Investment Evaluation Research Articles

Financial big data control and intelligent analysis method for investment decision of renewable energy projects

Abstract With the increasing scarcity of conventional energy and environmental degradation, countries around the world are increasing their investment in renewable energy development. In order to make a scientific investment evaluation of renewable energy projects, this paper examines the analysis and control of their financial data. The intelligent analysis system of financial data is constructed based on OLAP. Logistic regression model and decision tree algorithm model are selected as the operation algorithm of the system to complete the intelligent analysis of data. Combining random forest algorithm and autoregressive moving average model, under the guidance of Bagging idea, the financial status of renewable energy projects after investment is judged in order to achieve the purpose of dynamic control. According to the results of analysis and control of financial data of renewable energy projects, it is known that the correct probability of intelligent analysis of financial data reached 94.5%, 83.1%, and 92.7% for different sample sizes of data sets, respectively. There were significant improvements in the efficiency of capital usage and asset quality, with an increase in capital concentration of 30.42%, an increase in inventory turnover from 10.68% to 13.04%, and an increase in the recovery rate of overdue accounts receivable from 60.31% to 67.83%. It has been proven that the method can help investors to better utilize uncertainty to improve the investment value of project, providing investors with a new way of thinking about decision-making.

Comprehensive Benefit Evaluation of Power Grid Investment Considering Renewable Energy Development from the Perspective of Sustainability

To cope with the rapid development of renewable energy, the power grid system needs to invest in and construct transmission and distribution projects. Means of evaluating the economic, social, and environmental benefits generated by power grid investment are of great significance for enterprise cost recovery and government policy formulation. In this paper, an evaluation of the comprehensive benefit of a power grid investment considering renewable energy development from the perspective of sustainability is developed through the use of a hybrid multi-criteria decision-making (MCDM) method. The entropy weight method and fuzzy best worst method (BWM) are jointly employed to weight the comprehensive benefit criteria, which include economic, social, and environmental criteria and eight sub-criteria, and the measurement of alternatives and ranking according to compromise solution (MARCOS) method is utilized to evaluate the comprehensive benefit of a power grid investment. Five power grid investment projects for connecting renewable energy generation to a power grid in Ningxia, China, are selected as a case study, and the results indicate that the power grid investment project PGIP#1 has the largest comprehensive benefit (0.7099), followed by PGIP#3 (0.6800), PGIP#2 (0.6709), PGIP#5 (0.5959), and PGIP#4 (0.5861). The sensitivity analysis shows that the comprehensive benefit of PGIP#1 is always the best, indicating the robustness of the proposed method. By employing the proposed MCDM method to assess the comprehensive benefit of power grid investment projects, this research identifies outstanding projects which can provide guidance for the management of power grid investment and promote the sustainable development of the power industry.

Costs of Gasification Technologies for Energy and Fuel Production: Overview, Analysis, and Numerical Estimation

During recent years, gasification technology has gained a high potential and attractiveness to convert biomass and other solid wastes into a valuable syngas for energy production or synthesis of new biofuels. The implementation of real gasification facilities implies a good insight of all expenses that are involved, namely investments required in equipment during the project and construction phases (capital expenditures, CapEx) and costs linked to the operation of the plant, or periodic maintenance interventions (operational expenditures, OpEx) or costs related to operations required for an efficient and sustainable performance of a gasification plant (e.g., feedstock pre-treatment and management of by-products). Knowledge of these economic parameters and their corresponding trends over time may help decision-makers to make adequate choices regarding the eligible technologies and to perform comparisons with other conventional scenarios. The present work aims to provide an overview on CapEx associated with gasification technologies devoted to convert biomass or solid waste sources, with a view of reducing the carbon footprint during energy generation or production of new energy carriers. In addition, an analysis of technology cost trends over time using regression methods is also presented, as well as an evaluation of specific capital investments according to the amount of output products generated for different gasification facilities. The novelty of this work is focused on an analysis of CapEx of existing gasification technologies to obtain distinct products (energy and fuels), and to determine mathematical correlations relating technology costs with time and product output. For these purposes, a survey of data and categorization of gasification plants based on the final products was made, and mathematical regression methods were used to obtain the correlations, with a statistical analysis (coefficient of determination) for validation. Specific investments on liquid biofuel production plants exhibited the highest decreasing trend over time, while electricity production became the least attractive solution. Linear correlations of specific investment versus time fitted better for electricity production plants (R2 = 0.67), while those relating the product output were better for liquid biofuel plants through exponential regressions (R2 = 0.65).

