Pricing and hedging American-style options with deep learning

Sebastian Becker, Patrick Cheridito and Arnulf Jentzen

Papers from arXiv.org

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.

Date: 2019-12, Revised 2020-07
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Citations: View citations in EconPapers (23)

Published in Journal of Risk and Financial Management 13, 7 (2020)

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:1912.11060

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