The purpose of this study is to develop and test an Integrated Innovation Activity Indicator (IIAI) for small and medium-sized enterprises (SMEs), designed to assess their contribution to ensuring the technological sovereignty in the Russian Federation, taking into account participation in state innovation support programs. The paper justifies the need to move away from fragmented assessments of innovative development towards comprehensive models that take into account the combined influence of factors determining the ability of businesses to create and implement critical technologies. The methodological framework of the study is based on the approaches of the World Intellectual Property Organization (WIPO) and the Organization for Economic Co-operation and Development (OECD). The proposed IIAI is a composite index that integrates four key factors: the extent of SME participation in government support programs, the level of financial provision for projects, the focus on priority technological sectors, and human capital. The practical significance of the study lies in its potential to use the IIAI by government authorities, development institutions, and the expert community to improve innovation support instruments and enhance the contribution of SMEs to achieving technological sovereignty and sustainable economic growth.

The aim of the study is to prove that dynamic portfolios can effectively reflect the temporal dynamics of current risks of a higher order, providing greater reliability and stability compared to traditional portfolios. The subject is the economic imbalance in portfolio models, which occurs when different participants have different level of knowledge about market conditions and the performance of assets. In an environment where traditional portfolios have shown low returns due to the pronounced peaks and sharp declines in financial asset returns, as well as their inability to account for dynamic changes in financial risks. This study incorporates higher-order short-term risks into traditional portfolios in order to mitigate the effects of deviations from the normal distribution. The methodology is based on the concept of multiple financial time series and the VAR-ICA-GARCH model. This model effectively captures the conditional mean, the covariance matrix, the mutual asymmetry matrix, and the mutual kurtosis matrix, thereby characterizing temporal changes at higher-order moments. Due to the inherent nonlinearities of dynamic portfolio optimization tasks, we use a genetic algorithm to solve the dynamic portfolio model. The results of the study show that dynamic portfolios can effectively reflect the changing dynamics of current higher-order risks, while providing greater reliability and stability than traditional portfolios. Even when exposed to such complex risks, dynamic portfolios perform better. The practical significance of this research lies in determining the time-varying weighting coefficients for the portfolio and conducting both simulation experiments and empirical analysis.

This study examines the relationship between earnings management and firm value, emphasizing the mediating role of corporate social responsibility (CSR) disclosure and the moderating effect of accounting conservatism. Using a sample of 731 non-financial companies listed on the Indonesia Stock Exchange from 2016 to 2023, with 5,848 firm-year observations, the research employs panel regression and conditional process modelling to test moderated mediation effects. The findings reveal that earnings management negatively impacts firm value, as profit manipulation erodes investor confidence and diminishes the reliability of financial statements. CSR disclosure fully mediates this relationship by mitigating the adverse effects of earnings management, signalling the firm’s commitment to social responsibility, and enhancing stakeholder trust. Furthermore, accounting conservatism moderates these relationships by weakening the negative association between earnings management and firm value while strengthening the positive effect of CSR disclosure on firm value. These results highlight the strategic importance of combining CSR disclosure and conservative accounting practices as governance mechanisms to bolster investor confidence and stabilize firm value.

The article presents the results of the research presented in the reports of the participants at the XXV scientific and practical conference “Insurance, Education and Science” on the topic “The Formation of Insurance Culture: Financial Education and Responsible Business”, organized by the All- Russian Union of Insurers and the Financial University under the Government of the Russian Federation. The article reflects the main findings of this event. The presentations of the participants covered the current state of the global and Russian insurance markets, as well as forecasts and possible models for its development. They also addressed a wide range of problems of certain types of insurance and reinsurance. Special attention was paid to the need to improve the level of insurance literacy and insurance culture among Russian citizens as a factor in the development of the insurance market. The results of research into the development of digitalization with a focus on increasing the efficiency of insurance companies and improving the quality of services offered to customers as well as the development of new software.

