Estimating copula densities through wavelets

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Probit Transformation for Nonparametric Kernel Estimation of the Copula Density (2014, background): “…(2004), Tsukuhara (2005), Segers (2012) and B¨ucher and Volgushev (2013), and turns out to be the cornerstone of a variety of nonparametric copula-based procedures, see e.g. Genest and R´emillard (2004), Genest et al (2009a), Gudendorf and Segers (2012) or Li and Genton (2013), to cite only a few.”
An Overview of the Goodness-of-Fit Test Problem for Copulas (2012, background): “Another solution is to estimate copula densities through wavelets, for which the border effects are handled automatically, due to the good localization properties of the wavelet basis: see [43].”
Portfolio optimization in the presence of dependent financial returns with long memory: A copula based approach. (2013, methodology): “More precisely, the smoothed density copula is estimated by using a non-parametric estimator based on the wavelet decomposition as advanced by Genest et al. (2009b).”
The Advent of Copulas in Finance (2009, unknown): “Genest and Favre 2007 ; Genest, Masiello, and Tribouley 2009 ).”
Flexible Copula Density Estimation with Penalized Hierarchical B‐splines (2013, background): “More recently, the use of wavelet-based estimation has been suggested by Morettin et al. (2010) for copula estimation or Genest et al. (2009) for copula density estimation; see also for a more theoretical investigation Autin et al. (2010).”