Optimal Allocation Of Funds Research Articles

Analisis Pembentukan Portofolio Optimal di Bursa Efek Indonesia dengan Menggunakan Model Markowitz

The purpose of this study is to utilize the Markowitz Model to build an optimal portfolio of stocks on the Indonesia Stock Exchange in 2019 to 2023, focusing on stocks in the IDX30 index. Based on information from KSEI, the public premium in capital market speculation continues to increase. On that basis, this study is important to be conducted in order to provide a reference for the public to invest. The IDX30 index was chosen as the subject of the study because it includes stocks with large market capitalization, high liquidity, and stable financial conditions. This study determines the optimal fund allocation for each stock and examines stocks in the IDX30 index from 2019 to 2023 that are worthy of consideration for inclusion in the optimal portfolio. In this test, it produces four stocks that become the optimal portfolio with the most extreme profits, namely ADRO 16.12%, BBCA 65.97%, BBRI 4.13%, and ICBP 13.76% with a return of 1.01% and a risk of 0.22%. In contrast, the minimum risk consists of ADRO of 5.29%, BBCA of 26.14%, CPIN of 13.91%, ICBP of 16.17%, INDF of 8%, KLBF of 0.48%, TLKM of 13.47%, and UNVR of 16.55%, with a risk of 0.1% and an expected portfolio return of 0.11%.

Problems of resource provision of Ukraine enterprises in the hotel sector in a state of war

Introduction. During the war in Ukraine, the hotel industry underwent significant changes. Due to restrictions and danger, the flow of tourists decreased, which affected the income of hotels. However, many institutions began to provide their premises for temporary accommodation of displaced persons and volunteers. This made it possible to maintain activities and save jobs. The use of resources in the hospitality industry during wartime is critical. Ensuring quality service in conditions of limited opportunities requires optimal allocation of funds, supplies and human resources. Control over resources helps enterprises not only to survive, but also to find new ways of development, in particular through innovative solutions, social projects and support of economic growth. The purpose of the paper is to determine the problems of resource provision of enterprises of the hotel sector of Ukraine in a state of war. Results. The war situation in Ukraine had a great impact on the hotel industry and forced businesses to adapt to new conditions. Hotels have become not only a place for temporary accommodation, but also a refuge for refugees, and restaurants have the ability to provide work flow and phone charges for customers. The difficulties in providing resources such as material, financial, human and other have become particularly relevant. Hotels and restaurants respond to these challenges by taking into account the protection of employees and guests, attracting financial and material support and adapting to limited conditions. Secured resources became a key part of the survival and further development of the hotel industry during the war. Conclusion. The specificity of resourcing the hotel industry requires the maximum level of security for consumers, and also becomes a problem for business owners who are faced with attacks on infrastructure and lack of materials due to a complex logistics process or financial situation. Problems with material, financial, human, informational, technical, natural and property support have become extremely urgent, so the provision of some resources in wartime conditions have become priorities for hotels and restaurants. Understanding resource management principles such as autonomy, continuity, compliance, adaptability, planning, focus, and resource conservation helps businesses respond to the challenges of war effectively and in time. An important component of success in these conditions is not only the preservation of operational activity, but also the ability to adapt to new conditions and provide anything needed, including personnel, in wartime conditions.

Assessing grid hardening strategies to improve power system performance during storms using a hybrid mechanistic-machine learning outage prediction model

Improvements of power system performance during severe weather events are targeted through grid hardening actions, such as strengthening aging infrastructure or performing vegetation management. However, due to the complexity of modeling power system interactions with the environment and the impacts of proposed reinforcements, the benefits of such hardening actions are often unclear. To support hardening assessments, comprehensive models capturing these intricate relationships are necessary. To this end, this study presents a novel application of a hybrid mechanistic-data-driven outage prediction model (OPM) designed to incorporate changes in infrastructure or environmental/vegetation parameters in the prediction of storm outages. The model incorporates physics-based structural fragility curves of the overhead pole-wire system within a machine learning OPM trained on meteorological, topographic, infrastructure, and historic outage data to quantify the benefits of adaptive change in reducing storm-related power outages. A prioritization scheme is formulated to inform improved strategies to strengthen grid resilience under budgetary constraints. As a case study of the distribution system in Connecticut, the model was trained on historical outage data from storms between 2005 and 2020, and a counterfactual analysis is conducted. The results indicate tree removal and pole strengthening are the most cost-effective strategies; for instance, under a $600 million budget, tree removal could have reduced up to 15,000 distribution grid outages over the events analyzed. The developed framework and models can be useful for utility companies, regulatory agencies, and governments to highlight areas of need, inform cost-risk-benefit analyses, and aid in the optimal allocation of funds and resources toward grid hardening.

