模型不确定性下的简化框架
Reduced-form framework under model uncertainty
摘要：
本文在逐步扩大的滤子上引入了关于一族可能非支配概率测度的次线性条件期望。通过这种方式，我们扩展了经典的简化形式设置信贷和保险市场的情况下，模型的不确定性，当我们考虑一个家庭的先验可能相互奇异的。在此基础上，研究了模型不确定性下支付流的连续时间超套期保值方法，建立了动态鲁棒超套期保值对偶的几个等价形式。这些结果缩小了金融市场，这是最近在密集的方式研究，和信贷和保险市场，这是在目前的文献中仅限于一些非常具体的情况下，一个强大的框架之间的差距。
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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