Investment Risk Research Articles

Study on Economic Risks of Chinese Outward Foreign Direct Investment in Countries along the “Belt and Road”

Study on Economic Risks of Chinese Outward Foreign Direct Investment in Countries along the “Belt and Road”

ЗАЛУЧЕННЯ ІНВЕСТИЦІЙ НА ЗАСАДАХ ДЕРЖАВНО-ПРИВАТНОГО ПАРТНЕРСТВА В УМОВАХ ПОВОЄННОЇ РОЗБУДОВИ НАЦІОНАЛЬНОГО ГОСПОДАРСТВА: ПЕРЕДУМОВИ ТА ІНСТРУМЕНТАРІЙ

The prerequisites for the implementation of the public-private partnership mechanism in the domestic economy are revealed, with an emphasis on the processes of national economy recovery in the post-war period. The importance and functional role of public-private partnership in building effective investment attraction strategies is argued, with the hypothetical assumption of their promotion of rapid modernization and development of key sectors of the national economy. The public-private partnership in various socio-economic and political environments was analyzed and it was established that it should be considered an adaptive system that uses a mechanism of its implementation adequate to the situation. It has been established that in many countries of the world, public-private partnership is currently recognized as an important socio-economic concept, which, moreover, with the change of socio-economic and political parameters in the world space, acquires new forms of its application, in particular methods of financing the development of infrastructure or providing higher quality and volume of various types of public services. The existing state of domestic legislative regulation of public-private partnership is summarized and the appropriate stages of its implementation in the processes of post-war recovery of the Ukrainian economy are given. Separate directions for creating a favorable investment climate in the post-war period are argued, which relate to the provisions of the legal framework and institutional infrastructure, investment guarantee criteria. It is substantiated that they are critically important for reducing risks for domestic and foreign investors, a factor in increasing the attractiveness of public-private partnership projects. It has been established that the Strategy for the implementation of public-private partnership in the process of socio-economic recovery of Ukraine should primarily be based on the rational planning of the stages of recovery work both for infrastructure projects important for the national economy, as well as the provision of public services and stimulation of economic growth, the application of regulatory mechanisms aimed at ensuring transparency, accountability and fair distribution of risks between public and private participants.

NAVIGATING FINANCIAL LANDSCAPES: A COMPARATIVE ANALYSIS OF INVESTMENT CHOICES THROUGH THE LENS OF PROSPECT THEORY

This study delves into the intricate realm of investment decisions through a comparative analysis, employing the lens of Prospect Theory to unravel the cognitive underpinnings that shape financial choices. Through a meticulous exploration of diverse investment strategies and risk preferences, this research aims to offer a nuanced understanding of how individuals navigate financial landscapes. The comparative approach sheds light on the psychological dynamics influencing investment decisions, providing insights valuable for both individual investors and financial professionals seeking to optimize decision-making processes.

Endowment fund investment strategy construction and risk assessment: An empirical analysis based on the EWMA methodology

Endowment fund investment strategy construction and risk assessment: An empirical analysis based on the EWMA methodology

Applications and Challenges of AI Technology in Financial Portfolio Management

With the rapid development of artificial intelligence technology, financial portfolio management has entered a new era characterized by data-driven and intelligent decision-making. Based on the customer- centered service philosophy, managers propose intelligent investment strategies that better meet market demand. Based on the dynamic development of AI technology, we build a theoretical analysis framework for intelligent portfolio management according to the internal logic of the financial market, which can explain the intelligent development mechanism consisting of the investment decision mechanism and risk control cycle mechanism of machine learning and quantitative analysis. Furthermore, we explore opportunities to move towards high-quality development goals from the perspective of practical changes and technological applications in financial portfolio management. The role of AI technology in financial portfolio management is to provide investors with investment portfolios that meet their personalized needs. Researchers are committed to continuously improving the quality of investment strategies and enhancing satisfaction. Therefore, it is necessary to strengthen portfolio control based on internal quality data flow, establish an interaction and risk assessment mechanism between investors' preferences and market performance quality perception, and establish a performance and market environment evaluation system to achieve qualitative evaluation and market performance evaluation, to realize the high-quality development of financial portfolio management, promote the stability and prosperity of the financial market, and truly meet the diversifying needs of investors.

