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2013 | OriginalPaper | Buchkapitel

5. Assessing and Modeling Asymmetry in Bivariate Continuous Data

verfasst von : Christian Genest, Johanna G. Nešlehová

Erschienen in: Copulae in Mathematical and Quantitative Finance

Verlag: Springer Berlin Heidelberg

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Abstract

A bivariate copula is the cumulative distribution function of a pair (U, V ) of uniform random variables. This copula is said to be symmetric if and only if (V, U) and (U, V ) have the same distribution. Many standard bivariate parametric families of copulas have this property; Archimedean and meta-elliptical copulas are prime examples. In practice, however, dependence is often asymmetric. This paper revisits key aspects of this issue from a modeling perspective. Measures of asymmetry and rank-based estimators thereof are discussed, along with recently proposed tests of symmetry. Several techniques for the construction of asymmetric dependence structures are critically reviewed. A hydrological data set is used for illustration purposes.

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Titel: Assessing and Modeling Asymmetry in Bivariate Continuous Data
verfasst von: Christian Genest
Johanna G. Nešlehová
Verlag: Springer Berlin Heidelberg
Buch: Copulae in Mathematical and Quantitative Finance
Print ISBN: 978-3-642-35406-9

Electronic ISBN: 978-3-642-35407-6

Copyright-Jahr: 2013
DOI: https://doi.org/10.1007/978-3-642-35407-6_5