Machine learning for option pricing: an empirical investigation of network architectures

14 July 2023

Papers citing "Machine learning for option pricing: an empirical investigation of network architectures"

7 / 7 papers shown

Title
A deep learning approach to data-driven model-free pricing and to martingale optimal transport Ariel Neufeld J. Sester 72 11 0 21 Mar 2021
A generative adversarial network approach to calibration of local stochastic volatility models Christa Cuchiero Wahid Khosrawi Josef Teichmann GAN 152 69 0 05 May 2020
Neural networks for option pricing and hedging: a literature review Johannes Ruf Weiguan Wang 62 129 0 13 Nov 2019
Pricing options and computing implied volatilities using neural networks Shuaiqiang Liu C. Oosterlee S. Bohté 52 123 0 25 Jan 2019
Deep neural networks algorithms for stochastic control problems on finite horizon: numerical applications Achref Bachouch Côme Huré N. Langrené H. Pham 89 88 0 13 Dec 2018
Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) Network A. Sherstinsky 95 3,729 0 09 Aug 2018
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 338 18,651 0 06 Feb 2015