Economic and Mathematical Modeling for the Process Management of the Company's Financial Flows

This paper presents an analysis of existing methods and models designed to solve the problem of planning the distribution of financial flows in the operational management cycle of the enterprise; it also offers tools for process management of enterprise financial flows based on the method of dynamic programming, which allows for determining the optimal combination of factors affecting the financial flow of the enterprise, taking into account existing restrictions on changes in the influencing parameters of the model. The current study develops an innovative model that maximizes the economic efficiency of investment in the sale of food products through retail chains and the practical implementation of the developed model based on the data from the financial reports of LLC "Kraft Heinz Vostok". The theoretical and methodological basis of the research includes the works of Russian and foreign experts in the fields of methodology of economic and mathematical modeling and decision-making, dynamic programming, system analysis, information approach to the analysis of systems, process management of enterprise financial flows, and human resource management. The author's methodology makes it possible to increase the company's profitability in key clients and categories in the range of 4 to 6 million dollars and to increase the return on investment by 10–17%. The scientifically innovative aim is to develop a toolkit for process management of enterprise financial flows, characterized by a systematic combination of methods of dynamic programming, social financial technologies, and economic evaluation of investments, which allows for the creation of mechanisms for managing the development of enterprises of all organizational and legal forms and the development of model projects of decision support systems with the prospects of their incorporation into existing information and analytical systems. Doi: 10.28991/ESJ-2023-07-03-017 Full Text: PDF

Development of a software tool for economic evaluation of health, safety, and environmental initiatives in a combined cycle power plant

Background: This study aimed to provide a comprehensive tool for the economic evaluation of investments in health, safety, and environment (HSE). Methods: This developmental cross-sectional study was conducted on the costs and benefits of HSE investments in a combined cycle power plant in Gilan province, 2021. The components of preventive measure costs (PMCs) and occupational accidents, diseases, and environmental pollution costs (ADPCs) were determined by an expert panel and review of scientific literature. The HSE economic assessment tool (HSE-EAT) was developed in Microsoft Excel software using macro/visual basic coding. The tool was designed to determine the efficient measures using the cost-benefit analysis (CBA) and the combination of control measures with the highest financial benefits using the cost-effectiveness analysis (CEA). Results: The application of the HSE-EAT in a combined cycle power plant showed the highest return on investment (ROI) for installation of drains for ducts of diesel fuel pipes and the lowest ROI value for renovation of emergency eyewash and shower. The ratio of indirect to direct benefits of implementing the preventive measures in the worst-case and best-case scenarios were 3.0 and 1.3, respectively. Conclusion: The HSE-EAT exhibited the advantages of comprehensiveness, flexibility, being user-friendly, and faster and more accurate calculations and could be also used for economic evaluation of health, safety and environmental initiatives in other industries and organizations.

Flattering or Really Understanding? Research on Stock Recommendations by Sell-Side Analysts in China

This article investigates whether the business relationships between brokerage firms and listed companies influence sell-side analysts’ stock recommendation ratings. Using the recommendation data of A-share listed companies disclosed by China’s domestic brokerage firms from 2004 to 2019, this article finds that sell-side analysts of brokerage firms that have securities underwriting relationships with listed companies are inclined to give those companies investment evaluations that are more-positive than evaluations from non-affiliated analysts. After a series of robustness tests and alleviating endogenous problems, such as the self-selection of underwriting relationships and of the sell-side analysts’ coverage samples, the empirical result remains unchanged. Using an event study method to compare differences in the cumulative abnormal returns of stocks during the event window of the recommendation releases, the authors find that it is information advantage rather than collusion of interests that leads affiliated sell-side analysts to issue more aggressive investment recommendations. Further research shows that “client pressure” will enhance the investment rating enthusiasm of analysts of related brokerage firms, whereas “peer pressure” will not weaken the investment rating enthusiasm of them, thus verifying the robustness of causality. The findings in this article enlighten the regulatory authorities and the capital market about the characteristics of stock recommendations of related brokerage firms’ analysts and the motives behind these recommendations, which is of great significance in protecting the interests of investors.

