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2005.02505
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A generative adversarial network approach to calibration of local stochastic volatility models
5 May 2020
Christa Cuchiero
Wahid Khosrawi
Josef Teichmann
GAN
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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
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
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
Johannes Ruf
Weiguan Wang
37
125
0
13 Nov 2019
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
Shuaiqiang Liu
Anastasia Borovykh
L. Grzelak
C. Oosterlee
67
103
0
23 Apr 2019
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
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
Christian Bayer
Benjamin Stemper
28
71
0
08 Oct 2018
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
Stephan Eckstein
Michael Kupper
OT
61
49
0
23 Feb 2018
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
Mengdi Wang
Ethan X. Fang
Han Liu
74
261
0
14 Nov 2014
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