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Multivariate radial symmetry of copula functions: finite sample comparison in the i.i.d case

Author

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  • Billio Monica

    (University Ca’ Foscari of Venice, Department of Economics, Venice, Italy)

  • Frattarolo Lorenzo

    (European Commission, Joint Research Centre (JRC), Ispra, Italy)

  • Guégan Dominique

    (University Paris-1 Panthéon-Sorbonne, Paris, France and University Ca’ Foscari of Venice, Department of Economics, Venice, Italy)

Abstract

Given a d-dimensional random vector X = (X1, . . ., Xd), if the standard uniform vector U obtained by the component-wise probability integral transform (PIT) of X has the same distribution of its point reflection through the center of the unit hypercube, then X is said to have copula radial symmetry. We generalize to higher dimensions the bivariate test introduced in [11], using three different possibilities for estimating copula derivatives under the null. In a comprehensive simulation study, we assess the finite-sample properties of the resulting tests, comparing them with the finite-sample performance of the multivariate competitors introduced in [17] and [1].

Suggested Citation

  • Billio Monica & Frattarolo Lorenzo & Guégan Dominique, 2021. "Multivariate radial symmetry of copula functions: finite sample comparison in the i.i.d case," Dependence Modeling, De Gruyter, vol. 9(1), pages 43-61, January.
    • Handle: RePEc:vrs:demode:v:9:y:2021:i:1:p:43-61:n:3
    DOI: 10.1515/demo-2021-0102
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    References listed on IDEAS

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