Beyond simplified pair-copula constructions

JOURNAL OF MULTIVARIATE ANALYSIS

卷:110

Article; Proceedings Paper

Acar, Elif F.¹  Genest, Christian¹  Neslehova, Johanna¹ 

[1] McGill Univ, Dept Math & Stat, Montreal, PQ H3A 0B9, Canada

关键词: Conditional copulas;    Kendall's tau;    Local likelihood;    Pair-copula constructions;    Ranks;    Vines;   

DOI  :  10.1016/j.jmva.2012.02.001

来源: Elsevier

【 摘 要 】

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. (C) 2012 Elsevier Inc. All rights reserved.

【 授权许可】

Free