scholarly journals Time-Consistent Investment-Reinsurance Strategies for the Insurer and the Reinsurer under the Generalized Mean-Variance Criteria

Mathematics ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 857 ◽  
Author(s):  
Helu Xiao ◽  
Tiantian Ren ◽  
Yanfei Bai ◽  
Zhongbao Zhou
Keyword(s):  
Optimization Problem ◽  
Continuous Process ◽  
Optimal Investment ◽  
Decision Makers ◽  
Weighted Sum ◽  
Proposed Model ◽  
Generalized Mean ◽  
Continuous Trading ◽  
The Impact ◽  
Mean Variance

Most of the existing literature on optimal investment-reinsurance only studies from the perspective of insurers and also treats the investment-reinsurance decision as a continuous process. However, in practice, the benefits of reinsurers cannot be ignored, nor can decision-makers engage in continuous trading. Under the discrete-time framework, we first propose a multi-period investment-reinsurance optimization problem considering the joint interests of the insurer and the reinsurer, among which their performance is measured by two generalized mean-variance criteria. We derive the time-consistent investment-reinsurance strategies for the proposed model by maximizing the weighted sum of the insurer’s and the reinsurer’s mean-variance objectives. We discuss the time-consistent investment-reinsurance strategies under two special premium principles. Finally, we provide some numerical simulations to show the impact of the intertemporal restrictions on the time-consistent investment-reinsurance strategies. These results indicate that the intertemporal restrictions will urge the insurer and the reinsurer to shrink the position invested in the risky asset; however, for the time-consistent reinsurance strategy, the impact of the intertemporal restrictions depends on who is the leader in the proposed model.

scholarly journals Optimizing a Reverse Supply Chain Network for Electronic Waste under Risk and Uncertain Factors

2021 ◽  
Vol 11 (4) ◽  
pp. 1946
Author(s):  
Linh Thi Truc Doan ◽  
Yousef Amer ◽  
Sang-Heon Lee ◽  
Phan Nguyen Ky Phuc ◽  
Tham Thi Tran
Keyword(s):  
Supply Chain ◽  
Electronic Waste ◽  
Decision Makers ◽  
Reverse Supply Chain ◽  
Satisfactory Solution ◽  
Level Of Satisfaction ◽  
Proposed Model ◽  
Objective Value ◽  
The Right ◽  
The Impact

Minimizing the impact of electronic waste (e-waste) on the environment through designing an effective reverse supply chain (RSC) is attracting the attention of both industry and academia. To obtain this goal, this study strives to develop an e-waste RSC model where the input parameters are fuzzy and risk factors are considered. The problem is then solved through crisp transformation and decision-makers are given the right to choose solutions based on their satisfaction. The result shows that the proposed model provides a practical and satisfactory solution to compromise between the level of satisfaction of constraints and the objective value. This solution includes strategic and operational decisions such as the optimal locations of facilities (i.e., disassembly, repairing, recycling facilities) and the flow quantities in the RSC.

THE IMPACT OF SAVINGS WITHDRAWALS ON A BANKER’S CAPITAL HOLDINGS SUBJECT TO BASEL III ACCORD

2020 ◽  
Vol 15 (02) ◽  
pp. 2050006
Author(s):  
RYLE S. PERERA ◽  
KIMITOSHI SATO
Keyword(s):  
Stock Returns ◽  
Optimal Investment ◽  
Investment Strategy ◽  
Short Selling ◽  
Terminal Condition ◽  
Capital Regulation ◽  
Basel Iii ◽  
Investment Strategies ◽  
The Impact ◽  
Mean Variance

