Investment Risk Research Articles

ЭКОНОМИЧЕСКАЯ СУЩНОСТЬ И ОСОБЕННОСТИ РИСКОВ В ИНВЕСТИЦИОННОЙ ДЕЯТЕЛЬНОСТИ

Investment risk assessment and management is an important aspect of successful investing that requires specialized knowledge and strategies. Risk analysis and forecasting techniques help investors make informed decisions and minimize potential losses. Effective risk management helps to minimize losses and maximize returns through various investment techniques and strategies. The ability to constantly monitor financial market conditions, analyze economic and political events and respond quickly to changes helps to reduce risk and maximize returns on investment activities. This article discusses the features of risk in investment activities and the factors that play the most important role in assessing the risk of investment projects, including their classification, causes of occurrence and methods of decision-making.

Factors Influencing the Financing of Renewable Energy Projects for Sustainable Development Goals with a Fuzzy Cognitive Map Approach

Objective: The aim of this study is to analyze the factors influencing the financing of renewable energy projects to achieve sustainable development goals using a fuzzy cognitive map approach. Methodology: This applied research was conducted in both qualitative and quantitative sections. In the qualitative section, content analysis with a conventional and directed approach was employed, and in the quantitative section, a causal method was used. Data were collected through semi-structured interviews in the qualitative phase and pairwise comparison questionnaires in the quantitative phase. The participants were senior managers and experts from the Renewable Energy and Energy Efficiency Organization (SATBA), selected using purposive and theoretical sampling (a total of 21 participants). Findings: The qualitative findings revealed key influencing factors, including "social responsibility," "direct and indirect government support," "sustainable economic development," "environmental sustainability," "support from financial funds," "commercial creditworthiness of financial suppliers," "foresight and capital planning," "financial capacities," "investment return policies," "empowerment of financial institutions," "renewable energy development policies," "investment culture in renewable energy," and "optimal management of investment risks." The fuzzy cognitive map results showed that "direct and indirect government support for the energy industry" had the highest output and influence, while "commercial creditworthiness of financial suppliers" had the highest input power and susceptibility to influence. Conclusion: This study provides a comprehensive analysis of the factors affecting the financing of renewable energy projects. It highlights the critical roles of government support policies and the commercial creditworthiness of financial suppliers in the success of these projects, suggesting that improvements in these areas can contribute to achieving sustainable development goals.

International business expansion and merger investment risk strategies by promoting innovation and circular economy: A case study analysis

This research paper investigates how Alpha, a leading European company in the architectural aluminum systems sector, adopts its international business expansion and merger strategy and integration of innovation and circular economy principles. The study focuses on Alpha’s dedication to sustainability through innovative methods, emphasizing the company’s efforts in recycling, waste management, and energy efficiency. As companies recognize their responsibility to reduce their environmental impact, they have begun by making changes within their own production sites and offices and are now extending their efforts to their supply chains and beyond. The circular economy offers solutions to these problems. Various studies indicate that the circular economy fosters economic growth by increasing employment and utilizing resources more efficiently. By embracing a circular economy approach, Alpha illustrates how environmental sustainability and economic growth can coexist. This study could serve as a company example strategy that tries to follow and achieve a significant transformation necessary for net-zero emissions and is transformed in order to be committed to renewable energy, renewable resources, and high-grade recycling.

G factor of the ESG agenda in the context of sustainable development of Russian electric power companies

Reducing associated investment risks in the context of the modern ESG agenda requires a certain transformation of corporate governance in Russian power generation companies. In order to achieve this objective, a correlation analysis was carried out between the generalized G components of the ESG agenda and the principles outlined in the Russian Corporate Governance Code (Code). The priority G components of authoritative international rating agencies and the largest foreign companies, leading national rating agencies, and the Bank of Russia were examined. The study involved the analysis of Russian power generation companies that are voluntarily enhancing their corporate governance practices. The results of a general assessment of their corporate governance and additional analysis of the fulfilment of the criteria for each section of the Code are presented. The data obtained are summarized and proposals for further transformations of corporate governance in these companies are formulated. These proposals are highly relevant in the context of sustainable development of these companies. They concern the reformatting of the ownership structure and business ethics into separate G components with an appropriate set of evaluation criteria, and the introduction of modern compliance control.