Influence of working capital efficiency on firm’s composite financial performance: evidence from India

PurposeThe objective of this paper is to investigate the effect of working capital efficiency (WCE) and its components on the composite financial performance of a sample of Indian firms.Design/methodology/approachOur sample includes 796 non-financial listed firms from 2015–16 to 2021–22. Sample firms’ profitability, liquidity, solvency, cash flow management, and financial and operational leverage have been used to classify them into companies with high composite financial performance (HCFP) and with low composite financial performance (LCFP) by using K-Means Clustering technique. A composite financial performance score (CFPS) of 1 has been assigned to HCFP and 0 to LCFP. We have used logistic regression models with fixed effect to estimate the effect of cash conversion cycle (CCC) and its components, i.e. inventory days, accounts receivable days and accounts payable days on CFPS in the presence of control variables such as growth, leverage, firm size, and age.FindingsThe study finds that CCC and inventory days are inversely associated with CFPS. This finding shows that the firms’ WCE leads to superior financial performance on a composite basis.Research limitations/implicationsThe research findings are based on samples drawn from the population of the listed Indian non-financial companies. Since the operation, financial practices, working capital policies, and management styles of firms vary greatly among nations, the results of this study should be extended to firms in other countries after taking into account the degree of resemblance to the sample firms.Practical implicationsThe findings of this study hold significant value for industry practitioners, as they provide guidance in determining the optimal allocation of funds for working capital and devising strategies for effectively managing inventory levels, credit sales, and vendor payments in order to increase the overall value of the company. This study aims to help investors in building their investment portfolios by identifying companies with superior composite financial performance. Investors can enhance the construction of their investment portfolios by strategically selecting companies that demonstrate superior overall performance.Social implicationsThe results of our study will help companies improve their WCM strategies to enhance their overall value, and their significance increases manifold during economic downturns. Business firms that perform well by efficiently managing their working capital have a multiplier effect on the economy and society at large in the form of GDP contribution, labor income, taxes to the government, investment in capital assets, and payments to suppliers.Originality/valueTo understand the impact of WCE on firms’ performance, the extant working capital literature focuses on some specific characteristics such as profitability, valuation, solvency, and liquidity. The limitation of employing a single parameter is its inability to present the comprehensive performance evaluation of firms. This study is among the earliest studies that focus on the holistic evaluation of WCE's impact on the composite performance of a company.

Philanthropy in art: locality, donor retention, and prestige

A significant portion of funding for art comes from foundations, representing a key revenue stream for most art organizations. Little is known, however, about the quantitative patterns that govern art funding, limiting the fundraising efficiency of organizations in need of resources, as well as optimal funding allocation of donors. To address these shortcomings, here we relied on the IRS e-file dataset to identify $36B in grants from 46,643 foundations to 48,766 art recipients between 2010 and 2019, allowing us to quantify donor-recipient relationships in art. We find that philanthropic giving is broadly distributed, following a stable power-law distribution, indicating that some funders give considerably and predictably more than others. Giving is highly localized, with 60% of grants and funds going to recipients in the donor’s state. Furthermore, donors often support multiple local organizations that offer distinct artforms, rather than advancing a particular subarea within art. Donor retention is strong, with nearly 70% of relationships continuing the next year. Finally, we explored the role of institutional prestige in foundation giving, finding that funding does correlate with prestige, with notable exceptions. Our results present the largest and most comprehensive data-driven exploration of giving by foundations to art to date, unveiling multiple insights that could benefit both donors and recipients.

