英文标题：
《Reduced-form framework under model uncertainty》
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作者：
Francesca Biagini, Yinglin Zhang
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最新提交年份：
2018
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英文摘要：
In this paper we introduce a sublinear conditional expectation with respect to a family of possibly nondominated probability measures on a progressively enlarged filtration. In this way, we extend the classic reduced-form setting for credit and insurance markets to the case under model uncertainty, when we consider a family of priors possibly mutually singular to each other. Furthermore, we study the superhedging approach in continuous time for payment streams under model uncertainty, and establish several equivalent versions of dynamic robust superhedging duality. These results close the gap between robust framework for financial market, which is recently studied in an intensive way, and the one for credit and insurance markets, which is limited in the present literature only to some very specific cases.
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中文摘要：
在本文中，我们在逐步扩大的过滤上引入了一类可能非支配概率测度的次线性条件期望。通过这种方式，我们将信贷和保险市场的经典简化形式设置扩展到模型不确定性情况下，当我们考虑一系列可能相互奇异的先验时。此外，我们研究了模型不确定性下支付流的连续时间超边缘方法，并建立了动态鲁棒超边缘对偶的几个等价版本。这些结果弥补了金融市场稳健框架与信贷和保险市场稳健框架之间的差距，目前的文献仅限于一些非常具体的案例。
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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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