Soul Investment Analysis Based on POCD Framework and Financial Analysis

With the rise of the young group represented by the post-1995 generation, the social needs of the market also began to show new changes. Thus, Soul came into being, which is a social app, as well as a leading algorithm-driven virtual social playground where people can create, share, explore and connect. This article assesses the potential of Soul from the perspective of an entrepreneur looking to seize opportunities based on the POCD framework. Besides, the financial situation of Soul is analyzed from three aspects: the financing process, the comparison of competitors from the perspective of finance, and the risk factors in finance. In addition, the investment evaluation and forecast based on the above analysis. Obviously, Soul has carved out its own niche in the current social market. However, at the present stage, Soul does not provide users with additional ecological value, nor does it create a native unique cultural atmosphere. This is undoubtedly a serious potential risk for an investor. The purpose of this article is to provide investors and software developers with some advice and analysis on how to improve Soul in terms of both finance and software itself, so that Soul can further develop in the meta universe social space.

Prediction of Electric Load Neural Network Prediction Model for Big Data

In the background of information network and big data era, the digitalization and information network level of China's financial industry has been improved, and many advanced big data analysis technologies have been derived, among which mobile big data analysis model is the most widely used. Based on the concept of financial investment, mobile big data analysis model can not only improve the accuracy of financial data analysis, but also quickly establish the financial investment evaluation and prediction model, providing a reliable basis for financial investment and financial development strategy. In this regard, the author combines relevant literature and his own work experience to conduct a detailed study on mobile big data analysis model based on financial investment concept. Mobile big data analysis model is a kind of data analysis model established based on big data technology, which has the characteristics of strong data collection ability, high accuracy of data statistics and analysis, and high efficiency of data application. Based on the concept of financial investment, the mobile big data analysis model can not only improve the financial investment analysis function of the mobile big data analysis model, but also improve the financial risk analysis ability of the model, which provides a reliable basis for financial investment and financial risk management. Therefore, the following briefly outlines financial investment, then analyzes the importance of building mobile big data analysis model based on financial investment concept, and finally analyzes the method of building mobile big data analysis model based on financial investment concept and briefly discusses the typical application of the model.

Assessment of Innovation and Investment Attractiveness of the Western Ukrainian Regional Market of Tourist Services

Abstract Methodological approaches to assessing the level of innovation and investment attractiveness of the Western Ukrainian market of tourist services (WUMTS) substantiated the dependence of WUMTS on investment factors analyzed the level of competitiveness of WUMTS. In order to determine the level of dependence (independence) of WUMTS on investment and innovation factors, a paired linear regression was built for each of the regions (regions) included in the WUMTS, Volyn, Rivne, Lviv, Ternopil, Khmelnytsky, Zakarpattia, I. Frankivsk, Chernivtsi). In order to eliminate the disproportionate impact of the size of the impact of tourist services (the so-called effect of scale), the studied absolute indicators were converted into relative (growth rate). To assess the innovation and investment attractiveness of WUMTS, it was decided to apply methodological approaches to implement and evaluate the effectiveness of state and regional policy with further improvement in several groups of indicators, monitoring and evaluation of innovation, investment, and social development of the studied areas. Data, information of central executive bodies, regional state administrations, etc. The assessment of WUMTS development indicators was carried out by calculating the rating for each area and the overall rating for all areas. The rating assessment was performed by comparing the deviations of the values of indicators for each specific region under the conditions of the best values for the relevant (reporting) period and the corresponding ranking of regions from 1st to 8th position. As a result of calculations, the integrated rating was determined as the arithmetic means of the sum of ratings in all areas using the formula. The competitiveness of regional tourism markets should be assessed comprehensively, where two groups of indicators should be used to determine the competitiveness of an individual region: indicators of the tourism market and indicators of development of the region as a whole.

