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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
Wahid Khosrawi
Josef Teichmann
    GAN
ArXivPDFHTML

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

13 / 13 papers shown
Title
Robust pricing and hedging via neural SDEs
Robust pricing and hedging via neural SDEs
Patryk Gierjatowicz
Marc Sabate Vidales
David Siska
Lukasz Szpruch
Zan Zuric
52
34
0
08 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
56
65
0
21 Jun 2020
Neural networks for option pricing and hedging: a literature review
Neural networks for option pricing and hedging: a literature review
Johannes Ruf
Weiguan Wang
37
125
0
13 Nov 2019
Deep Hedging: Learning to Simulate Equity Option Markets
Deep Hedging: Learning to Simulate Equity Option Markets
Magnus Wiese
Lianjun Bai
Ben Wood
Hans Buehler
GAN
58
67
0
05 Nov 2019
A neural network-based framework for financial model calibration
A neural network-based framework for financial model calibration
Shuaiqiang Liu
Anastasia Borovykh
L. Grzelak
C. Oosterlee
67
103
0
23 Apr 2019
Deep backward schemes for high-dimensional nonlinear PDEs
Deep backward schemes for high-dimensional nonlinear PDEs
Côme Huré
H. Pham
X. Warin
AI4CE
50
98
0
05 Feb 2019
Pricing options and computing implied volatilities using neural networks
Pricing options and computing implied volatilities using neural networks
Shuaiqiang Liu
C. Oosterlee
S. Bohté
40
120
0
25 Jan 2019
A* Tree Search for Portfolio Management
Xiaojie Gao
Shikui Tu
L. Xu
AIFin
29
3
0
07 Jan 2019
Deep calibration of rough stochastic volatility models
Deep calibration of rough stochastic volatility models
Christian Bayer
Benjamin Stemper
28
71
0
08 Oct 2018
Universal features of price formation in financial markets: perspectives
  from Deep Learning
Universal features of price formation in financial markets: perspectives from Deep Learning
Justin A. Sirignano
R. Cont
AIFin
52
255
0
19 Mar 2018
Computation of optimal transport and related hedging problems via
  penalization and neural networks
Computation of optimal transport and related hedging problems via penalization and neural networks
Stephan Eckstein
Michael Kupper
OT
61
49
0
23 Feb 2018
Stochastic Portfolio Theory: A Machine Learning Perspective
Stochastic Portfolio Theory: A Machine Learning Perspective
Yves-Laurent Kom Samo
A. Vervuurt
25
23
0
09 May 2016
Stochastic Compositional Gradient Descent: Algorithms for Minimizing
  Compositions of Expected-Value Functions
Stochastic Compositional Gradient Descent: Algorithms for Minimizing Compositions of Expected-Value Functions
Mengdi Wang
Ethan X. Fang
Han Liu
74
261
0
14 Nov 2014
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