Financial assets against inflation: Capturing the hedging properties of gold, housing prices, and equities

<abstract> <p>In this study, we employed a developed Fractional Cointegrating Vector Autoregressive (FCVAR) model to analyze the relationship between three different securities, i.e., housing prices, S&P500 stock prices and gold, and inflation rate, to determine the hedging properties of each type of asset against inflation shocks. Our analyses covered seven decades; ranging from January 1953 to January 2023. Our results suggested that housing prices and S&P500 performed partially against inflation and gold did not have hedging properties when attending to the full sample. Accounting for structural breaks, we discovered that these results changed. We found that housing prices and the S&P500 showed a superior hedging performance against inflation since the second regime. On the other hand, when we studied the behavior of gold, this security showed the inverse results, i.e., it showed no hedging performance in the second regime. Finally, these results were important for an optimal investment strategy, risk diversification, and monetarism.</p> </abstract>

Modeling the Investment Efficiency and Risk Assessment of Great Health Industry in the Context of Digital Economy

Abstract With the development of the economy and society, people pay more and more attention to physical health. In order to make the big health enterprises in the long term at the level of smooth development, it is necessary to carry out an in-depth study on the investment efficiency and potential risk of the big health industry. This study constructs an investment efficiency evaluation method based on the DEA model. Firstly, the comprehensive efficiency is decomposed through the CCR model to further obtain the output results. Then, the effectiveness of enterprise investment is evaluated. The changes in the investment efficiency of the big health industry and other sample decision-making units are analyzed through the DEA-Malmquist model to output the trend of the overall investment efficiency. Logistic regression, support vector machine, and random forest models are used to assess the risk of the large health industry, respectively, and several classifiers are trained. When predicting the final sample, the voting or mean value method is used to count the effect of classification. The overall mean value of big health enterprises hovered between 0.96 and 0.98 in five years, indicating that the comprehensive investment efficiency of the big health industry is relatively stable. The average AUC value of the random forest model is 0.635, which is 0.028 higher than the average AUC value of the support vector machine; thus, it is concluded that there is no great fluctuation in the investment efficiency of the big health industry under the background of the digital economy, and the random forest model is more suitable for the risk assessment of the big health industry.

Research on the Netflix Stock Price based on Linear regression Models

This article uses a linear regression model to predict Netflix’s stock from 2018 to 2022, and divides the data set into pre- and post-epidemic analysis. The before-and-after analysis aims to explore the impact of COVID-19 on Netflix stock price. By collecting and collating Netflix’s historical stock price data, financial indicators, and other relevant information, a linear regression model was constructed. Through model training and verification, the prediction results of future stock prices are obtained, and a comparative analysis before and after the epidemic is carried out. The research results have important reference value for investors, analysts and decision makers in formulating investment strategies and risk management.

R&D Investment, Financing Constraints, and Financial Risks

R&D Investment, Financing Constraints, and Financial Risks

РИСКОВАЯ СРЕДА РОССИЙСКИХ ПРЕДПРИЯТИЙ НЕФТЕГАЗОВОЙ ОТРАСЛИ

The scientific article is devoted to an overview of the current risk environment of the Rus-sian oil and gas sector. Based on statistical data, it is shown that oil and gas enterprises make a significant contribution to the GDP of the Russian Federation, to the formation of the country’s budget, while soon, the importance of the oil and gas industry in both the domestic and global econ-omies is not expected to decrease. Nevertheless, there is an obvious trend towards a decrease in the share of oil and gas budget revenues since 2014, as well as their absolute value. As a result of the analysis of scientific sources, it was revealed that the functioning of oil and gas enterprises is accom-panied by a wide range of risks of various nature. The author has reviewed the risks characteristic of oil and gas industry enterprises, considered some approaches to their classification, most studies highlight technological, personnel, geological, environmental, price, financial, investment, regula-tory, and political risks. According to insurance companies, the most significant damage is caused by the implementation of man-made risks. The accumulated risk management experience has allowed Russian oil and gas sector enterprises to form effective integrated risk management systems. At the same time, there is an increase in uncertainty about the operating conditions of oil and gas enterprises in Russia, due to a significant increase in sanctions pressure on the industry after Febru-ary 2022. The sanctions significantly limit the opportunities for trade in products of Russian enter-prises in the oil and gas sector, and erect barriers to the innovative development of the oil and gas industry in Russia. Nevertheless, enterprises, with the support of the state, managed to reduce the negative impact of sanctions risks by redirecting their flows mainly to Asian markets, using parallel import technologies for critical oilfield service infrastructure and transfer of critical technologies. This will partially reduce the increase in the technological lag of the industry in the face of sanctions, however, given the continued high level of geopolitical risks in the foreseeable future, a prerequisite for the successful development of Russian oil and gas enterprises is the activation of import substi-tution processes, as well as ensuring interaction with high-tech enterprises of the military-industrial complex.

