律不变风险测度：可拓性质和定性鲁棒性
Law-invariant risk measures: extension properties and qualitative robustness
摘要：
我们刻画了当一个凸风险测度与$L^\infty$中的一个律不变的接受集相关联时，它可以扩展到$L^p$，$1\leq p<\infty$，保持有限性和连续性。这个问题与相应风险度量的统计稳健性密切相关。特别注意的是具体的例子，包括基于期望效用的风险措施，最大相关风险措施，失真风险措施。
英文摘要：
We characterize when a convex risk measure associated to a law-invariant acceptance set in $L^\infty$ can be extended to $L^p$, $1\leq p<\infty$, preserving finiteness and continuity. This problem is strongly connected to the statistical robustness of the corresponding risk measures. Special attention is paid to concrete examples including risk measures based on expected utility, max-correlation risk measures, and distortion risk measures.
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