This article is devoted to the issue of choosing the most effective way to sell the property of a bankrupt entity. It discusses the sale of each asset individually or selling of the entire property complex as an operating business. At the same time, there is no unified practice on this issue in the judicial practice in bankruptcy cases. The purpose of the study is to determine the optimal way to sell a debtor’s property during bankruptcy by establishing the main criteria for analysis during the selection of either an object-based sale of assets or a sale of a property complex as a whole as a single production and technological unit of business. In the course of the research, methods such as content analysis of sources, regulatory regulation, and market analysis were used. These studies were carried out by taking into account the analysis of the current legislation norms, general economic market trends and the study of judicial practice in bankruptcy cases of business entities. This study is based on a forensic examination conducted by the author as a judicial expert in a bankruptcy case of a legal entity. In the course of the study, the author analyzed the main reasons for the location of non-current assets in business entities, examined the basic conditions and market trends in the sale of property of bankrupt entities, and identified the main criteria and factors that influence the decision on choosing the optimal method for selling the debtor’s property during bankruptcy. The study shows that there is no consensus on this issue among the scientific community and judicial practice. The author has developed and proposed recommendations that are most likely to lead to cost-effective decisions when choosing a mechanism for selling the property of a bankrupt entity. The sale of industrial and real estate on site would be more appropriate if the production process was destroyed, and part of the equipment was dismantled. Conversely, the sale of the debtor’s property as a single lot (excluding non-core assets) would be most effective if the debtor’s assets could be sold as a going concern.

This study examines the relationships between natural rent streams, financial development, institutional quality, and economic growth in the Middle East and North Africa (MENA) region and is the development of fixed effects panel models during 1990–2020. The analysis of the MENA region sheds light on the complex, dynamic nature of the region’s economies and societies, as this region is an interesting case study where economic, political and cultural dynamics are diverse. The region faces economic diversification needs, conflicts, migration, and climate change, making this study timely and relevant. To this end, fixed effects regressions and scenario approaches were applied to the collected panel data. The findings reveal natural resource rents as the primary driver of economic growth, their effectiveness dependent on financial development and institutional quality levels. A well-developed financial sector facilitates efficient channeling of rents into productive investments, while strong institutions mitigate resource curse effects. In contrast, while remittances and foreign aid do not directly impact growth, their effectiveness is enhanced by financial development and institutional frameworks. The results highlight the critical roles of financial sector development, institutional quality, and robust governance in shaping the impacts of resource rents in this resource-rich region. The policy recommendations emphasize strategies for managing resource wealth, strengthening financial systems, promoting inclusion, improving institutions, and fostering an enabling environment for remittances and foreign aid to promote sustainable economic growth.

Legitimacy theory posits that organizations strive to align with societal expectations to gain advantages, yet its focus has primarily been at the company level. The purpose of the study is to investigate the global applicability of legitimacy theory by examining the relationship between Environmental, Social, and Governance (ESG) disclosures and Foreign Direct Investment (FDI). In particular, the study sets the task: analyze the impact of ESG disclosures on FDI across twenty-eight countries; compare the ESG performance of different nations; and explore the role of regional ESG standards in influencing ESG performance and FDI. The application of the Kruskal-Wallis test revealed the dominant position of Western nations with developed ESG standards. The Bonferroni adjustment post hoc test on World Bank data indicated that countries with well-developed ESG standards act as global investors, trusting the high standards of rapidly improving Western regions. Statistical tests confirmed that countries in the developing stage, with values somewhat similar to the most developed areas, present attractive alternatives for foreign investors. However, the lack of standardized norms hinders the establishment of trustworthy economic relationships. These findings suggest that just as businesses use Corporate Social Responsibility (CSR) to gain legitimacy, countries can adopt ESG practices to align with global norms and attract FDI. Although this transition may be time-consuming, developing regional ESG disclosure norms could serve as an effective stepping stone.

Precious metals are key elements of the asset class in the international financial market. They have a number of advantages: they are a valuable tool for preserving wealth, they are not at risk of default, and they provide effective protection against inflation. In addition, they are considered safe-haven assets during periods of unfavorable geopolitical conditions. The purpose of this research is to find methods for improving the accuracy of predicting the price of precious metals through the use of advanced machine learning models. The methodological basis is the concept of predicting the effectiveness of precious metals as a stabilizing asset (and a safe-haven asset) in the context of future financial instability. The research methodology is based on evaluating the effectiveness of machine learning models using information criteria such as AIC and BIC, determination coefficients R2 and Adj-R2, and RMSE and MAPE as measures of the closeness between the actual and predicted values of time series and error measures. The information base for this study was based on daily data on the prices of four precious metals (gold, silver, platinum, and palladium), provided by Investing.com. Given the increasing importance of precious metals as indicators of investor sentiment and the state of the global economy, and in light of the escalating geopolitical tensions from 2020 to 2025, we conducted a comparative analysis using modern machine learning models. The results obtained demonstrate the advantages of the KAN model as a promising tool for improving the accuracy of forecasts and the interpretability of results in various scenarios. This is highly significant for the development of an effective investment strategy in the precious metal markets.

