scholarly journals THE INFLUENCE OF THE COVID-19 PANDEMIC ON ALLOCATION OF ASSETS IN INVESTORS PORTFOLIO

2021 ◽  
Vol 2 ◽  
pp. 1-8
Author(s):  
Maroš Bobulský ◽  
Mária Bohdalová
Keyword(s):  
Risk Aversion ◽  
Optimization Problem ◽  
Expected Returns ◽  
Worst Case ◽  
Robust Approach ◽  
Robust Model ◽  
Proposed Model ◽  
The Us ◽  
The Individual ◽  
Difficult Times

Investing during a pandemic is very challenging. Even in these difficult times, the investor must appropriately allocate assets into his portfolio. In this article, we discuss investing in the stock market. We are interested in creating portfolios of shares that consist of financial assets. The individual methods we use are designed to provide an allocation of funds in between individual shares.  In the modern portfolio theory, the Markowitz model (Markowitz, 1952) is being used to solve these problems. The paper's main goal is to propose an efficient, robust approach to solve the Markowitz optimization problem adjusted for periods of a global decline in financial markets. In our research, we focus on robust optimization. Instead of precisely given input parameters, we propose a set of parameters from which we always select the worst possible parameter (so-called worst-case optimization). The robustness of optimization is achieved using so-called filter matrices. These matrices are used to modify historical data directly during optimization. The proposed model modifies the data by using different lengths of historical returns. Our proposed model is then compared with the original Markowitz non-robust model. We compare these two models using the properties of the second derivative of the optimization problem. Our results are visualized for different levels of investor’s risk aversion. We present our methods on historical price data of five randomly selected companies traded on the US market. By comparing the proposed robust approach with the non-robust one, we show that different lengths of historical returns capture volatility changes earlier. The investor can thus reduce his risk aversion and increase his expected returns.

scholarly journals Robust Optimization Model with Shared Uncertain Parameters in Multi-Stage Logistics Production and Inventory Process

Mathematics ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 211
Author(s):  
Lijun Xu ◽  
Yijia Zhou ◽  
Bo Yu
Keyword(s):  
Robust Optimization ◽  
Optimization Model ◽  
Optimization Problems ◽  
Optimal Solution ◽  
Uncertain Parameters ◽  
Worst Case ◽  
Robust Model ◽  
Multi Stage ◽  
Proposed Model ◽  
Dual Forms

In this paper, we focus on a class of robust optimization problems whose objectives and constraints share the same uncertain parameters. The existing approaches separately address the worst cases of each objective and each constraint, and then reformulate the model by their respective dual forms in their worst cases. These approaches may result in that the value of uncertain parameters in the optimal solution may not be the same one as in the worst case of each constraint, since it is highly improbable to reach their worst cases simultaneously. In terms of being too conservative for this kind of robust model, we propose a new robust optimization model with shared uncertain parameters involving only the worst case of objectives. The proposed model is evaluated for the multi-stage logistics production and inventory process problem. The numerical experiment shows that the proposed robust optimization model can give a valid and reasonable decision in practice.

Robust Portfolio Optimization with Transaction Cost for Risky and Risk-Free Assets Coexisting

2014 ◽  
Vol 543-547 ◽  
pp. 4339-4345
Author(s):  
Jiang Ping Zhu ◽  
Xi Kun Liang
Keyword(s):  
Transaction Cost ◽  
Efficient Frontier ◽  
Expected Returns ◽  
Worst Case ◽  
Robust Portfolio Optimization ◽  
Proposed Model ◽  
Robust Portfolio ◽  
Mean Variance Portfolio ◽  
Portfolio Selection Model ◽  
Mean Variance

A robust mean-variance portfolio selection model with transaction cost is presented for the case that both risky and risk-free assets exist in the market and expected returns of assets are uncertain and belong to a convex polyhedron. The model helps investors to identify such portfolios that expectations of investors are ensured even if the worst case in the expected returns of assets occurs. Analytical expression of the optimal portfolio determined by the proposed model is derived based on the Lagrange method for constrained optimization. Empirical analysis with three real stocks is performed to give the efficient frontier of portfolios.

scholarly journals Feature Selection Based on a Large-Scale Many-Objective Evolutionary Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yue Li ◽  
Zhiheng Sun ◽  
Xin Liu ◽  
Wei-Tung Chen ◽  
Der-Juinn Horng ◽  
...  
Keyword(s):  
Feature Selection ◽  
Evolutionary Algorithm ◽  
Large Scale ◽  
Optimization Problem ◽  
Selection Problem ◽  
Feature Selection Problem ◽  
Worst Case ◽  
Research Fields ◽  
Proposed Model ◽  
Polynomial Mutation

