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

Monica Billio, Frattarolo Lorenzo () and Guégan Dominique ()
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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

Dependence Modeling, 2021, vol. 9, issue 1, 43-61

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].

Keywords: Copula; reflection symmetry; radial symmetry; empirical process (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:vrs:demode:v:9:y:2021:i:1:p:43-61:n:3

DOI: 10.1515/demo-2021-0102

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