Machine Learning-Based Tap Temperature Prediction and Control for Optimized Power Consumption in Stainless Electric Arc Furnaces (EAF) of Steel Plants

The steel industry has been forced to switch from the traditional blast furnace to the electric arc furnace (EAF) process to reduce carbon emissions. However, EAF still relies entirely on the operators’ proficiency to determine the electrical power input. This study aims to enhance the efficiency of the EAF process by predicting the tap temperature in real time through a data-driven approach and by applying a system that automatically sets the input amount of power to the production site. We developed a tap temperature prediction model (TTPM) with a machine learning (ML)-based support vector regression (SVR) algorithm. The operation data of the stainless EAF, where the actual production work was carried out, were extracted, and the models using six ML algorithms were trained. The model validation results show that the model with an SVR radial basis function (RBF) algorithm resulted in the best performance with a root mean square error (RMSE) of 20.14. The SVR algorithm performed better than the others for features such as noise. As a result of a five-month analysis of the operating performance of the developed TTPM for the stainless EAF, the tap temperature deviation decreased by 17% and the average power consumption decreased by 282 kWh/heat compared with the operation that depended on the operator’s skill. In the results of the economic evaluation of the facility investment, the economic feasibility was found to be sufficient, with an internal rate of return (IRR) of 35.8%. Applying the developed TTPM to the stainless EAF and successfully operating it for ten months verified the system’s reliability. In terms of the increasing proportion of EAF production used to decarbonize the steel industry, it is expected that various studies will be conducted more actively to improve the efficiency of the EAF process in the future. This study contributes to the improvement of steel companies’ manufacturing competitiveness and the carbon neutrality of the steel industry by achieving the energy and production efficiency improvements associated with the EAF process.

Coffee Industry Analysis Based on Indicators: Evidence from Starbucks, Luckin and Nestle S.A.

Coffee is a favorite beverage worldwide, and its unique ability to keep people awake and energized has dramatically increased the sales volume. Its high popularity has led to a considerable investment market. Therefore, whether the coffee industry is worth investing in and how to evaluate it has become one of the most critical research classes today. Based on previous investigations, most investment evaluations of the coffee industry have focused on companies in the same geographic area. However, there is a research gap in whether the international coffee industry is worth investing in. On this basis, this study will analyze whether the coffee industry is worth investing in by collecting data on stock prices and financial reports as well as calculate WACC values and compare them using the data. According to the analysis, the WACC values of all three companies selected are generally high, which means that the investment risk is high. It is indicated that the coffee industry is not worth investing in nowadays because of the high risk and high cost. These results shed light on guiding further exploration of how to do the right choice of investment in the coffee market.

Protocol for a realist and social return on investment evaluation of the use of patient-reported outcomes in four value-based healthcare programmes

IntroductionThere is growing recognition that in order to remain sustainable, the UK’s National Health Service must deliver the best patient outcomes within available resources. This focus on outcomes relative to...

ECONOMIC EFFICIENCY ASSESSMENT OF INVESTMENTS IN AGRICULTURAL PRODUCTION

The purpose of this study is to assess the economic benefits of agricultural production and provide guidance to manufacturers and investors interested in agriculture. This paper applies dynamic efficiency evaluation methods i.e. net present value, profitability index, and internal rate of return, together with the sensitivity analysis that is useful in cases of market turbulences. The presented investment is purchasing 10 hectares of arable land and cultivating two alternative crops: corn and soybeans. Research results and projections imply that both scenarios are acceptable and economically profitable with the preference for the cultivation of corn giving better economic efficiency. This study can provoke further investment evaluations with dynamic capital budgeting methods in other crops or implementation of mechanization in agricultural production.

