A Radial Basis Function Scheme for Option Pricing in Exponential Lévy Models

Article


Brummelhuis, Raymond and Chan, R. 2013. A Radial Basis Function Scheme for Option Pricing in Exponential Lévy Models. Applied Mathematical Finance. 21 (3), pp. 238-269. https://doi.org/10.1080/1350486X.2013.850902
AuthorsBrummelhuis, Raymond and Chan, R.
Abstract

We use Radial Basis Function (RBF) interpolation to price options in exponential Lévy models by numerically solving the fundamental pricing PIDE (Partial integro-differential equations). Our RBF scheme can handle arbitrary singularities of the Lévy measure in 0 without introducing further approximations, making it simpler to implement than competing methods. In numerical experiments using processes from the CGMY-KoBoL class, the scheme is found to be second order convergent in the number of interpolation points, including for processes of unbounded variation.

JournalApplied Mathematical Finance
Journal citation21 (3), pp. 238-269
ISSN1350-486X
Year2013
PublisherTaylor & Francis
Accepted author manuscript
Digital Object Identifier (DOI)https://doi.org/10.1080/1350486X.2013.850902
Web address (URL)https://doi.org/10.1080/1350486X.2013.850902
Publication dates
Online17 Dec 2013
Publication process dates
Deposited01 Dec 2017
Accepted08 Aug 2013
Accepted08 Aug 2013
Copyright information© 2013 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Applied Mathematical Finance on 17/12/2013, available online: http://www.tandfonline.com/10.1080/1350486X.2013.850902.
Permalink -

https://repository.uel.ac.uk/item/85v90

Download files


Accepted author manuscript
  • 103
    total views
  • 230
    total downloads
  • 0
    views this month
  • 2
    downloads this month

Export as

Related outputs

Pricing European-type, early-exercise and discrete barrier options using an algorithm for the convolution of Legendre series
Chan, R. and Hale, N. 2020. Pricing European-type, early-exercise and discrete barrier options using an algorithm for the convolution of Legendre series. Quantitative Finance. 20 (8), pp. 1307-1324. https://doi.org/10.1080/14697688.2020.1736612
An SFP–FCC method for pricing and hedging early-exercise options under Lévy processes
Chan, R. 2020. An SFP–FCC method for pricing and hedging early-exercise options under Lévy processes. Quantitative Finance. 20 (8), pp. 1325-1343. https://doi.org/10.1080/14697688.2020.1736322
Hedging and pricing early-exercise options with complex fourier series expansion
Chan, R. 2019. Hedging and pricing early-exercise options with complex fourier series expansion. The North American Journal of Economics and Finance. 54 (Art. 100973). https://doi.org/10.1016/j.najef.2019.04.016
Efficient computation of european option prices and their sensitivities with the complex fourier series method
Chan, R. 2019. Efficient computation of european option prices and their sensitivities with the complex fourier series method. The North American Journal of Economics and Finance. 50 (Art. 100984). https://doi.org/10.1016/j.najef.2019.100984
Singular Fourier-Padé Series Expansion of European Option Prices
Chan, R. 2018. Singular Fourier-Padé Series Expansion of European Option Prices. Quantitative Finance. 18 (7), pp. 1149-1171. https://doi.org/10.1080/14697688.2017.1414952
Options pricing under the one-dimensional jump-diffusion model using the radial basis function interpolation scheme
Chan, R. and Hubbert, Simon 2014. Options pricing under the one-dimensional jump-diffusion model using the radial basis function interpolation scheme. Review of Derivatives Research. 17 (2), pp. 161-189. https://doi.org/10.1007/s11147-013-9095-3
Adaptive Radial Basis Function Methods for Pricing Options Under Jump-Diffusion Models
Chan, R. 2016. Adaptive Radial Basis Function Methods for Pricing Options Under Jump-Diffusion Models. Computational Economics. 47 (4), pp. 623-643. https://doi.org/10.1007/s10614-016-9563-6
Option pricing with Legendre polynomials
Hok, Julien and Chan, R. 2017. Option pricing with Legendre polynomials. Journal of Computational and Applied Mathematics. 322, pp. 25-45. https://doi.org/10.1016/j.cam.2017.03.027