ECONOMIC-INSTITUTIONAL PROBLEMS OF EUROPEAN REMILITARIZATION

When managing the processes of implementing investment and construction projects, conditions of varying levels of uncertainty arise, giving rise to risky situations. Ignoring risk situations when implementing investment and construction projects leads to the emergence of risk combinations and increased risk costs and eliminating their consequences. Determining the risk intensity of a risk situation (combination) is becoming increasingly relevant; in this regard, the relevance of developing a model for monitoring the total cost of risks of investment and construction projects is increasing.
 The purpose of the study is to develop an economic and mathematical model for monitoring the total cost of risks of investment and construction projects. It has been established that in the military sphere, the amount of material costs for product development is significantly influenced by risks associated with the internal and external environment. This article examines existing models of investment and construction projects and identifies their distinctive aspects. The novelty of the ongoing research lies in the author’s approach to developing a model for monitoring the total cost of risks at various stages of the life cycle of investment and construction projects. The practical significance of the results lies in the possibility of monitoring the total cost of risks of investment and construction projects at all stages of its life cycle, estimating, based on the proposed model, the final total cost of investment and construction projects by summing up all the total costs of risks of the stages of investment and construction projects. These measures are aimed at preventing a risk situation or risk combination and ensuring the implementation of investment and construction projects. A design-process approach to feasibility studies and process management of investment and construction projects is proposed.
 Recommendations for applying the results obtained are the need to assess the total cost of risks of investment and construction projects at all stages of its life cycle in order to determine the source of its occurrence.

Making the investment decisions means making some of the most subtle and most important decisions with long-term implications. Investors expect their investments to bring them returns greater than the invested funds, i.e. they want the projects to achieve a positive net present value. Since investing means making an investment in the present in order to achieve certain effects in the future, the risk is an inevitable part of the investment process. It refers to uncertainty that the expected effects of the project mayl not be achieved, or may not reach those expected. Risk and uncertainty are some of the main characteristics of any project. The risk of an investment project is the variability of the project cash flows in relation to the expected flows. The project with higher variability of net cash flows and lower probability of acceptance is more risky than a project whose cash flows are more stable and with a better chance of acceptance. The degree of risk of the projects varies according to the nature of projects. In assessing the risk of the project, the Sensitivity analysis, the Scenario analysis, the Simulation analysis, and the Decision Tree analysis are used. The scope of this paper is the identification and explanation of the risk sources, factors and types present in investment projects. The aim is to identify, explain and illustrate with practical examples the methods for measuring the risk of investment projects and its impact on the cost of capital. Starting from the above objective, the following hypothesis is defined: there is no universal method of evaluating the risk of investment projects and measuring its impact on the cost of capital, which is applicable in any circumstances. To prove or to dispute the above hypothesis, the paper is based on the descriptive and analytical methods.

This article is devoted to the study of improving the use of expert assessments for risk analysis, affecting the effectiveness of the implementation of a comprehensive investment project in the global instability of the economic space. The existing methods of expert assessments and Monte-Carlo simulation methods used to identify and assess the risks of investment projects are described. A systematic analysis of the main risks of investment projects in the context of globalization and risk management methods was carried out. The author’s classification of risks of investment projects using the criteria of economic efficiency has been developed. An approach to risk analysis, affecting the effectiveness of the implementation of complex investment projects based on existing methods using the concept of the “reduced” random factor, is proposed. This approach is used to analyse project implementation risks in the conditions of market instability with the development of recommendations for managing the main project risks. The author’s risk classification of investment projects is important at the stage of analysing risks arising from the study of sales markets, as well as during the management decision-making process, which minimizes the possible adverse impact on an organization, including losses caused by random events. The proposed approach can be applied to the analysis, express-analysis and risk management of long-term complex investment projects in the conditions of global instability of the economic space.

With the development of the economy and real-time embedded systems and the progress of science and technology, people’s economic income forms have undergone tremendous changes, and the concept of financial management has become clearer in people’s property income arrangements. Project investment is one of the most popular financial management methods in the era of big data. Both large enterprise groups and individual petty bourgeoisie groups have begun to pay attention to the risks and benefits brought by the new financial management method of project investment. This paper’s goal is to develop a fuzzy comprehensive evaluation (FCE) model for project investment risk based on computer vision technology and explore the application of computer vision technology in project investment risk evaluation. This article first uses a real-time embedded system to understand the basic process of project investment and select 10 investment experts for risk assessment, risks, and causes of the risks through literature research and case analysis. Then, this paper establishes a model of fuzzy comprehensive evaluation of project investment risk through computer vision technology, real-time embedded systems, and neural network models in big data and artificial intelligence technology to realize the analysis and prediction of project investment risk. The fuzzy comprehensive evaluation method and analytic hierarchy process (AHP) are used in this evaluation model to evaluate and forecast project investment risks. In addition, this paper also trains and tests the risk evaluation model of this research through the support vector machine classification algorithm, the real-time embedded system, and the average random consistency index. The research shows that the fuzzy comprehensive evaluation model of this study has higher accuracy for project investment risk evaluation than other risk evaluation methods. For example, for the investment risk of chemical fiber projects, this research model evaluated the factors such as organization, management, technology, and economy and found that the risks were all higher than 21.36%, which concluded that the overall investment risk of chemical fiber projects was relatively high.

