A generative adversarial network approach to calibration of local
stochastic volatility models

A generative adversarial network approach to calibration of local stochastic volatility models

5 May 2020

Christa Cuchiero

Josef Teichmann

Papers citing "A generative adversarial network approach to calibration of local stochastic volatility models"

12 / 12 papers shown

Title
Global universal approximation of functional input maps on weighted spaces Christa Cuchiero Philipp Schmocker Josef Teichmann 34 21 0 05 Jun 2023
Instance-Dependent Generalization Bounds via Optimal Transport Songyan Hou Parnian Kassraie Anastasis Kratsios Andreas Krause Jonas Rothfuss 29 6 0 02 Nov 2022
Deep neural network expressivity for optimal stopping problems Lukas Gonon 32 6 0 19 Oct 2022
Chaotic Hedging with Iterated Integrals and Neural Networks Ariel Neufeld Philipp Schmocker 39 10 0 21 Sep 2022
Risk-Neutral Market Simulation Magnus Wiese M. Phillip 33 2 0 28 Feb 2022
Designing Universal Causal Deep Learning Models: The Geometric (Hyper)Transformer Beatrice Acciaio Anastasis Kratsios G. Pammer OOD 54 20 0 31 Jan 2022
Multi-Asset Spot and Option Market Simulation Magnus Wiese Ben Wood Alexandre Pachoud R. Korn Hans Buehler Phillip Murray Lianjun Bai 32 21 0 13 Dec 2021
Sig-Wasserstein GANs for Time Series Generation Hao Ni Lukasz Szpruch Marc Sabate Vidales Baoren Xiao Magnus Wiese Shujian Liao SyDa AI4TS 24 73 0 01 Nov 2021
Random feature neural networks learn Black-Scholes type PDEs without curse of dimensionality Lukas Gonon 28 35 0 14 Jun 2021
Robust pricing and hedging via neural SDEs Patryk Gierjatowicz Marc Sabate Vidales David Siska Lukasz Szpruch Zan Zuric 27 34 0 08 Jul 2020
Consistent Recalibration Models and Deep Calibration Matteo Gambara Josef Teichmann 33 5 0 16 Jun 2020
Neural Controlled Differential Equations for Irregular Time Series Patrick Kidger James Morrill James Foster Terry Lyons AI4TS 32 451 0 18 May 2020