TIME-VARYING HIERARCHICAL ARCHIMEDEAN COPULAS: A NON-PARAMETRIC APPROACH

A non-parametric approach based on U-statistics in the construction of the time-varying hierarchical Archimedean copula model has been proposed. The procedure aims to analyze changes in the Kendall correlation matrix computed from the observations. This makes it possible to identify local segments of homogeneity and to construct a hierarchical Archimedean copula model on each segment. The simulations performed made it possible to assess the power of the proposed procedure.

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Publication Details

Journal
Far East Journal of Theoretical Statistics
Published
2024-10-19
DOI
https://doi.org/10.17654/0972086324022
Primary Topic
Stochastic processes and financial applications
Type
article
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article

TIME-VARYING HIERARCHICAL ARCHIMEDEAN COPULAS: A NON-PARAMETRIC APPROACH

Diakarya Barro, Dodo Natatou Moutari, Saley Bisso, Hassane Abba Mallam et al.
Far East Journal of Theoretical Statistics
Stochastic processes and financial applications
article

TIME-VARYING HIERARCHICAL ARCHIMEDEAN COPULAS: A NON-PARAMETRIC APPROACH

Diakarya Barro, Dodo Natatou Moutari, Saley Bisso, Hassane Abba Mallam, Benjamin Wengoundi Nikiéma
article en

Abstract

A non-parametric approach based on U-statistics in the construction of the time-varying hierarchical Archimedean copula model has been proposed. The procedure aims to analyze changes in the Kendall correlation matrix computed from the observations. This makes it possible to identify local segments of homogeneity and to construct a hierarchical Archimedean copula model on each segment. The simulations performed made it possible to assess the power of the proposed procedure.

Far East Journal of Theoretical StatisticsVol. 68(3)
Openalex Percentile: Top 75%
Stochastic processes and financial applications
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