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A Fast and Accurate FFT-Based Method for Pricing Early-Exercise Options Under Levy Processes

Roger Lord
Cardano, United Kingdom

Fang Fang
Delft University of Technology

Frank Bervoets
Rabobank International, London Branch

Kees Oosterlee
Center for Mathematics and Computer Science (CWI)


February 27, 2007


Abstract:     
A fast and accurate method for pricing early exercise and certain exotic options in computational finance is presented. The method is based on a quadrature technique and relies heavily on Fourier transformations. The main idea is to reformulate the well-known risk-neutral valuation formula by recognising that it is a convolution. The resulting convolution is dealt with numerically by using the Fast Fourier Transform (FFT). This novel pricing method, which we dub the Convolution method, CONV for short, is applicable to a wide variety of payoffs and only requires the knowledge of the characteristic function of the model. As such the method is applicable within exponential Lévy models, including the exponentially affine jump-diffusion models. For an M-times exercisable Bermudan option, the overall complexity is O(MN log(N)) with N grid points used to discretise the price of the underlying asset. It is shown how to price American options efficiently by applying Richardson extrapolation to the prices of Bermudan options.

Keywords: Option pricing , Bermudan options, American options, convolution, Lévy processes, Fast Fourier Transform

JEL Classifications: C63, G13

Working Paper Series

Date posted: February 28, 2007 ; Last revised: March 25, 2007

Suggested Citation

Lord, Roger, Fang, Fang, Bervoets, Frank and Oosterlee, Kees W., A Fast and Accurate FFT-Based Method for Pricing Early-Exercise Options Under Levy Processes (February 27, 2007). Available at SSRN: http://ssrn.com/abstract=966046


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Contact Information

Roger Lord (Contact Author)
Cardano, United Kingdom ( email )
St Clements House
5th Floor
London EC4N 7AE
United Kingdom
HOME PAGE: http://www.cardano.com
Frank Bervoets
Rabobank International, London Branch ( email )
Thames Court
1 Queenhithe
London EC 4V 3RL United Kingdom
Fang Fang
Delft University of Technology ( email )
2628 EB Delft Netherlands
Cornelis W. Oosterlee
Center for Mathematics and Computer Science (CWI) ( email )
P.O. Box 94079
NL-1090 GB Amsterdam Netherlands
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