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arXiv 1003.4431math.PR
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基于集结的准必然随机分析

Quasi-sure Stochastic Analysis through Aggregation

H. Mete Soner, Nizar Touzi, Jianfeng Zhang

摘要:

本文是在一般的概率测度族不受单一概率测度支配的情况下,同时发展随机分析。对这个问题的兴趣源于完全非线性偏微分方程的概率表示及其在金融数学中的应用。现有的文献要么依赖于容量理论(Denis和Martini),要么依赖于潜在的非线性偏微分方程(Peng)。在这两种方法中,所得到的理论都要求相应的过程和随机变量在潜在的规范过程方面是光滑的。在本文中,我们研究这个问题的一个更大的类的“非光滑”的过程,但与一个有限的家庭的非支配概率测度。对于光滑过程,我们的方法导致类似的结果,在以前的文献中,限制家庭满足一个额外的密度属性。

英文摘要:

This paper is on developing stochastic analysis simultaneously under a general family of probability measures that are not dominated by a single probability measure. The interest in this question originates from the probabilistic representations of fully nonlinear partial differential equations and applications to mathematical finance. The existing literature relies either on the capacity theory (by Denis and Martini), or on the underlying nonlinear partial differential equation (by Peng). In both approaches, the resulting theory requires the smoothness of the corresponding processes and random variables in terms of the underlying canonical process. In this paper, we investigate this question for a larger class of "non-smooth" processes, but with a restricted family of non-dominated probability measures. For smooth processes, our approach leads to similar results as in previous literature, provided the restricted family satisfies an additional density property.

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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