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Optimizing distortion risk measures under partial information constraints

发布日期:2025-06-20点击数:

报告人:尹传存 教授(曲阜师范大学)

时间:2025年06月25日 09:00--

地点:数统公司LD402


摘要:This talk considers the best- and worst-case of a general class of distortion risk measures when only partial information regarding the underlying distributions is available. Specifically, explicit sharp lower and upper bounds for a general class of distortion risk measures are derived based on the first two moments along with some shape information, such as symmetry/unimodality property of the underlying distributions. The proposed approach provides a unified framework for extremal problems of distortion risk measures.


邀请人:张志民


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