The feature selection problem is a fundamental issue in many research fields. In this paper, the feature selection problem is regarded as an optimization problem and addressed by utilizing a large-scale many-objective evolutionary algorithm. Considering the number of selected features, accuracy, relevance, redundancy, interclass distance, and intraclass distance, a large-scale many-objective feature selection model is constructed. It is difficult to optimize the large-scale many-objective feature selection optimization problem by using the traditional evolutionary algorithms. Therefore, this paper proposes a modified vector angle-based large-scale many-objective evolutionary algorithm (MALSMEA). The proposed algorithm uses polynomial mutation based on variable grouping instead of naive polynomial mutation to improve the efficiency of solving large-scale problems. And a novel worst-case solution replacement strategy using shift-based density estimation is used to replace the poor solution of two individuals with similar search directions to enhance convergence. The experimental results show that MALSMEA is competitive and can effectively optimize the proposed model.

Small talk as work talk: Enacting the patient-centered approach in nurse-practitioner-patient visits

2018 ◽  
Vol 14 (2) ◽  
pp. 97-107 ◽  
Author(s):  
Staci Defibaugh
Keyword(s):  
Nurse Practitioners ◽  
Nurse Practitioner ◽  
Medical Visit ◽  
Patient Centered ◽  
Small Talk ◽  
Medical Visits ◽  
Relational Work ◽  
The Us ◽  
The Individual ◽  
Patient Relationships

Small talk in medical visits has received ample attention; however, small talk that occurs at the close of a medical visit has not been explored. Small talk, with its focus on relational work, is an important aspect of medical care, particularly so considering the current focus in the US on the patient-centered approach and the desire to construct positive provider– patient relationships, which have been shown to contribute to higher patient satisfaction and better health outcomes. Therefore, even small talk that is unrelated to the transactional aspect of the medical visit in fact serves an important function. In this article, I analyze small talk exchanges between nurse practitioners (NPs) and their patients which occur after the transactional work of the visit is completed. I focus on two exchanges which highlight different interactional goals. I argue that these examples illustrate a willingness on the part of all participants to extend the visit solely for the purpose of constructing positive provider–patient relationships. Furthermore, because exchanges occur after the ‘work’ of the visit has been completed, they have the potential to construct positive relationships that extend beyond the individual visit.

Risk-Based Robust Bidding Strategies for EVs’ Aggregators in Day-ahead Markets with Uncertainty

2020 ◽  
Author(s):  
Ahmed Abdelmoaty ◽  
Wessam Mesbah ◽  
Mohammad A. M. Abdel-Aal ◽  
Ali T. Alawami
Keyword(s):  
Robust Optimization ◽  
Electricity Market ◽  
Real Life ◽  
Optimization Approach ◽  
Case Scenario ◽  
Worst Case ◽  
Bidding Strategies ◽  
Wind Generators ◽  
Proposed Model ◽  
Optimal Bidding

In the recent electricity market framework, the profit of the generation companies depends on the decision of the operator on the schedule of its units, the energy price, and the optimal bidding strategies. Due to the expanded integration of uncertain renewable generators which is highly intermittent such as wind plants, the coordination with other facilities to mitigate the risks of imbalances is mandatory. Accordingly, coordination of wind generators with the evolutionary Electric Vehicles (EVs) is expected to boost the performance of the grid. In this paper, we propose a robust optimization approach for the coordination between the wind-thermal generators and the EVs in a virtual<br>power plant (VPP) environment. The objective of maximizing the profit of the VPP Operator (VPPO) is studied. The optimal bidding strategy of the VPPO in the day-ahead market under uncertainties of wind power, energy<br>prices, imbalance prices, and demand is obtained for the worst case scenario. A case study is conducted to assess the e?effectiveness of the proposed model in terms of the VPPO's profit. A comparison between the proposed model and the scenario-based optimization was introduced. Our results confirmed that, although the conservative behavior of the worst-case robust optimization model, it helps the decision maker from the fluctuations of the uncertain parameters involved in the production and bidding processes. In addition, robust optimization is a more tractable problem and does not suffer from<br>the high computation burden associated with scenario-based stochastic programming. This makes it more practical for real-life scenarios.<br>

