Approximation of the Ultimate Ruin Probability in the Classical Risk Model Using Erlang Mixtures

Abstract

In this paper, we approximate the ultimate ruin probability in the Cramer-Lundberg risk model when claim sizes have an arbitrary continuous distribution. We propose two approximation methods, based on Erlang Mixtures, which can be used for claim sizes distribution both light and heavy tailed. Additionally, using a continuous version of the empirical distribution, we develop a third approximation which can be used when the claim sizes distribution is unknown and paves the way for a statistical application. Numerical examples for the gamma, Weibull and truncated Pareto distributions are provided.