Deep Neural Network Framework Based on Backward Stochastic Differential Equations for Pricing and Hedging American Options in High Dimensions

25 September 2019

Papers citing "Deep Neural Network Framework Based on Backward Stochastic Differential Equations for Pricing and Hedging American Options in High Dimensions"

7 / 7 papers shown

Title
Deep Learning vs. Black-Scholes: Option Pricing Performance on Brazilian Petrobras Stocks Joao Felipe Gueiros Hemanth Chandravamsi Steven H. Frankel 28 0 0 25 Apr 2025
A backward differential deep learning-based algorithm for solving high-dimensional nonlinear backward stochastic differential equations Lorenc Kapllani Long Teng 36 2 0 12 Apr 2024
Simultaneous upper and lower bounds of American option prices with hedging via neural networks Ivan Guo Nicolas Langrené Jiahao Wu 30 0 0 24 Feb 2023
Quantum-Inspired Tensor Neural Networks for Option Pricing Raj G. Patel Chia-Wei Hsing Serkan Şahi̇n Samuel Palmer S. Jahromi ... Mustafa Abid Stephane Aubert Pierre Castellani Samuel Mugel Roman Orus 30 3 0 28 Dec 2022
An overview on deep learning-based approximation methods for partial differential equations C. Beck Martin Hutzenthaler Arnulf Jentzen Benno Kuckuck 35 146 0 22 Dec 2020
mlOSP: Towards a Unified Implementation of Regression Monte Carlo Algorithms M. Ludkovski 30 7 0 01 Dec 2020
Uniform error estimates for artificial neural network approximations for heat equations Lukas Gonon Philipp Grohs Arnulf Jentzen David Kofler David Siska 37 34 0 20 Nov 2019