The relevance of the research topic is due to the Indonesian government’s policy plan which will increase the VAT rate from 11% to 12% in early 2025, and has become a hot topic. The aim of this research is to provide the best alternative policy options by providing comprehensive solutions. The research method uses a system dynamics simulation model, employing qualitative and quantitative approaches facilitated by Powersim constructor software by considering three scenarios: pessimistic, moderate, and optimistic. This study uses six main variables and three additional variables. The research results reveal that, in a pessimistic simulation scenario, an increase in the VAT rate will reduce people’s purchasing power and increase tax avoidance. In a moderate scenario simulation, there will be a balance in economic conditions, but in the future, this will reduce the potential for taxes and increase tax avoidance. In an optimistic scenario, reducing the VAT rate will reduce the tax burden, increase potential tax purchasing power, increase exports, and reduce imports, while decreasing tax avoidance and increase tax potential. This research concludes that, of the three scenarios, the best choice is to use the optimistic scenario because it will benefit overall economic conditions. It recommends that the government should reduce the tax avoidance ratio and simplify the supply chain, as supply chain complexity contributes to increased costs.

The article provides a comparative analysis of the principles of organization and functioning of financial systems of metaverses in the public sector based on decentralized finance (DEFI) and digital currencies of central banks (CBDC). The purpose of the study is to evaluate the effectiveness of financial systems based on DEFI and CBDC in order to develop scientifically proved recommendations for choosing the optimal model of financial organization in the state metaverse. The objectives of the study are to systematize the characteristics of DEFI and CBDC, identify the potential opportunities and limitations of each system and develop recommendations for selecting a metaverse financial model. The research methodology includes a comprehensive comparative analysis of systems based on key criteria: centralization, legal regulation, accessibility, technological aspects, inflation control, security, scalability, and other parameters. Based on the results of the study, the authors conclude that the choice between DEFI and CBDC is determined by the state’s goals, the level of trust in financial institutions, and the readiness for digital transformation. Each system has its own advantages and limitations, which require an individual approach based on the national characteristics and strategic goals of the state’s development. The practical significance of the study lies in the possibility of applying the developed recommendations in the formation of the state’s financial strategy in the context of the development of the digital economy and metaverses.

The relevance of this study is due to the digital transformation of public and corporate finance, which has led to the emergence of new methods and channels for government-business communication. This data-driven platform economy is characterized by a lack of end-to-end digitalization of government information systems and established approaches to presenting an organization’s digital profile. Implementing the digital profile concept through government digital platforms will lead to the creation of a unified information space within the public financial management system. The object of this study is the development of a unified digital data system for Russia, based on the concept of a digital profile. The subject of this study is the system of financial and non-financial reporting information for strategic and systemically important Russian organizations, which forms the core of the digital profile. The aim of the study is to develop a terminology and conceptual framework for the formation of a digital profile of organizations in the field of corporate finance which will serve as the basis for a unified digital data system in Russia. The methodological framework for this study is based on an integrated approach that combines content analysis, comparative, factor, and cluster analysis of information about the activities of strategic and systemically significant Russian organizations. This information is derived from existing regulations, as well as actual financial and non-financial data about the activities of these organizations, which are publicly disclosed on specialized digital platforms. The scientific novelty of this work lies in the development of theoretical principles and conceptual approaches aimed at achieving Russia’s sustainable development goals. These principles are designed to create a unified digital data system in the form of a digital profile for strategic and systemically important organizations, using platform solutions. The practical significance of this research lies in its potential for direct implementation of the proposed approaches into public and corporate financial management mechanisms.

