Articles by Bernhard Hientzsch
Pricing barrier options with deep backward stochastic differential equation methods
This paper presents a novel and direct approach to solving boundary- and final-value problems, corresponding to barrier options, using forward pathwise deep learning and forward–backward stochastic differential equations.
Estimating future value-at-risk from value samples, and applications to future initial margin
This paper discusses several methods to estimate fVaR or margin requirements and their expected time evolution, from simple options to more complex interest swaps.
Solving final value problems with deep learning
Pricing vanilla and exotic options with a deep learning approach for PDEs