Pricing and hedging American-style options with deep learning
Computational Finance
2021-03-23 v3
Abstract
In this paper we introduce a deep learning method for pricing and hedging American-style options. It first computes a candidate optimal stopping policy. From there it derives a lower bound for the price. Then it calculates an upper bound, a point estimate and confidence intervals. Finally, it constructs an approximate dynamic hedging strategy. We test the approach on different specifications of a Bermudan max-call option. In all cases it produces highly accurate prices and dynamic hedging strategies with small replication errors.
Keywords
Cite
@article{arxiv.1912.11060,
title = {Pricing and hedging American-style options with deep learning},
author = {Sebastian Becker and Patrick Cheridito and Arnulf Jentzen},
journal= {arXiv preprint arXiv:1912.11060},
year = {2021}
}