英文标题：
《Non-Arbitrage under a Class of Honest Times》
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作者：
Tahir Choulli, Anna Aksamit, Jun Deng and Monique Jeanblanc
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最新提交年份：
2016
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英文摘要：
This paper quantifies the interplay between the non-arbitrage notion of No-Unbounded-Profit-with-Bounded-Risk (NUPBR hereafter) and additional information generated by a random time. This study complements the one of Aksamit/Choulli/Deng/Jeanblanc [1] in which the authors studied similar topics for the case of stopping at the random time instead, while herein we are concerned with the part after the occurrence of the random time. Given that all the literature -up to our knowledge- proves that the NUPBR notion is always violated after honest times that avoid stopping times in a continuous filtration, herein we propose a new class of honest times for which the NUPBR notion can be preserved for some models. For this family of honest times, we elaborate two principal results. The first main result characterizes the pairs of initial market and honest time for which the resulting model preserves the NUPBR property, while the second main result characterizes the honest times that preserve the NUPBR property for any quasi-left continuous model. Furthermore, we construct explicitly \"the-after-tau\" local martingale deflators for a large class of initial models (i.e. models in the small filtration) that are already risk-neutralized.
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中文摘要：
本文量化了无风险无无界利润的无套利概念（下文简称NUPBR）与随机时间产生的附加信息之间的相互作用。这项研究补充了Aksamit/Choulli/Deng/Jeanblanc[1]中的研究，在该研究中，作者研究了在随机时间停止的情况下的类似主题，而在本文中，我们关注的是随机时间发生后的部分。鉴于所有文献（据我们所知）都证明，在避免连续过滤中停止时间的诚实时间之后，NUPBR概念总是被违反，本文提出了一类新的诚实时间，对于某些模型，NUPBR概念可以保留。对于这个诚实时代的家族，我们阐述了两个主要结果。第一个主要结果刻画了初始市场和诚实时间对，由此得到的模型保持NUPBR性质，而第二个主要结果刻画了任何准左连续模型保持NUPBR性质的诚实时间对。此外，我们为一大类已被风险中和的初始模型（即小过滤模型）明确构造了“后tau”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：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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