英文标题：
《Non-Arbitrage Under Additional Information for Thin Semimartingale
Models》
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作者：
Anna Aksamit, Tahir Choulli, Jun Deng and Monique Jeanblanc
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最新提交年份：
2015
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英文摘要：
This paper completes the two studies undertaken in \\cite{aksamit/choulli/deng/jeanblanc2} and \\cite{aksamit/choulli/deng/jeanblanc3}, where the authors quantify the impact of a random time on the No-Unbounded-Risk-with-Bounded-Profit concept (called NUPBR hereafter) when the stock price processes are quasi-left-continuous (do not jump on predictable stopping times). Herein, we focus on the NUPBR for semimartingales models that live on thin predictable sets only and the progressive enlargement with a random time. For this flow of information, we explain how far the NUPBR property is affected when one stops the model by an arbitrary random time or when one incorporates fully an honest time into the model. This also generalizes \\cite{choulli/deng} to the case when the jump times are not ordered in anyway. Furthermore, for the current context, we show how to construct explicitly local martingale deflator under the bigger filtration from those of the smaller filtration.
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中文摘要：
本文完成了在{aksamit/choulli/deng/jeanblanc2}和{aksamit/choulli/deng/jeanblanc3}进行的两项研究，在这两项研究中，作者量化了当股票价格过程是准左连续的（不跳到可预测的停止时间）时，随机时间对具有有限利润概念的无无界风险（下文称为NUPBR）的影响。在此，我们主要研究仅存在于薄可预测集上的半鞅模型的NUPBR以及随机时间的渐进放大。对于这种信息流，我们解释了当一个人以任意随机时间停止模型时，或者当一个人将完全诚实的时间纳入模型时，NUPBR属性受到的影响有多大。这也将{choulli/deng}推广到了跳转时间不按顺序排列的情况。此外，在当前的背景下，我们展示了如何在较大过滤条件下从较小过滤条件下显式构造局部鞅平减指数。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Mathematical Finance 数学金融学
分类描述：Mathematical and analytical methods of finance, including stochastic, probabilistic and functional analysis, algebraic, geometric and other methods
金融的数学和分析方法，包括随机、概率和泛函分析、代数、几何和其他方法
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