一维扩散过程的时间不一致停止平衡

IF 1.6 3区 经济学 Q3 BUSINESS, FINANCE
Erhan Bayraktar, Zhenhua Wang, Zhou Zhou
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引用次数: 8

摘要

我们考虑了文献中针对时间不一致停止问题提出的三个平衡概念,包括温和平衡(在Huang和Nguyen‐Huu(2018)中引入)、弱平衡(在Christensen和Lindensjö(2018))和强平衡(在Bayraktar等人中引入)。(2021))。折扣函数被假设为对数次加法,其基本过程是一维扩散。我们首先为弱平衡的刻画提供了充分必要的条件。平滑拟合条件是作为副产品获得的。其次,基于弱平衡的特征,我们证明了最优温和平衡也是弱的。然后我们给出了弱平衡是强平衡的条件。我们进一步证明了在一定条件下,最优温和平衡也是强的。最后,我们提供了几个例子,包括一个显示弱平衡的例子可能不是强的,而另一个显示强平衡的例子则可能不是最佳温和的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Equilibria of time-inconsistent stopping for one-dimensional diffusion processes

Equilibria of time-inconsistent stopping for one-dimensional diffusion processes

We consider three equilibrium concepts proposed in the literature for time-inconsistent stopping problems, including mild equilibria (introduced in Huang and Nguyen-Huu (2018)), weak equilibria (introduced in Christensen and Lindensjö (2018)), and strong equilibria (introduced in Bayraktar et al. (2021)). The discount function is assumed to be log subadditive and the underlying process is one-dimensional diffusion. We first provide necessary and sufficient conditions for the characterization of weak equilibria. The smooth-fit condition is obtained as a by-product. Next, based on the characterization of weak equilibria, we show that an optimal mild equilibrium is also weak. Then we provide conditions under which a weak equilibrium is strong. We further show that an optimal mild equilibrium is also strong under a certain condition. Finally, we provide several examples including one showing a weak equilibrium may not be strong, and another one showing a strong equilibrium may not be optimal mild.

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来源期刊
Mathematical Finance
Mathematical Finance 数学-数学跨学科应用
CiteScore
4.10
自引率
6.20%
发文量
27
审稿时长
>12 weeks
期刊介绍: Mathematical Finance seeks to publish original research articles focused on the development and application of novel mathematical and statistical methods for the analysis of financial problems. The journal welcomes contributions on new statistical methods for the analysis of financial problems. Empirical results will be appropriate to the extent that they illustrate a statistical technique, validate a model or provide insight into a financial problem. Papers whose main contribution rests on empirical results derived with standard approaches will not be considered.
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