American option pricing using multi-layer perceptron and support vector machine

Michael M. Pires, Tshilidzi Marwala

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

23 Citations (Scopus)

Abstract

An option is the right to buy or sell an underlying asset at a future date. The field of option pricing produces a challenge because of the complexity with pricing American styled options which cannot be done by the Black-Scholes equations for option pricing. A Multi-Layer Perceptron neural network has been used before to price these options with limited success. In this paper we will compare the performance of a Multi-Layer Perceptron neural network and a Support Vector Machine in pricing American styled options. It was found that a Support Vector Machine approach provided much better results than that found with Multi-Layer Perceptrons.

Original languageEnglish
Title of host publication2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
Pages1279-1285
Number of pages7
DOIs
Publication statusPublished - 2004
Externally publishedYes
Event2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004 - The Hague, Netherlands
Duration: 10 Oct 200413 Oct 2004

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2
ISSN (Print)1062-922X

Conference

Conference2004 IEEE International Conference on Systems, Man and Cybernetics, SMC 2004
Country/TerritoryNetherlands
CityThe Hague
Period10/10/0413/10/04

Keywords

  • Kernel function
  • Multi-Layer Perceptron
  • Nodes
  • Option
  • Support Vector Machines

ASJC Scopus subject areas

  • General Engineering

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