In this paper, we analyze the impact of savings withdrawals on a bank’s capital holdings under Basel III capital regulation. We examine the interplay between savings withdrawals and the investment strategies of a bank, by extending the classical mean–variance paradigm to investigate the bankers optimal investment strategy. We solve this via an optimization problem under a mean–variance paradigm, subject to a quadratic optimization function which incorporates a running penalization cost alongside the terminal condition. By solving the Hamilton–Jacobi–Bellman (HJB) equation, we derive the closed-form expressions for the value function as well as the banker’s optimal investment strategies. Our study provides a novel insight into the way banks allocate their capital holdings by showing that in the presence of savings withdrawals, banks will increase their risk-free asset holdings to hedge against the forthcoming deposit withdrawals whilst facing short-selling constraints. Moreover, we show that if the savings depositors of the bank are more stock-active, an economic expansion will imply a greater reduction in bank savings. As a result, the banker will reduce his/her loan portfolio and will depend on high stock returns with short-selling constraints to conform to Basel III capital regulation.

Topology Optimization Design of Bars Structure Based on SKO Method

2013 ◽  
Vol 394 ◽  
pp. 515-520 ◽  
Author(s):  
Wen Jun Li ◽  
Qi Cai Zhou ◽  
Xu Hui Zhang ◽  
Xiao Lei Xiong ◽  
Jiong Zhao
Keyword(s):  
Global Optimization ◽  
Topology Optimization ◽  
Optimization Design ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Optimization Methods ◽  
Topology Optimization Problem ◽  
Proposed Model ◽  
Continuum Structure ◽  
The Impact

There are less topology optimization methods for bars structure than those for continuum structure. Bionic intelligent method is a powerful way to solve the topology optimization problems of bars structure since it is of good global optimization capacity and convenient for numerical calculation. This article presents a SKO topology optimization model for bars structure based on SKO (Soft Kill Option) method derived from adaptive growth rules of trees, bones, etc. The model has been applied to solve the topology optimization problem of a space frame. It uses three optimization strategies, which are constant, decreasing and increasing material removed rate. The impact on the optimization processes and results of different strategies are discussed, and the validity of the proposed model is proved.

scholarly journals A Model for the Optimal Investment Strategy in the Context of Pandemic Regional Lockdown

Mathematics ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1058
Author(s):  
Antoine Tonnoir ◽  
Ioana Ciotir ◽  
Adrian-Liviu Scutariu ◽  
Octavian Dospinescu
Keyword(s):  
Mathematical Model ◽  
Negative Impact ◽  
Optimal Investment ◽  
Investment Strategy ◽  
Economic Consequences ◽  
Decision Makers ◽  
Investment Strategies ◽  
Negative Consequences ◽  
Optimal Investment Strategy ◽  
Proposed Model

The Covid-19 pandemic has generated major changes in society, most of them having a negative impact on the quality of life and income obtained by the population and businesses. The negative consequences have been highlighted in the decrease of the GPD level for regions, countries and even continents. Returning to pre-pandemic levels is a considerable effort for both economic and political decision-makers. This article deals with the construction of a mathematical model for economic aspects in the context of variable productivity in time. Through this mathematical model, we propose to maximize revenues in pandemic conditions, in order to limit the economic consequences of the lockdown. One advantage of the proposed model consists in the fact that it is based on units that can be regions, economic branches, economic units or fields of investment. Another strength of the model is determined by the fact that it offers the possibility to choose between two different investment strategies, based on the specific options of the decision makers: the consistent increase of the state revenues or the amelioration of the disparity phenomenon. Furthermore, our model extends previous approaches from the literature by adding some generalization options and the proposed model can be applied in lockdown cases and seasonal situations.

scholarly journals Development of a Sustainability Assessment Algorithm and Its Validation Using Case Studies on Cryogenic Machining

2020 ◽  
Vol 4 (2) ◽  
pp. 42 ◽  
Author(s):  
Prathamesh Bhat ◽  
Chetan Agrawal ◽  
Navneet Khanna
Keyword(s):  
Case Studies ◽  
Sustainability Assessment ◽  
Decision Makers ◽  
Machining Processes ◽  
Entropy Weight ◽  
Proposed Model ◽  
Order Preference ◽  
Entropy Weight Method ◽  
Weight Method ◽  
The Impact

