Extreme Value Theory For Vehicle Insurance Data

Abstract

We study the Ethiopian vehicle insurance dataset using the models block maxima and peaks-over-threshold based on extreme value theory for estimating the risk measures, Value-at-Risk and Expected Shortfall. The extreme observations are fitted to the generalized extreme value distribution and the generalized Pareto distribution using maximum likelihood estimation. When estimating the model parameters and risk measures, the difference in estimates between the models is observed.