From rank-based models with common noise to pathwise entropy solutions of SPDEs

Mykhaylo Shkolnikov, Lane Chun Yeung
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Abstract

We study the mean field limit of a rank-based model with common noise, which arises as an extension to models for the market capitalization of firms in stochastic portfolio theory. We show that, under certain conditions on the drift and diffusion coefficients, the empirical cumulative distribution function converges to the solution of a stochastic PDE. A key step in the proof, which is of independent interest, is to show that any solution to an associated martingale problem is also a pathwise entropy solution to the stochastic PDE, a notion introduced in a recent series of papers [32, 33, 19, 16, 17].
从具有共同噪声的基于秩的模型到 SPDE 的路径熵解
我们研究了具有共同噪声的基于秩的模型的均值场极限,该模型是对随机投资组合理论中企业市值模型的扩展。我们证明,在漂移系数和扩散系数的某些条件下,经验累积分布函数收敛于随机 PDE 的解。证明的一个关键步骤是证明相关马氏问题的任何解也是随机 PDE 的路径熵解,这是最近一系列论文[32, 33, 19,16,17]中提出的概念。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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