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We propose a new methodology for pricing options on flow forwards by applying infinite-dimensional neural networks.
Approximation by superpositions of a sigmoidal function
G. Cybenko · 1989
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Brownian Motion and Stochastic Calculus
I. Karatzas and S. E. Shreve · 1991
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Dynamic Asset Pricing Theory
D. Duffie · 1992
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Arbitrage Theory in Continuous Time
T. Björk · 1998
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Energy Derivatives – Pricing and Risk Management
L. Clewlow and C. Strickland · 2000
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Consistency Problems for Heath-Jarrow-Morton Interest Rate Models
D. Filipović · 2001
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Commodities and Commodity Derivatives
H. Geman · 2005
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Stochastic Partial Differential Equations with Lévy Noise
D. Peszat and J. Zabczyk · 2007
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Stochastic modeling of financial electricity contracts
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Stochastic Modelling of Electricity and Related Markets
F. E. Benth, J. Šaltytė Benth, and S. Koekebakker · 2008
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Jump-diffusions in Hilbert spaces: existence, stability and numerics
D. Filipović, S. Tappe, and J. Teichmann · 2010
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Some refinements of existence results for SPDEs driven by Wiener processes and Poisson random measures
S. Tappe · 2012
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Approximating Lévy semistationary processes via Fourier methods in the context of power markets
F. E. Benth, H. Eyjolfsson, and A. Veraart · 2014
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Representation of infinite dimensional forward price models in commodity markets
F. E. Benth and P. Krühner · 2014
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Representation of infinite dimensional forward price models in commodity markets
F. E. Benth and P. Krühner · 2015
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Deep calibration of rough stochastic volatility models, 2018
Neural networks for option pricing and hedging: a literature review
J. Ruf and W. Wang · 2020
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Solving the Kolmogorov PDE by means of deep learning
C. Beck, S. Becker, P. Grohs, N. Jaafari, and A. Jentzen · 2021
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An overview on deep learning-based approximation methods for partial differential equations, 2021
C. Beck, M. Hutzenthaler, A. Jentzen, and B. Kuckuck · 2021
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Neural networks in Fréchet spaces, 2021
F. E. Benth, N. Detering, and L. Galimberti · 2021
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Accuracy of deep learning in calibrating HJM forward curves
F. E. Benth, N. Detering, and S. Lavagnini · 2021
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Deep ReLU network expression rates for option prices in high-dimensional, exponential Lévy models
L. Gonon and C. Schwab · 2021
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On deep calibration of (rough) stochastic volatility models, 2019
C. Bayer, B. Horvath, A. Muguruza, B. Stemper, and M. Tomas · 2019
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A proof that rectified deep neural networks overcome the curse of dimensionality in the numerical approximation of semilinear heat equations
M. Hutzenthaler, A. Jentzen, T. Kruse, and T. A. Nguyen · 2020
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Dynamic term structure models for SOFR futures
J. B. Skov and D. Skovmand · 2021
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Stochastic Volterra integral equations and a class of first order stochastic partial differential equations
F. E. Benth, N. Detering, and P. Krühner · 2022
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The Stochastics of Prices in Commodity and Energy Markets – an Infinite Dimensional View
F. E. Benth and P. Krühner · 2022
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