Policy assessment in photovoltaic development using system dynamics: Case study of power generation in Iran

The development of renewable energies is inevitable due to the outstanding share of energy section in greenhouse gas production. This research presents a system dynamics model for a photovoltaic (PV) ecosystem. The model considers the inherent and economic properties of supportive policies and reflects their effects on investment evaluation. The development of PV power generation can be modelled as S-shape growth if the adjustment and elimination of supportive policies occur on time. Delay in policy change, energy market fluctuations, and the interaction of influential factors may cause overshoot or oscillation in the ecosystem. After validation and case study, measures are proposed for comprehensive understanding of different states. Compatibility of supportive policies with state of the PV ecosystem facilitates the development path. The results show that the deployment of PV in Iran prevents 101 million tons of CO2 production in 20 years. However, the current state of power purchase agreement (PPA) policy does not guarantee the economic feasibility of investment in PV power generation, which explains Iran's slow development and expansion in this field. The model is beneficial for both developed and developing countries, especially for those in the Middle East with massive fossil fuel resources, to modify supportive policies based on the state of their PV ecosystem.

Socio-economic approach to transport investments evaluation

Background: Transport plays a crucial role in socio-economic and social processes. Despite the fact that transport can be considered as an independent industry, and transport development projects can be considered as independent business projects, the spectrum of transport influence has not yet been fully studied. A qualitative examination of the spheres of influence of transport shows its impact on all significant aspects of socio-economic relations in society.
 Nevertheless, classical methods of financial management are used to assess the effectiveness of investments in transport, which do not allow to fully reflect the effects arising from the implementation of such investments.
 As practice shows, the use of classical approaches does not allow us to reliably assess the effectiveness of investments in transport. The choice of approaches to assessment is directly dependent on the socio-economic model of the state. The capitalist model focuses on the income received from the implementation of any investment project, whereas the socially oriented model peculiar to Russia is initially focused on the formation of the public good.
 The latter approach, in our opinion, is strategically more advantageous on a national scale and requires wide dissemination for the purposes of financial and economic analysis
 Aim: to consider the list of methods for evaluating investments in transport and determine a set of factors that require consideration for a socially oriented economy.
 Materials and methods: the research methodology is based on the analysis of methods of financial and economic evaluation of investment projects, socio-economic analysis, as well as macroeconomic methods. The information base of the study is based on official legal and methodological information of the authorities of the Russian Federation.
 Results: as a result of the study, a list of factors that need to be taken into account when assessing the effectiveness of investments in transport within the framework of the paradigm of socially oriented public administration is determined.
 Conclusion: the study confirms that the methods currently used to assess the effectiveness of investments in transport do not fully reflect the effects arising from their implementation. The proposed approach to determining the list of socio-economic effects resulting from the impact of transport projects will improve the quality of management decisions in the transport sector.

Integrated approach to solving the mining-environmental issues based on the analysis of internal and external factors

Introduction. ESG – Environmental, Social and Corporate Governance is a set of characteristics of company management, in which the involvement of this company in solving environmental, social and management problems is achieved. ESG criteria appeared as a response to environmental degradation, global warming and increasing economic inequality between rich and poor countries, which created additional ground for the emergence and development of new investment evaluation criteria. Modern society has begun to impose additional requirements not only to the business activities of companies and their financial statements, but started to evaluate it in terms of investments in sustainable development. Methodology. It seems that the ESG-approach could be an integral part of the general approach to the description and evaluation of the functioning of a nature-technology system which is based on the mining of mineral resources. The article shows the possibility of depiction of a mining enterprise as a nature-technology ESG-system for solving combined mining and environmental issues. Results and their analysis. As an example a mining system is described consisting of three subsystems, presented in the form of intersecting sets: “mining operations that are a source of nitrogen pollution of drainage waters” – “natural-technical complex for the purification of polluted waters” – “organization of the discharge of purified waters”. Such a representation of the said system fits into the generalized scheme of the socially-centric approach to ESG-assessment of investments. The area of intersection of the sets is the area where the optimal solution of the problem lies in terms of achieving an acceptable concentrations of nitrogen compounds when the purified water is discharged to the water body. The said problem could be solved by an appropriate combination of the technological, management and investment decisions. Conclusions. Making such kind of decisions in relation to a nature-technology system requires a periodic assessment of the system external and internal environment as well as in-system interconnections. For such type of assessments SWOT and PESTEL methodologies can be effectively applied being spread from economic factors assessments only to a wide range of environmental, technological and environmentally related economic factors.