АНАЛІЗУВАННЯ ІНВЕСТИЦІЙНОГО КЛІМАТУ УКРАЇНИ В ПЕРІОД ВОЄННОГО СТАНУ

For Ukraine, the investment climate is one of the main factors in ensuring its stable development, which means that all economic activities in the country are on a sustainable socio-economic development path. The investment climate is an important and determining factor in the decision of foreign or domestic investors to invest. It is a combination of investment attractiveness factors and investment risk factors. The article provides a detailed analysis of Ukraine's investment attractiveness for foreign investors. The problematic aspects of legislative and managerial nature in attracting foreign investment are highlighted. The real state of investment attraction in 2019–2022 is reflected. The index of investment attractiveness for 2019–2023 is investigated. The dynamics and structure of foreign direct investment in the economy of Ukraine by types of economic activity for 2019–2022 are presented. Foreign investment is undoubtedly one of the leading drivers of economic growth for many countries, including Ukraine. Foreign investment can increase competition in the market by investing in lagging enterprises, improve the welfare of citizens, and strengthen the competitiveness of recipient enterprises on the global stage. Studies have shown that the net inflow of foreign direct investment significantly exceeds the net outflow. Although the investment attractiveness index is still low, the number of top managers who believe that new investments in Ukraine will be profitable has almost doubled. The government continues to develop legislation to capitalize on this potential with numerous draft laws on corporate governance and other economic reforms aimed at bringing Ukraine in line with EU standards and regulations currently being advanced. In Ukraine, the most attractive sectors of the economy for foreign investors are financial and insurance activities, trade, and information and communications. Ukraine's increasing movement toward integration with the EU opens up potential opportunities for investors seeking access to the EU market. The support from the European community and the United States is significant. After Ukraine's victory, the investment attractiveness of our country will certainly increase.

Introducing an Innovative Approach to Mitigate Investment Risk in Financial Markets: A Case Study of Nikkei 225

Introducing an Innovative Approach to Mitigate Investment Risk in Financial Markets: A Case Study of Nikkei 225

OPTIMIZATION OF THE PROCESS OF SELECTION OF TECHNOLOGIES AND EQUIPMENT FOR PURIFICATION OF WASTEWATER OF ELECTROPLATE PRODUCTION

More and more attention is being paid to energy and resource efficiency issues, which is why for existing technological processes the solution of optimization problems comes to the fore in order to optimize material costs. No less important is the assessment of the human resource, as well a minimizing the possibility of errors at the stage of making a decision on the implementation / design of new processes. It is the environmental sphere that is associated with a high degree of investment risks and requires a careful approach to justifying the introduction of environmental technologies. As part of the work done, the concept of automated decision making was proposed and an economic and mathematical model was developed for solving the optimization problem for choosing a technology or equipment for wastewater treatment systems of an enterprise using the example of electrochemical enterprises (electroplating production) at the stage of justifying investments. As the main tool for processing input data, it is proposed to use software systems based on the use of partial-integer linear programming methods. As input parameters of the system, the initial concentrations of pollutants, volume flow and the required cleaning efficiency are selected. The main technologies for the treatment and neutralization of wastewater from galvanic production, which are currently used or included in the list of the best available technologies, are presented, and a model is proposed that allows the choice of methods and instrumentation for multi-stage treatment processes to achieve the required quality of discharged water with minimal integral costs for the creation and operation of the designed system. The proposed mathematical model can be used both as a training tool for training specialists in water treatment, and for management personnel in the process of selecting and justifying environmental protection measures or at the stage of supervision of equipment suppliers.

