Josef Teichmann: Machine Learning in Finance
Time: Fri 2019-01-18 14.15 - 15.15
Location: Seminarierummet F11, KTH, Lindstedtsvägen 22
Participating: Josef Teichmann, ETH Zurich
Abstract: We show three instances of machine learning in finance: deep hedging, deep calibration and deep simulation. The first two applications are direct application of universal approximation theorems, in contrast to deep simulation where Johnson-Lindenstrauss random projection are used to obtain expressive but tractable sets of trajectories.