Weak and strong approximations of reflected diffusions via penalization methods

We study approximations of reflected Itô diffusions on convex subsets D of Rd by solutions of stochastic differential equations with penalization terms. We assume that the diffusion coefficients are merely measurable functions. In the case of Lipschitz continuous coefficients we give the rate of Lp approximation for every p≥1. We prove that if D is a convex polyhedron then the rate is O((lnnn)1/2), and in the general case the rate is O((lnnn)1/4).

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Year of publication:	2013
Authors:	Słomiński, Leszek
Published in:	Stochastic Processes and their Applications. - Elsevier, ISSN 0304-4149. - Vol. 123.2013, 3, p. 752-763
Publisher:	Elsevier
Subject:	Reflected diffusions \| Penalization methods

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011065008