Neural networks for option pricing and hedging: a literature review
Computational Finance
2020-05-12 v2 Machine Learning
Risk Management
Statistical Finance
Machine Learning
Abstract
Neural networks have been used as a nonparametric method for option pricing and hedging since the early 1990s. Far over a hundred papers have been published on this topic. This note intends to provide a comprehensive review. Papers are compared in terms of input features, output variables, benchmark models, performance measures, data partition methods, and underlying assets. Furthermore, related work and regularisation techniques are discussed.
Keywords
Cite
@article{arxiv.1911.05620,
title = {Neural networks for option pricing and hedging: a literature review},
author = {Johannes Ruf and Weiguan Wang},
journal= {arXiv preprint arXiv:1911.05620},
year = {2020}
}
Comments
Minor changes. Accepted for publications in Journal of Computational Finance