Selected Publications
- C. Fontana and T. Schmidt. “General dynamic term structures under default risk”, 2017, Stochastic Processes and their Applications, https://doi.org/10.1016/j.spa.2017.11.003
- Gehmlich, F. and T. Schmidt. “Dynamic defaultable term structure modelling beyond the intensity paradigm”, forthcoming in Mathematical Finance
- E. Eberlein, Z. Grabc and T. Schmidt. “Discrete tenor models for credit risky portfolios driven by time-inhomogeneous Levy processes.”, 2013, SIAM Journal of Financial Mathematics 4 (1), 616-649.
- R. Frey and T. Schmidt. “Pricing and Hedging of Credit Derivatives via the Innovations Approach to Nonlinear Filtering”, 2012. Finance and Stochastics 16, 105-133
- D. Filipovic, L. Overbeck and T. Schmidt. “Dynamic CDO Term Structure Modelling”, 2011. Mathematical Finance 21, 53-71.
- R. Frey, T. Schmidt and L. Xu, “On Galerkin Approximations for the Zakai Equation with Diffusive and Point Process Observations”, 2013, SIAM Journal of Numerical Analysis 51 (4), pp. 2036-2062.
FRIAS Project
Linking Finance and Insurance: Theory and Applications
The goal of this research group is to tackle problems which lie in the intersection of finance and insurance. Under the current market situation this is of particular interest, as the present low interest rate environment is both a big challenge for insurance companies and a key driving factor of stock markets. This shows the high topicality of this endeavor on one side and the enormous potential for future developments on the other side. The main topics we aim at are hybrid derivatives which have equity and interest rates as underlying instruments. This type of derivatives appears naturally in equity-linked insurance products, variable annuities and other financial products from the area of pensions and life-insurance. Our first step is to develop fundamental results on assets of this type, in particular we are looking for valuation and risk-management methodologies. We will also cover the important question of model risk utilizing methods from robust finance and Bayesian finance. The second step is to apply these results by studying specific industry-relevant problems and developing tailor-made solutions.