Pair-copula constructions of multiple dependence

Kjersti Aas, Claudia Czado, Arnoldo Frigessi and Henrik Bakken

Insurance: Mathematics and Economics, 2009, vol. 44, issue 2, pages 182-198

Abstract: Building on the work of Bedford, Cooke and Joe, we show how multivariate data, which exhibit complex patterns of dependence in the tails, can be modelled using a cascade of pair-copulae, acting on two variables at a time. We use the pair-copula decomposition of a general multivariate distribution and propose a method for performing inference. The model construction is hierarchical in nature, the various levels corresponding to the incorporation of more variables in the conditioning sets, using pair-copulae as simple building blocks. Pair-copula decomposed models also represent a very flexible way to construct higher-dimensional copulae. We apply the methodology to a financial data set. Our approach represents the first step towards the development of an unsupervised algorithm that explores the space of possible pair-copula models, that also can be applied to huge data sets automatically.

Keywords: Pair-copulae; Vines; Conditional; distribution; Decomposition; Multivariate; distribution (search for similar items in EconPapers)
Date: 2009

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Persistent link: http://EconPapers.repec.org/RePEc:eee:insuma:v:44:y:2009:i:2:p:182-198

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