Multivariate Reflection Symmetry of Copula Functions

Monica Billio, Lorenzo Frattarolo () and Dominique Guegan ()
Additional contact information
Lorenzo Frattarolo: University Ca' Foscari of Venice - Department of Economics, https://www.unive.it/
Dominique Guegan: Centre d'Economie de la Sorbonne and LabEx ReFi, https://cv.archives-ouvertes.fr/dominique-guegan

Documents de travail du Centre d'Economie de la Sorbonne from Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne

Abstract: We propose a multivariate nonparametric copula test of reflection symmetry. The test is valid in any number of dimensions, extending previous results that cover the bivariate case. Furthermore, the asymptotic theory for the test relies on recent results on the dependent multiplier bootstrap, valid for sub-exponentially strongly mixing data. Consequently to the introduction of those two features, the procedure is suitable for financial time series whose asymmetric dependence, in distressed periods, has already been documented elsewhere. We conduct an extensive simulation study of empirical size and power and provide several examples of applications. In particular, we investigate the use of the statistic as a financial stress indicator by comparing it with the CISS, the leading ECB indicator

Keywords: Dependence Asymmetry; Copula; Reflection Symmetry; Radial Symmetry; Empirical Process; Dependent Multiplier Bootstrap; Financial Stress (search for similar items in EconPapers)
JEL-codes: C10 C40 C52 D81 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2017-07
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ftp://mse.univ-paris1.fr/pub/mse/CES2017/17033.pdf (application/pdf)

Related works:
Working Paper: Multivariate Reflection Symmetry of Copula Functions (2017)
Working Paper: Multivariate Reflection Symmetry of Copula Functions (2017)
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Persistent link: https://EconPapers.repec.org/RePEc:mse:cesdoc:17033

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