Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5096355 | Journal of Econometrics | 2013 | 16 Pages |
Abstract
In this paper we provide a method for estimating multivariate distributions defined through hierarchical Archimedean copulas. In general, the true structure of the hierarchy is unknown, but we develop a computationally efficient technique to determine it from the data. For this purpose we introduce a hierarchical estimation procedure for the parameters and provide an asymptotic analysis. We consider both parametric and nonparametric estimation of the marginal distributions. A simulation study and an empirical application show the effectiveness of the grouping procedure in the sense of structure selection.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
Ostap Okhrin, Yarema Okhrin, Wolfgang Schmid,