Copula estimation through wavelets

Autor(es)

Medina, Francyelle L. ^[1] ; Morettin, Pedro A. ^[2] ; Toloi, Clelia M. C. ^[2]

Afiliação do(s) autor(es)

^[1] Univ Fed Pernambuco, Dept Stat, BR-50740560 Recife, PE - Brazil

^[2] Univ Sao Paulo, Dept Stat, BR-05508090 Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS; v. 34, n. 3, p. 439-463, AUG 2020.
• Citações Web of Science: 0

Resumo

Recently some nonparametric estimation procedures have been proposed using kernels and wavelets to estimate the copula function. In this context, knowing that a copula function can be expanded in a wavelet basis, we propose a new nonparametric copula estimation procedure through wavelets for independent data and times series under an alpha-mixing condition. The main feature of this estimator is that we make no assumptions on the data distribution and there is no need to use ARMA-GARCH modelling before estimating the copula. Convergence rates for the estimator were computed, showing the estimator consistency. Some simulation studies are presented, as well as analysis of real data sets. (AU)

• Processo FAPESP: 13/00506-1 - Séries temporais, ondaletas e análise de dados funcionais
• Beneficiário: Pedro Alberto Morettin
• Modalidade de apoio: Auxílio à Pesquisa - Temático