Optimal Investment Policy for Pension Annuitants in Malaysia under Economic Exposure

This research has conducted a profound evaluation into the annuity market in Malaysia from both the business and individual perspective. To a great extent, analysis is made on how the annuity insurers could better maintain the solvency level of annuity fund which is exposed under significant economic risks by obtaining an optimal fund allocation to maximise investment returns through the development of Asset-Liability Management (ALM). By adapting the concept from Wilkie model, six fundamental models including inflation rate, real interest rate, KLCI stock return, KLCI stock dividend yield, 10-year MGS return as well as Malaysian property return were formulated accordingly to the Box-Jenkins modelling approach. It concludes that the optimal weightages combination suggests that the annuity insurers should allocate 94% of the single premium such as RM100,000 which collected from the annuitant to bond market, whereas the other 5% of the fund should be invested in stock but only 1% of the premium should be allocated into the property investment.

Developing modified congestion index and congestion-based level of service

Traffic flow and travel time-based measures are used to quantify and characterize congestion levels on urban roadway networks. However, under low-density conditions, contradictory results are observed when these two measures are used to identify the prevailing congestion levels. This accentuates the need to develop a new measure of congestion that effectively integrates traffic flow and travel time-based measures. The present study develops a new measure termed modified congestion index (MCI) by integrating traffic flow and travel time-based congestion measures for identifying prevailing congestion levels. As proof of the concept, the application of the methodology was demonstrated using empirical data collected at the corridor and network level and simulated data developed for a real-world urban network. The traffic flow and travel time-based congestion measures were integrated using a generalized least square framework (GLS) to derive MCI. Investigations revealed that traffic states bifurcated based on MCI follow the general philosophy of traffic state bifurcation using the macroscopic fundamental diagram (MFD) and fundamental diagram (FD). MCI, when correlated with existing performance measures, revealed that MCI could characterize both reliability and congestion simultaneously. As an important outcome from a policy and practical application perspective, MCI-based level of service (LOS) thresholds were developed. The application of the LOS thresholds was demonstrated by (a) analysing the effect of traffic signal control using a before-after perspective and (b) ranking and prioritizing segments in an urban network for optimal allocation of funds for developing congestion mitigation strategies. The developed LOS thresholds are expected to facilitate planners and engineers to comprehend the operational level of urban networks in terms of congestion and develop mitigation measures accordingly.

Recording adverse events following orthopaedic trauma: Financial implications and validation of an adverse event assessment form in an Irish regional trauma unit

BackgroundIn Ireland, funding of orthopaedic trauma is based on an activity-based funding (ABF) model. Clinically similar cases are split into diagnostic-related groups (DRG), with base funding per DRG provided. Increased complexity of cases (length of stay; complications incurred; occurrence of adverse events) attracts additional remuneration to the base funding. In our institution these adverse events are recorded via retrospective chart-abstraction methods by administrative staff. Incidences which are not included from this review affect both follow up with family physicians and patient care; as well as skewing budgetary decisions that impact fiscal viability of the service. The aim of this study was to compare a prospectively implemented adverse events form with the current national retrospective chart abstraction method. Our outcomes in terms of pay-by-results financial implications. MethodsAn adverse events database adapted from a similar validated model was used to prospectively record complications in 216 patients admitted via the orthopaedic trauma service. Data was contemporaneously collected via a GDPR compliant secure medical messaging platform. Results were compared with the same cohort using an existing data abstraction method. Both data sets were coded in accordance with current standards for case funding. ResultsOverall, 49 adverse events were recorded during the study through prospective charting of adverse events, compared with 26 events documented by customary method (p<0.01).Anaemia requiring blood transfusion n = 11 22.4%) was the most common complication, followed by delirium n = 6 (12%), acute kidney injury n = 6 (12%), and pneumonia n = 5 (10.2%). Missed appropriate funding through conventional methods totalled €40,293 . ConclusionThis pilot study demonstrates the ability to improve capture of adverse events through use of a well-designed assessment form. Proper perioperative data handling is a critical aspect of financial subsidies, enabling optimal allocation of funds.

