Solving high-dimensional optimal stopping problems using deep learning

Solving high-dimensional optimal stopping problems using deep learning

5 August 2019

Patrick Cheridito

Papers citing "Solving high-dimensional optimal stopping problems using deep learning"

10 / 10 papers shown

Title
Deep Signature Algorithm for Multi-dimensional Path-Dependent Options Erhan Bayraktar Qiaochu Feng Zhao-qin Zhang 33 2 0 21 Nov 2022
Deep neural network expressivity for optimal stopping problems Lukas Gonon 32 6 0 19 Oct 2022
Solving the optimal stopping problem with reinforcement learning: an application in financial option exercise L. Felizardo E. Matsumoto E. Del-Moral-Hernandez 15 2 0 21 Jul 2022
An overview on deep learning-based approximation methods for partial differential equations C. Beck Martin Hutzenthaler Arnulf Jentzen Benno Kuckuck 30 146 0 22 Dec 2020
mlOSP: Towards a Unified Implementation of Regression Monte Carlo Algorithms M. Ludkovski 30 7 0 01 Dec 2020
Space-time deep neural network approximations for high-dimensional partial differential equations F. Hornung Arnulf Jentzen Diyora Salimova AI4CE 29 19 0 03 Jun 2020
Solving high-dimensional Hamilton-Jacobi-Bellman PDEs using neural networks: perspectives from the theory of controlled diffusions and measures on path space Nikolas Nusken Lorenz Richter AI4CE 38 105 0 11 May 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
Deep Neural Network Framework Based on Backward Stochastic Differential Equations for Pricing and Hedging American Options in High Dimensions Yangang Chen J. Wan 19 59 0 25 Sep 2019
Space-time error estimates for deep neural network approximations for differential equations Philipp Grohs F. Hornung Arnulf Jentzen Philipp Zimmermann 34 33 0 11 Aug 2019