The object of the study is digital assets and digital intellectual assets as objects of valuation. The subject of the research are the principles, factors, approaches and methods of assessing the value of digital assets, including digital intellectual assets, in order to involve them in civil turnover in modern realities. The relevance of the problem is caused, on the one hand, by the formation of new types of assets — digital, including intellectual — in the context of digitalization of the economy and public relations, on the other — by the uncertainties arising during their identification, as well as the need to substantiate the applicability of valuation principles, approaches and methods to determine the value of such assets for further involvement in civil turnover. The purpose of the study is to substantiate the principles, factors, approaches and methods applicable to the valuation of digital intellectual assets, their approbation on specific examples (domain names). Methods of statistical and comparative analysis, generalization, classification, and valuation were used. The essential characteristics of digital intellectual assets have been defined: intangible nature, creation with the help of digital technology; manifestation of value in the information system; the ability to civil (property) turnover as objects of intellectual rights. The applicability of valuation principles, income and comparative approaches to the valuation of digital intellectual assets is substantiated. The factors influencing the value of digital intellectual assets, as well as specific factors characteristic of one of the types of digital intellectual assets — domain names are identified. An example of using the analogs method to estimate the cost of a second-level domain name in the framework of a comparative approach is shown. It is concluded that digital intellectual assets satisfying all essential characteristics can be put on the balance sheet as intangible assets, and their market value is determined on the basis of income or comparative approaches using the principles of evaluation and identified factors.

Nowadays, companies traditionally use economic capital and follow the interests of profit-making by shareholders or financial structures. However, recently there has been a tendency to analyze non-financial factors affecting equity. Multicapitalism is a doctrine that studies the impact of social, environmental, and economic indicators on equity. The subject of the study is the Chinese oil and gas companies’ sustainable growth. The paper’s purpose is to consider the interdependence of non-financial indicators with the Higgins Sustainable Growth Rate (SGR) and the Ivashkovskaya Sustainable Growth Index (SGI). The primary task is to solve the problems faced by China oil and gas companies regarding the introduction of non-financial reporting. The methodological basis of the study is a regression analysis of the influence of non-financial factors on sustainable growth indices. The authors analyze the impact of non-financial factors EROI, PRP, ES, ROE_env, ROL, ROE_sr on the China oil and gas companies’ SGR and SGI. It is shown that non-financial indicators show a stronger correlation with SGR than SGI. The study’s main conclusion is that there is a significant positive correlation between individual non-financial indicators and sustainable growth indices. The practical application of the obtained research results is seen in the development of non-financial reporting of oil and gas companies in China by including indicators EROI, PRP, ES, ROE_env, ROL, ROE_sr to assess the work of sustainable growth of the enterprise.

Macroeconomic policy in Armenia over the past 30 years has led to a slowdown in economic growth. This, in turn, entails the need to revise approaches to macroeconomic regulation, as well as to search for key drivers of economic growth, which the state should emphasize in the future macroeconomic policy. The aim of this research is to analyze and assess the main drivers of economic growth in Armenia. We have employed the methods of statistical and comparative analysis, deductive analysis, as well as the analysis of historical data and the current state of the problem. The paper examines the key drivers of economic growth in Armenia, as well as periods of both a stable macroeconomic environment and economic crises, from the point of view of the efficiency and optimality of macroeconomic regulation. The current study identifies the most important sectors of the economy, analyses macroeconomic policy regulation in Armenia, and assesses the impact of such policies on economic growth in the country. The results show that today’s macroeconomic regulation can be considered ineffective, which certainly has a negative effect on the rate of economic growth. The key conclusion of the research is the thesis that it is urgent to develop new socio-economic policy approaches to ensure sustainable economic growth in the future and to emerge quickly from future economic growth crises without restricting or halting economic activity.

