Stephan is a PhD candidate in Actuarial Science at Cass Business School.
His research is mainly in methodology for actuarial reserving but the forecasting problems on which he is working can also be found in many other fields.
Hence, his work ranges from non-parametric statistics, survival analysis and computational statistics to reserving in non-life insurance.
At the moment, he is working on different continuous extensions of the chain ladder method involving kernel density and kernel hazard estimators. This involves various tasks from asymptotic theory to data application and simulation studies.
Non-parametric statistics, local linear kernel estimation, smooth backfitting, survival analysis, counting processes, in-sample forecasting, general reserving, chain ladder method, operational time.
- MSc in Mathematics, Heidelberg University, Germany
- BSc in Mathematics, Heidelberg University, Germany
English, French and German.
Title of thesis: Estimating operational time in a survival analysis setting and application in actuarial reserving
Summary of research
The aim of my research is to add operational time, i.e., a certain dependence stucture, to the continuous chain ladder model. There is empirical evidence that such a generalisation of the continuous chain ladder model is appropriate and that independence should not be assumed. The goal is to derive full asymptotics for our new estimators and to compare it with another already existing one. Besides, we are interested in the results on small datasets as they can be found in practice.
Furthermore, I examine and compare the performance of simpler, multiplicative models for small samples sizes in simulations and on a dataset.
- Professor Jens Perch Nielsen, Professor of Actuarial Science
- Dr Munir Hiabu, Research Fellow
- Mammen, E. Heidelberg.