On the simplified pair-copula construction - Simply useful or too simplistic?
Journal of Multivariate Analysis
An Introduction to Copulas
Semiparametric estimation of conditional copulas
Journal of Multivariate Analysis
Comparison of estimators for pair-copula constructions
Journal of Multivariate Analysis
A review of copula models for economic time series
Journal of Multivariate Analysis
Semiparametric estimation of conditional copulas
Journal of Multivariate Analysis
Journal of Multivariate Analysis
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Pair-copula constructions (PCCs) offer great flexibility in modeling multivariate dependence. For inference purposes, however, conditional pair-copulas are often assumed to depend on the conditioning variables only indirectly through the conditional margins. The authors show here that this assumption can be misleading. To assess its validity in trivariate PCCs, they propose a visual tool based on a local likelihood estimator of the conditional copula parameter which does not rely on the simplifying assumption. They establish the consistency of the estimator and assess its performance in finite samples via Monte Carlo simulations. They also provide a real data application.