Инвестиционное развитие сельского хозяйства и его инвестиционная привлекательность в условиях современных вызовов и угроз

The article is devoted to the issues of investment development of agriculture and its investment attractiveness. The authors consider the main elements of the economic mechanism that influence investment activity in agriculture. The article also identifies the need to assess the investment attractiveness of the agricultural sector based on the analysis of investment potential and risks in order to develop solutions in the formation of investment agricultural policy and attract potential investors. Based on the assessment of the level of investment attractiveness in the context of the subjects of the Russian Federation and federal districts, the authors propose measures and mechanisms to increase investment potential in agriculture.

Design of Subway Investment Management Platform Under the Background of Informatization

Abstract This article aims to design a subway investment management platform based on DL (Deep Learning) to improve subway projects' investment efficiency and risk management levels. The article adopted the DL algorithm to comprehensively analyze historical subway investment data and constructed prediction and risk assessment models to achieve this goal. The application effect of the DL algorithm in subway investment management and the practicality of the platform were verified through simulation experiments. This article first collected a large amount of historical subway investment data and processed and learned these data using the DL algorithm. By constructing an NN (Neural Network) model, accurate prediction of investment return rate and market demand for subway projects has been successfully achieved. Furthermore, a risk assessment model was also constructed to quantify and evaluate potential risks in subway projects. The experimental results indicate that the DL algorithm has significant prediction and risk assessment advantages. Compared with traditional statistical learning methods and machine learning algorithms, the DL algorithm can more accurately predict investment return and market demand, providing users with more reliable decision support. In addition, the risk assessment model effectively helps users understand the risk status of the project and formulate corresponding risk management measures.

Influence of Artificial Intelligence on Forecasting Net Asset Value and Return Volatility in Indian Mutual Fund

Predicting the critical net asset value (NAV) in the financial market is difficult for investors and fund agencies. The present study introduces machine learning (ML) and deep learning (DL) models such as linear regression, deep long short-term memory recurrent neural network (DLSTM-RNN), and autoregressive integrated moving averages (ARIMA) for predicting the NAV. The five different equity sectoral technology mutual fund direct growth plans from January 2013 to December 2022 have been collected. The novelty of the current study is deeply examining, which ML or DL model devotedly predicts the NAV closing price. The major key findings of the experimental results proved that the DLSTM-RNN model makes statistically viable predictions, whereby the mean absolute percent error (MAPE) average prediction accuracy value is 0.02. Based on the accuracy of a superior model, we compute the annualized return volatility to compare the risk of investments with annual return periods over different time horizons. The Jarque-Bera statistics of the return volatility over time Gaussian distribution is rejected at the 0.01 level. Statistical paired t-test and Pearson correlation coefficient are used to compare the effects of the proposed three models. In addition, the benchmark portfolio strategy yields a Sharpe ratio of 7.0193 and the maximum drawdown is 0.3743. The AI performed deep LSTM neural network model simulation, especially when using a daily and monthly MAPE strategy giving 81% and 84% highest NAV prediction consistency than the linear regression and ARIMA models.

