Risk analysis is one of the most important issues in the financial world, but plays also a prominent role in engineering safety analysis and in the life sciences, in particular, in genetics and ecology. The basis for an adequate risk analysis is formed by appropriate stochastic models. The complexity of the processes involved calls for the use of sophisticated stochastic models beyond Gaussian models, allowing also for discontinuities in order to model abrupt changes.
Combining the expertise of both TUM and international scientists it is aimed to extend and deepen present research and to explore new areas of stochastic modelling and applications. In particular, it is planned to extend the focus of research to engineering, science and the life sciences.