MCRF
Forward backward SDEs in weak formulation
Haiyang Wang Jianfeng Zhang
Mathematical Control & Related Fields 2018, 8(3&4): 1021-1049 doi: 10.3934/mcrf.2018044

Although having been developed for more than two decades, the theory of forward backward stochastic differential equations is still far from complete. In this paper, we take one step back and investigate the formulation of FBSDEs. Motivated from several considerations, both in theory and in applications, we propose to study FBSDEs in weak formulation, rather than the strong formulation in the standard literature. That is, the backward SDE is driven by the forward component, instead of by the Brownian motion. We establish the Feyman-Kac formula for FBSDEs in weak formulation, both in classical and in viscosity sense. Our new framework is efficient especially when the diffusion part of the forward equation involves the $Z$-component of the backward equation.

keywords: Forward backward SDEs strong formulation weak formulation dynamic programming principle stochastic maximum principle quasilinear PDEs path dependent PDEs weak solution viscosity solution martingale problem

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