherche en Économie et Statistique [CREST]
Sharifova, Manizha
status unknown
Type
Document de travail / Working paper
Abstract (EN)
Systemic risk measures generally aim to identify systemically important financial institutions (SIFIs) that would allow regulators to allocate macro-prudential capital requirements in order to reduce risk stemming from such institutions. Among widely-cited are the measures of tail dependence in financial institutions’ equity returns, such as ΔCoVaR of Adrian and Brunnermeier (2011) and Marginal Expected Shortfall (MES) of Acharya et al. (2010). This paper compares nonlinear and linear approaches to modeling return dependence in the estimation of the ΔCoVaR and MES. Our results show that while the refined and complicated estimation techniques are able to produce more accurate value of institution’s systemic risk contribution they do not greatly improve in terms of identifying SIFIs compared to simpler linear estimation method. Modeling dependence linearly sufficient to identify and rank SIFIs.

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