Displaying similar documents to “New estimates and tests of independence in semiparametric copula models”

About tests of the “simplifying” assumption for conditional copulas

Alexis Derumigny, Jean-David Fermanian (2017)

Dependence Modeling

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We discuss the so-called “simplifying assumption” of conditional copulas in a general framework. We introduce several tests of the latter assumption for non- and semiparametric copula models. Some related test procedures based on conditioning subsets instead of point-wise events are proposed. The limiting distributions of such test statistics under the null are approximated by several bootstrap schemes, most of them being new. We prove the validity of a particular semiparametric bootstrap...

A copula test space model how to avoid the wrong copula choice

Frederik Michiels, Ann De Schepper (2008)

Kybernetika

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We introduce and discuss the test space problem as a part of the whole copula fitting process. In particular, we explain how an efficient copula test space can be constructed by taking into account information about the existing dependence, and we present a complete overview of bivariate test spaces for all possible situations. The practical use will be illustrated by means of a numerical application based on an illustrative portfolio containing the S&P 500 Composite Index, the JP...

Multivariate probability integral transformation: application to maximum likelihood estimation.

Abderrahmane Chakak, Layachi Imlahi (2001)

RACSAM

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Sea (X, X) un vector aleatorio con una función de distribución F. La transformación integral de la probabilidad (pit) es la variable aleatoria unidimensional P = F(X, X). La expresion de su función de distribución, y un algoritmo de simulación en términos de la función cuantil, dada por Chakak et al [2000], cuando la distribución es absolumente continua, son extendidas a distribuciones que pueden tener singularidades. La estimación de máxima verosimilitud del parámetro de dependencia...

Quantifying the impact of different copulas in a generalized CreditRisk + framework An empirical study

Kevin Jakob, Matthias Fischer (2014)

Dependence Modeling

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Without any doubt, credit risk is one of the most important risk types in the classical banking industry. Consequently, banks are required by supervisory audits to allocate economic capital to cover unexpected future credit losses. Typically, the amount of economical capital is determined with a credit portfolio model, e.g. using the popular CreditRisk+ framework (1997) or one of its recent generalizations (e.g. [8] or [15]). Relying on specific distributional assumptions, the credit...

A simple non-parametric goodness-of-fit test for elliptical copulas

Miriam Jaser, Stephan Haug, Aleksey Min (2017)

Dependence Modeling

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In this paper, we propose a simple non-parametric goodness-of-fit test for elliptical copulas of any dimension. It is based on the equality of Kendall’s tau and Blomqvist’s beta for all bivariate margins. Nominal level and power of the proposed test are investigated in a Monte Carlo study. An empirical application illustrates our goodness-of-fit test at work.

Semiparametric estimation of the parameters of multivariate copulas

Eckhard Liebscher (2009)

Kybernetika

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In the paper we investigate properties of maximum pseudo-likelihood estimators for the copula density and minimum distance estimators for the copula. We derive statements on the consistency and the asymptotic normality of the estimators for the parameters.