Error expansion for the discretization of backward stochastic differential equations

Emmanuel Gobet, Céline Labart

Research output: Contribution to journalArticlepeer-review

Abstract

We study the error induced by the time discretization of decoupled forward-backward stochastic differential equations (X, Y, Z). The forward component X is the solution of a Brownian stochastic differential equation and is approximated by a Euler scheme XN with N time steps. The backward component is approximated by a backward scheme. Firstly, we prove that the errors (YN - Y, ZN - Z) measured in the strong Lp-sense (p ≥ 1) are of order N- 1 / 2 (this generalizes the results by Zhang [J. Zhang, A numerical scheme for BSDEs, The Annals of Applied Probability 14 (1) (2004) 459-488]). Secondly, an error expansion is derived: surprisingly, the first term is proportional to XN - X while residual terms are of order N- 1.

Original languageEnglish
Pages (from-to)803-829
Number of pages27
JournalStochastic Processes and their Applications
Volume117
Issue number7
DOIs
Publication statusPublished - 1 Jul 2007
Externally publishedYes

Keywords

  • Backward stochastic differential equation
  • Discretization scheme
  • Malliavin calculus
  • Semi-linear parabolic PDE

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