This work presents a comprehensive structure for evaluating the sustainability of machining processes. Industries can contribute towards developing a sustainable future by using algorithms that evaluate the sustainability of their processes. Inspired by the literature, the proposed model involves a set of metrics that are critical in evaluating the impact of a process on society, environment, and economy. The flexibility of this model allows decision-makers to use the available responses to identify the most favorable process. The entropy weight method was suggested for objectively calculating the weights of each indicator. A multi-criteria decision-making method i.e., Technique for Order Preference based on Similarity to Ideal Solution (TOPSIS), was used to rank processes in the decreasing order of their sustainability. The proposed algorithm was successfully validated with case studies from the published literature. A MATLAB code was also created so that industries may expeditiously apply this method to evaluate the sustainability of machining processes.

scholarly journals Optimal investment strategies for pension funds with regulation-conform dynamic pension payment management in the absence of guarantees

2021 ◽  
Author(s):  
Andreas Lichtenstern ◽  
Rudi Zagst
Keyword(s):  
Continuous Time ◽  
Optimization Problem ◽  
Wealth Distribution ◽  
Optimal Investment ◽  
Investment Strategy ◽  
Cash Flows ◽  
Iteration Algorithm ◽  
Coverage Ratio ◽  
Proposed Model ◽  
Bellman Principle

AbstractIn this article we consider the post-retirement phase optimization problem for a specific pension product in Germany that comes without guarantees. The continuous-time optimization problem is defined consisting of two specialties: first, we have a product-specific pension adjustment mechanism based on a certain capital coverage ratio which stipulates compulsory pension adjustments if the pension fund is underfunded or significantly overfunded. Second, due to the retiree’s fear of and aversion against pension reductions, we introduce a total wealth distribution to an investment portfolio and a buffer portfolio to lower the probability of future potential pension shortenings. The target functional in the optimization, that is to be maximized, is the client’s expected accumulated utility from the stochastic future pension cash flows. The optimization outcome is the optimal investment strategy in the proposed model. Due to the inherent complexity of the continuous-time framework, the discrete-time version of the optimization problem is considered and solved via the Bellman principle. In addition, for computational reasons, a policy function iteration algorithm is introduced to find a stationary solution to the problem in a computationally efficient and elegant fashion. A numerical case study on optimization and simulation completes the work with highlighting the benefits of the proposed model.

scholarly journals SEAHIR: A Specialized Compartmental Model for COVID-19

2021 ◽  
Vol 18 (5) ◽  
pp. 2667
Author(s):  
Alexandros Leontitsis ◽  
Abiola Senok ◽  
Alawi Alsheikh-Ali ◽  
Younus Al Nasser ◽  
Tom Loney ◽  
...  
Keyword(s):  
United Arab Emirates ◽  
Decision Makers ◽  
The Novel ◽  
Seir Model ◽  
Control Center ◽  
Testing Strategies ◽  
Proposed Model ◽  
Unique Nature ◽  
And Control ◽  
The Impact

The SEIR (Susceptible-Exposed-Infected-Removed) model is widely used in epidemiology to mathematically model the spread of infectious diseases with incubation periods. However, the SEIR model prototype is generic and not able to capture the unique nature of a novel viral pandemic such as SARS-CoV-2. We have developed and tested a specialized version of the SEIR model, called SEAHIR (Susceptible-Exposed-Asymptomatic-Hospitalized-Isolated-Removed) model. This proposed model is able to capture the unique dynamics of the COVID-19 outbreak including further dividing the Infected compartment into: (1) “Asymptomatic”, (2) “Isolated” and (3) “Hospitalized” to delineate the transmission specifics of each compartment and forecast healthcare requirements. The model also takes into consideration the impact of non-pharmaceutical interventions such as physical distancing and different testing strategies on the number of confirmed cases. We used a publicly available dataset from the United Arab Emirates (UAE) as a case study to optimize the main parameters of the model and benchmarked it against the historical number of cases. The SEAHIR model was used by decision-makers in Dubai’s COVID-19 Command and Control Center to make timely decisions on developing testing strategies, increasing healthcare capacity, and implementing interventions to contain the spread of the virus. The novel six-compartment SEAHIR model could be utilized by decision-makers and researchers in other countries for current or future pandemics.

