Data driven partition-of-unity copulas with applications to risk management
Risk Management
2020-11-13 v4
Abstract
We present a constructive and self-contained approach to data driven general partition-of-unity copulas that were recently introduced in the literature. In particular, we consider Bernstein-, negative binomial and Poisson copulas and present a solution to the problem of fitting such copulas to highly asymmetric data.
Cite
@article{arxiv.1703.05047,
title = {Data driven partition-of-unity copulas with applications to risk management},
author = {Dietmar Pfeifer and Andreas Mändle and Olena Ragulina},
journal= {arXiv preprint arXiv:1703.05047},
year = {2020}
}
Comments
this paper has been upgraded with the paper "New copulas based on general partition-of-unity copulas and their application to risk management part II" arXiv article arXiv:1709.07682