Norms Based on Generalized Expected-Shortfalls and Applications

Fuente: arXiv
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Main Authors: Gong, Shuyu, Hu, Taizhong, Zou, Zhenfeng
Format: Preprint
Published: 2025
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author Gong, Shuyu
Hu, Taizhong
Zou, Zhenfeng
author_facet Gong, Shuyu
Hu, Taizhong
Zou, Zhenfeng
contents This paper proposes a novel class of generalized Expected-Shortfall (ES) norms constructed via distortion risk measures, establishing a unified analytical framework for risk quantification. The proposed norms extend conventional ES methodology by incorporating flexible distortion functions. Specifically, we develop the mathematical duality theory for generalized-ES norms to support portfolio optimization tasks, while demonstrating their practical utility through projection problem solutions. The generalizedES norms are also applied to detect anomalies of financial time series data.
format Preprint
id arxiv_https___arxiv_org_abs_2507_09444
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Norms Based on Generalized Expected-Shortfalls and Applications
Gong, Shuyu
Hu, Taizhong
Zou, Zhenfeng
Risk Management
This paper proposes a novel class of generalized Expected-Shortfall (ES) norms constructed via distortion risk measures, establishing a unified analytical framework for risk quantification. The proposed norms extend conventional ES methodology by incorporating flexible distortion functions. Specifically, we develop the mathematical duality theory for generalized-ES norms to support portfolio optimization tasks, while demonstrating their practical utility through projection problem solutions. The generalizedES norms are also applied to detect anomalies of financial time series data.
title Norms Based on Generalized Expected-Shortfalls and Applications
topic Risk Management
url https://arxiv.org/abs/2507.09444