The recent trend is to increase companies’ attention to the quality of life in their territory. The main reason for this is the need to attract and retain human resources. The territory of presence for companies is becoming an “asset” from investments in which a positive economic effect is expected. The purpose of the article is to show how the company’s investment in the development of its territory is reflected in accounting and reporting and to justify the use of each option. The study was conducted based on regulatory documents that govern accounting and reporting, including international financial reporting standards, and non-financial reporting standards. From the standpoint of dynamic balance theory, it is possible to classify investments in the development of a territory as expenses of future periods or as assets of a company. However, it is difficult to reliably assess these assets and the issue of asset management is controversial. The article shows the rationale for the importance of separately accounting for investments in the development of territories considering their future economic importance. We suggest evaluating the effectiveness of investments in the development of the territory by analyzing the achievement of the company’s most pressing goal — the retention and attraction of professional staff. In the accounting system of an enterprise, it is necessary to organize control over the effectiveness of investments in the development of the territory: to introduce an object of accounting supervision — “investments in the sustainable development of the territory” and to reflect this object as future expenses or as a noncurrent asset, depending on the expected period of benefits. Off-balance sheet accounting for the object is also possible. The reporting on geographical segments should reflect the costs of sustainable development of the territory of presence. The reporting on geographical segments should reflect the costs of sustainable development of the territory of presence. We propose to include information about business investments in sustainable development in comprehensive sources of information about the territory, as well as in the development of statistical accounting. On behalf of the territorial management authorities.

The condition for the effective functioning of any economic mechanism is to consider objective economic laws when constructing it. At present, there are large-scale transformations taking place in the field of credit relations, and credit mechanisms are undergoing modernization at both the micro and macro levels. The subject of the research in the article is the objective laws of credit. The purpose of the work is to systematize the laws of credit and reveal the directions for their use. The main research methods are the dialectical method, the systematic approach, the methods of scientific abstraction, and induction and deduction. The scientific novelty consists in the formation of the author’s concept for a system of objective economic credit laws. The main results of the study are: 1) In the system of laws of credit, there are three groups: laws of credit emergence, laws of credit functioning and laws of credit development. Within each group there are both basic and derivative laws. 2) The laws of credit emergence include the law of the necessity for credit and the law of ensuring the continuity of reproduction on the basis of credit. The laws of credit functioning include the law of repayment of credit and the law of the economic limit for credit. The laws of credit development comprise the law of complication of credit and the law of ensuring economic growth through the development of the institutional structure of credit relations. 3) The direction of using the laws of credit functioning is the organization of credit relations at the micro level (in the process of building a lending mechanism), and the direction of using the laws of credit emergence and development is the organization of credit relations at the macro level (in the process of building a mechanism to regulate the banking system and the financial market).

The subject of the study is the inflationary processes and monetary policy of the Bank of Russia. The purpose is to analyze the impact of these factors on the state of the Russian economy. To achieve this goal, the following tasks have been set: to consider the theoretical aspects of the relationship between inflation, PREP and economic growth; to analyze the dynamics of inflation and the key tools of the PREP of the Bank of Russia for the period from 2010 to 2024; to conduct an econometric analysis of the impact of inflation and the key rate on GDP growth. The relevance of the topic arises from the importance of finding a balance between ensuring price stability and supporting economic growth within the framework of the policy of the Bank of Russia. The methods of comparative and statistical analysis and econometric modeling are used in this work. The dynamics of inflation, key rates, GDP growth rates and lending to the economy are analyzed from 2010 to August 2024. A regression model of the impact of inflation and the key rate on GDP growth was built. The results of the analysis showed that periods of accelerated inflation and a tightening of the monetary policy were accompanied by a slowdown in economic activity. An increase in annual inflation by 1 percentage point on average slows quarterly GDP growth by 0.096 percentage points, and an increase in the key rate by 1 percentage point reduces the GDP growth rate by 0.137 percentage points (other things being equal). The model explains 58% of the variation in the dependent variable. The coefficients are statistically significant. The conclusion is made regarding the need for the Bank of Russia to pursue a balanced PREP aimed at ensuring price stability without compromising economic growth. The scientific novelty of this study lies in the quantitative assessment of the effects of inflation and the key rate on economic dynamics in Russia based on current data. The prospects for further analysis are related to the use of alternative econometric methods and the study of monetary transmission channels of PREP.