The relevance of the article is due to the need to develop gender budgeting in Belarus, as a recognized and increasingly demanded tool around the world to achieve gender equality, the United Nations Sustainable Development Goals and the implementation of the Beijing Platform for Action. The purpose of the study is to analyse the work done and the existing problems in the implementation of gender budgeting in Belarus, and to identify measures of State policy that contribute to a more comprehensive implementation of gender budgeting in the country. The methodology of the study consists in the analysis of the normative legal acts and state programs of the Republic of Belarus, scientific publications, Internet sources, official statistics, survey data, and recommendations of international organizations on compliance of the Belarusian policy with international best practice in gender budgeting. The results of the work are an reviewed progress and remaining problems in achieving gender equality and implementation of certain aspects of gender budgeting in Belarus; calculation of the composite indicator on gender budgeting and comparison of its value with OECD countries; development of a set of measures (action plan) for the implementation of gender budgeting in Belarus. The author makes a conclusion that at the moment gender budgeting is practically not applied in Belarus, however, some basis for its implementation already exists. Despite a relatively good position of Belarus in specialized international ratings, the problems of inequality remain relevant, to a greater or lesser extent, for many sectors of the economy and aspects of life of women and men. Comprehensive implementation of a gender approach in the budget process is to be an effective tool for solving such problems. Promising areas for further research are a comprehensive and detailed analysis of the impact of activities and the existing distribution of state programs expenditures on gender equality in Belarus, and implementation of gender budgeting at the level of local budgets.

The study focuses on identifying the driving forces behind the digital transformation of the economy in the financial sector and the development of the digital financial assets (DFA) market. The subject of the research is the factors of digital transformation and the DFA market. The relevance is due to the transformation of the world economy, associated, among other things, with the active development of the DFA market, the expansion of the possibilities of using distributed ledger technologies (DLT) and blockchain against the background of high growth rates of the cryptoasset market. The aim of the paper is to summarize the main trends in the development of the global cryptoasset market, determine the main factors of investment attractiveness of cryptocurrencies and explore the conditions for the successful implementation of various models of digital currencies of central banks (CBDC). In the course of the work, the methods of systematization and classification of information, multivariate statistical analysis were used. As a result of the study, 5 clusters of cryptocurrencies were identified, depending on the dominance in the market and the dynamics of price changes. The resulting functions can be used to predict the attribution of cryptocurrencies to the corresponding clusters. Among the factors that have a significant impact on the development of CBDC projects in general and with the wholesale model in particular, one can single out “capital”. At the same time, CBDC projects with a retail model are actively and successfully implemented in countries with a high level of technical knowledge and entrepreneurial talent, ahead of the capital factor in their importance. Taking into account the review of global trends, the development of fintech technologies, it was concluded that the processes of digitalization of financial assets are inevitable, the emergence of new forms of digital assets that dictate the need for the advanced development of their legal regulation.

redicting currency rates is important, for everyone who is trading and trying to build an investment portfolio from a range of crypto currencies. It is not subject to the same restrictions as fiat currencies. In this study, we seek to predict the exchange rate of BIT-COIN against the US dollar. The short-term data (365 observations) is processed using the LSTM model as one of the neural network models. Modeling is conducted by training a sample size of 67%, taking into account sharp fluctuations in the price of trade and a certain level of market efficiency. The GARCH model is used to select appropriate historical periods for how the LSTM model works and to test proficiency at the weak, semi-strong, and strong levels. The data series obtained from the website (Investing.com) have been processed. The researchers have found that the performance of the neural network improves as the EPOCH value increases with a training (research) period of 50 days before, which is consistent with the results of the proficiency test at the weak level. It agrees with the results of the sufficiency test at the weak level, which indicates that in the case under study (the Bitcoin market is effective at the weak level). It is advised that crypto-currency investors rely more on the historical trend of the price of the currency than on its current price, taking advantage of the artificial neural network model (LSTM) in dealing with little data of high volatility.

The business strategy, the underwriting policy, the investment strategy of insurance companies and some external factors influence their ability to meet liabilities. The risk management mechanism, based on regulatory requirements and the best expertise, should allow to identify and assess all significant risks, including the market risk. The purpose of this research is comparing the European and Russian regulatory requirements for capital calculation for market risks of insurance companies. The methodological base is the comparison analysis of different capital calculation approaches for interest rate, FX, real estate and equity risks in accordance with Solvency II for the European insurers or Regulation 710-P for the Russian insurers. As a result, the author has found the compatibility of regulations to vary depending on the type of the risk in question. Regulations diverge the least when it comes to FX and real estate risks, yet the most in regards to interest rate and equity risks since the Central Bank of Russia has accounted for some national market peculiarities. Overall, the research results have a practical value and could be used by the Russian insurers in transition to the riskoriented regulation.

