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Title: An optimization approach to weak approximation of Lévy-driven stochastic differential equations with application to option pricing
Authors: Kashima, Kenji
Kawai, Reiichiro
First Published: 2009
Publisher: IEEE
Citation: Proceedings of the 48th IEEE Conference on Decision and Control held jointly with the 2009 28th Chinese Control Conference, 2009, pp. 3673-3678.
Abstract: 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.
DOI Link: 10.1109/CDC.2009.5400355
ISSN: 0191-2216
ISBN: 978-1-4244-3871-6
Version: Post-print
Status: Peer-reviewed
Type: Conference Paper
Rights: © 2009 IEEE. Deposited with reference to the publisher's archiving policy available on SHERPA/RoMEO.
Description: 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.
Appears in Collections:Conference Papers & Presentations, Dept. of Mathematics

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