ФАКТОРИ ІНВЕСТИЦІЙНОЇ ПРИВАБЛИВОСТІ УКРАЇНИ

The article examines factors of Ukraine's investment attractiveness and ways of its activation. The modern legislative regulation of the activation of investment activities and the statistical dynamics of investments in the domestic economy are considered. It was noted about the effective legislative incentives of the laws of Ukraine "Regarding risk insurance of investments in Ukraine against war risks" and "On state support of investment projects with significant investments in Ukraine". The main tasks of the legislative decisions of the government during the full-scale military invasion of the occupiers are the activation and support of the innovative environment in Ukraine, the attraction of strategic investors to the domestic economy, and the provision of state support for large investment projects. This especially applies to such branches of the national economy as processing industry, extraction and beneficiation of minerals, transport, logistics, health care, etc. But this support will refer to large investment projects, namely, investment amounts must be equivalent to 12 million euros and the term of implementation of such projects should not exceed 5 years. The most active international companies are noted. Guarantees offered by the domestic government to foreign investors are given. Actual and planned reinvestments since the beginning of the military invasion of Ukraine are given. The international rankings of Ukraine are given. According to the rating compiled on the basis of research by Aswat Damodaran from the Stern School of Business at New York University, Ukraine is among the 20 countries in the world with a high investment risk. The rating was formed with the factors of political risk, economic structure, economic growth prospects, fiscal flexibility, debt burden of the public administration sector, stability of the financial sector, flexibility of monetary policy and gross and net external debt. The areas of activation of investment attractiveness in Ukraine are recommended - in the state and banking systems, and in the sphere of regulation of the market environment.

ВИСОКОПЕРСПЕКТИВНІ ОБ'ЄКТИ МІНЕРАЛЬНО-СИРОВИННОЇ БАЗИ УКРАЇНИ. ЧАСТИНА 2. НЕМЕТАЛІЧНІ КОРИСНІ КОПАЛИНИ

A brief description of highly prospective objects of the mineral-raw material base of non-metallic minerals of Ukraine is given. Based on an expert assessment of their investment attractiveness, the following types of raw materials were selected as the most prospective: kaolin (Zhezhelivske, Glukhovetske, Turbivske, Velikogadomynetske deposits); facing stones (Slipchytske and Golovinske deposits of labradorite; Omelyanivske, Tokivske, Kapustianske, Lyznitske and Kornynske deposits of granite); refractory clays (Chasiv-Yarske, Novoraiske, Volodymyrivske, Pologivske); graphite (Zavallivske, Burtynske (Khmelivska section) deposits); granate (Slobidske, Ivanivske); quartz raw materials (Husarivske, Velikohlibovitske); piezoquartz (Volynske); phosphorites (Zhvanske); limestones for the sugar industry (Zamok, Lysohirka); bentonite (Cherkaske deposit). Among the non-metallic minerals of Ukraine, these deposits have the highest level of investment attractiveness, the lowest investment risks, and can be recommended as priority objects for investment in their study and industrial development. To determine the investment prospects of concrete objects, a preliminary geological and economic assessment of the feasibility and profitability of their industrial development is necessary.

Financial investment risk analysis and countermeasures research based on CVaR-GARCH model

Abstract In this paper, based on the vector autoregressive algorithm, the conditional value-at-risk algorithm is used to compute the optimal portfolio, and the mean-CVaR model oriented to portfolio optimization is established based on the mean-variance model. To explain the volatility accumulation characteristics of financial asset return series, the autoregressive conditional heteroskedasticity model with CvaR is designed. After the design and optimization of the algorithm are completed, the daily closing price of a commodity futures contract, CSI 300 and the stock situation of different companies, and the daily closing index data of the financial index of a city are collected, and the three major groups of data are tested for the model of this paper. The results show that the maximum value of the CVaR-GARCH model at 95% and 90% confidence levels is generally 4000~6000, which is higher than that of the VaR model alone at 1000~2000. The difference between the actual loss and the loss predicted by the model in this paper is 88.618~279.181. The number of failures at 90% confidence level is 44. The number of failures at 95% confidence level is 31, while the number of failures at 99% confidence level is 1,000~1,000. The number of failures at 99% confidence level is 1,000~1,000. Number of times is 31. At a 99% confidence level, the number of failures is 11. This results in a generalized failure rate of 6.03%. Investors can make program adjustments with more accuracy due to the model in this paper’s ability to predict stock market risk.