The subject of the research are the companies of the IT sector, as a strategically important sector in the information age. Their development of companies in the IT sector is associated with high risks and requires large volumes of investments, including attracting bank loans. In this regard, the purpose of the study was to develop an adequate sectoral methodology for rating companies in the IT sector by the level of creditworthiness risks using mathematical and statistical tools that make it possible to reliably assess the potential risks of investors. To achieve this goal, the study proposes a methodology for assessing the creditworthiness of IT companies based on a system of risk factors, which makes it possible to quantify the exposure of companies to two generalized risk groups: financial risk and business risks. Based on the cluster analysis, a rating table has been developed, according to which, depending on the calculated score, the category of the company’s creditworthiness is determined. The study concluded that the key factors affecting the creditworthiness of companies are: indicators of financial stability, return on assets, liquidity ratio, online advertising market size, as well as the share of intangible assets in the structure of assets and the amount of research costs. development and capital investments. The constructed scoring model was tested on the Mail.ru Group company (from 12.10.2021 — VK). Practical significance of the research results includes in the fact that the developed model can be applied not only for assessing creditworthiness, but also as one of the express methods of risk management in an organization.

The object of the research is the diagnosis and evaluation of financial risks in order to create an effective risk management policy. The subject of the research is the methodology of direct fuzzy evaluation of financial risk “chains” of an organisation. The relevance of the problem is due, on the one hand, to the dynamic and chaotic macro-environment and the business environment of organisations, on the other hand, to the drawback of the analytical and expert methods used to assess financial risks. The former, moreover, imply statistical data processing and operate with quantitative measures. For the latter, the difficulty is the impossibility of their application in a short time interval. From the perspective of operational risk management, financial risks deserve special attention since the effective operation of the entire organisation depends on them. The purpose of the research is to form a methodology for direct fuzzy evaluation of financial risk “chains” of an organisation. The authors apply the methods of mathematical forecasting, fuzzy modelling, calculation of financial and economic indicators, and expert risk assessment. The proposed methodology consists of 12 stages, beginning with the analysis of business processes and the identification of financial risks of the organisation. The main stage is the construction of a fuzzy evaluation model and the calculation of indicators: the probability of occurrence and realization of risks and risky situations of the financial risk “chains”, and the degree of confidence of the calculations conducted. The final stage of the methodology is an analysis of the results obtained to adjust the selected development strategy of the organisation, and the choice of methods for managing identified financial risks bearing the most significant financial and economic losses. The authors conclude the developed methodology allows to accurately assess the threat of a certain risk “chain” and losses from the implementation of specific risk situations for any organisation in the conditions of dynamic changes in internal and external elements of the business environment. The advantage of the methodology should be considered in the comparability of the accuracy of the evaluation and the low cost of modelling.

The subject of the study is to evaluate the contribution of strategic asset allocation to the variability of Moroccan pension funds performance. The aim of the paper is to identify the role of active management factors, namely tactical allocation and security selection, in generating a performance surplus compared to strategic allocation. The relevance of the study is justified by the need to identify the sources of performance creation in order to face the commitments of Moroccan pension funds and to compensate for the decline and volatility of asset returns. The article addresses, through the use of simple linear regression methods, the relative importance of strategic asset allocation in explaining the variability of the performance of Moroccan pension funds. It introduces a scientific novelty through the use of the “performance attribution” method. The conclusions of the paper confirm the main role of strategic asset allocation, which varies according to the size of the fund, the asset classes, and the risk aversion of the manager.

This paper investigates the financial performance of the largest Gulf Cooperation Council (GCC) banks by total assets before and during the recent COVID‑19 pandemic. The purpose of the study was to identify the impact of the COVID‑19 pandemic on banks’ financial performance. Financial ratios analysis during the period 2017–2020 is employed to measure the financial performance of the largest GCC banks mainly based in Saudi Arabia, Qatar, United Arab Emirates, Kuwait, Oman, and Bahrain. The ratios cover key performance areas such as profitability, efficiency, liquidity, asset quality, asset risk, and expense management. Two significant developments in 2020 are the COVID‑19 pandemic and severe drop in oil prices, both of which led to a sharp drop in the region’s GDP growth rate from an average of –0.09% in year 2019 to –5.9% in 2020, which in turn is expected to negatively impact bank performance. Using paired samples t-test the research study found statistically significant results that the financial performance of all banks suffered on almost all the key parameters in 2020 compared to the earlier period which can explained by the decline in economic activity due to COVID‑19. The focus of this study and its conclusions are novel to the extent that there are no country specific studies related to impact of COVID 19 on the biggest banks in a country. Further as far as the authors know there are no studies on the topic of impact of COVID‑19 on big banks operating in the Gulf cooperation council countries. The conclusions of the study would of importance to the regulators who would not like the big banks to fail.

