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Systemic risk attribution in the EU

Author

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  • G. Farina
  • R. Giacometti
  • M. E. De Giuli

Abstract

Systemic default risk is due to multiple private and/or public entities’ simultaneous default. This risk has caused great concern in the recent past and its assessment is not a trivial subject. We have provided a model for systemic risk attribution in order to disentangle its different components. We have applied it to a selection of EU countries consistent with previous research. We have extracted a common EU factor and analysed the residual components related to an individual country’s banking system, to the interaction between banking system and government, and to the country’s and banking idiosyncratic components, as well.For this purpose, we have introduced a multivariate distribution for all the countries and the relative banks, also providing an integrated analysis. We have applied the multivariate Marshall–Olkin distribution, where the marginal probability of default for any country or bank depends on its default intensity. Risk attribution has been performed using weekly market data referred to sovereign and bank CDSs over the period 2009–2015. Our results have highlighted relevant differences between Northern and Southern EU countries, as far as risk decomposition is concerned. In Southern countries, risk is mainly concentrated in a country-banking system shock at each level. In Northern countries, the prevailing components of risk are the systemic EU shock at country level, and the idiosyncratic component at banking system level and individual bank level.

Suggested Citation

  • G. Farina & R. Giacometti & M. E. De Giuli, 2019. "Systemic risk attribution in the EU," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(7), pages 1115-1128, July.
  • Handle: RePEc:taf:tjorxx:v:70:y:2019:i:7:p:1115-1128
    DOI: 10.1080/01605682.2018.1487823
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    Cited by:

    1. R. Giacometti & G. Torri & G. Farina & M. E. Giuli, 2020. "Risk attribution and interconnectedness in the EU via CDS data," Computational Management Science, Springer, vol. 17(4), pages 549-567, December.
    2. Ballester, Laura & López, Jesúa & Pavía, Jose M., 2023. "European systemic credit risk transmission using Bayesian networks," Research in International Business and Finance, Elsevier, vol. 65(C).

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