Evaluation of companies (Magazine Luiza SA) and investments in the E-commerce area during the Covid-19 pandemic period

In view of the economic impact and the changes in life habits caused by the Covid-19 pandemic in Brazil, the main objective of this article refers to the application of the fundamentalist valuation method of companies, called discounted cash flow, during the beginning, the course and the end of the pandemic period. The company in question is Magazine Luiza SA, given the positive variation in the value of the company's shares during this interval, as well as the investments made in digital transformation and the consequent significant increase in sales. The methodology adopted consists of collecting data disclosed by the company itself and, through the application of FCFF, performing the company's evaluation during the years 2019 to 2022, which characterized the duration of the pandemic, in addition to performing a projection based on the analysis performed until the year 2028. The analysis obtained showed slow and steady growth in the pre-pandemic period, that the initial pandemic period, between the years 2019 and 2020 represented for Magazine Luiza, contrary to what is expected for a retail company, a period of accelerated growth, which can be associated with the investments made for the digital transformation. Moreover, the projection obtained indicates, for the company, an initial crisis in the post-pandemic period, given the current political-economic environment. However, it presents trends for a recovery followed by subsequent accelerated growth.

A Literature Study on the Capital Asset Pricing Model

Capital Asset Pricing Model (CAPM) is an important theory in financial economics. It was based on Markowitz's Modern Asset Allocation Theory (MPT) and proposed by Sharpe. This model expresses the relationship between risk coefficient, asset return rate, and systematic risks by simple mathematical formulas. The model has four advantages, handling of risks when evaluating investment behavior, accuracy when estimating equity capital, relatively reliable and better than Weighted Average Cost of Capital (WACC) in investment evaluation. CAPM also has some weakness, consisting of variables and application in investment evaluation. There are three variables in CAPM model, risk-free rate of return, equity risk premium and beta. The weakness about application in investment evaluation shows that in beta of projects and firms are different, complex restructure and periods. The Arbitrage Pricing Theory (APT) can be an option of CAPM, and it is a more flexible and complex model compared with CAPM. However, the latest research proves that Portfolio Theory has very big problems. High-risky assets do not necessarily have high returns. This view may be embodied in "low-risk anomalies" and "Idiosyncratic Volatility". In the future, researchers will introduce more elements for CAPM to improve accuracy, or develop new models.

Comparison Between NPV and IRR: Evaluation of Investment

The net present value (NPV) and internal rate of return (IRR) are frequently used criteria for choosing capital investment projects which has been used for long days since they been created. But these two indicators may lead to contrary result in certain situations. This difference caused the debate that last more than a century about which investment deciding methods is better. Naturally, research on the inadequacy of these two methods has also continued for a long time and achieved many results such as a more reliable IRR calculation method - MIRR, the analysis of multiple roots in the IRR calculation in complex cases to determine the final result. This paper gives the brief definitions of NPV and IRR, and how they are calculated. The questions of when to use different investment decision-making methods is also answered in the paper. After that, the advantages and disadvantages of NPV and IRR were analyzed. At the same time, this paper has also fully researched the improvement of the deficiencies of two investment deciding methods. Finally, this paper compares NPV and IRR, and analyzes why these two methods lead to different results in some certain situations and which investment decision methods is relatively better in investment and draw the final conclusion.

Valuation and Industry Analysis of New Energy Vehicles

With the increasingly harsh global environment, the new energy industry has received strong support from national policies. On this basis, the enthusiasm of relevant departments and enterprises for the new energy industry has increased. This paper discusses the development of new energy vehicles by analyzing the development status, market development prospects and limitations of new energy vehicles. In addition, we conduct a corresponding valuation analysis of BYD Automobile, which is a leader in the new energy vehicles of China. According to the analysis, the intrinsic value of BYD's stock will be lower than its stock value, indicating that the investment value is higher perceived at this stage. As a consequence, the investment in BYD nowadays ought to be reduced in the future. These results shed light on offering better understanding of the development status and limitations of new energy vehicles, as well as providing a guideline for investment evaluation of the industry.