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Deep calibration of rough stochastic volatility models

Deep calibration of rough stochastic volatility models

8 October 2018
Christian Bayer
Benjamin Stemper
ArXiv (abs)PDFHTML

Papers citing "Deep calibration of rough stochastic volatility models"

12 / 12 papers shown
A Risk-Neutral Neural Operator for Arbitrage-Free SPX-VIX Term Structures
A Risk-Neutral Neural Operator for Arbitrage-Free SPX-VIX Term Structures
Jianán Zhang
161
0
0
09 Nov 2025
Deep Learning-Enhanced Calibration of the Heston Model: A Unified Framework
Deep Learning-Enhanced Calibration of the Heston Model: A Unified Framework
Arman Zadgar
Somayeh Fallah
Farshid Mehrdoust
Juan E. Trinidad Segovia
88
0
0
28 Oct 2025
Applying Deep Learning to Calibrate Stochastic Volatility Models
Applying Deep Learning to Calibrate Stochastic Volatility ModelsSocial Science Research Network (SSRN), 2023
Abir Sridi
Paul Bilokon
119
3
0
14 Sep 2023
Deep Calibration With Artificial Neural Network: A Performance
  Comparison on Option Pricing Models
Deep Calibration With Artificial Neural Network: A Performance Comparison on Option Pricing ModelsSocial Science Research Network (SSRN), 2023
Y. S. Kim
H. Kim
Jaehyung Choi
168
6
0
15 Mar 2023
Pricing options on flow forwards by neural networks in Hilbert space
Pricing options on flow forwards by neural networks in Hilbert spaceSocial Science Research Network (SSRN), 2022
F. Benth
Nils Detering
Luca Galimberti
278
11
0
17 Feb 2022
Interpretability in deep learning for finance: a case study for the
  Heston model
Interpretability in deep learning for finance: a case study for the Heston modelSocial Science Research Network (SSRN), 2021
D. Brigo
Xiaoshan Huang
A. Pallavicini
Haitz Sáez de Ocáriz Borde
FAtt
209
14
0
19 Apr 2021
Robust pricing and hedging via neural SDEs
Robust pricing and hedging via neural SDEsSocial Science Research Network (SSRN), 2020
Patryk Gierjatowicz
Marc Sabate Vidales
David Siska
Lukasz Szpruch
Zan Zuric
356
41
0
08 Jul 2020
Weak error analysis for stochastic gradient descent optimization
  algorithms
Weak error analysis for stochastic gradient descent optimization algorithms
A. Bercher
Lukas Gonon
Arnulf Jentzen
Diyora Salimova
316
4
0
03 Jul 2020
A Data-driven Market Simulator for Small Data Environments
A Data-driven Market Simulator for Small Data Environments
Hans Bühler
Blanka Horvath
Terry Lyons
Imanol Perez Arribas
Ben Wood
312
74
0
21 Jun 2020
A generative adversarial network approach to calibration of local
  stochastic volatility models
A generative adversarial network approach to calibration of local stochastic volatility modelsRisks (Risks), 2020
Christa Cuchiero
Wahid Khosrawi
Josef Teichmann
GAN
439
77
0
05 May 2020
Neural networks for option pricing and hedging: a literature review
Neural networks for option pricing and hedging: a literature reviewJournal of Computational Finance (JCF), 2019
Johannes Ruf
Weiguan Wang
254
150
0
13 Nov 2019
Unbiased deep solvers for linear parametric PDEs
Unbiased deep solvers for linear parametric PDEs
Marc Sabate Vidales
David Siska
Lukasz Szpruch
OOD
381
10
0
11 Oct 2018
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