Risk Measure Inference

Christophe Hurlin (1) , Sebastien Laurent (2, 3) , Rogier Quaedvlieg (4) , Stephan Smeekes (4)

1 LEO - Laboratoire d'économie d'Orleans [2008-2011]
2 AMU IAE - Institut d'Administration des Entreprises (IAE) - Aix-en-Provence
3 GREQAM - Groupement de Recherche en Économie Quantitative d'Aix-Marseille
4 Maastricht University [Maastricht]

We propose a widely applicable bootstrap based test of the null hypothesis of equality of two firms' Risk Measures (RMs) at a single point in time. The test can be applied to any market-based measure. In an iterative procedure, we can identify a complete grouped ranking of the RMs, with particular application to finding buckets of fi rms of equal systemic risk. An extensive Monte Carlo Simulation shows desirable properties. We provide an application on a sample of 94 U.S. financial institutions using the ΔCoVaR, MES and %SRISK, and conclude only the %SRISK can be estimated with enough precision to allow for a meaningful ranking.

Mots clés: Bootstrap; Grouped Ranking; Risk Measures; Uncertainty

Domaines: Economies et finances

Christophe Hurlin, Sebastien Laurent, Rogier Quaedvlieg, Stephan Smeekes. Risk Measure Inference. 2013. ⟨halshs-00877279v2⟩