A sensitivity analysis approach to reduce economic risks in the design of edge-cloud automation systems in industry

The migration of field-level automation systems to an edge-cloud hosted on premises can reduce the operation costs of a manufacturing line and increase its flexibility thanks to computation scalability and use of cloud-native operation concepts. Nonetheless, due to the novelty of the concept, a transparent life-cycle costs (LCC) assessment for edge-cloud automation systems (ECASs) is complex to achieve. In particular, uncertainties concerning costs related to the engineering and operation of an ECAS, such as commissioning delays or unexpected failures, increase the risks of investments towards its adoption. In this paper we propose a sensitivity analysis approach based on Monte Carlo (MC) life-cycle simulations. Through the approach, design parameters of an edge-cloud are investigated concerning their impact on the magnitude and distribution of LCC. The use of the approach is tested on a real-world case study to optimize the choice of the edge-cloud components and reduce the economic risks for its adoption. The proposed approach is expected to be integrated in early stages of the design process of a production line to identify cost-viable designs of ECASs, thus fostering the transition towards smart manufacturing systems.

Управління бізнесом під час війни

The interaction between business and hostilities represents a complex dynamic, as both of these aspects have a huge impact on each other. When discussing this connection, one should consider not only the challenges, but also the opportunities it opens up for businesses in the face of instability and conflicts. The high level of discordance and geopolitical turbulence creates special conditions for strategic thinking and adaptability of business leaders. Hostilities cause economic instability, reduced production, destruction of infrastructure and loss of jobs, which leads to losses for local enterprises and causes great risks for investors who have to invest in countries with ongoing military conflicts, due to the instability of government structures and doubts about the economic recovery after the end of the certain conflict. The conditions of military conflict require a high level of attention from business organizations to ensure the safety and security of their employees, since this category of assets is one of the most important for the sustainability of the enterprise. Simultaneously, the protection of property assets is of great importance, as enterprises must minimize the possible risks of destruction or damage in the conditions of hostilities. In addition, effective risk management requires the enterprise to develop and implement strategies to adapt to the changing geopolitical environment, which allows it to maintain stability and efficiency of operation during adverse conditions. It is important to note that competent risk management is a crucial factor for maintaining business activity and the successful functioning of the enterprise even in the most complex scenarios of a conflict environment. War, as a complex phenomenon, creates not only challenges but also opportunities for business, especially in the context of certain industries and scenarios. For example, it stimulates the demand for products and services related to the defense industry, which contributes to the development of technology, weapons production, transport and communication systems. Post-conflict recovery markets open up new opportunities for companies in the fields of construction, reconstruction and infrastructure solutions. Thus, military conflicts, although they pose significant challenges to society and the economy, at the same time provide opportunities for the development of new technologies, markets and management strategies that require comprehensive analysis and response on the part of business and politics.

ВПЛИВ СОЦІАЛЬНО-ЕКОНОМІЧНИХ ЧИННИКІВ НА ФОРМУВАННЯ БІЗНЕС-СЕРЕДОВИЩА ПІДПРИЄМСТВА

Socio-economic factors play a key role in shaping the business environment of an enterprise, influencing its stability, development and competitiveness. These factors can be conditionally divided into macro- and micro-levels, where each of them has its own specificity and power of influence. Macroeconomic factors include the inflation rate, the state of economic growth, the exchange rate, the unemployment rate, and government policy. Economic growth contributes to an increase in the incomes of the population and investments, which has a positive effect on business. Social factors include demographic changes, educational attainment, cultural characteristics, and social values. Demographic changes, such as population aging or migration processes, affect the size and structure of the labor market and the consumer market. Cultural characteristics and social values shape consumer behavior and preferences, which is important to consider when developing marketing strategies. Political stability and the legal framework also have a significant impact on the business environment. Political instability can create risks for investors and lead to unpredictable changes in regulatory policy. Instead, a stable political environment promotes predictability and long-term planning. The development of technologies and their implementation in business processes is another important factor. Innovative technologies can significantly increase production efficiency, reduce costs and open new sales markets. Enterprises that actively implement the latest technologies have a competitive advantage and can quickly adapt to changes in the business environment. Thus, socio-economic factors have a complex impact on the formation of the enterprise’s business environment. For successful functioning and development, enterprises need to constantly analyze and adapt to changes in the external environment, taking into account both macroeconomic and microeconomic aspects. This will allow not only to maintain a position in the market, but also to find new opportunities for growth and development.