The main hypothesis of the paper was the assumption that the increase in the level of innovation of the financial sector in the post-Soviet states and young European Union (EU) members with an imperfect banking sector and a protracted financial crisis is accompanied by difficulties accessing financing sources and significantly depends on the volume foreign banking capital. The aim of the study is to identify the correlation between the growth of financial innovativeness of the country and the level of foreign banking capital, using Panel data analysis from 2009 to 2019. Unlike previous studies, it was taken into account that the level of financial innovation of the republics of the former Soviet Union is increasingly dependent on external credit resources, while the innovative development of the EU countries becomes financially independent, and this constitutes the scientific novelty of the research. The results confirm the relationship between foreign banking capital and the growth of financial innovativeness of the country, especially with its low and medium levels. To test his hypothesis, the author presented empirical models with the conditions of interaction with the Financial Innovativeness Index. Based on a comparison of indicators of the financial innovation of the country and foreign banking capital, clusters of countries are distinguished according to the nature and direction of the relationship of the analyzed indicators. The author concludes that the increase in the level of innovation in the financial sector of the countries of the former Soviet Union and young EU members depends on the amount of foreign banking capital and the need to consistently expand the tools for the country’s economic growth by attracting it.

The purpose of the study is to assess the empirical relationship between economic growth and unemployment in the Russian economy. The research methodology is based on an econometric analysis of time series representing data on unemployment and economic growth to identify an empirical relationship between these variables. In the article continued the work on identifying the relationship between the unemployment rate and GDP in Russia based on empirical data. Based on the results of the optimal length model, the long-term Okun coefficient describing the relationship between GDP and unemployment is calculated. As a result of the empirical assessment, the Okun coefficient was obtained equal to 0.87, which is consistent with previous studies based on the data of the Russian economy. The discrepancies can be explained by the pandemic factor in 2020. It is concluded that the value of the long-term Okun coefficient confirms the stable relationship between GDP and the unemployment rate. However, its value for Russia is somewhat inferior to estimates for most developed countries and is comparable to indicators for emerging market countries. The results of the study can be used in the construction of short-term forecasts of the response of unemployment to changes in GDP, as well as in the development of macroeconomic policy measures in Russia as a whole.

The subject of the research is the analysis of priority directions of improvement of financial provisioning of activity of extra-budgetary funds of the Russian Federation that make up the system of social insurance institutions. The purpose of the study is to develop active and passive opportunities to improve the activities of the institution of social insurance, allowing to increase the level, stability and volume of insurance contributions to extra budgetary funds by improving the quality of the internal financial environment in certain types of economic activity, in particular “Manufacturing”. The relevance of the topic is confirmed by the fact that in recent years, the share of insurance contributions in revenues of social insurance institutions does not exceed 65%, i. e. in terms of the insurance mechanism, the budgets of social insurance institutions are deficit. Therefore, financial and economic solutions are required to improve the financial situation of social insurance institutions and stabilize their activities, including through intensive methods to encourage the activity of contribution payers to increase the rate base and reduce non-payments. The scientific novelty of the study lies in the development of author’s algorithm of forming the financial security program of social insurance institutions, combining active and passive opportunities, including financial instruments of solvency of economic entities. The main methods of the study include the method of content-analysis, tabular and graphical methods, analysis and synthesis as universal methods of scientific knowledge, as well as methods of effectiveness assessment. As a result of the study the basic elements of the program of improvement of financial maintenance of institutes of social insurance, including, in particular, offers on formation of passive possibilities at the expense of realization of measures of financial support from Government of the Russian Federation and active support at the expense of inclusion of actions in branch development strategies. And also recommendations are given on the inclusion of proposed measures in the activities of authorities and adopted sectoral strategies, including on the basis of the distribution of powers between the executive authorities and other interested parties on the basis of normative legal acts.