본 연구는 최근 급격하게 상승하는 전세가격에 의해 한국시장에 존재하는 독특한 주거형태인 전세의 사용가치와 서민 주거안정에 대한 심각한 사회 문제가 대두됨에 따라 주거부담 완화를 위한 금융 정책 수립의 올바른 방향을 모색하기 위해 전세보증대출에 영향을 미치는 직접적 요인과 시장 변동성에 대해 분석하고자 했다. 이에 전세가격, 매매가격, 대출금리 등과 같은 전세보증대출 수요에 영향을 미치는 직접적인 관련 변수를 정의하고, 분석 데이터들의 동태적인 설명을 위해 시계열 분석 모형인 벡터오차수정모형(Vector Error Correction Model, VECM)을 이용하였다. 2010년 1월부터 2014년 12월까지의 전세가격과 대출에 관한 은행 자료들을 활용하여 분석한 결과, 전세가격의 상승은 대출금리 인하나 주택 매매가격 상승보다 전세보증대출 증가의 직접적인 요인으로 작용하고 있음을 확인할 수 있었다. With the rapid increase in the price of house lease, a unique housing form in Korea, a serious social issue has been raised as to the use value of house lease and residence stability of the ordinary people. This study thus aimed to analyze the direct factors that affect lease guaranteed loan and market volatility in order to explore the right direction of financial policy to reduce housing burdens. To this end, the direct variables affecting house lease guaranteed loan, including lease price, transaction price and lending rate, were defined. Vector Error Correction Model (VECM), a time series analysis, was employed to dynamically explain the data. Based on the house lease prices and bank data on loans between January 2010 and December 2014, it was found that the increase in lease price was the direct result of the increase in lease guaranteed loan, not that of the decrease in lending rate or increase in housing transaction price.

Objective: When assessing the risks of an investment project, it is necessary to take into account the uniqueness of each project, which requires the search for completely new solutions, the application and combination of various tools and assessment methods for the effective implementation of the project. The objective is to develop and test an algorithm for express risk assessment of an investment project using an integral risk factor. In order to achieve this the following issues are considered: the development of the risk theory and the main stages of its development, the modern concept of risk and risk classification in the context of investment projects, modern methods for assessing the risks of investment projects and their problems. Next, the concept of an integral risk factor is introduced and an express assessment of risks of a local investment project is carried out using an integral risk factor. Methods: The classical methods of identifying and assessing project risks (the method of expert estimates, the Monte-Carlo simulation method), the comparative method, analysis, and synthesis are used in the study. Results: The basic characteristics of the concept of “risk” inherent in the modern understanding were formulated. A new concept of the integral risk factor and the method of its calculation were proposed. Alternative scenarios for the implementation of the investment project using the integral risk factor were developed. An algorithm for complex risk express assessment of an investment project on a multi-brand dealer auto center construction was developed by means of an integral risk factor and Monte-Carlo simulation method. Practical importance: The developed algorithm can be used by managers to identify and evaluate or carry out an express assessment of complex risks of investment projects in the process of operating real projects, as well as to provide background for developing new and more advanced methods of project risks assessment.

