Neural Networks for Option Pricing and Hedging : A Literature Review

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

MoreLess

Year of publication:	2020
Authors:	Ruf, Johannes
Other Persons:	Wang, Weiguan (contributor)
Publisher:	[2020]: [S.l.] : SSRN
Subject:	Hedging \| Neuronale Netze \| Neural networks \| Optionspreistheorie \| Option pricing theory \| Derivat \| Derivative \| Bibliometrie \| Bibliometrics

freely available

Full text |

More access options

doi.org

Check Google Scholar

In German libraries (KVK)

I need help

Extent:	1 Online-Ressource (32 p)
Type of publication:	Book / Working Paper
Language:	English
Notes:	In: Journal of Computational Finance Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments November 13, 2019 erstellt
Other identifiers:	10.2139/ssrn.3486363 [DOI]
Classification:	G13 - Contingent Pricing; Futures Pricing ; C45 - Neural Networks and Related Topics
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012846802