5 papers
Numerical approximation of Markovian BSDEs in infinite horizon and elliptic PDEs
Emmanuel Gobet, Adrien Richou, Charu Shardul
We study backward stochastic differential equations (BSDEs) in infinite horizon and design efficient numerical schemes for solving them. We establish a probabilistic representation…
Numerical approximation of ergodic BSDEs using non linear Feynman-Kac formulas
Emmanuel Gobet, Adrien Richou, Lukasz Szpruch
In this work we study the numerical approximation of a class of ergodic Backward Stochastic Differential Equations. These equations are formulated in an infinite horizon framework…
Numerical approximations of McKean Anticipative Backward Stochastic Differential Equations arising in Initial Margin requirements
A. Agarwal, S. De Marco, E. Gobet +3
We introduce a new class of anticipative backward stochastic differential equations with a dependence of McKean type on the law of the solution, that we name MKABSDE. We provide ex…
Stratified regression Monte-Carlo scheme for semilinear PDEs and BSDEs with large scale parallelization on GPUs
E. Gobet, J. G. López-Salas, P. Turkedjiev +1
In this paper, we design a novel algorithm based on Least-Squares Monte Carlo (LSMC) in order to approximate the solution of discrete time Backward Stochastic Differential Equation…
Quasi-Regression Monte-Carlo scheme for semi-linear PDEs and BSDEs with large scale parallelization on GPUs
E. Gobet, J. G. López-Salas, C. Vázquez
In this article we design a novel quasi-regression Monte Carlo algorithm in order to approximate the solution of discrete time backward stochastic differential equations (BSDEs), a…