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arXiv 0901.2790math.PR
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正倒向随机微分方程的弱解--一个鞅问题方法

Weak solutions for forward--backward SDEs--a martingale problem approach

Jin Ma, Jianfeng Zhang, Ziyu Zheng

摘要:

本文提出了正倒向鞅问题(FBMP)的新概念,并研究了它与正倒向随机微分方程(FBSDEs)弱解的关系. FBMP扩展了Stroock和Varadhan的著名(前向)鞅问题的思想,但它的结构特别适合FBMP的性质。我们首先证明了FBMP解存在的一般充分条件。在系数一致连续的马尔可夫情形下,我们证明了FBMP的弱解(或等价地,FBMP的解)确实存在。证明了FBMP的唯一性(从而弱解的唯一性)是由相应拟线性偏微分方程的黏性解的唯一性决定的.

英文摘要:

In this paper, we propose a new notion of Forward--Backward Martingale Problem (FBMP), and study its relationship with the weak solution to the forward--backward stochastic differential equations (FBSDEs). The FBMP extends the idea of the well-known (forward) martingale problem of Stroock and Varadhan, but it is structured specifically to fit the nature of an FBSDE. We first prove a general sufficient condition for the existence of the solution to the FBMP. In the Markovian case with uniformly continuous coefficients, we show that the weak solution to the FBSDE (or equivalently, the solution to the FBMP) does exist. Moreover, we prove that the uniqueness of the FBMP (whence the uniqueness of the weak solution) is determined by the uniqueness of the viscosity solution of the corresponding quasilinear PDE.

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