Abstract
We propose a generic framework for the analysis of Monte Carlo simulation schemes of backward SDEs. The general results are used to re-visit the convergence of the algorithm suggested by Bouchard and Touzi (2004) [6]. By keeping the higher order terms in the expansion of the Skorohod integrals resulting from the Malliavin integration by parts in [6], we introduce a variant of the latter algorithm which allows for a significant reduction of the numerical complexity. We prove the convergence of this improved Malliavin-based algorithm, and derive a bound on the induced error. In particular, we show that the price to pay for our simplification is to use a more accurate localizing function.
Original language | English (US) |
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Pages (from-to) | 1133-1158 |
Number of pages | 26 |
Journal | Stochastic Processes and their Applications |
Volume | 120 |
Issue number | 7 |
DOIs | |
State | Published - Jul 2010 |
Keywords
- BSDEs
- Malliavin calculus
- Monte Carlo methods
- Weak approximations
ASJC Scopus subject areas
- Statistics and Probability
- Modeling and Simulation
- Applied Mathematics