Discrete-Time Approximation and Monte-Carlo Simulation of Backward Stochastic Differential Equations
Touzi, Nizar; Bouchard, Bruno (2004), Discrete-Time Approximation and Monte-Carlo Simulation of Backward Stochastic Differential Equations, Stochastic Processes and their Applications, 111, 2, p. 175-206. http://dx.doi.org/10.1016/j.spa.2004.01.001
Type
Article accepté pour publication ou publiéDate
2004Journal name
Stochastic Processes and their ApplicationsVolume
111Number
2Publisher
Elsevier
Pages
175-206
Publication identifier
Metadata
Show full item recordAbstract (EN)
We suggest a discrete-time approximation for decoupled forward–backward stochastic differential equations. The Lp norm of the error is shown to be of the order of the time step. Given a simulation-based estimator of the conditional expectation operator, we then suggest a backward simulation scheme, and we study the induced Lp error. This estimate is more investigated in the context of the Malliavin approach for the approximation of conditional expectations. Extensions to the reflected case are also considered. Author Keywords: Monte-Carlo methods for (reflected) forward–backward SDEs; Malliavin calculus; Regression estimationSubjects / Keywords
Méthode de Monte-Carlo; Numerical ProbabilityRelated items
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