5 citations · 14 across the 12 of their papers we have counts for
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q-fin.CP2023
Parametric Differential Machine Learning for Pricing and Calibration
Arun Kumar Polala, Bernhard Hientzsch
Differential machine learning (DML) is a recently proposed technique that uses samplewise state derivatives to regularize least square fits to learn conditional expectations of fun…
q-fin.CP2023★ 1 cited
A Comparison of Reinforcement Learning and Deep Trajectory Based Stochastic Control Agents for Stepwise Mean-Variance Hedging
Ali Fathi, Bernhard Hientzsch
We consider two data-driven approaches to hedging, Reinforcement Learning and Deep Trajectory-based Stochastic Optimal Control, under a stepwise mean-variance objective. We compare…