Law-invariant risk measures: extension properties and qualitative robustness
classification
💱 q-fin.RM
math.STstat.TH
keywords
riskmeasuresinftylaw-invariantrobustnessacceptanceassociatedattention
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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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