Parameter estimation of a Levy copula of a discretely observed bivariate compound Poisson process with an application to operational risk modelling

TL;DR

This paper introduces a new method for estimating Levy copula parameters in bivariate compound Poisson processes, enhancing operational risk modeling by enabling better fit and application to real data.

Contribution

It develops a novel estimation technique for Levy copulas without relying on common shocks, and applies it to operational risk data with a goodness of fit test.

Findings

Method performs well in small sample simulations.

Successfully applied to real operational risk data.

Provides a goodness of fit test for Levy copula models.

Abstract

A method is developed to estimate the parameters of a Levy copula of a discretely observed bivariate compound Poisson process without knowledge of common shocks. The method is tested in a small sample simulation study. Also, the method is applied to a real data set and a goodness of fit test is developed. With the methodology of this work, the Levy copula becomes a realistic tool of the advanced measurement approach of operational risk.