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arXiv 2103.07536math.PR
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一般信息流中驱动项依赖于解的鞅部分的非线性 BSDE

Nonlinear BSDEs in general filtration with drivers depending on the martingale part of a solution

Tomasz Klimsiak, Maurycy Rzymowski

AI总结:

本文研究一般信息流中驱动项依赖解的鞅部分、可含未来路径依赖及分布依赖的多维非线性 BSDE,并在单调连续与自然可积条件下证明任意期限全局解的存在唯一性。

摘要:

在本文中,我们考虑多维非线性倒向随机微分方程(BSDE),其驱动项依赖于解的鞅部分 $M$。我们假设非线性项关于状态变量仅是单调连续的。关于驱动项对鞅变量的正则性,我们考虑一个非常一般的条件,该条件允许对过程 $M$ 的“未来”具有路径依赖,也允许依赖于其分布(McKean-Vlasov 型方程)。对于此类驱动项,在数据满足自然可积性条件的情况下,我们证明了 BSDE 全局解(即对任意到期日 $T>0$)的存在性与唯一性。

英文摘要:

In the present paper, we consider multidimensional nonlinear backward stochastic differential equations (BSDEs) with a driver depending on the martingale part $M$ of a solution. We assume that the nonlinear term is merely monotone continuous with respect to the state variable. As to the regularity of the driver with respect to the martingale variable, we consider a very general condition which permits path-dependence on "the future" of the process $M$ as well as a dependence of its law (McKean-Vlasov-type equations). For such driver, we prove the existence and uniqueness of a global solution (i.e. for any maturity $T>0$) to BSDE with data satisfying natural integrability conditions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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