Resumen de Quasi-Regression Monte-Carlo Method for Semi-Linear PDEs and BSDEs
Emmanuel Gobet, José Germán López Salas, Carlos Vázquez
In this work we design a novel and efficient quasi-regression Monte Carlo algorithm in order to approximate the solution of discrete time backward stochastic differential equations (BSDEs), and we analyze the convergence of the proposed method. With the challenge of tackling problems in high dimensions we propose suitable projections of the solution and efficient parallelizations ofthe algorithm taking advantage of powerful many core processors such as graphics processing units (GPUs).
