Mathematics – Numerical Analysis
Scientific paper
2009-05-04
Mathematics
Numerical Analysis
Published at http://rspa.royalsocietypublishing.org/content/early/2010/12/08/rspa.2010.0348.full.html in the Proceedings of
Scientific paper
10.1098/rspa.2010.0348
The stochastic Euler scheme is known to converge to the exact solution of a stochastic differential equation with globally Lipschitz continuous drift and diffusion coefficient. Recent results extend this convergence to coefficients which grow at most linearly. For superlinearly growing coefficients finite-time convergence in the strong mean square sense remained an open question according to [Higham, Mao & Stuart (2002); Strong convergence of Euler-type methods for nonlinear stochastic differential equations, SIAM J. Numer. Anal. 40, no. 3, 1041-1063]. In this article we answer this question to the negative and prove for a large class of stochastic differential equations with non-globally Lipschitz continuous coefficients that Euler's approximation converges neither in the strong mean square sense nor in the numerically weak sense to the exact solution at a finite time point. Even worse, the difference of the exact solution and of the numerical approximation at a finite time point diverges to infinity in the strong mean square sense and in the numerically weak sense.
Hutzenthaler Martin
Jentzen Arnulf
Kloeden Peter E.
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