Funding allocations for disaster preparation considering catastrophe insurance

In disaster management, material reserves are defined by uncertain demand. Overstock may lead to wasted funds, while shortages increase purchase pressures in the post-disaster environment. The funding allocation for pre disaster reserve and post disaster procurement is a dilemma. Catastrophe insurance is intended to moderate this dilemma. The relief organization is intended to insure against the surge in demand that accompanies disaster, which may require it to purchase a large amount of materials urgently post disaster. This study develops a funding allocation optimization model for disaster response planning and preparedness, with the added leverage of catastrophe insurance. The goal of this paper is to determine the relief organization's optimal allocation of funds for material reserve, insurance premiums and possible post-disaster purchases to minimize long-term total relief costs. We model the problem as a two-stage robust optimization model designed to minimize the overall costs, and adopt an efficient column and constraint generation algorithm to calculate it. Using data from the flood disasters of Heilongjiang, China, some of the scenarios indicate a reduction in the government's relief costs by adopting insurance instead of applying option contract or just returning unused relief supplies. Our study confirms the advantages of catastrophe insurance in leveraging capital, and reducing disaster material overstocks and insufficient risks.

Optimal Management of Irrigation Water from Aquifer and Surface sources

AbstractWe explore the economic merits of on-farm water storage with tailwater recovery systems to reduce aquifer depletion in a region with expanding irrigated acreage and substantial off-season precipitation. Gains are substantial on a broad scale and long planning horizon, including more than $4 billion in producer surplus, 5 million acre-feet of conserved groundwater, and land capitalization of $24 per acre. Sensitivity analyses provide insights with respect to the impact of discount rates, rainfed returns, return flows, and aquifer recharge rates. Results can inform stakeholders about the optimal allocation of funds directed at agricultural practice adoption and agricultural water investments.

Disparities in Health Financing Allocation among Infectious Diseases in Ebola Virus Disease (EVD)-Affected Countries, 2005-2017.

The Ebola virus disease (EVD) outbreaks impacted the population health due to overstretched health systems and disrupted essential health services. Despite a call to achieve equal financial allocation depending on public health needs, there has been scant examination of the fairness of investment among infectious diseases. This study analyzes the extent to which equitable development assistance for health (DAH) has been provided in accordance with disease burden in EVD-affected countries. Estimates of disability-adjusted life years (DALYs) in the Global Burden of Disease (GBD) Study 2017 and DAH Database 1990–2019 in 2005–2017 were analyzed by disease category: vaccine-preventable diseases (VPDs), HIV/AIDS, malaria, tuberculosis, and EVD. HIV/AIDS generally recorded higher ratios of DAH per DALYs (DAH/DALYs). Malaria and tuberculosis showed different trends by country, and VPDs generally presented lower ratios. In West Africa in 2013–2016, DAH/DALYs surged in EVD and fluctuated in HIV/AIDS and malaria. Tuberculosis and VPDs consistently recorded lower ratios. To achieve the risk reduction during and after health emergencies, optimal funding allocation between diseases based on the disease burden is warranted in the pre-emergency period, along with measurement of immediate health needs of populations in real-time during an emergency.

Ability parity model for optimal fund allocation: Evidence from China's mutual fund markets

We propose in this article a novel ability parity model for optimal fund allocation. Compared with the traditional portfolio selection methods which directly work on asset returns and/or risk (volatility), the proposed ability parity method focuses mainly on the allocation between the stock selection ability and market timing ability of fund managers, which essentially determines fund performance (Fama, 1972). Using the data of China's mutual fund markets, we find strong and robust evidence that the proposed ability parity model delivers significantly higher return, skewness, and Sharpe ratio than traditional models and the benchmark index, while having volatilities comparable with traditional models.

The Ethos of Science and the Perception of the Polish System of Financing Science

The reforms of the Polish system of science emphasise the importance of research and the international activity of Polish scientists. Optimal allocation of funds, taking into account the needs of researchers, is one of the current key objectives of research policy in Poland. The aim of this article is to discover values that Polish researchers identify with as well as defining their approach to the current system of research financing in Poland. The results presented here come from a nationwide study implemented at the turn of 2016. In total, we surveyed 800 randomly selected researchers. The interviewees had at least a PhD degree and were employed in Polish research institutions. The results of the study confirm that the researchers who identify with different ethoses of science have varied approaches to the Polish system of research financing. The scientists who take the least favourable view of the system are those who identify with the academic tradition. Compared with the scientists with deeply-rooted academic values, those in favour of a post-academic ethos more appreciate the available funding opportunities as well as the features of competition-based research funding. They also more often claim that the rules of financing research institutions in Poland have a positive impact on the development of science.

