169
Views
4
CrossRef citations to date
0
Altmetric
Section B

Boundary value methods with the Crank–Nicolson preconditioner for pricing options in the jump-diffusion model

, &
Pages 1730-1748 | Received 06 Jan 2010, Accepted 13 Sep 2010, Published online: 14 Mar 2011
 

Abstract

Under a jump-diffusion process, the option pricing function satisfies a partial integro-differential equation. A fourth-order compact scheme is used to discretize the spatial variable of this equation. The boundary value method is then utilized for temporal integration because of its unconditional stability and high-order accuracy. Two approaches, the local mesh refinement and the start-up procedure with refined step size, are raised to avoid the numerical malfunction brought by the nonsmooth payoff function. The GMRES method with a preconditioner which comes from the Crank–Nicolson formula is employed to solve the resulting large-scale linear system. Numerical experiments demonstrate the efficiency of the proposed method when pricing European and double barrier call options in the jump-diffusion model.

2000 AMS Subject Classifications :

Acknowledgements

This work was partially supported by the research grant 033/2009/A from FDCT of Macao and UL020/08-Y3/MAT/JXQ01/FST and RG057/09-10S/SHW/FST from the University of Macau. The authors are also grateful to the anonymous referees for their constructive comments and suggestions which substantially improved the content of this paper.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,129.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.