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An Optimization Approach to Weak Approximation of Lévy-Driven Stochastic Differential Equations

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posted on 22.06.2010, 13:36 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.

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Citation

Lecture Notes in Control and Information Sciences, 2010, 398, pp. 263-272.

Published in

Lecture Notes in Control and Information Sciences

Publisher

Springer Verlag

issn

0170-8643

isbn

9783540939177

Available date

22/06/2010

Publisher version

http://link.springer.com/book/10.1007/978-3-540-93918-4

Notes

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

Language

en

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