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Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/8091

Title: An Optimization Approach to Weak Approximation of Lévy-Driven Stochastic Differential Equations
Authors: Kashima, Kenji
Kawai, Reiichiro
Issue Date: 10-Mar-2010
Publisher: Springer Verlag
Citation: Lecture Notes in Control and Information Sciences, 2010, 398, pp. 263-272.
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.
ISSN: 0170-8643
ISBN: 9783540939177
Links: http://dx.doi.org/10.1007/978-3-540-93918-4
Type: Book chapter
Description: This is the authors' final draft of the paper published as Lecture Notes in Control and Information Sciences, 2010, 398, pp. 263-272. The original publication is available at www.springerlink.com. Doi: 10.1007/978-3-540-93918-4
Appears in Collections:Books & Book Chapters, Dept. of Mathematics

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