New Robust Reward‐Risk Ratio Models with CVaR and Standard Deviation

Xu, Lijun; Zhou, Yijia

doi:10.1155/2022/8304411

Cited by 3 publications

(1 citation statement)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…However, it assumes that the uncertain parameters fluctuate in an interval [26][27][28][29][30]. Since its emergence, robust optimization theories have been applied to many fields, such as group decision-making [31][32][33][34][35][36], portfolios [37][38][39][40][41], efficiency evaluation [42,43], supply chain management [44][45][46][47][48][49], etc. In emergency medical location decisions, some scholars have adopted the stochastic programming method for modeling [50][51][52][53][54].…”

Section: Introductionmentioning

confidence: 99%

The Robust Emergency Medical Facilities Location-Allocation Models under Uncertain Environment: A Hybrid Approach

Meng

Wang

et al. 2022

Sustainability

View full text Add to dashboard Cite

In emergency medical facilities location, the hierarchical diagnosis and treatment system plays an obvious role in the rational allocation of medical resources and improving the use efficiency of medical resources. However, few studies have investigated the operational mechanism of hierarchical medical systems in uncertain environments. To address this research gap, this paper proposes a hybrid approach for emergency medical facilities’ location-allocation. In the first stage, in order to concentrate on the utilization of medical resources, we choose alternative facility points from the whole facilities through the entropy weight method (EWM). In the second stage, uncertainty sets are used to describe the uncertain number of patients at emergency medical points more accurately. We propose a robust model to configure large base hospitals based on the robust optimization method. Furthermore, the proposed robust models are applied to the emergency management of Huanggang City under COVID-19. The results show that the optimal emergency medical facility location-allocation scheme meets the actual treatment needs. Simultaneously, the disturbance ratio and uncertainty level have a significant impact on the configuration scheme.

show abstract

Section: Introductionmentioning

confidence: 99%

The Robust Emergency Medical Facilities Location-Allocation Models under Uncertain Environment: A Hybrid Approach

Meng

Wang

et al. 2022

Sustainability

View full text Add to dashboard Cite

show abstract

A new distributionally robust reward-risk model for portfolio optimization

Zhou,

2024

Open Mathematics

View full text Add to dashboard Cite

A new distributionally robust ratio optimization model is proposed under the known first and second moments of the uncertain distributions. In this article, both standard deviation (SD) and conditional value-at-risk (CVaR) are used to measure the risk, avoiding both fat-tail and volatility. The new model can be reduced to a simple distributionally robust model under assumptions on the measurements of reward, CVaR and SD. Furthermore, it can be rewritten as a tractable semi-definite programming problem by the duality theorem under partially known information of the uncertain parameters. Finally, the model is tested on portfolio problems and verified from numerical results that it can give a reasonable decision under only the first and second moments.

show abstract

The worst-case scenario: robust portfolio optimization with discrete distributions and transaction costs

Mills

2024

MATH

View full text Add to dashboard Cite

This research introduces min-max portfolio optimization models that incorporating transaction costs and focus on robust Entropic value-at-risk. This study offers a unified approach to handl the distribution of random parameters that affect the reward and risk aspects. Utilizing the duality theorem, the study transforms the optimization models into manageable forms, thereby accommodating the underlying random variables' discrete box and ellipsoidal distributions. The impact of transaction costs on optimal portfolio selection is examined through numerical examples under a robust return-risk framework. The results underscore the importance of the proposed model in safeguarding capital and reducing exposure to extreme risks, thus outperforming other strategies documented in the literature. This demonstrates the model's effectiveness in balancing maximizing returns and minimizing potential losses, making it a valuable tool for investors that seek to navigate uncertain financial markets.

show abstract

New Robust Reward‐Risk Ratio Models with CVaR and Standard Deviation

Cited by 3 publications

References 36 publications

The Robust Emergency Medical Facilities Location-Allocation Models under Uncertain Environment: A Hybrid Approach

The Robust Emergency Medical Facilities Location-Allocation Models under Uncertain Environment: A Hybrid Approach

A new distributionally robust reward-risk model for portfolio optimization

The worst-case scenario: robust portfolio optimization with discrete distributions and transaction costs

Contact Info

Product

Resources

About