401-3932-19L  Machine Learning in Finance

SemesterSpring Semester 2019
LecturersJ. Teichmann
Periodicityyearly recurring course
Language of instructionEnglish


AbstractThe course will deal with the following topics with rigorous proofs and many coding excursions: Universal approximation theorems, Stochastic gradient Descent, Deep
networks and wavelet analysis, Deep Hedging, Deep calibration,
Different network architectures, Reservoir Computing, Time series analysis by machine learning, Reinforcement learning, generative adversersial networks, Economic games.
Objective
Prerequisites / NoticeBachelor in mathematics, physics, economics or computer science.