A University Education

2017 ◽  
Author(s):  
David Willetts
Keyword(s):  
Higher Education ◽  
Modern Society ◽  
University Education ◽  
Modern World ◽  
Controversial Issues ◽  
The Us ◽  
The Individual ◽  
The University ◽  
First Time ◽  
The Relationship

Universities have a crucial role in the modern world. In England, entrance to universities is by nation-wide competition which means English universities have an exceptional influence on schools--a striking theme of the book. This important book first investigates the university as an institution and then tracks the individual on their journey to and through university. In A University Education, David Willetts presents a compelling case for the ongoing importance of the university, both as one of the great institutions of modern society and as a transformational experience for the individual. The book also makes illuminating comparisons with higher education in other countries, especially the US and Germany. Drawing on his experience as UK Minister for Universities and Science from 2010 to 2014, the author offers a powerful account of the value of higher education and the case for more expansion. He covers controversial issues in which he was involved from access for disadvantaged students to the introduction of L9,000 fees. The final section addresses some of the big questions for the future, such as the the relationship between universities and business, especially in promoting innovation.. He argues that the two great contemporary trends of globalisation and technological innovation will both change the university significantly. This is an authoritative account of English universities setting them for the first time in their new legal and regulatory framework.

Punk as Folk: Continuities and Tensions in the UK and Beyond

2020 ◽  
Author(s):  
Pete Dale
Keyword(s):  
Folk Music ◽  
Music Making ◽  
Collective Creativity ◽  
Living Tradition ◽  
Wide Range ◽  
The Us ◽  
The Common ◽  
The Individual ◽  
The Uk

Numerous claims have been made by a wide range of commentators that punk is somehow “a folk music” of some kind. Doubtless there are several continuities. Indeed, both tend to encourage amateur music-making, both often have affiliations with the Left, and both emerge at least partly from a collective/anti-competitive approach to music-making. However, there are also significant tensions between punk and folk as ideas/ideals and as applied in practice. Most obviously, punk makes claims to a “year zero” creativity (despite inevitably offering re-presentation of at least some existing elements in every instance), whereas folk music is supposed to carry forward a tradition (which, thankfully, is more recognized in recent decades as a subject-to-change “living tradition” than was the case in folk’s more purist periods). Politically, meanwhile, postwar folk has tended more toward a socialist and/or Marxist orientation, both in the US and UK, whereas punk has at least rhetorically claimed to be in favor of “anarchy” (in the UK, in particular). Collective creativity and competitive tendencies also differ between the two (perceived) genre areas. Although the folk scene’s “floor singer” tradition offers a dispersal of expressive opportunity comparable in some ways to the “anyone can do it” idea that gets associated with punk, the creative expectation of the individual within the group differs between the two. Punk has some similarities to folk, then, but there are tensions, too, and these are well worth examining if one is serious about testing out the common claim, in both folk and punk, that “anyone can do it.”

scholarly journals Heuristic Optimization of Overloading Due to Electric Vehicles in a Low Voltage Grid

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6069
Author(s):  
Sajjad Haider ◽  
Peter Schegner
Keyword(s):  
Electric Vehicles ◽  
Low Voltage ◽  
Optimization Methods ◽  
Monte Carlo Analysis ◽  
Heuristic Optimization ◽  
Optimization Approach ◽  
Worst Case ◽  
Voltage Drops ◽  
The Individual ◽  
Nodal Voltage

It is important to understand the effect of increasing electric vehicles (EV) penetrations on the existing electricity transmission infrastructure and to find ways to mitigate it. While, the easiest solution is to opt for equipment upgrades, the potential for reducing overloading, in terms of voltage drops, and line loading by way of optimization of the locations at which EVs can charge, is significant. To investigate this, a heuristic optimization approach is proposed to optimize EV charging locations within one feeder, while minimizing nodal voltage drops, cable loading and overall cable losses. The optimization approach is compared to typical unoptimized results of a monte-carlo analysis. The results show a reduction in peak line loading in a typical benchmark 0.4 kV by up to 10%. Further results show an increase in voltage available at different nodes by up to 7 V in the worst case and 1.5 V on average. Optimization for a reduction in transmission losses shows insignificant savings for subsequent simulation. These optimization methods may allow for the introduction of spatial pricing across multiple nodes within a low voltage network, to allow for an electricity price for EVs independent of temporal pricing models already in place, to reflect the individual impact of EVs charging at different nodes across the network.

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