Computing expectiles via fixed point iterations

Expectiles are statistical parameters which also provide a class of sublinear financial risk measures. They are solutions of continuous optimization problems. The corresponding first order condition provides two different fixed point characterizations for expectiles, both of which can be utilized for computing them. Although especially the so-called two-sided version is already implemented and widely used, a general convergence proof appears to be new. Finite termination conditions for sample versions are also given.

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Publication Details

Journal
Statistics & Probability Letters
Published
2026-04-01
DOI
https://doi.org/10.1016/j.spl.2026.110760
Primary Topic
Risk and Portfolio Optimization
Type
article
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article

Computing expectiles via fixed point iterations

Daniel Kostner, Andreas H. Hamel, Ha Thi Khanh Linh
Statistics & Probability Letters
Risk and Portfolio Optimization
article

Computing expectiles via fixed point iterations

Daniel Kostner, Andreas H. Hamel, Ha Thi Khanh Linh
article en

Abstract

Expectiles are statistical parameters which also provide a class of sublinear financial risk measures. They are solutions of continuous optimization problems. The corresponding first order condition provides two different fixed point characterizations for expectiles, both of which can be utilized for computing them. Although especially the so-called two-sided version is already implemented and widely used, a general convergence proof appears to be new. Finite termination conditions for sample versions are also given.

Statistics & Probability Letters
Free University of Bozen-Bolzano (IT), University of Luxembourg (LU)
Decent work and economic growth
Openalex Percentile: Top 27%
Risk and Portfolio Optimization
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