A new approach to measure systemic risk: A bivariate copula model for dependent censored data

Silvia Angela Osmetti, Raffaella Calabrese

Risultato della ricerca: Contributo in rivistaArticolo in rivista

7 Citazioni (Scopus)

Abstract

We propose a novel approach based on the Marshall-Olkin (MO) copula to estimate the impact of systematic and idiosyncratic components on cross-border systemic risk. To use the data on non-failed banks in the suggested method, we consider the time to bank failure as a censored variable. Therefore, we propose a pseudo-maximum likelihood estimation procedure for the MO copula for a Type I censored sample. We derive the log-likelihood function, the copula parameter estimator and the bootstrap confidence intervals. Empirical data on the banking system of three European countries (Germany, Italy and the UK) shows that the proposed censored model can accurately estimate the systematic component of cross-border systemic risk. (C) 2019 Elsevier B.V. All rights reserved.
Lingua originaleEnglish
pagine (da-a)1053-1064
Numero di pagine12
RivistaEuropean Journal of Operational Research
Volume279
DOI
Stato di pubblicazionePubblicato - 2019

Keywords

  • Censored sampling
  • Copula models
  • OR in banking
  • Pseudo-maximum likelihood estimation
  • Systemic risk

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