Variance reduction for numerical solutions of stochastic differential equations
Abstract
We give a variance reduction method evaluating for numerical SDEs. The reduction of variance is explicitly given and can be achieved without extra overhead asymptotically. The method is general in the sense that it works for Non-Markovian continuous SDEs as well as for SDEs driven by Lévy processes. Some numerical examples are also given.
Degree
Ph.D.
Advisors
Protter, Purdue University.
Subject Area
Mathematics
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