We study an efficient numerical method for pricing European options when the dynamics of the underlying asset are described by Levy processes. In this case. we can write a characteristic function solution for a specific Levy option model and then take its inversion numerically. Specifically we use Variance Gamma process as an example of Levy option model and consider various characteristic function representation forms of European option price such as Carr and Madan (1999), Bakshi and Madan (2000). and Lewis (2001). Fast Fourier Transform method is applied to solve the numerical inversion problem with parameters for the KOSPI 200 options data. After analysing the problems in the FFT method, we propose alternative numerical inversion method, Gaussian Quadrature. This paper reports that Gaussian Quadrature numerical inversion method with the representation form of Bakshi & Madan (2000) is more efficient and accurate than other alternatives considered in this paper.
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30 November 2007
Research Article|
November 30 2007
An Efficient Numerical Method for Pricing Levy Option Models : With Variance Gamma Process
Woon Wook Jang
Woon Wook Jang
Yonsei University
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Publisher: Emerald Publishing on behalf of Korea Derivatives Association
Online ISSN: 2713-6647
Print ISSN: 1229-988X
© 2007 Emerald Publishing Limited
2007
This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Journal of Derivatives and Quantitative Studies: Seonmul yeon’gu (2007) 15 (2): 1–29.
Citation
Ku BI, Eom YH, Jang WW (2007), "An Efficient Numerical Method for Pricing Levy Option Models : With Variance Gamma Process". Journal of Derivatives and Quantitative Studies: Seonmul yeon’gu, Vol. 15 No. 2 pp. 1–29, doi: https://doi.org/10.1108/JDQS-02-2007-B0001
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