Investigation of alternative methods of option pricing

ABSTRACT This dissertation comprising part of a Master Course in Computational Finance investigates the performance of binomial method and neural networks when they mimic Black-Scholes function in pricing European call option. A binomial option pricing calculator with GUI was written in java and an...

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Main Author: Wang, Mingxiu
Format: Dissertation (University of Nottingham only)
Published: 2006
Online Access:https://eprints.nottingham.ac.uk/21565/
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author Wang, Mingxiu
author_facet Wang, Mingxiu
author_sort Wang, Mingxiu
building Nottingham Research Data Repository
collection Online Access
description ABSTRACT This dissertation comprising part of a Master Course in Computational Finance investigates the performance of binomial method and neural networks when they mimic Black-Scholes function in pricing European call option. A binomial option pricing calculator with GUI was written in java and an artificial data set was created by using Excel based on Black-Scholes formula. The data set was divided into three subsets for the purpose of training, validating and testing artificial neural networks. The experiments of artificial neural networks architecture were carried out by using MATLAB neural network toolbox. I conclude that binomial converges to B-S model as the number of time steps increases. But there is round-off error should be aware of. Also I find that training function Resilient Backpropagation (trainrp) and Levenberg-Marquardt (trainlm) are capable of perform the task of European option pricing. From my experiments, the network using trainrp with eight neurons in the middle layer and the network using trainlm with ten neurons in the middle layer can produce option prices most closet to B-S results.
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format Dissertation (University of Nottingham only)
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institution University of Nottingham Malaysia Campus
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last_indexed 2025-11-14T18:41:43Z
publishDate 2006
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spelling nottingham-215652014-11-18T12:10:27Z https://eprints.nottingham.ac.uk/21565/ Investigation of alternative methods of option pricing Wang, Mingxiu ABSTRACT This dissertation comprising part of a Master Course in Computational Finance investigates the performance of binomial method and neural networks when they mimic Black-Scholes function in pricing European call option. A binomial option pricing calculator with GUI was written in java and an artificial data set was created by using Excel based on Black-Scholes formula. The data set was divided into three subsets for the purpose of training, validating and testing artificial neural networks. The experiments of artificial neural networks architecture were carried out by using MATLAB neural network toolbox. I conclude that binomial converges to B-S model as the number of time steps increases. But there is round-off error should be aware of. Also I find that training function Resilient Backpropagation (trainrp) and Levenberg-Marquardt (trainlm) are capable of perform the task of European option pricing. From my experiments, the network using trainrp with eight neurons in the middle layer and the network using trainlm with ten neurons in the middle layer can produce option prices most closet to B-S results. 2006 Dissertation (University of Nottingham only) NonPeerReviewed Wang, Mingxiu (2006) Investigation of alternative methods of option pricing. [Dissertation (University of Nottingham only)] (Unpublished)
spellingShingle Wang, Mingxiu
Investigation of alternative methods of option pricing
title Investigation of alternative methods of option pricing
title_full Investigation of alternative methods of option pricing
title_fullStr Investigation of alternative methods of option pricing
title_full_unstemmed Investigation of alternative methods of option pricing
title_short Investigation of alternative methods of option pricing
title_sort investigation of alternative methods of option pricing
url https://eprints.nottingham.ac.uk/21565/