All forms and types of investment activity are inherently associated with an element of risk, the degree of which is contingent upon the evolution of market relations within the economy. In the contemporary era, the escalation of risk is contingent upon the instability and accelerated transformation of the economic milieu at the national level and within the investment sector. This encompasses the availability of privatised assets for investment, the advent of novel financial instruments, the emergence of new investment vehicles and a multitude of additional factors. Investment risk pertains to the potential for unforeseen financial losses (reduced profitability, income, capital erosion, etc.) in the context of uncertainty inherent to investment activities. The primary functions of investment management encompass a range of activities, including: the formulation of current forecasts and the planning of future activities; the identification of potential risk sources; the selection of appropriate management decisions aimed at eliminating or mitigating the impact of negative factors; the calculation of economic feasibility and the justification of proposed projects; the assurance of normal operations in the context of changing conditions; the determination of an acceptable level of risk; the development and implementation of measures designed to minimise the identified risks associated with a given project; the forecasting and modelling of relationships between factors; and the undertaking of complex analysis. The necessity to manage investment risks is contingent upon their existence. At present, a number of techniques are employed for the purpose of evaluating the degree of risk. A risk management method may be defined as a system of techniques or methods for performing individual operations within the risk management process. Nevertheless, the principal challenge lies in selecting the most suitable risk assessment approach, as each method possesses a distinct scope, along with inherent advantages and disadvantages. The main types of risk insurance in project finance are as follows: - Direct, which includes an unconditional guarantee of full payment from a guarantor with a sound financial position and cash security;- restrictions, including quantitative, time and other limitations. Simultaneously, project financing is beset with a number of challenges, including a dearth of local expertise in the development of large-scale projects, a paucity of qualified managers to oversee the data of individual entrepreneurs, insufficient resources for the large-scale financing of capital-intensive projects, the low qualifications of project financing participants, and the absence of a developed and legally approved mechanism for sharing risks between participants, among other factors that exacerbate project risks. The resolution of contemporary problems necessitates a multifaceted methodology that considers the interests of multiple stakeholders. The most crucial elements are the reinforcement of the state's role in guaranteeing project risk insurance, the provision of tax incentives for investment mechanisms, and the advancement of interbank collaboration in the domain of joint crediting of individual entrepreneurs. The article examined the classification of risks in investment projects, the methods of risk assessment and the minimisation of risks in investment projects.

Introduction. The article deals with the modeling features in the implementation of investment projects using the Monte Carlo method. The purpose of the article is to substantiate the feasibility of using economic and mathematical models to identify the risks of investment projects in agricultural production, taking into account the randomness of factors. Results. The expediency of using this method during the analysis of projects in agriculture is determined. This type of modeling is a universal method of research and evaluation of the effectiveness of open systems, the behavior of which depends on the influence of random factors. Particular attention is paid in such cases to decisions on the implementation of investment projects. The expediency of using this method in the analysis of projects in agriculture is determined. The main characteristics of the investment project are considered: investments involve significant financial costs; investment return can be obtained in a few years; there are elements of risk and uncertainty in forecasting the results of the investment project. The algorithm of the analysis of investment projects consisting of various stages is offered. The importance of investigating the risks of investment projects in agricultural production is substantiated. It is investigated that the basis of the Monte Carlo method is a random number generator, which consists of two stages: generation of a normalized random number (uniformly distributed from 0 to 1) and conversion of a random number into an arbitrary distribution law. The task of choosing an investment project for a pig farm is proposed. The calculations revealed that the amount of the expected NPV is UAH 63,158.80 with a standard deviation of UAH 43,777.90. The coefficient of variation was 0.69, so the risk of this project is generally lower than the average risk of the investment portfolio of the farm. Conclusions. The results of the analysis obtained using the method of Monte Carlo simulation are quite simple to interpret and reflect the change of factors over a significant interval, taking into account the probabilistic nature of economic factors. Thus, this method allows the implementation of the investment project to assess the impact of uncertainty on the final result of the project.

Ambitious climate targets, such as the 2 °C target, are likely to require the removal of carbon dioxide from the atmosphere. Afforestation is one such mitigation option but could, through the competition for land, also lead to food prices hikes. In addition, afforestation often decreases land-surface albedo and the amount of short-wave radiation reflected back to space, which results in a warming effect. In particular in the boreal zone, such biophysical warming effects following from afforestation are estimated to offset the cooling effect from carbon sequestration. We assessed the food price response of afforestation, and considered the albedo effect with scenarios in which afforestation was restricted to certain latitudinal zones. In our study, afforestation was incentivized by a globally uniform reward for carbon uptake in the terrestrial biosphere. This resulted in large-scale afforestation (2580 Mha globally) and substantial carbon sequestration (860 GtCO2) up to the end of the century. However, it was also associated with an increase in food prices of about 80% by 2050 and a more than fourfold increase by 2100. When afforestation was restricted to the tropics the food price response was substantially reduced, while still almost 60% cumulative carbon sequestration was achieved. In the medium term, the increase in prices was then lower than the increase in income underlying our scenario projections. Moreover, our results indicate that more liberalised trade in agricultural commodities could buffer the food price increases following from afforestation in tropical regions.