Investment risk assessment based on improved BP neural network

Investment risk assessment based on improved BP neural network

Formation of the financial policy of Russian agro-industrial enterprises in modern conditions

Financial policy plays a key role in the management of agro-industrial enterprises, especially in the context of modern economic dynamics and changes. Currently, companies in the agro-industrial sector of Russia are at the stage of active growth, which is due to the systematic support from the state. There is a steady increase in the flow of investments, an increase in the number of new projects and investor activity. The introduction of Western sanctions led to a reduction in foreign investment due to the unstable political situation, but contributed to growth through import substitution programs. This article will examine how the financial policy of companies is formed as a result of investments in various sectors of agriculture. A fuzzy model for assessing investment risks in an agro-industrial holding for technical equipment using Fuzzy Tech technologies is also provided.

Research on Power Investment and Expansion Planning Considering Coal-fired Power Capacity and Electricity Price in Market-Driven Environment

The market-oriented environment and the shift away from the coal-fired power are inevitable trends in the future development of electric power energy. Based on this, this article establishes a dual-level model for power investment expansion planning with wind power system in an oligopoly competitive electricity market. In the upper-level model, power generation companies make investment decisions and formulate their bidding strategies in market transactions, while the lower-level model simulates the day-ahead market clearing process under the centralized bidding and trading mode. To encourage the transition from coal-fired power plants, a model for expected annual operating revenue of coal-fired power companies under a dual pricing system is proposed, and the conditional value-at-risk (CVaR) is used to measure the investment risk brought by the uncertainty of competitors in the investment planning game for power generation companies. The numerical results verify the effectiveness of the proposed model and method.

A model to define a real estate investment risk index for the administrative municipalities of Naples

Real estate redevelopment processes represent an important avenue for achieving sustainable development goals, but at the same time, they pose complex and opaque decision-making problems. Most existing risk assessment tools involve aggregate-scale analysis or require knowledge of extensive project financial data, which is often not yet available under ex-ante evaluation conditions. The aim of the work is to define a specific index through a spatial decision support system based on an innovative model that enables public and private entities to conduct effective ex-ante risk assessment at a sub-municipal territorial scale for public-private partnership risks. The proposed model adopts the flexibility of the Analytic Hierarchy Process (AHP) technique and the GIS system’s ability to clearly display the spatial distribution of real estate risk.

Neural Networks for Portfolio Analysis With Cardinality Constraints.

Portfolio analysis is a crucial subject within modern finance. However, the classical Markowitz model, which was awarded the Nobel Prize in Economics in 1991, faces new challenges in contemporary financial environments. Specifically, it fails to consider transaction costs and cardinality constraints, which have become increasingly critical factors, particularly in the era of high-frequency trading. To address these limitations, this research is motivated by the successful application of machine learning tools in various engineering disciplines. In this work, three novel dynamic neural networks are proposed to tackle nonconvex portfolio optimization under the presence of transaction costs and cardinality constraints. The neural dynamics are intentionally designed to exploit the structural characteristics of the problem, and the proposed models are rigorously proven to achieve global convergence. To validate their effectiveness, experimental analysis is conducted using real stock market data of companies listed in the Dow Jones Index (DJI), covering the period from November 8, 2021 to November 8, 2022, encompassing an entire year. The results demonstrate the efficacy of the proposed methods. Notably, the proposed model achieves a substantial reduction in costs (which combines investment risk and reward) by as much as 56.71% compared with portfolios that are averagely selected.

