2019
DOI: 10.1080/1350486x.2019.1702068
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A Copula-based Markov Reward Approach to the Credit Spread in the European Union

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 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 s… Show more

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Cited by 2 publications
(2 citation statements)
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“…At the same time, the test is carried out in order to assess statistically significant differences among the transition probability matrices found. Additional details on this statistical test are available in Polansky (2007) andD'Amico et al (2019).…”
Section: The Changepoint Class and Related CLImentioning
confidence: 99%
“…At the same time, the test is carried out in order to assess statistically significant differences among the transition probability matrices found. Additional details on this statistical test are available in Polansky (2007) andD'Amico et al (2019).…”
Section: The Changepoint Class and Related CLImentioning
confidence: 99%
“…The implication of a country's default and generally, of an increase of the sovereign credit risk is of crucial importance concerning both its effects on the domestic economy but also on the neighborhood economies. We have focused our attention on the financial risk in European Union by applying dynamic measure of inequality to evaluate how the financial risk is distributed among countries and to assess its behavior over time (D'Amico et al, 2018a;2018b;2019). The financial risk of a country refers to the ability to cope with its financial commitments and it is expressed by the amount of credit spread that the country has to pay on its debt.…”
Section: Introductionmentioning
confidence: 99%