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Nonparametric estimation of the tree structure of a nested Archimedean\n copula

2013/04/04 by Johan Segers, Segers, Johan, Nathan Uyttendaele +1
Computer Science · Economics, Econometrics and Finance · Mathematics · #62G05 #62G09 #62G10 #62G30 #Bayesian Methods and Mixture Models #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Financial Risk and Volatility Modeling #Methodology (stat.ME) #Statistical Methods and Inference

paper · pdf · doi:10.48550/arxiv.1304.1384

openalex publication_date 2013/04/04 · openalex created_date 2022/10/02 · openalex updated_date 2026/07/28

Abstract

One of the features inherent in nested Archimedean copulas, also called\nhierarchical Archimedean copulas, is their rooted tree structure. A\nnonparametric, rank-based method to estimate this structure is presented. The\nidea is to represent the target structure as a set of trivariate structures,\neach of which can be estimated individually with ease. Indeed, for any three\nvariables there are only four possible rooted tree structures and, based on a\nsample, a choice can be made by performing comparisons between the three\nbivariate margins of the empirical distribution of the three variables. The set\nof estimated trivariate structures can then be used to build an estimate of the\ntarget structure. The advantage of this estimation method is that it does not\nrequire any parametric assumptions concerning the generator functions at the\nnodes of the tree.\n

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