A fast and accurate FFT-based method for pricing early-exercise options under Lévy processes

Roger Lord, Fang Fang (), Frank Bervoets and Cornelis Oosterlee

MPRA Paper from University Library of Munich, Germany

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 exponentially 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 (search for similar items in EconPapers)
JEL-codes: C63 G13 (search for similar items in EconPapers)
Date: 2007-02-28
New Economics Papers: this item is included in nep-cmp and nep-knm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (50)

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/1952/1/MPRA_paper_1952.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:1952

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().