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Data driven partition-of-unity copulas with applications to risk management

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  • Dietmar Pfeifer
  • Andreas Mandle
  • Olena Ragulina

Abstract

We present a constructive and self-contained approach to data driven general partition-of-unity copulas that were recently introduced in the literature. In particular, we consider Bernstein-, negative binomial and Poisson copulas and present a solution to the problem of fitting such copulas to highly asymmetric data.

Suggested Citation

  • Dietmar Pfeifer & Andreas Mandle & Olena Ragulina, 2017. "Data driven partition-of-unity copulas with applications to risk management," Papers 1703.05047, arXiv.org, revised Nov 2020.
    • Handle: RePEc:arx:papers:1703.05047
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    References listed on IDEAS

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    1. Durante, Fabrizio & Fernández Sánchez, Juan & Sempi, Carlo, 2013. "Multivariate patchwork copulas: A unified approach with applications to partial comonotonicity," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 897-905.
    2. Pfeifer Dietmar & Tsatedem Hervé Awoumlac & Mändle Andreas & Girschig Côme, 2016. "New copulas based on general partitions-of-unity and their applications to risk management," Dependence Modeling, De Gruyter, vol. 4(1), pages 1-18, July.
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    Cited by:

    1. Andreas Masuhr, 2018. "Bayesian Estimation of Generalized Partition of Unity Copulas," CQE Working Papers 7318, Center for Quantitative Economics (CQE), University of Muenster.

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