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A Copula-based Markov Reward Approach to the Credit Spread in the European Union

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  • Guglielmo D’Amico
  • Filippo Petroni
  • Philippe Regnault
  • Stefania Scocchera
  • Loriano Storchi

Abstract

In this paper, we propose a methodology based on piecewise homogeneous Markov chain for credit ratings and a multivariate model of the credit spreads to evaluate the financial risk in the European Union (EU). Two main aspects are considered: how the financial risk is distributed among the European countries and how large is the value of the total risk. The first aspect is evaluated by means of the expected value of a dynamic entropy measure. The second one is solved by computing the evolution of the total credit spread over time. Moreover, the covariance between countries’ total spread allows the understanding of any contagions in the EU. The methodology is applied to real data of 24 European countries for the three major rating agencies: Moody’s, Standard & Poor’s and Fitch. Obtained results suggest that both the financial risk inequality and the value of the total risk increase over time at a different rate depending on the rating agency. Moreover, the results indicate that the dependence structure is characterized by a strong correlation between most of the European countries.

Suggested Citation

  • Guglielmo D’Amico & Filippo Petroni & Philippe Regnault & Stefania Scocchera & Loriano Storchi, 2019. "A Copula-based Markov Reward Approach to the Credit Spread in the European Union," Applied Mathematical Finance, Taylor & Francis Journals, vol. 26(4), pages 359-386, July.
    • Handle: RePEc:taf:apmtfi:v:26:y:2019:i:4:p:359-386
    DOI: 10.1080/1350486X.2019.1702068
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    Cited by:

    1. Guglielmo D'Amico & Stefania Scocchera & Loriano Storchi, 2021. "Randentropy: a software to measure inequality in random systems," Papers 2103.09107, arXiv.org.

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