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arXiv:1202.4625 [math.PR]AbstractReferencesReviewsResources

Malliavin calculus for backward stochastic differential equations and application to numerical solutions

Yaozhong Hu, David Nualart, Xiaoming Song

Published 2012-02-21Version 1

In this paper we study backward stochastic differential equations with general terminal value and general random generator. In particular, we do not require the terminal value be given by a forward diffusion equation. The randomness of the generator does not need to be from a forward equation, either. Motivated from applications to numerical simulations, first we obtain the $L^p$-H\"{o}lder continuity of the solution. Then we construct several numerical approximation schemes for backward stochastic differential equations and obtain the rate of convergence of the schemes based on the obtained $L^p$-H\"{o}lder continuity results. The main tool is the Malliavin calculus.

Comments: Published in at http://dx.doi.org/10.1214/11-AAP762 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Journal: Annals of Applied Probability 2011, Vol. 21, No. 6, 2379-2423
Categories: math.PR
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