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

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posted on 2010-06-22, 13:36 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

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

2010-06-22

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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