The impact on the properties of the EFGM copulas when extending this family

Saminger‐Platz, Susanne; Kolesárová, Anna; Šeliga, Adam; Mesiar, Radko; Klement, Erich Peter

doi:10.1016/j.fss.2020.11.001

Cited by 9 publications

(2 citation statements)

References 55 publications

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“…The second section is devoted to define the symmetrized and the radial symmetrized copulas. We give some properties linking a given copula and its symmetrized and radial symmetrized ones in the same spirit of [22].…”

Section: Introductionmentioning

confidence: 99%

New asymmetric perturbations of FGM bivariate copulas and concordance preserving problems

Maazouz¹,

Sani²

2023

Moroccan Journal of Pure and Applied Analysis

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New copulas, based on perturbation theory, are introduced to clarify a symmetrization procedure for asymmetric copulas. We give also some properties of the symmetrized copula mainly conservation of concordance. Finally, we examine some copulas with a prescribed symmetrized part. The start point of the treatment is the independence copula and the last one will be an arbitrary member of Farlie-Gumbel-Morgenstein family. By the way, we study topologically, the set of all symmetric copulas and give some of its classical and new properties.

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Section: Introductionmentioning

confidence: 99%

New asymmetric perturbations of FGM bivariate copulas and concordance preserving problems

Maazouz¹,

Sani²

2023

Moroccan Journal of Pure and Applied Analysis

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“…Indeed, the classical Sklar's Theorem (see Sklar 1959) assures that copulas can capture the stochastic dependence among a set of random quantities. In this respect, the large number of existing copulas provides rather complete coverage of the possible types of association, ranging from tail dependence (see, e.g., Dolati et al 2014;Fernandez-Sanchez and Ubeda-Flores 2019) to generalized concepts of positive dependence, like the multivariate total positivity of order 2 (see, e.g., Cerqueti and Lupi 2016;Wysocki 2015) and the positive quadrant dependence (see, e.g., Gijbels et al 2010;Saminger-Platz et al 2021).…”

Section: Introductionmentioning

confidence: 99%

A new family of modified Gaussian copulas for market consistent valuation of government guarantees

et al. 2022

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This paper deals with a copula-based stochastic dependence problem in the context of financial risks. We discuss the financial framework for assessing the theoretical up-front value of government guarantees on bank liabilities. EU States widely use these contracts to improve the financial system’s stability and manage the banking sector in crisis situations; in Italy, they have also been used to address the consequences of the Covid-19 emergency. From a market viewpoint, we deal with a defaultable guarantee contract where the State-guarantor and the bank-borrower are both subject to default risk, and their risks are interconnected. We show that the classical Gaussian copula is not satisfactory for modeling the dependence among the considered risks. Indeed, using the benchmark market model for credit risk portfolio management, we highlight some contradictory results observed for the up-front values of the guarantee when the default intensity of the guarantor is smaller than that of the borrower. Then, we introduce a new family of modified Gaussian copulas that overcomes the limitations of the standard approach, allowing to determine realistic results in terms of the guarantees “mark-to-model” value when the benchmark market model does not work. Numerical simulations validate the theoretical proposal.

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Multivariate failure time distributions derived from shared frailty and copulas

Wang

Emura

2021

Jpn J Stat Data Sci

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The impact on the properties of the EFGM copulas when extending this family

Cited by 9 publications

References 55 publications

New asymmetric perturbations of FGM bivariate copulas and concordance preserving problems

New asymmetric perturbations of FGM bivariate copulas and concordance preserving problems

A new family of modified Gaussian copulas for market consistent valuation of government guarantees

Multivariate failure time distributions derived from shared frailty and copulas

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