Inaugural lecture by David Banos

Abstract: In this talk we aim at modeling stochastic transition rates of state processes in life insurance by using generalized Cox processes. A feature of our non-Gaussian model is that it can be used to capture "regime switching" effects of data which may be due to regulatory changes in insurance markets or external "shocks" caused e.g. by an economical crisis, natural disasters or epidemics. We propose a method how to estimate the unknown parameters of our model for stochastic transition rates from insurance data by using non-linear filtering techniques for Lévy processes. As a result we also obtain an explicit formula for the unnormalized density of a filtering problem with singular coefficients. An implementation of the model will be offered. This talk is based on a collaboration with Prof. Erik Bølviken and Prof. Frank Proske.