PROBLEMS OF IMPLEMENTATION OF PROGRAM-TARGETED METHOD OF BUDGET EXPENDITURES IN THE RUSSIAN FEDERATION

The ongoing reform of public administration and the budgetary system has increasingly focused on improving budgetary efficiency. The best method to achieve this is a program-targeted method of planning and financing budget expenditures. While earlier planning in terms of the functions of local governments did not create incentives for optimal allocation of funds and focused only on the costs of maintaining the relevant bodies and subordinate institutions, the application of program-targeted planning requires a shift in the focus of budgetary expenditures towards results. Developed countries have begun to apply these planning methods since the middle of the last century, and to date there has been a wealth of experience that can be used in the practice of the Russian Federation, for which this method of planning expenditures is still quite new and causes a number of problems and difficulties in implementation. The article presents an overview study and systematization of the problems of implementation and evaluation of the effectiveness of the program-targeted method of planning state and municipal expenditures in the Russian Federation. The author identifies main difficulties faced by the budget system in 2018-2019, makes conclusions and recommendations for its improvement in the Russian Federation.

Applying Dynamic Programming Method to Solving the Problem of Optimal Allocation of Funds between Projects

Applying Dynamic Programming Method to Solving the Problem of Optimal Allocation of Funds between Projects

Great achievements and development trends of power systems

The power system ranks the first among the greatest engineering achievements in the 20th century. With “strong electric power” as the carrier, the power system constitutes the great aorta of modern society for energy transmission; while with “weak electric power” as the carrier, the information network constitutes the nervous system of modern society. Both of them penetrate into all aspects of human society (e.g., science, production, life, international relations), and then promote the modern civilization to achieve rapid development. In terms of science, the power system has promoted the developments of materials, physics, chemistry, automation, information, medicine, and so on. This way, the system of modern science and technology is constituted. In terms of production, the second industrial revolution marked by the wide application of “strong electric power” is also called the electric power technology revolution. It has promoted another major leap in the productivity of human society after the steam revolution. The third industrial revolution marked by the widespread application of “weak electricity” is also known as the information technology revolution, which promotes the continuous evolution of industrial civilization to a much higher level. And the fourth industrial revolution, which is centered on the energy revolution, will meet the needs of human beings at a higher level and get rid of the constraints of the environment on human activities. In terms of life, electric power has become the most indispensable part of human life, ranging from material life to spiritual life, from behavioral habits to thinking ways, and from personal life to social life. In terms of international relations, the development of the power system is conducive to the fundamental solution of energy and environmental problems, thus the international political and economic competition around energy and environment has turned to the competition centered on clean power systems to some extent. As the basic platform for energy production and supply, the development of the future power system must follow the general orientation of the energy revolution. The basic form, management mechanism and technical characteristics of the power system will also undergo tremendous changes as follows: (1) The proportion of renewable energy in the power system will be increased continuously, and the power system will be tightly coupled with gas system and thermal system to form an electricity-centric energy internet. (2) The development mode of building “higher, farther and larger” power grid will turn to the co-development mode of large power grid and small power grid, and the trend of power electronation of power system will be strengthened gradually. (3) Market competition will penetrate into the weak monopolies of the power system. Each subject can play a full game in each link, so as to obtain the optimal allocation of funds, technology and human resources. (4) Digitalization and intellectualization will be the most important technical characteristics of the future power system, which will achieve leapfrog development in observability, controllability and intellectualization.

Optimization models for financing innovations in green energy technologies

Commercialization of emerging green technologies is essential to improve the sustainability of industrial processes. However, there are risks inherent in funding the development of new technologies that act as a significant barrier to their commercialization. Mathematical models can provide much-needed decision support to allow optimal allocation of funds, while managing the implications of techno-economic risk. The Technology Readiness Level (TRL) scale is a well-established figure of merit approach for quantifying the maturity of stand-alone technologies, while the more recently developed System Readiness Level (SRL) scale is applicable to technology networks with interdependent components. These technology maturity scales are intended mainly to be used for the passive assessment of a given state of technology, but may be incorporated within an optimization model to aid in innovation planning. In this work, two mixed integer linear programming (MILP) models are proposed to optimize strategies for funding innovation. The first model is a bi-objective MILP for optimizing the allocation of funds to a portfolio of independent innovation projects. The model is based on source-sink formulation and uses information on TRL and return on investment (ROI) to determine the best allocation of funds. The second model is a robust MILP that optimizes the allocation of limited project funds in order to maximize the SRL of a system of emerging technologies. This approach accounts for Integration Readiness Level (IRL) among mutually interdependent technologies. Both models are demonstrated with illustrative case studies on biorefinery technologies in order to demonstrate their capabilities.

