模型不确定性下的动态风险度量：利用隐概率测度
Dynamic risk measuring under model uncertainty: taking advantage of the hidden probability measure
摘要：
我们在一个非常一般的框架中研究动态风险度量，从而能够对不确定性和跳跃过程进行建模。我们以前表明存在一个典型的等价类的概率测度隐藏在一组给定的概率测度可能非支配。利用这一结果，我们展示了一个双重表示，完全特征的动态风险度量。我们证明了连续性和时间一致性的特点。然后，我们证明了与时间一致的凸动态风险测度相关的所有过程的正则性。我们还研究了次线性风险度量的时间因子分解。最后，我们考虑的例子（不确定波动率和G-期望）。
英文摘要：
We study dynamic risk measures in a very general framework enabling to model uncertainty and processes with jumps. We previously showed the existence of a canonical equivalence class of probability measures hidden behind a given set of probability measures possibly non dominated. Taking advantage of this result, we exhibit a dual representation that completely characterizes the dynamic risk measure. We prove continuity and characterize time consistency. Then, we prove regularity for all processes associated to time consistent convex dynamic risk measures. We also study factorization through time for sublinear risk measures. Finally we consider examples (uncertain volatility and G-expectations).
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