Development of the long-term investment market is a condition for the formation of the main factors of economic growth and successful implementation of long-term infrastructure projects in modern Russia. The role of bank lending for long-term investment projects is to increase against the background of the consequences of the economic crisis and budget deficit. The article presents bank performance indicators for financing of long-term investment (infrastructure) projects. The author draws a conclusion on the dominant position of banks with state participation in long-term lending. The article considers the factors affecting the tendency of banks to long-term lending. The author also analyzes the practical experience of large domestic banks’ participation in financing of long-term investment projects. Problems and credit risks of long-term investment projects are identified. In conclusion, the author formulates recommendations on the directions and tools to improve the system for assessing the credit risks of investment projects in commercial banks. It is recommended to supplement this system with indicators of the structure of long-term investments, profitability of permanent capital and stability of the loaner’s efficient operation, as well as to ensure additional consideration of risk factors. The author defines the measures to expand the practice of syndicated lending, improving the mechanism providing state guarantees, and developing tools for cooperation between the bank and the loaner as promising areas for the development of long-term loans.

The article substantiates the need for business risk management of investment projects in the real estate market at the current stage. The place of entrepreneurial risks in an investment project is studied. The types of risks that appear in an investment project are systematized. An algorithm for managing business risks of investment projects is proposed. It includes the analysis of potential risks, determination of the probability of occurrence and impact of each risk on the project, development of strategies for avoiding, mitigating, transferring, and accepting risk, systematic monitoring of risks throughout the project, which will allow timely detection of new risks and taking measures to eliminate them. It is substantiated that the management of business risks in investment projects involves a systematic, comprehensive, and transparent approach to the identification, assessment, and management of risks in order to achieve successful results.

The article analyzes the existing approaches to making optimal investment decisions from the point of view of solving the "risk-income" contradiction. Both such characteristics of the investment project as its efficiency (income) and risk are equally important for making investment decisions, they should be considered simultaneously and influence the decision made by the investor. The most well-known theories and approaches to solving the «risk-income" contradiction based on probabilistic characteristics and considering the investor's attitude to risk are analyzed. Recommendations on selecting indicators by which the risks of investment projects should be assessed are provided. It is explained in the article how exactly to use those indicators when approving investment projects in conditions of high uncertainty. It is noted that the investor's attitude to risk is one of the main factors in the decision-making process. It is considered in the article how to build and use “indifference” curves, and how to find the most effective projects from the point of view of solving the "risk-income" contradiction. To make the right investment decision, only knowing the profitability and risk of the evaluated projects is not enough. It is necessary to consider all qualitative factors that can affect the project's usefulness for the investor and make a choice according to the priorities of these factors. Recommendations are provided on making decisions that allow the investor to achieve the most “useful” result. It is noted that in each specific case, the optimal solution will be a compromise not only between the income and risk of the projects, but also between all the qualitative advantages and disadvantages of the projects under consideration, and this compromise solution is designed to ensure the maximum "usefulness" for the investor.

This paper presents a novel methodology to introduce the risk in the valuation of random investment projects. Traditionally, a constant risk-adjusted premium has been added up to the interest rate to include the uncertainty associated with the project. Nevertheless, this method is not objective because the choice of this parameter is not directly identified with a risk measure inherent to the project. Our approach is based on a model that describes the perception that the lender (supplier) has about the expected time to obtain the payment of debts (which will be identified with the cash flows). Thus we will be able to eliminate the subjectivity of traditional valuation methods when considering the risk in investment projects. © 2013 Wiley Periodicals, Inc.

SUMMARY What caused the housing boom of the 2000s? A number of researchers have suggested that loose monetary policy during the first half of the 2000s was a primary cause of the substantial run-up in house prices in many countries. However, using a common statistical approach, we find that monetary policy was not the main factor. That should not be surprising: Although low interest rates raise house prices, the increase in prices during the mid-2000s was much larger than the historical relationship between the two variables would suggest. Instead, we investigate further the link between the marked loosening in terms and standards for mortgage credit and the most rapid increases in house prices. This link provides some evidence for a story where credit provision and the demand for housing fed on each other and helped spur the housing boom. Our work suggests a greater role for macroprudential regulation rather than monetary policy in managing asset price booms.

After ten years of unprecedented increases in both prices and activity levels, the Irish housing market has entered a period of significant decline. In 2007, Irish house prices, for the first time in recent history, experienced negative growth rates. Similarly, rates of house building began to slow appreciably and leading indicators within the housing sector suggest that house building will contract significantly in the years ahead to levels well below the record level of construction in 2006. The sustained increase in housing construction prompted by the rapid increase in prices resulted in the Irish construction sector assuming a position of considerable importance within the overall economy. A significant slowdown in housing activity could have far-reaching domestic consequences. In this paper, we use a recently developed model of the housing sector to gauge what the likely future supply levels of housing will be in response to the slowdown in demand-side pressures.