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STATISTICAL INFERENCE FOR COPULAS IN HIGH DIMENSIONS: A SIMULATION STUDY

Published online by Cambridge University Press:  18 June 2013

Paul Embrechts  and
Marius Hofert
Paul Embrechts*
Affiliation:
RiskLab, Department of Mathematics, ETH Zurich, 8092 Zurich, Switzerland
Marius Hofert
Affiliation:
RiskLab, Department of Mathematics, ETH Zurich, 8092 Zurich, Switzerland, E-Mail: marius.hofert@math.ethz.ch
*
E-Mail: embrechts@math.ethz.ch
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Abstract

Statistical inference for copulas has been addressed in various research papers. Due to the complicated theoretical results, studies have been carried out mainly in the bivariate case, be it properties of estimators or goodness-of-fit tests. However, from a practical point of view, higher dimensions are of interest. This work presents the results of large-scale simulation studies with particular focus on the question to what extent dimensionality influences point and interval estimators.

Keywords

Maximum likelihood estimatorinference functions for marginsmaximum pseudo-likelihood estimatorKendall's tau estimatorconfidence intervalshigh dimensions
Type
Research Article
Information
ASTIN Bulletin: The Journal of the IAA , Volume 43 , Issue 2 , May 2013 , pp. 81 - 95
Copyright
Copyright © ASTIN Bulletin 2013 

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