Testing for Equality between Two Copulas

Rémillard, Bruno; Scaillet, Olivier

doi:10.2139/ssrn.1014550

Cited by 70 publications

(150 citation statements)

References 29 publications

(21 reference statements)

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“…Fermanian et al (2004) proposed a bootstrap procedure based on resampling and proved its consistency. A wild bootstrap approach based on the multiplier method was recently proposed by Rémillard and Scaillet (2009) and applied to the problem of testing the equality between two copulas. Recently and Kojadinovic, Yan and Holmes (2009) used the same method to construct a goodness-of-fit test for the parametric form of a copula.…”

Section: Introductionmentioning

confidence: 99%

“…The present paper has two purposes. On the one hand our work is motivated by the fact that the multiplier approach proposed by Rémillard and Scaillet (2009) still requires the estimation of the partial derivatives of the unknown copula. For this reason we propose a modification of this method, which avoids this estimation problem.…”

Section: Introductionmentioning

confidence: 99%

“…For this reason we propose a modification of this method, which avoids this estimation problem. On the other hand we investigate the finite sample properties of the resampling bootstrap, a slightly modified version of the bootstrap proposed by Rémillard and Scaillet (2009) and the new direct multiplier bootstrap proposed in this paper. In particular it is demonstrated that despite the fact that the new multiplier method has the most attractive theoretical properties and avoids the problem of estimating derivatives, the procedure proposed in Rémillard and Scaillet (2009) yields the best results in most cases.…”

Section: Introductionmentioning

confidence: 99%

“…In a recent paper Rémillard and Scaillet (2009) considered the problem of testing the equality between two copulas [see also Scaillet (2005)] and proposed a multiplier bootstrap to approximate the distribution of the limiting process G C . To be precise let Z 1 , .…”

Section: Introductionmentioning

confidence: 99%

“…, X n , which satisfy ||Z|| 2,1 = ∞ 0 P (|Z| > x) dx < ∞. Rémillard and Scaillet (2009) defined the bootstrap process…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A note on bootstrap approximations for the empirical copula process

Bücher

Dette

2010

Statistics & Probability Letters

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It is well known that the empirical copula process converges weakly to a centered Gaussian field. Because the covariance structure of the limiting process depends on the partial derivatives of the unknown copula several bootstrap approximations for the empirical copula process have been proposed in the literature. We present a brief review of these procedures.Because some of these procedures also require the estimation of the derivatives of the unknown copula we propose an alternative approach which circumvents this problem. Finally a simulation study is presented in order to compare the different bootstrap approximations for the empirical copula process.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…, X n , which satisfy ||Z|| 2,1 = ∞ 0 P (|Z| > x) dx < ∞. Rémillard and Scaillet (2009) defined the bootstrap process…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A note on bootstrap approximations for the empirical copula process

Bücher

Dette

2010

Statistics & Probability Letters

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Large-sample tests of extreme-value dependence for multivariate copulas

2011

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cited By (since 1996)3International audienceStarting from the characterization of extreme-value copulas based on max-stability, large-sample tests of extreme-value dependence for multivariate copulas are studied. The two key ingredients of the proposed tests are the empirical copula of the data and a multiplier technique for obtaining approximate p-values for the derived statistics. The asymptotic validity of the multiplier approach is established, and the finite-sample performance of a large number of candidate test statistics is studied through extensive Monte Carlo experiments for data sets of dimension two to five. In the bivariate case, the rejection rates of the best versions of the tests are compared with those of the test of Ghoudi et al. (1998) recently revisited by Ben Ghorbal et al. (2009). The proposed procedures are illustrated on bivariate financial data and trivariate geological data. © 2011 Statistical Society of Canada

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Graphical and formal statistical tools for the symmetry of bivariate copulas

Quessy

Bahraoui

2013

Can J Statistics

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Statistical tools to check whether the underlying copula of a pair of random variables is symmetric are developed. The proposed methods are based on the theoretical and empirical versions of the C‐power functions introduced and formally studied by Bahraoui & Quessy (2013). On one part, a methodology is developed for testing the null hypothesis that the copula of a given population is symmetric. To this end, a sequential testing procedure is proposed where at each level, the P‐value is estimated with the help of the multiplier bootstrap method. On another side, a related graphical method is proposed in order to gain an idea of the degree of asymmetry in bivariate data. The good properties of the methods in small samples are investigated with the help of Monte Carlo simulations under various scenarios of symmetric and asymmetric dependence. The newly introduced procedures are used to analyse the Nutrient and the Walker Lake data sets. The Canadian Journal of Statistics 41: 637–656; 2013 © 2013 Statistical Society of Canada

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Testing for Equality between Two Copulas

Cited by 70 publications

References 29 publications

A note on bootstrap approximations for the empirical copula process

A note on bootstrap approximations for the empirical copula process

Large-sample tests of extreme-value dependence for multivariate copulas

Graphical and formal statistical tools for the symmetry of bivariate copulas

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