Applications of artificial neural networks to simulating Lévy processes

Processes with independent increments; Lévy processes (60G51) Artificial neural networks and deep learning (68T07) Derivative securities (option pricing, hedging, etc.) (91G20)

Cites Work

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A Jump-Diffusion Model for Option Pricing
Advantages of the Laplace transform approach in pricing first touch digital options in Lévy-driven models
A Wiener-Hopf Monte Carlo simulation technique for Lévy processes
Fast and accurate pricing of barrier options under Lévy processes
Processes of normal inverse Gaussian type
Hyperbolic distributions in finance
A neural network-based framework for financial model calibration
Multilevel Monte Carlo simulation for Lévy processes based on the Wiener-Hopf factorisation
OPTION PRICING FOR TRUNCATED LÉVY PROCESSES
Feller processes of normal inverse Gaussian type
PRICING OF THE AMERICAN PUT UNDER LÉVY PROCESSES
Financial Modelling with Jump Processes
The Variance Gamma Process and Option Pricing
Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models
Deep learning volatility: a deep neural network perspective on pricing and calibration in (rough) volatility models
Machine Learning in Finance
Approximate Wiener--Hopf Factorization and Monte Carlo Methods for Lévy Processes
Applying the Wiener-Hopf Monte Carlo Simulation Technique for Lévy Processes to Path Functionals
SINH-ACCELERATION: EFFICIENT EVALUATION OF PROBABILITY DISTRIBUTIONS, OPTION PRICING, AND MONTE CARLO SIMULATIONS
Option pricing when underlying stock returns are discontinuous
A Proof that Artificial Neural Networks Overcome the Curse of Dimensionality in the Numerical Approximation of Black–Scholes Partial Differential Equations
Approximation by superpositions of a sigmoidal function

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