DocumentCode :
427843
Title :
American option pricing using multi-layer perceptron and support vector machine
Author :
Pires, Michael M. ; Marwala, Tshilidzi
Author_Institution :
Sch. of Electr. & Information Eng., Univ. of the Witwatersrand, Johannesburg, South Africa
Volume :
2
fYear :
2004
fDate :
10-13 Oct. 2004
Firstpage :
1279
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.
Keywords :
multilayer perceptrons; pricing; stock markets; support vector machines; American option pricing; Black-Scholes equations; multilayer perceptron neural network; support vector machine; underlying asset; Africa; Contracts; Equations; Multi-layer neural network; Multilayer perceptrons; Neural networks; Pricing; Random processes; Supervised learning; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2004 IEEE International Conference on
ISSN :
1062-922X
Print_ISBN :
0-7803-8566-7
Type :
conf
DOI :
10.1109/ICSMC.2004.1399801
Filename :
1399801
Link To Document :
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