121 citations · 377 across the 72 of their papers we have counts for
12 papers · 1 filter
Discrete-time signatures and randomness in reservoir computing
Christa Cuchiero, Lukas Gonon, Lyudmila Grigoryeva +2
A new explanation of geometric nature of the reservoir computing phenomenon is presented. Reservoir computing is understood in the literature as the possibility of approximating in…
Deep Replication of a Runoff Portfolio
Thomas Krabichler, Josef Teichmann
To the best of our knowledge, the application of deep learning in the field of quantitative risk management is still a relatively recent phenomenon. This article presents the key n…
Deep Investing in Kyle's Single Period Model
Paul Friedrich, Josef Teichmann
The Kyle model describes how an equilibrium of order sizes and security prices naturally arises between a trader with insider information and the price providing market maker as th…
Stopper-Controller Games embedded in Single-Player Control Problems
Martin Larsson, Marvin S. Mueller, Josef Teichmann
In 2002, Benjamin Jourdain and Claude Martini discovered that for a class of payoff functions, the pricing problem for American options can be reduced to pricing of European option…
Consistent Recalibration Models and Deep Calibration
Matteo Gambara, Josef Teichmann
Consistent Recalibration models (CRC) have been introduced to capture in necessary generality the dynamic features of term structures of derivatives' prices. Several approaches hav…
Neural Jump Ordinary Differential Equations: Consistent Continuous-Time Prediction and Filtering
Calypso Herrera, Florian Krach, Josef Teichmann
Combinations of neural ODEs with recurrent neural networks (RNN), like GRU-ODE-Bayes or ODE-RNN are well suited to model irregularly observed time series. While those models outper…