Goodness-of-fit tests for copulas

By Jean-David Fermanian. 2005

409 citations recorded by the source corpus.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/d917f844a260b6bbae2f490318d2158e0f24e652

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Citations in the corpus

Goodness-of-fit tests for parametric families of Archimedean copulas (2008, methodology): “A very good introduction to the copula concept is Nelsen (1999) and, with some extensions, Joe (1997).”
Asymmetric copula in multivariate flood frequency analysis (2006, methodology): “On formal goodness of fit test for copulas, only few works are available (see [3,13,17]), so the best copula is selected using a test proposed by Chen et al.”
An updated review of Goodness-of-Fit tests for regression models (2013, methodology): “Finally, inspired by the previous ideas, Fermanian (2005) proposed distribution free GoF for copulas, investigating their asymptotic distribution, and Bücher and Dette (2010) derived the asymptotic properties under fixed alternatives.”
Estimating copula densities through wavelets (2009, methodology): “Six graphical representations of the LOSS/ALAE data of Frees and Valdez (1998). Panel a): Original data on the logarithmic scale; panel b): rank-rank plot; panel c): 3D-histogram on a 16×16 grid; panel d): wavelet-based copula density estimate without boundary correction; panel e) recommended wavele”
National Centre of Competence in Research Financial Valuation and Risk Management (2005, methodology): “We compare the performance of rejection rules based on 1) asymptotic sets of the chi-square test statistic derived in Fermanian [10] Corollary 4 for a vanishing bandwidth, 2) sets computed with a bootstrap procedure for the same test statistic, 3) sets computed with a bootstrap procedure for the tes”
An Overview of the Goodness-of-Fit Test Problem for Copulas (2012, neutral): “This idea of applying an arbitrary categorization of the data into conti ngency tables[0,1]d has been applied more or less fruitfully in a lot of papers: [46], [59], [33], [4], [58], etc.”
Index flood–based multivariate regional frequency analysis (2009, background): “Recently, some statistical tests (numerical or graphical) have been developed to test copula’s goodness of fit [see, e.g., Fermanian, 2005; Genest et al., 2009].”
Nonparametric estimation of copula functions for dependence modelling (2007, methodology): “The estimator considered by Fermanian & Scaillet (2003) is of the above form based on the original kernel K rather than the local linear kernels Ku,h.”
Multivariate quantiles in hydrological frequency analysis (2011, methodology): “Some statistical tests (numerical or graphical) have also been developed to treat copula’s goodness-of-fit (see, e.g. Genest and Rivest, 1993; Fermanian, 2005 and Genest et al., 2009).”
Probit Transformation for Nonparametric Kernel Estimation of the Copula Density (2014, background): “Although some papers ignored these issues [18,20,46], it is clear that accurate estimation of c calls for some boundary correction.”