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arXiv 0705.3788math.PR
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倒向随机微分方程的测度解

On measure solutions of backward stochastic differential equations

Stefan Ankirchner, Peter Imkeller, Alexandre Popier

摘要:

本文研究了具有非线性生成元的倒向随机微分方程,生成元的控制变量具有二次增长。这样一个Besides的测度解可以理解为一个概率测度,在这个测度下,生成元被看作为零,因此经典解可以通过条件运算和鞅表示的组合来重建。在终端条件是有界的情况下,生成元满足通常的连续性和有界性条件,我们证明了具有等价测度的测度解只是重新解释了经典解。在终端条件只有指数有界矩的情况下,我们讨论了一系列的例子,表明在非唯一性的情况下,非测度解的经典解可以与不同的测度解共存.

英文摘要:

We consider backward stochastic differential equations (BSDE) with nonlinear generators typically of quadratic growth in the control variable. A measure solution of such a BSDE will be understood as a probability measure under which the generator is seen as vanishing, so that the classical solution can be reconstructed by a combination of the operations of conditioning and using martingale representations. In case the terminal condition is bounded and the generator fulfills the usual continuity and boundedness conditions, we show that measure solutions with equivalent measures just reinterpret classical ones. In case of terminal conditions that have only exponentially bounded moments, we discuss a series of examples which show that in case of non-uniqueness classical solutions that fail to be measure solutions can coexists with different measure solutions.

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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