scholarly journals Multi-period Investment Strategies with Transaction Costs Under Cumulative Prospect Theory

2019 ◽  
Vol 5 (2) ◽  
pp. 53
Author(s):  
Liurui Deng ◽  
Lan Yang ◽  
Bolin Ma
Keyword(s):  
Transaction Costs ◽  
Prospect Theory ◽  
Optimization Problem ◽  
Optimal Investment ◽  
Original Data ◽  
Cumulative Prospect Theory ◽  
Optimal Portfolio ◽  
Investment Strategies ◽  
Optimal Portfolios ◽  
The Impact

This paper focuses on optimal investment strategies under cumulative prospect theory (CPT). Considering transaction costs, we investigate CPT investors multi-period optimal portfolios. Our main contributions relative to previous work are expanding a single-period optimization problem to a multi-period optimization problem and investigating the impact of transaction costs on optimal portfolio selections. In a numerical analysis that applied original data on four stocks from the NASDAQ, we examine the effects of different risks on the optimal portfolio. Moreover, in contrast with the results without transaction costs, we come to conclusion that the optimal strategy with transaction costs is less sensitive to risk.

Time-Consistent Strategies for the Generalized Multiperiod Mean-Variance Portfolio Optimization Considering Benchmark Orientation

Mathematics ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. 723 ◽  
Author(s):  
Helu Xiao ◽  
Tiantian Ren ◽  
Zhongbao Zhou
Keyword(s):  
Portfolio Optimization ◽  
Backward Induction ◽  
Performance Gap ◽  
Feedback Strategy ◽  
Time Period ◽  
Proposed Model ◽  
Intermediate Time ◽  
Generalized Mean ◽  
Mean Variance Portfolio ◽  
Mean Variance

In this paper, we propose a generalized multiperiod mean-variance portfolio optimization based on consideration of benchmark orientation and intertemporal restrictions, in which the investors not only focus on their own performance but also tend to compare the performance gap between themselves and the benchmark. We aim to find the time-consistent strategy under the generalized mean-variance criterion, such that their relative performance is maximized. We derive the time-consistent strategy for the proposed model with and without a risk-free asset by using the backward induction approach. The results show that, in the case that there exists a risk-free asset, the time-consistent strategy is a feedback strategy about the benchmark process. However, in the other case, the time-consistent strategy is a double feedback strategy on both the benchmark process and the wealth process. Finally, we carry out some numerical simulations to show the evolution process of the time-consistent strategy. These simulations indicate that the proposed strategy can not only reduce the risk of investment existed in the intermediate time period but also imitate the return of the benchmark process.

A New Active Contours Image Segmentation Model Driven by Generalized Mean with Outlier Restoration Achievements

2020 ◽  
Vol 34 (11) ◽  
pp. 2054026
Author(s):  
Haider Ali ◽  
Amna Shujjahuddin ◽  
Lavdie Rada
Keyword(s):  
Optimization Problem ◽  
Active Contours ◽  
State Of The Art ◽  
Negative Effects ◽  
Two Phase ◽  
Model Driven ◽  
Proposed Model ◽  
Generalized Mean ◽  
Multi Phase ◽  
Vector Valued

In this paper, we propose a robust variational segmentation model capable of overcoming the problem of the negative effects of outliers. The proposed method is based on the combination of the characteristics of the generalized mean with the concept of the active contours. The optimization problem raising in this combination employs a power method technique. We demonstrate the performance of the proposed model on a series of sample images from diverse modalities and show an outperforming proposed model in comparison with the state-of-the-art methods. The proposed method shows better or equivalent performance in terms of accuracy and robustness than the conventional state-of-the-art models. The validation of the efficiency of the proposed two-phase algorithm is further extended to vector-valued images and multi-phase formulation.

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