The subject of the research is the models of collection and consolidation (pooling) of resources for payment of public (free at the place of delivery) medical care to the population in developed countries and in the Russian Federation. The purpose of the study is to develop practical recommendations on the development of a system for financing medical guarantees for the population of the Russian Federation. The relevance of the study is due to the lack of resources to pay for public health care for the entire population in our country. The scientific novelty lies in the comparison of single-channel and multichannel pooling models used by developed countries in terms of their financial-economic and medico-social efficiency with the conclusion about a higher level of costs of the multichannel model with a comparable level of coverage with medical services of the population and indicators of its health compared to the model single payer. The research methodology is based on the use of complex, statistical, comparative and retrospective analyzes. It was concluded that the use of a multichannel pooling model in the financing of healthcare in the Russian Federation with the participation of competing insurers and the use of different channels of budgetary financing for different groups of the population is an important reason for the low efficiency of the Russian healthcare system. The prospect of further research is in the formation of a scientific and methodological justification for replacing the multichannel pooling model, which has historically developed in healthcare in Russia, with a single-channel model of a single payer represented by the Federal Compulsory Medical Insurance Fund (hereinafter- CMIF).

The relevance of the study is underpinned by continuing sharp scientific and practical discussion on the evolution of economic science aimed at obtaining exhaustive answers to such questions as: “What is orthodoxy in economic science? Why is it that the theoretical and methodological orthodoxy that accompanies the emergence and transformation of alternative directions of world economic thought cannot be overcome not only in the past but also at the present time? What is the historical significance of a retrospective analysis of vectors, stages and problems of the formation of unorthodox foundations in the development of this branch of human knowledge? and others. The findings of prominent Russian and foreign scientists-economists, allowing to reveal and comprehend the diverse methodological and theoretical components of orthodoxy in the past and present set the subject of this review article. The purpose of the study is to consider, systematize and generalize the evidentiary warnings published in the works of prominent modern researchers about the urgent need to overcome the negative consequences of orthodox maxims, which, having been absolutized since the time of the “fathers of political economy”, continue to manifest themselves to this day. The key research methods include systematic approach, evolutionary and cross-industry analysis. The results of the review incorporate conclusions and evidence that make it possible to unbiasedly comprehend the key scientific and practical problems for the fate of this science in the past and present. In particular, the author’s position is argued that the examples of postulating judgments about the presence and coexistence of “Western-non-Western”, “bourgeoisnon- bourgeois” economic science, which are still found in Russian economic literature, are based solely on the classformational research approach and therefore are completely untenable. It has been proved that from its “ancestors” and “fathers” of economics, i. e. adherents mercantilism and classical political economy principles to modern economists (from institutionalists to Keynesians and neoliberals) the existing palette of orthodox theoretical and methodological innovations accompanying the development of economic science explicitly or implicitly along with its commitment to the class analytical approach are due to a certain subtext of the absolutization of “objective economic laws”.

Identifying where to invest and how much to invest can be very challenging for common people who have limited knowledge in the domain. Portfolio managers are financial professionals who spend a lot of time and effort to help investors in investing funds and implementing investment strategies, but not all can afford to consult them. The study aims to develop a weighted hybrid recommendation system that recommends an optimized investment portfolio based on the investor’s preferences regarding risk and return. Generally, investors usually ask investment for advice from friends or relatives with similar risk preferences or if they are interested in a particular item, the investors ask for the experience of someone who already has invested in the same item. Therefore, the methodology considers the investor’s past behavior and the past behavior of the nearest neighbor investors with similar risk preferences. Using user-based collaborative filtering the number of stocks is recommended using Pearson correlation based on the investor’s income, then using another user-based collaborative filtering the number of stocks is recommended based on the investor’s age. Weights are assigned to the recommended number of stocks generated based on income and age and their weighted average is finally considered. Finally, the feasibility of the proposed system was assessed through various experiments. Based on the received results, the authors conclude that the proposed weighted hybrid approach is robust enough for implementation in the real world. The novelty of the paper lies in the fact that none of the existing approaches make use of more than one type of weighted recommendation algorithm. Additionally, the final results obtained this way have been never further fortified with the highest Sharpe ratio and minimum risk for the investor. This combination of hybrid and Sharpe ratios has never been explored before.