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Hilbert transform, spectral filters and option pricing

Phelan, Carolyn E., Marazzina, Daniele, Fusai, Gianluca and Germano, Guido (2018) Hilbert transform, spectral filters and option pricing. Annals of Operations Research. pp. 1-26. ISSN 0254-5330

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Identification Number: 10.1007/s10479-018-2881-4

Abstract

We show how spectral filters can improve the convergence of numerical schemes which use discrete Hilbert transforms based on a sinc function expansion, and thus ultimately on the fast Fourier transform. This is relevant, for example, for the computation of fluctuation identities, which give the distribution of the maximum or the minimum of a random path, or the joint distribution at maturity with the extrema staying below or above barriers. We use as examples the methods by Feng and Linetsky (Math Finance 18(3):337–384, 2008) and Fusai et al. (Eur J Oper Res 251(4):124–134, 2016) to price discretely monitored barrier options where the underlying asset price is modelled by an exponential Lévy process. Both methods show exponential convergence with respect to the number of grid points in most cases, but are limited to polynomial convergence under certain conditions. We relate these rates of convergence to the Gibbs phenomenon for Fourier transforms and achieve improved results with spectral filtering.

Item Type: Article
Official URL: https://link.springer.com/journal/10479
Additional Information: © 2018 Springer Science+Business Media, LLC
Divisions: Systemic Risk Centre
Subjects: Q Science > QA Mathematics
Date Deposited: 05 Jun 2019 15:21
Last Modified: 20 Jun 2020 02:47
URI: http://eprints.lse.ac.uk/id/eprint/100978

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