TY - JOUR
T1 - Refinements of Kusuoka representations on L ∞
AU - Uğurlu, Kerem
N1 - Funding Information:
The author has been graciously funded by the Social Policy Grant and Competitive Research Grant of Nazarbayev University. The author is grateful for many insightful discussions with Alexander Shapiro during the preparation of this manuscript.
Publisher Copyright:
© 2022 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2022
Y1 - 2022
N2 - We study Kusuoka representations of law-invariant coherent risk measures on the space of bounded random variables, which says that any law-invariant coherent risk measure is the supremum of integrals of Average-Value-at-Risk measures. We refine this representation by showing that the supremum in Kusuoka representation is attained for some probability measure in the unit interval. Namely, we prove that any law-invariant coherent risk measure on the space of bounded random variables can be written as an integral of the Average-Value-at-Risk measures on the unit interval with respect to some probability measure. This representation gives a numerically constructive way to bound any law-invariant coherent risk measure on the space of essentially bounded random variables from above and below. The results are illustrated on specific law-invariant coherent risk measures along with numerical simulations.
AB - We study Kusuoka representations of law-invariant coherent risk measures on the space of bounded random variables, which says that any law-invariant coherent risk measure is the supremum of integrals of Average-Value-at-Risk measures. We refine this representation by showing that the supremum in Kusuoka representation is attained for some probability measure in the unit interval. Namely, we prove that any law-invariant coherent risk measure on the space of bounded random variables can be written as an integral of the Average-Value-at-Risk measures on the unit interval with respect to some probability measure. This representation gives a numerically constructive way to bound any law-invariant coherent risk measure on the space of essentially bounded random variables from above and below. The results are illustrated on specific law-invariant coherent risk measures along with numerical simulations.
KW - average value-at-risk
KW - Coherent risk measures
KW - comonotonic risk measures
KW - law invariance
KW - robust performance measures
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U2 - 10.1080/02331934.2022.2038152
DO - 10.1080/02331934.2022.2038152
M3 - Article
AN - SCOPUS:85124765555
SN - 0233-1934
VL - 71
SP - 3351
EP - 3362
JO - Optimization
JF - Optimization
IS - 11
ER -