Time discretization of Quadratic Forward-Backward SDEs with singular drifts
Rhoss Likibi Pellat, Emmanuel Che Fonka, Olivier Menoukeu Pamen

TL;DR
This paper studies the convergence rate of time discretization schemes for quadratic backward SDEs with singular drifts, revealing how noise regularization improves numerical approximation accuracy.
Contribution
It introduces a novel analysis connecting noise regularization effects to enhanced convergence rates in discretizing singular forward-backward SDEs.
Findings
Achieves an error rate close to 1/2 for explicit schemes.
Extends Zhang's L^2-time regularity to singular SDEs.
Demonstrates noise regularization improves numerical convergence.
Abstract
We investigate the convergence rate for the time discretization of a class of quadratic backward SDEs -- potentially involving path-dependent terminal values -- when coupled with non-standard Lipschitz-type forward SDEs. In our review of the explicit time-discretization schemes in the spirit of Pag\`es \& Sagna (see \cite{PaSa18}), we achieve an error control close to , even under the modest assumptions considered in this work (see \cite{ChaRichou16}, for comparison). A central element of our approach is a thorough re-examination of Zhang's of the martingale integrand which follows from an extension of the first-order variational regularity for this class of singular forward-backward SDEs with non-uniform Cauchy-Lipschitz drivers. This is complemented by the recently introduced caracterisation of stochastic processes of {\it bounded mean…
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Taxonomy
TopicsStochastic processes and financial applications
