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Divergence-Based Risk Measures: A Discussion on Sensitivities and Extensions
This paper introduces a new family of the convex divergence-based risk measure by specifying [Formula: see text]-divergence, corresponding with the dual representation. First, the sensitivity characteristics of the modified divergence risk measure with respect to profit and loss (P&L) and the re...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515127/ https://www.ncbi.nlm.nih.gov/pubmed/33267348 http://dx.doi.org/10.3390/e21070634 |
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author | Xu, Meng Angulo, José M. |
author_facet | Xu, Meng Angulo, José M. |
author_sort | Xu, Meng |
collection | PubMed |
description | This paper introduces a new family of the convex divergence-based risk measure by specifying [Formula: see text]-divergence, corresponding with the dual representation. First, the sensitivity characteristics of the modified divergence risk measure with respect to profit and loss (P&L) and the reference probability in the penalty term are discussed, in view of the certainty equivalent and robust statistics. Secondly, a similar sensitivity property of [Formula: see text]-divergence risk measure with respect to P&L is shown, and boundedness by the analytic risk measure is proved. Numerical studies designed for Rényi- and Tsallis-divergence risk measure are provided. This new family integrates a wide spectrum of divergence risk measures and relates to divergence preferences. |
format | Online Article Text |
id | pubmed-7515127 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75151272020-11-09 Divergence-Based Risk Measures: A Discussion on Sensitivities and Extensions Xu, Meng Angulo, José M. Entropy (Basel) Article This paper introduces a new family of the convex divergence-based risk measure by specifying [Formula: see text]-divergence, corresponding with the dual representation. First, the sensitivity characteristics of the modified divergence risk measure with respect to profit and loss (P&L) and the reference probability in the penalty term are discussed, in view of the certainty equivalent and robust statistics. Secondly, a similar sensitivity property of [Formula: see text]-divergence risk measure with respect to P&L is shown, and boundedness by the analytic risk measure is proved. Numerical studies designed for Rényi- and Tsallis-divergence risk measure are provided. This new family integrates a wide spectrum of divergence risk measures and relates to divergence preferences. MDPI 2019-06-27 /pmc/articles/PMC7515127/ /pubmed/33267348 http://dx.doi.org/10.3390/e21070634 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Xu, Meng Angulo, José M. Divergence-Based Risk Measures: A Discussion on Sensitivities and Extensions |
title | Divergence-Based Risk Measures: A Discussion on Sensitivities and Extensions |
title_full | Divergence-Based Risk Measures: A Discussion on Sensitivities and Extensions |
title_fullStr | Divergence-Based Risk Measures: A Discussion on Sensitivities and Extensions |
title_full_unstemmed | Divergence-Based Risk Measures: A Discussion on Sensitivities and Extensions |
title_short | Divergence-Based Risk Measures: A Discussion on Sensitivities and Extensions |
title_sort | divergence-based risk measures: a discussion on sensitivities and extensions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515127/ https://www.ncbi.nlm.nih.gov/pubmed/33267348 http://dx.doi.org/10.3390/e21070634 |
work_keys_str_mv | AT xumeng divergencebasedriskmeasuresadiscussiononsensitivitiesandextensions AT angulojosem divergencebasedriskmeasuresadiscussiononsensitivitiesandextensions |