Estimation problems for some perturbations of the independence copula

Abstract This work provides a study of copula parameters estimators based on functions of Markov chains they generate. Copulas of interest are perturbations of the independence copula. We provide asymptotic distributions of maximum likelihood estimators and confidence intervals for parameters of several copula families introduced in Longla (Stat Pap 65:4331–4363, 2024). A set of moment-like estimators is proposed along with a multivariate asymptotic distribution. We investigate the particular case of Markov chains generated by sine copulas, sine-cosine copulas and the extended Farlie-Gumbel-Morgenstern (FGM) copula family. We provide evidence that our extension of the FGM copula does a better job at capturing the dependence in the Bearing Data Set . Some tests of independence of the sample are proposed. A simulation study is provided for the three examples of copula families that we propose from Type I Longla copulas. This simulation study proposes a comparative study of the introduced estimators, the maximum likelihood estimators and the robust estimators of Longla and Peligrad (J Stat Plan Inference 211:90–106, 2024). It showcases advantages of the proposed estimators.

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Journal
Statistical Papers
Published
2025-11-21
DOI
https://doi.org/10.1007/s00362-025-01778-8
Citations
1
Primary Topic
Financial Risk and Volatility Modeling
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article
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2.21
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article

Estimation problems for some perturbations of the independence copula

Mous-Abou Hamadou, Martial Longla
1 citations
Statistical Papers
Financial Risk and Volatility Modeling
2.21
article

Estimation problems for some perturbations of the independence copula

Mous-Abou Hamadou, Martial Longla
article en
1 citations

Abstract

Abstract This work provides a study of copula parameters estimators based on functions of Markov chains they generate. Copulas of interest are perturbations of the independence copula. We provide asymptotic distributions of maximum likelihood estimators and confidence intervals for parameters of several copula families introduced in Longla (Stat Pap 65:4331–4363, 2024). A set of moment-like estimators is proposed along with a multivariate asymptotic distribution. We investigate the particular case of Markov chains generated by sine copulas, sine-cosine copulas and the extended Farlie-Gumbel-Morgenstern (FGM) copula family. We provide evidence that our extension of the FGM copula does a better job at capturing the dependence in the Bearing Data Set . Some tests of independence of the sample are proposed. A simulation study is provided for the three examples of copula families that we propose from Type I Longla copulas. This simulation study proposes a comparative study of the introduced estimators, the maximum likelihood estimators and the robust estimators of Longla and Peligrad (J Stat Plan Inference 211:90–106, 2024). It showcases advantages of the proposed estimators.

Statistical PapersVol. 66(7)
University of Mississippi (US)
Openalex Percentile: Top 9%
Financial Risk and Volatility Modeling
2.21
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