This study examines the foundations and prospects of competitive money supply in the context of digital transformation. The relevance of this topic is due to the fact of rapid development of digital technologies, as well as such innovative phenomena of the financial world as cryptocurrency, which is becoming an increasingly significant element of the financial system. The study incorporates such deep issues of economic theory as the essence and functions of money, correlating them with modern processes of digitalization of the economy. The author concludes that the prospects for a competitive money supply in the context of digital transformation depend on many factors, including technological innovations, regulatory policies and changing consumer needs, and technological innovations such as digital currencies, blockchain technologies, mobile payments and fintech startups are changing the landscape of the financial sector.

The article deals with the urgent problem of improving the accuracy of forecasting the price movements of shares of companies from the information technology sector, which is due to the increased interest of investors and traders in this sector in recent years. The aim of the study is to compare the accuracy of forecasts based on classical and non-standard price bars and evaluate their impact on the effectiveness of trading strategies.

Modern statistical methods and machine learning were used as the main research method to analyze and evaluate the predictive abilities of different types of price bars. In the course of the work, software functionality was developed to generate non-standard price bars, such as bars based on the price of gold, and various trading strategies based on moving averages and AutoML models were tested.

The author's results showed that the use of non-standard price bars improves the predictive properties of the models, which leads to an increase in the efficiency of trading strategies. The practical significance of the obtained results lies in providing recommendations to traders and investors on the selection of optimal types of price bars to improve the accuracy of forecasts. Theoretical significance consists in confirming the hypothesis of higher efficiency of non-standard price bars in trading systems focused on IT companies.

Since February 2022, the Russian stock market has been almost completely cut off from international investors (the so-called "new reality") amid sanctions pressure, and, accordingly, the initial public offering (IPO) process for domestic issuers has also undergone significant changes. At the same time, IPOs as a tool have become more accessible to domestic companies and have also gained more popularity among retail investors (after rising activity in 2H2020-21), who have become a new driving force in the stock market. The Russian IPO market of the "new reality" is gradually forming its own characteristics (IPO size, transaction pricing, demand structure, etc.), and its methodological study may have significant practical significance. The purpose of the study is to identify the key features of the Russian IPO market of the "new reality". As part of state initiatives to double the capitalization of the stock market, the Government has been instructed to take additional measures to support IPOs of Russian companies, which confirms the relevance of this study. The findings may be useful for new issuers planning an IPO, as well as for the scientific community studying the problems of the Russian equity capital market.

Based on the idea of the dual nature of the results of economic research, we consider the problematic field of aligning incentives for scientific research with the needs of users of researchbased economic knowledge, represented by government agencies carrying out their functions. We reveal the lack of attention from the state towards implementing scientific policy in relation to the established interdisciplinary features of Russian economics that are important for organizing transactions regarding the production and transfer of expert knowledge between the source and public authorities. We conclude that it is necessary to adjust approaches to forming scientific policy, considering both applied and basic directions of economic science development. Using the elements of economic theory of transaction costs, we propose a model of interaction between researchers, external authorized bodies, and end users, as suggested by E.V.Balatsky and N. A. Ekimova (2023) argue that the identified three-way transaction management mechanism should be supplemented with tools of a new industrial policy. This policy, in addition to addressing resource endowments, can create conditions for fair competition within the academic community.

The article addresses the issues of dynamic pricing in taxi and courier delivery markets, where search frictions and matching failures play a significant role, leading to increased costs and reduced efficiency in resource allocation. The study demonstrates how the use of matching technologies and dynamic pricing helps reduce costs and enhance resource allocation efficiency amid changing demand and supply. A taxi service market model is constructed to analyze the impact of price surge multipliers on eliminating matching failures. The analysis showed that dynamic pricing reduces the probability of matching failures, enabling market equilibrium, especially during periods of high demand. This improves consumer and producer welfare.

In article are researched current trends and strategic prospects of investment policy as important state regulation instrument of Russian oil and gas complex, are assessed key indicators of investment in the fuel and energy sector. Are considered the issues of comprehensive implementation of the largest oil and gas projects, their financial support and development of energy infrastructure. Is scientifically justified the feasibility of developing unified methodic for ensuring access to budget financing for oil and gas projects, which is designed to provide additional added value to the final products. The adoption of state measures of stimulating character contributes to the emergence of new forms of interaction between the state and the oil and gas business within the framework of the created special economic zones. The accumulated investment experience, in particular the provision of state guarantees of the safety of investments for the development of industrial production, can be effectively applied in the national energy market. In the context of unprecedented external challenges, effective interaction between the state and oil and gas companies contributes to improving the efficiency of its functioning and ensuring the sustainability of the national economy.

The main provisions of the international methodology for assessing investments in the development of the national economy, the economy of individual industries and regions, as well as specific enterprises, adapted to Russian conditions, reflected in the officially valid methodological recommendations, as they are mastered by business, need to take into account and generalize the accumulated experience, revise and supplement a number of provisions, starting with the conceptual scheme, which is no longer fully reflects the realities that are important for the practice of investment design. The article discusses a number of specific proposals aimed at improving this well-known scheme.

Artificial intelligence technologies penetrate all spheres of the society and change the market. Companies should master them not only in order to succeed but also to survive on the market. Franchising nets strive to master artificial intelligence as soon as possible and spread the technologies all over the net. Nevertheless, the usage of the artificial intelligence technologies has some risks. That determines the relevance of studying the perspectives and the risks of artificial intelligence in franchising nets. The aim of this article is to study the perspectives of artificial intelligence usage in franchising as well as the risks which faces the net while implementing the new technologies. To achieve the aim the experience of the Russian franchisors mastering the artificial intelligence as well as their results were analyzed. It was determined that many franchising nets already use artificial intelligence while contacting franchisees and consumers but face such risks as cybersecurity and the lack of qualified personnel in the sphere of artificial intelligence.

The article proposes a methodological approach that makes it possible to rank territories according to the level of sustainable development over time using the cluster analysis method. The approach is based on dividing regions into groups (clusters) according to selected indicators that reflect the economic, environmental and social development of the provinces. Testing of this approach on the example of the provinces of the People's Republic of China made it possible to identify the key factors that determine the movement of territories into sustainable development clusters. Based on the analysis of economic and energy policies in successful provinces, measures have been identified that contribute to the movement of provinces into clusters with a higher level of sustainable development. It is shown that the transition of provinces to clusters of a higher level of sustainable development is due to two main factors: - changing the structure of the energy balance due to access to pipeline natural gas (Yunnan, Heilongjiang provinces), development of nuclear (Liaoning province) and renewable energy (Guizhou, Hebei provinces); - increasing the environmental and economic efficiency of the use of energy resources by rationalizing energy production and energy consumption, as well as energy saving (provinces of Liaoning, Jiangxi, Guangxi, Qinghai, Henan, Anhui, Chongqing).

In this article we systematize the modern challenges of the teaching of macroeconomic science for ndergraduate students, and possible answers to these challenges. We demonstrate how these answers can be implemented in practice in the process of reading relevant bachelor's courses. The article is based on the experience of teaching macroeconomics at the Faculty of Economics of Lomonosov Moscow State University. The intense discussion about the education of Russian economists in modern conditions, which is conducted in academic and expert literature, makes the article relevant.