New copulas based on general partitions-of-unity and their applications to risk management

TL;DR

This paper introduces new multivariate copulas derived from a generalized infinite partition-of-unity method, enabling modeling of tail dependence and asymmetry, with applications in quantitative risk management.

Contribution

It presents a novel class of copulas based on infinite partitions-of-unity, extending finite methods to better capture tail dependence and asymmetry in risk modeling.

Findings

Copulas can model tail dependence and asymmetry.

Method suitable for fitting to real risk data.

Potential applications in quantitative risk management.

Abstract

We construct new multivariate copulas on the basis of a generalized infinite partition-of-unity approach. This approach allows - in contrast to finite partition-of-unity copulas - for tail-dependence as well as for asymmetry. A possibility of fitting such copulas to real data from quantitative risk management is also pointed out.