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An optimization approach to weak approximation of Lévy-driven stochastic differential equations with application to option pricing
conference contributionposted 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.
CitationProceedings 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
- AM (Accepted Manuscript)