The random walk approximation for Markovian BSDEs converges in Wasserstein distance at rate n^{-(α∧ε/2)}, improving n^{-ε/4} and reaching the CLT-optimal n^{-1/2} for Lipschitz data.
In this section, we state the main result of this paper which g ives the rate of convergence in the Wasserstein distance between the solution to the BSDE (
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Donsker-Type Theorem for BSDEs: Rate of Convergence
The random walk approximation for Markovian BSDEs converges in Wasserstein distance at rate n^{-(α∧ε/2)}, improving n^{-ε/4} and reaching the CLT-optimal n^{-1/2} for Lipschitz data.