The subject of the study is the dynamics of food prices and their variations influenced by internal and external factors. This study assesses the impact of rainfall, fuel prices, and interest rates on food price fluctuations and analyzes the relative contributions of these variables. This study aims to determine the extent to which internal (intrinsic) factors and external (exogenous) factors contribute to variations of food prices, determine the relative dominance of each factor, and provide policy recommendations to stabilize food prices. This study uses a method of the Vector Error Correction Model with exogenous variables (VECMX) to analyze the dynamic relationship between endogenous variables (food inflation) and exogenous variables, such as interest rates, rainfall, and fuel prices. The relevance of this study is to provide insight into the factors that influence the dynamics of food prices, which can be used as a basis for formulating a policy of food price stabilization. The results showed that the persistence of changes in food prices is relatively high if it is affected by shocks from fiscal policy factors, monetary policy, and natural factors. The average food price change takes about 20–30 months to return to its natural value (new equilibrium) after receiving a shock. Most variations in food prices (more than 70%) are influenced by internal factors. After a certain period, the impact of fuel prices becomes more dominant than rainfall and the benchmark interest rate has the least effect.

The issue of herding bias and investment decision-making has been extremely important in recent times to understand the irrationality of investors. This study comprehensively analyzes the literature on herding bias and investment decision-making to understand the various dimensions of herding biases and their impact on the decision-making of investors. A systematic literature review of relevant research papers from leading databases was conducted to determine the current research trends, develop a nomological network by identifying the variables used as antecedents, mediators, moderators, and outcomes, and highlight the most popular theories referred in studies. The findings of this study reveal behavioural biases, herding bias, investment decision-making as the main thematic domains. Further, the study also found a dearth of literature, especially relating to collectivist and individualistic societies, and concluded that future studies should also contemplate different psychological and social aspects, such as trading behaviour and investor patterns while studying the impact of herding bias on decision-making of investors.

The article is devoted to the urgent problem of diagnosing the financial health of Internet service providers (ISPs) in a dynamically developing digital economy. The main attention is paid to the development of specialized analytical tools that take into account the unique industry features of the ISP industry, such as the high capital investment required for infrastructure projects, the rapid technological obsolescence, the specific nature of cash flow generation and the significant proportion of intangible assets. The purpose of the research is to develop a specialized analytical toolkit that provides accurate diagnosis of the financial condition of telecommunications companies in an environment characterized by high capital intensity, rapid technological change, and regulatory challenges. This toolkit aims to overcome the limitations of traditional methods, such as coefficient analysis and Altman models. The paper uses a systematic approach that combines comparative analysis of international practices (the USA, the EU, China) with Russian realities, quantitative methods of financial analysis (modified coefficients of liquidity, profitability). It also uses qualitative methods like stress testing. Additionally, the paper incorporates elements of predictive modeling using Big Data technologies. The main results of the study include: the development of eight key financial indicators that have been adapted to the specific needs of the industry. We have also proposed a three-tiered assessment system, which includes strategic, tactical and operational levels. Moreover, we have provided a rationale for a combined approach that integrates DCF analysis, AI analytics and regular stress testing. The results obtained are of great practical importance for financial managers in telecommunications companies. They allow for a more accurate assessment of investment risks and the sustainability of business models that optimize debt burden and investment management. Regulators can use the proposed methodology to monitor the stability of the industry. Investors can also use it to make informed decisions. The theoretical value of the work lies in the development of a new methodology for financial analysis of high-tech industries that takes into account their unique characteristics. The research conducted has shown that by adapting traditional methods to the specific needs of these industries, it is possible to improve the accuracy of financial diagnostics by 20–30%, which is critically important in a market high volatility such as the telecommunications industry.

The relevance of the study stems from the importance of identifying mechanisms that increase the economic stability of Russian households during times of socio-economic uncertainty. The purpose of the study is to investigate the relationship between public and private transfers and household economic stability as perceived by individuals. The research information base is grounded in data from the HSE household survey for 2016, 2020 and 2024, which were combined into one dataset. The tools of multinomial logistic regression were used to model the impact of transfers on subjective evaluation of economic stability. The subject of the study is public and private monetary transfers received by households in the context of their impact on economic stability. This is measured through a subjective assessment of material stability. It was revealed that during the pandemic, there was a sharp decrease in both intra-family mutual assistance and assistance from external benefactors. The state benefits and benefits included in the survey performed poorly the function of supporting socially vulnerable groups. The study has established a relationship between transfers and subjective stability of households demonstrating that the nature of this association is determined by the source of monetary transfers. Households receiving government transfers increased their sense of stability, while financially vulnerable households were more likely to receive inter-family and charitable assistance.