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摘要翻译：
在最优多次停止问题的标准模型中，假定在两次练习之间总是有一个确定长度的时间周期，即所谓的折射周期。这可以防止在一次锻炼的情况下，最优锻炼时间在最优停止时间的基础上聚集在一起。本文通过考虑随机折射次数对标准模型进行了推广。我们发展了该理论，并将问题归结为一系列普通停止问题，从而将结果推广到确定性时间。这需要扩展基本的过滤。此外，我们考虑了马尔可夫情形，并显式地处理了一个例子。
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英文标题：
《Optimal multiple stopping with random waiting times》
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作者：
S\"oren Christensen, Albrecht Irle, Stephan J\"urgens
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最新提交年份：
2012
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分类信息：
一级分类：Quantitative Finance 数量金融学
二级分类：Pricing of Securities 证券定价
分类描述：Valuation and hedging of financial securities, their derivatives, and structured products
金融证券及其衍生产品和结构化产品的估值和套期保值
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一级分类：Mathematics 数学
二级分类：Probability 概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
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英文摘要：
In the standard models for optimal multiple stopping problems it is assumed that between two exercises there is always a time period of deterministic length $\delta$, the so called refraction period. This prevents the optimal exercise times from bunching up together on top of the optimal stopping time for the one-exercise case. In this article we generalize the standard model by considering random refraction times. We develop the theory and reduce the problem to a sequence of ordinary stopping problems thus extending the results for deterministic times. This requires an extension of the underlying filtrations in general. Furthermore we consider the Markovian case and treat an example explicitly.
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PDF链接：
https://arxiv.org/pdf/1205.1966
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