Robust optimized certainty equivalents and quantiles for loss positions with distribution uncertainty

Zixin Feng, Weiwei Li and Dejian Tian

Papers from arXiv.org

Abstract: This paper investigates the robust optimized certainty equivalents and analyzes their properties as risk measures under distribution uncertainty. Building on this, robust generalized quantiles are proposed and discussed. We then consider robust expectiles with two specific penalization functions. For the one with a linear penalization function, it is proved to be a coherent risk measure and its dual representation is provided. Furthermore, numerical simulations are conducted to examine the effect of the penalization functions on the robust expectiles and to compare them with classical expectiles.

Date: 2023-04, Revised 2026-09
New Economics Papers: this item is included in nep-rmg
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