no code implementations • 30 Oct 2023 • Blanka Hovart, Anastasis Kratsios, Yannick Limmer, Xuwei Yang
Deep Kalman filters (DKFs) are a class of neural network models that generate Gaussian probability measures from sequential data.
no code implementations • 5 Jul 2023 • Yannick Limmer, Blanka Horvath
This is achieved through an interplay of three modular components: (i) a (deep) hedging engine, (ii) a data-generating process (that is model agnostic permitting a large variety of classical models as well as machine learning-based market generators), and (iii) a notion of distance on model space to measure deviations between our market prognosis and reality.
no code implementations • 26 Oct 2021 • Yannick Limmer, Thilo Meyer-Brandis
Eventually, we suggest an approach to verify absence of Lp-free lunch on markets with multiple brokers endowed with deviating trading speeds.
