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An optimization approach to weak approximation of Lévy-driven stochastic differential equations with application to option pricing

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conference contribution
posted on 2012-03-14, 11:34 authored by Kenji Kashima, Reiichiro Kawai
We propose an optimization approach to weak approximation of Lévy-driven stochastic differential equations. We employ a mathematical programming framework to obtain numerically upper and lower bound estimates of the target expectation, where the optimization procedure ends up with a polynomial programming problem. An advantage of our approach is that all we need is a closed form of the Lévy measure, not the exact simulation knowledge of the increments or of a shot noise representation for the time discretization approximation. We also investigate methods for approximation at some different intermediate time points simultaneously.

History

Citation

Proceedings of the 48th IEEE Conference on Decision and Control held jointly with the 2009 28th Chinese Control Conference, 2009, pp. 3673-3678.

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Mathematics

Version

  • AM (Accepted Manuscript)

Published in

Proceedings of the 48th IEEE Conference on Decision and Control held jointly with the 2009 28th Chinese Control Conference

Publisher

IEEE

issn

0191-2216

isbn

978-1-4244-3871-6;978-1-4244-3872-3

Copyright date

2009

Available date

2012-03-14

Publisher version

http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5379695

Notes

Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.

Language

en

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