Cost-Effectiveness of Multifaceted Built Environment Interventions for Reducing Transmission of Pathogenic Bacteria in Healthcare Facilities.

The objective of this study is to determine the optimal allocation of budgets for pairs of alterations that reduce pathogenic bacterial transmission. Three alterations of the built environment are examined: handwashing stations (HW), relative humidity control (RH), and negatively pressured treatment rooms (NP). These interventions were evaluated to minimize total cost of healthcare-associated infections (HAIs), including medical and litigation costs. HAIs are largely preventable but are difficult to control because of their multiple mechanisms of transmission. Moreover, the costs of HAIs and resulting mortality are increasing with the latest estimates at US$9.8 billion annually. Using 6 years of longitudinal multidrug-resistant infection data, we simulated the transmission of pathogenic bacteria and the infection control efforts of the three alterations using Chamchod and Ruan's model. We determined the optimal budget allocations among the alterations by representing them under Karush-Kuhn-Tucker conditions for this nonlinear optimization problem. We examined 24 scenarios using three virulence levels across three facility sizes with varying budget levels. We found that in general, most of the budget is allocated to the NP or RH alterations in each intervention. At lower budgets, however, it was necessary to use the lower cost alterations, HW or RH. Mathematical optimization offers healthcare enterprise executives and engineers a tool to assist with the design of safer healthcare facilities within a fiscally constrained environment. Herein, models were developed for the optimal allocation of funds between HW, RH, and negatively pressured treatment rooms (NP) to best reduce HAIs. Specific strategies vary by facility size and virulence.

Optimal asset management strategies for mixed transit fleet

Transit agencies require equitable and optimal allocation of funds among transit agencies for not just regular operations and maintenance, but also for asset management including purchase of new buses and rehabilitation of aging fleet. The paper proposes a hierarchical structure of resource allocation where federal funding is routed through the state, and ultimately to local transit agencies. The framework encompasses multiple dimensions such as selection of different improvement program options (rehabilitation, remanufacturing, and replacement) of a mixed transit fleet spread over a temporally continuous planning period. It leverages optimization models for capital allocation among transit agencies in the state. Four sub-models are developed—two maximizing passenger miles traveled, and the other two maximizing the total fleetwide remaining life, all under agency-specific budget, capacity and policy constraints, and planning objectives. They are applied on real-world data from set of transit agencies spread across the state of Tennessee, containing a heterogenous fleet of 254 total buses at various levels of aging. Results indicate that by application of the framework, an average 40 percent additional mileage is generated through the planning period with the same levels of fleet size, with nearly 30 percent of the fleet receiving some form of improvement treatment per year.

A source-sink model for optimum allocation of technology innovation portfolios

Commercialization of emerging green technologies is essential to improving the sustainability of industrial processes. In practice, it is necessary to match funding sources (e.g., research and development grants, venture capital, etc.) with projects at different maturity levels. Because of inherent uncertainties that characterize and evaluate new technologies, the decision-making process is typically fraught with risk, which can be mitigated with the use of systematic decision support methods. In this work, an optimization model is developed for optimal allocation of funds to a portfolio of innovation projects based on the available funds and different levels of technology maturity. The model is based on source-sink formulation typically used in process integration applications. Each source is a fund of known size and can only be used for projects of a specified minimum return on investment (ROI) and minimum technological readiness level (TRL); each project has an estimated cost, TRL and an ROI range across techno-economic risk scenarios. The model is formulated as a bi-objective mixed integer linear programming (MILP) model, using the conservative and optimistic total portfolio ROI as dual objective functions. The methodology is demonstrated using a pedagogical case study.