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Optimal Control of Background-Based Uncertain Systems with Applications in DC Pension Plan

In this paper, we propose a new optimal control model for uncertain systems with jump. In the model, the background-state variables are incorporated, where the background-state variables are governed by an uncertain differential equation. Meanwhile, the state variables are governed by another uncert...

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Detalles Bibliográficos
Autores principales: Liu, Wei, Wu, Wanying, Tang, Xiaoyi, Hu, Yijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140549/
https://www.ncbi.nlm.nih.gov/pubmed/35626616
http://dx.doi.org/10.3390/e24050734
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author Liu, Wei
Wu, Wanying
Tang, Xiaoyi
Hu, Yijun
author_facet Liu, Wei
Wu, Wanying
Tang, Xiaoyi
Hu, Yijun
author_sort Liu, Wei
collection PubMed
description In this paper, we propose a new optimal control model for uncertain systems with jump. In the model, the background-state variables are incorporated, where the background-state variables are governed by an uncertain differential equation. Meanwhile, the state variables are governed by another uncertain differential equation with jump, in which both the background-state variables and the control variables are involved. Under the optimistic value criterion, using uncertain dynamic programming method, we establish the principle and the equation of optimality. As an application, the optimal investment strategy and optimal payment rate for DC pension plans are given, where the corresponding background-state variables represent the salary process. This application in DC pension plans illustrates the effectiveness of the proposed model.
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spelling pubmed-91405492022-05-28 Optimal Control of Background-Based Uncertain Systems with Applications in DC Pension Plan Liu, Wei Wu, Wanying Tang, Xiaoyi Hu, Yijun Entropy (Basel) Article In this paper, we propose a new optimal control model for uncertain systems with jump. In the model, the background-state variables are incorporated, where the background-state variables are governed by an uncertain differential equation. Meanwhile, the state variables are governed by another uncertain differential equation with jump, in which both the background-state variables and the control variables are involved. Under the optimistic value criterion, using uncertain dynamic programming method, we establish the principle and the equation of optimality. As an application, the optimal investment strategy and optimal payment rate for DC pension plans are given, where the corresponding background-state variables represent the salary process. This application in DC pension plans illustrates the effectiveness of the proposed model. MDPI 2022-05-21 /pmc/articles/PMC9140549/ /pubmed/35626616 http://dx.doi.org/10.3390/e24050734 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Liu, Wei
Wu, Wanying
Tang, Xiaoyi
Hu, Yijun
Optimal Control of Background-Based Uncertain Systems with Applications in DC Pension Plan
title Optimal Control of Background-Based Uncertain Systems with Applications in DC Pension Plan
title_full Optimal Control of Background-Based Uncertain Systems with Applications in DC Pension Plan
title_fullStr Optimal Control of Background-Based Uncertain Systems with Applications in DC Pension Plan
title_full_unstemmed Optimal Control of Background-Based Uncertain Systems with Applications in DC Pension Plan
title_short Optimal Control of Background-Based Uncertain Systems with Applications in DC Pension Plan
title_sort optimal control of background-based uncertain systems with applications in dc pension plan
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140549/
https://www.ncbi.nlm.nih.gov/pubmed/35626616
http://dx.doi.org/10.3390/e24050734
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