ДЕРЖАВНЕ РЕГУЛЮВАННЯ ТА ПІДТРИМКА ІННОВАЦІЙНОЇ ДІЯЛЬНОСТІ

State regulation of innovative activity is necessary and has many advantages that contribute to economic development, increasing the country's competitiveness and sustainable growth in the face of global challenges. Regulation of this sphere by the state plays a decisive role in creating favorable conditions for the development of innovative processes, their stimulation and effective use of the national scientific and technical potential. The state plays an important role in stimulating innovative activity. With the help of financial support, such as subsidies, grants or preferential loans, the state helps to reduce risks for investors, which, in turn, stimulates investment activity in this area. In addition, state regulation contributes to the creation of a favorable investment climate, the protection of intellectual property and the development of institutional infrastructure, which are necessary conditions for the successful development of innovations. Thus, government intervention is justified, as it allows overcoming market shortcomings and ensuring the necessary level of investment in innovation, which is of strategic importance for the development of the economy. State regulation of innovative activity creates conditions for the development of entrepreneurship and contributes to increasing the competitiveness of the economy. Thanks to the integration of various regulatory mechanisms, the state can effectively respond to modern challenges and ensure stable economic development. State regulation of innovations should be aimed at creating effective interaction between science, business and the state to stimulate innovative activities and their introduction into the economy. A comprehensive approach combining direct and indirect regulation is necessary for the continuous development of innovative enterprises and the use of the country's scientific potential. The state plays an important role in stimulating innovative activity by creating a favorable environment for the development of innovative infrastructure. This includes funding of scientific research, training of highly qualified personnel, protection of intellectual property and promotion of commercialization of scientific developments. Since direct funding has its limitations, the government is increasingly using indirect instruments, such as tax incentives and regulatory simplifications, to attract the private sector to innovation.

Investment risk early warning method of listed companies based on EMD-RF-LSTM

Investment risk early warning method of listed companies based on EMD-RF-LSTM

Ein gesamtstaatlicher „Transformations- und Infrastrukturfonds“ zur Stabilisierung der Schuldenbremse

Abstract With its judgement on the federal budget, the German Federal Constitutional Court has thrown the government’s financial planning into disarray. Important public investments are at stake, as the debt brake sets tight limits for the treasury and debt-financed shadow budgets. But the green transition requires public investment as the time horizons are short and the investment risk for technologies and international competition is high. A transformation and infrastructure fund (TIF) anchored in the constitution, combined with planning accelerations should be established in order to finance government investments while at the same time leaving the debt brake in the core budget untouched.

ІНВЕСТИЦІЙНА НЕВИЗНАЧЕНІСТЬ: ВИКЛИКИ ТА МОЖЛИВОСТІ ДЛЯ УКРАЇНИ

The article highlights the problems of attracting foreign direct investment in the conditions of war and the postwar period, which should be defined for the country as a period of investment uncertainty. It was emphasized that for Ukraine, which actively attracts investments from abroad, such a situation leads to the loss of opportunities for economic development and deterioration of competitiveness and can also affect the general decrease in the rate of economic growth. The volume of investment in the national economy before the war had unstable dynamics, but with the beginning of the war, the fall in investment became critical. It was noted that political instability, economic turbulence, changes in government policy, geopolitical conflicts, technological changes, or natural disasters are among the causes of investment uncertainty. It was pointed out that the result of investment uncertainty may be the delay or rejection of the implementation of investment projects. It was determined that to overcome uncertainty in the investment sphere, it is necessary to develop effective strategies for attracting investments, which is currently the most difficult task. Most of the countries that are large exporters of foreign direct investments, such as the USA, Germany, Great Britain, Japan, and others, have already aided Ukraine since the beginning of the war, so further attracting investments and their involvement in the restoration of the national economy in the post-war period will be problematic. It was emphasized that when building investment strategies, the principal things are: understanding modern investment trends (for Ukraine, in this context, it is possible to attract investments per the implementation of the Sustainable Development Goals); ensuring effective management of investment risks (insurance of direct foreign investment during wartime is especially relevant); transparency of government policy and regulatory measures, as well as the creation of a favorable business environment that will form the basis of investment stability and reliability