Testing for Concordance Ordering

Ana C. Cebrián, Michel Denuit and Olivier Scaillet
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Ana C. Cebrián: Universidad de Zaragoza
Michel Denuit: Université Catholique de Louvain

FAME Research Paper Series from International Center for Financial Asset Management and Engineering

Abstract: We propose inference tools to analyse the ordering of concordance of random vectors. The analysis in the bivariate case relies on tests for upper and lower quadrant dominance of the true distribution by a parametric or semiparametric model, i.e. for a parametric or semiparametric model to give a probability that two variables are simultaneously small or large at least as great as it would be were they left unspecified. Tests for its generalisation in higher dimensions, namely analysed. The parametric and semiparametric setting are based on the copula representation for multivariate distribution, which allows for disentangling behaviour of margins and dependence structure. We propose two types of testing procedures for each setting. The first procedure is based on a formulation of the dominance concepts in terms of values taken by random variables, while the second procedure is based on a formulation in terms of probability levels. For each formulation a distance test and an intersection-union test for inequality constraints are developed depending on the definition of null and alternative hypotheses. An empirical illustration is given for US insurance claim data.

Keywords: Nonparametric; Concordance ordering; Quadrant dominance; Orthant dominance; Copula; Inequality constraint tests; Risk management; Loss severity distribution (search for similar items in EconPapers)
JEL-codes: C12 D81 G10 G21 G22 (search for similar items in EconPapers)
Date: 2002-03
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Citations: View citations in EconPapers (5)

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Related works:
Journal Article: Testing for Concordance Ordering (2004)
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