6533b7defe1ef96bd12768a7

RESEARCH PRODUCT

Donsker-Type Theorem for BSDEs: Rate of Convergence

Christel GeissCéline LabartStefan GeissPhilippe Briand

subject

Statistics and Probability[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]Markov processType (model theory)scaled random walk01 natural sciencesconvergence rate010104 statistics & probabilitysymbols.namesakeMathematics::ProbabilityConvergence (routing)FOS: MathematicsOrder (group theory)Applied mathematicsWasserstein distance0101 mathematicsDonsker's theoremstokastiset prosessitMathematicskonvergenssiProbability (math.PR)010102 general mathematicsFinite differenceRandom walk[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Rate of convergencebackward stochastic differential equationssymbolsapproksimointiDonsker’s theoremfinite difference schemedifferentiaaliyhtälötMathematics - Probability

description

In this paper, we study in the Markovian case the rate of convergence in Wasserstein distance when the solution to a BSDE is approximated by a solution to a BSDE driven by a scaled random walk as introduced in Briand, Delyon and Mémin (Electron. Commun. Probab. 6 (2001) Art. ID 1). This is related to the approximation of solutions to semilinear second order parabolic PDEs by solutions to their associated finite difference schemes and the speed of convergence. peerReviewed

yearjournalcountryeditionlanguage
2019-06-26
https://hal.archives-ouvertes.fr/hal-02165750