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On Weak Predictor–Corrector Schemes for Jump-Diffusion Processes in Finance

  • Nicola Bruti-Liberati
  • Eckhard PlatenEmail author
Conference paper
Part of the Springer Proceedings in Mathematics & Statistics book series (PROMS, volume 19)

Abstract

Event-driven uncertainties such as corporate defaults, operational failures, or central bank announcements are important elements in the modeling of financial quantities. Therefore, stochastic differential equations (SDEs) of jump-diffusion type are often used in finance. We consider in this paper weak discrete time approximations of jump-diffusion SDEs which are appropriate for problems such as derivative pricing and the evaluation of risk measures. We present regular and jump-adapted predictor–corrector schemes with first and second order of weak convergence. The regular schemes are constructed on regular time discretizations that do not include jump times, while the jump-adapted schemes are based on time discretizations that include all jump times. A numerical analysis of the accuracy of these schemes when applied to the jump-diffusion Merton model is provided.

Keywords

Poisson Process Weak Convergence Implicit Scheme Corrector Scheme Euler Scheme 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  1. 1.School of Finance & EconomicsUniversity of TechnologySydneyAustralia
  2. 2.School of Finance & Economics and Department of Mathematical SciencesUniversity of TechnologySydneyAustralia

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