Neural Networks for Option Pricing and Hedging: A Literature Review

Journal of Computational Finance

32 Pages Posted: 25 Nov 2019 Last revised: 11 May 2020

See all articles by Johannes Ruf

Johannes Ruf

London School of Economics & Political Science (LSE) - London School of Economics

Weiguan Wang

London School of Economics & Political Science (LSE) - Department of Mathematics

Date Written: November 13, 2019

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: Neural network, Option pricing, Option hedging, Survey

JEL Classification: G13, C45

Suggested Citation

Ruf, Johannes and Wang, Weiguan, Neural Networks for Option Pricing and Hedging: A Literature Review (November 13, 2019). Journal of Computational Finance, Available at SSRN: https://ssrn.com/abstract=3486363 or http://dx.doi.org/10.2139/ssrn.3486363

Johannes Ruf

London School of Economics & Political Science (LSE) - London School of Economics ( email )

United Kingdom

Weiguan Wang (Contact Author)

London School of Economics & Political Science (LSE) - Department of Mathematics ( email )

Houghton Street
GB-London WC2A 2AE
United Kingdom

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