Generalized Information Matrix Tests for Copulas

Artem Prokhorov, Ulf Schepsmeier and Yajing Zhu

No 2015-05, Working Papers from University of Sydney Business School, Discipline of Business Analytics

Abstract: We propose a family of goodness-of-fit tests for copulas. The tests use generalizations of the information matrix (IM) equality of White (1982) and so relate to the copula test proposed by Huang and Prokhorov (2014). The idea is that eigenspectrum-based statements of the IM equality reduce the degrees of freedom of the test's asymptotic distribution and lead to better size-power properties, even in high dimensions. The gains are especially pronounced for vine copulas, where additional benefits come from simplifications of score functions and the Hessian. We derive the asymptotic distribution of the generalized tests, accounting for the non-parametric estimation of the marginals and apply a parametric bootstrap procedure, valid when asymptotic critical values are inaccurate. In Monte Carlo simulations, we study the behavior of the new tests, compare them with several Cramer-von Mises type tests and confirm the desired properties of the new tests in high dimensions.

Keywords: R-vines; goodness-of- fit; vine copulas; copula; information matrix eq uality (search for similar items in EconPapers)
Date: 2015-09-11
New Economics Papers: this item is included in nep-ecm
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/2123/13798

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:syb:wpbsba:2123/13798

Access Statistics for this paper

More papers in Working Papers from University of Sydney Business School, Discipline of Business Analytics Contact information at EDIRC.
Bibliographic data for series maintained by Artem Prokhorov ().