How Rates of $L^p$-Convergence Carry over to Numerical Approximations of Some Convex, Non-Smooth Functionals of SDEs

How Rates of $L^p$-Convergence Carry over to Numerical Approximations of Some Convex, Non-Smooth Functionals of SDEs

Year:    2008

Author:    Henri Schurz

International Journal of Numerical Analysis and Modeling, Vol. 5 (2008), Iss. 1 : pp. 55–72

Abstract

The relation between weak and $p$-th mean convergence of numerical methods for integration of some convex, non-smooth and path-dependent functionals of ordinary stochastic differential equations (SDEs) is discussed. In particular, we answer how rates of $p$-th mean convergence carry over to rates of weak convergence for such functionals of SDEs in general. Assertions of this type are important for the choice of approximation schemes for discounted price functionals in dynamic asset pricing as met in mathematical finance and other commonly met functionals such as passage times in engineering.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/2008-IJNAM-797

International Journal of Numerical Analysis and Modeling, Vol. 5 (2008), Iss. 1 : pp. 55–72

Published online:    2008-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    18

Keywords:    stochastic differential equations approximation of convex and path-dependent functionals numerical methods stability $L^p$-convergence weak convergence rates of convergence non-negativity discounted price functionals asset pricing approximation of stochastic exponentials.

Author Details

Henri Schurz