Dividend problem of an investment risk model under random observation

<p>We mainly studied the dividend payout with a two-sided jumps risk model under random observation. The two-sided jumps in the model represent random claims and random returns. First, we obtained the integral differential equation of the expected dividend under the boundary conditions. Because the equations cannot be solved directly under normal circumstances, we chose the sinc numerical method here to approximate the solution of the equations. Then the error analysis of the approximate solution was carried out to illustrate the rationality of the numerical method. Finally, some concrete numerical examples were given.</p>

The Board of Commissioners Moderates Cash Holding and Profitability on Earnings Management

One of the parameters that isused as a reference for investors and shareholders in making financial decisions is profit information in the company's financial reports. The assumption that companies with stable profits reflect optimal performance and have low investment risk encourages managers to make efforts to provide a good picture of performance, one of which is by carrying out earnings management.Deviant earnings management practices are carried out when information asymmetry occurs which arises from moral hazard and encourages management to behave opportunistically, resulting in poor earnings management, which is carried out in an inadequate manner.Earnings management is influenced by several factors, including cash holding, profitability and the board of commissioners. This research aims to examine the influence of cash holding and profitability through the interaction of the board of commissioners which is proportional to the proportion of independent board of commissioners as an internal mechanism for Good Corporate Governance within the company. The population used is all manufacturing companies listed on the Indonesia Stock Exchange, using purposive sampling to obtain 50 selected companies in the 2020-2023 observation period, with a total data sample of 200. Moderated Regression Analysis (MRA) is used as a technique to test the relationship between variables.The test results show that partially cash holding, profitability and the board of commissioners have a significant effect on earnings management. The test results alsoshow that the independent board of commissioners is able to moderate cash holding and profitability on earnings management.

Economic investment risk prediction model and algorithm based on data mining method

Economic investment risk prediction model and algorithm based on data mining method

Optimization analysis of blockchain technology in enterprise digital financial management

Abstract The rise of mobile Internet has not only changed the business model of many enterprises, but also had a profound impact on the financial management model of enterprises. Based on this, this paper applies blockchain technology to enterprise financial management, using decision trees and information entropy alignment to optimize and promote its digital transformation. Regarding optimizing financial management processes, blockchain technology converts the enterprise’s financial management data into a distributed ledger. It integrates it with information entropy to create a digital financial data decision tree. This paper takes enterprise A as the research object, after optimizing the financial management process with blockchain technology, enterprise A’s financing ability is enhanced, and the current ratio as a whole maintains an upward state, reaching a maximum value of 0.86 in 2021, and then it has been maintained at about 0.8, indicating that the optimized short-term solvency capacity has been significantly improved. The total debt amount of enterprises is decreasing yearly, falling to 35.26 billion yuan in 2023. The amount of owners’ equity has shown an upward trend and has remained at a high level of 25 billion yuan since 2021. Therefore, blockchain technology strengthens the financial management capabilities of enterprises and explores a feasible path to reduce investment risks.

ДИВЕРСИФИКАЦИЯ ИНВЕСТИЦИОННЫХ РИСКОВ ПРИ УПРАВЛЕНИИ АКТИВАМИ НА ФОНДОВОМ РЫНКЕ

This article deals with an important problem for any entrepreneur-investor - identification of the main methods to combat investment risks. In order to fulfill the task we have considered the theoretical basis of risks in the sphere of investment, and also we have carried out works on making a classification of risks by main types. Undoubtedly, the chosen topic of research is very relevant and to date, because almost every businessman in the course of business activities almost every day faces many varieties of risks. Confirmation of this thought is the fact that any entrepreneurial activity, as a rule, goes along with various risks. And the main goal of any entrepreneur is to maximize profits with minimal costs. But to fulfill this goal requires special knowledge and skills that will help the investor to choose and apply the best methods to maximize the effective use of company resources.