Financial Data Analysis; Mathematical Finance; Stochastic Processes; Numerical Analysis
Dr. Linus Wunderlich (Postdoctoral Researcher)
Christian Pötz (PhD student)
Domagoj Demeterfi (PhD student)
Financial data and low-rank tensor techniques: Boosting data-driven machine learning algorithms, creation of synthetic datasets, storing and processing large financial datasets, approximation of high-dimensional nonlinear data, modelling.
Function approximation methods: Fourier transform, Partial (integral) differential equations, reduced basis, interpolation, sparse grids, low-rank tensor approximation, deep neural networks, Monte Carlo, kernel learning,...
Modelling with stochastic processes: modelling with semimartingales, particularly Lévy processes
Applications in Finance: pricing, hedging, calibration, credit exposure calculation,