Purpose: to identify the degree of macroeconomic, industry, and internal factors influence on the fair value of PJSC Norilsk Nickel shares in the context of macroeconomic and geopolitical instability.Methods: сorrelation and regression analysis were the primary methods used to identify statistically significant relationships between fair value and various corporate, industry, and macroeconomic indicators. The analysis was conducted using R programming language, with statistical packages and visualization tools. Stationarity of time series was confirmed using ADF testing; non-stationary components were differenced. Multiple linear regression was used to build the model, followed by residual diagnostics.Results: correlation analysis indicated that global nickel prices and the IMOEX index are key positive drivers of the fair value for Norilsk Nickel shares. Notable inter-variable relationships were observed: global nickel and copper prices are correlated; the IMOEX index and USD/RUB exchange rate show a positive connection; RVI (Russian Volatility Index) and OFZ yields relate, reflecting growing uncertainty and interest rates. ROA and ROE are logically linked, while the debt burden shows a weak negative correlation with ROE. The final model demonstrates high statistical significance, stability, and absence of multicollinearity and heteroscedasticity. It explains the majority of fair value variation during 2015–2024.Conclusions and Relevance: the study confirms the significance of both industry-specific and general market factors in determining the fair share value for metallurgical companies. The resulting model holds forecasting potential and aids decision-making amid uncertainty. The findings can help investors assess the investment attractiveness of PJSC MMK Norilsk Nickel and assist corporate governance in strengthening resilience to external shocks.
Purpose: to formulate proposals for the stable development of the crowdinvesting segment in the conditions of the current market challenges.Methods: the research is based on the processing and analysis of data on deals conducted using crowdinvesting in 2022 – the first half of 2025. Systematization, classification and statistics methods were used to form the database. The methods of direct and indirect analysis were used to analyse the investors’ structure. The method of content analysis and comparison is applied to foreign scientific researches. To identify the market development prospects the analysis perimeter involves the regulatory environment, strategic financial market development documents, as well as modelling analysis of crowdinvesting platform and financial infrastructure interaction.Results: the database of investors in crowdinvesting was investigated, which served as the basis for the analysis of market participants in quantitative and qualitative aspects. The author's typologization of business models of crowdinvesting platforms and classification of transactions is proposed, which can become a part of the methodological basis for the formation of a risk management system for this financial instrument. The risks inherent in the involvement of retail investors in venture financing are indicated. A conceptual fork in the financial market development strategy is outlined in the format of minority investors’ participation in the equity of joint-stock companies.Conclusions and Relevance: recommendations for reducing risks and overcoming the limitations of the long-term development of the crowdinvesting tool were given. A comprehensive approach is proposed, which includes improving financial and investment literacy; increasing the share of institutional investors, taking into account the specifics of the early stages of the company's development, market segmentation depending on the type of transaction and characteristics of the company; risk distribution among market participants, taking into account the risk of transactions; improving the trust of all market participants by increasing information openness.
Purpose: to assess the potential of interstate integration as a foundation for achieving technological sovereignty within the Union State.Methods: the study is grounded оn systemic and spatial-economic approaches that conceptualize integration as a multilevel system of technological, production, and institutional interactions. An assessment of national approaches to technological sovereignty is conducted using a comparative analysis of academic literature and a macroeconomic analysis of indicators reflecting key factors of scientific and technological development. The potential for economic integration is evaluated through a structural analysis of mutual trade, a dynamic analysis of regional trade flows, and an institutional analysis of joint ventures.Results: the findings identify distinct models of technological sovereignty within the Union State. The Russian model is characterized by large-scale public financing of science and the development of a domestic research base, while the Belarusian model is primarily based on enterprise-level innovation activity and industrial modernization. Analysis of the structure of mutual trade indicates increasing sectoral complementarity, particularly in mechanical engineering and the chemical industry, while hydrocarbons remain a key driver of economic convergence. Interstate integration demonstrates growing spatial concentration in capital cities and industrially developed regions. Institutional constraints remain, but coordinated actions and harmonization of standards contribute to reducing barriers to integration, creating a technological and economic platform for it.Conclusions and Relevance: the study demonstrates that increased political tensions and sanctions pressure have intensified both similarities and differences in the models of technological sovereignty within the Union State, while simultaneously stimulating deeper economic integration. This is reflected in the convergence of trade relations, development strategies, and regional economic interaction toward more intensive contractual and industrial partnerships.
Purpose: to assess the impact of patent activity on the financial performance (EBITDA and ROA) of oil and gas companies in the context of import substitution policy in the framework of the open innovation concept.Methods: comparative, correlation and regression analysis with time lags of data from eight leading vertically integrated oil and gas companies – 4 Russian (PJSC Gazprom, Lukoil, Rosneft, Tatneft) and 4 international (BP, ExxonMobil, Chevron, Shell) for the period 2015– 2023. To assess the impact of import substitution on the operating profit of Russian companies, models with interaction variables were used.Results: universal positive relationship between patent activity and subsequent growth in EBITDA and ROA (with a 3-year lag) was not identified. Significant differences in the effectiveness of innovation strategies between companies were revealed. The correlation turned out to be strongly positive for Tatneft and ExxonMobil, and negative for Lukoil and Gazprom. This reflects different approaches, from formal patenting and meeting institutional requirements to the targeted creation of commercialized technological assets. Regression analysis with the interaction variable revealed a tendency to weaken the positive impact of patents on operating profits of Russian companies compared with international ones in the context of import substitution policy.Conclusions and Relevance: the import substitution policy stimulated the quantitative growth of patenting, but weakened its positive impact on the operational efficiency of Russian companies. This indicates a shift towards a more "closed" innovation model, where patent growth is often formal and does not provide the expected financial returns in the medium term. The study confirms that the quality of patents, the effectiveness of their commercialization, and the depth of integration into business processes are critical to financial results, rather than the volume of the patent portfolio.
Purpose: to justify the need to coordinate fiscal and monetary policies in order to create a favourable environment for the development of companies in the technology sector.Methods: the methodological basis of the study is a comprehensive interdisciplinary approach incorporating tools from behavioural economics, economic analysis, and event modeling. The computational part of the work is based on an analysis of technology companies' reactions to the Bank of Russia's key rate decisions using an abnormal return model. The empirical analysis utilized the returns of the Moscow Exchange MOEXIT index. The research objects include the shares of Ozon, YDEX (Yandex), HEAD (Headhunter), VKCO (VKontakte), POSI (the Positive Group), CNRU (Zian), ASTR (Astra Group), SOFL (Softline), DATA (the Arenadata Group).Results: the results of the analysis show that despite increased budget support for the technology sector, budgetary funds are being utilized insignificantly, while private investor funds are declining. Furthermore, investor reactions to key rate changes are weak and statistically insignificant. This means that when fiscal and monetary impacts are multidirectional – when fiscal measures stimulate development and high interest rates simultaneously restrain it – an environment is formed in which the technology sector does not receive sufficient impulse for accelerated development.Conclusions and Relevance: this paper substantiates the need to align fiscal and monetary policies as a key condition for effectively reorienting investment flows toward strategically important sectors that contribute to achieving technological leadership. The findings highlight the need to rethink the role of the stock market as a channel for transmitting macroeconomic incentives in the face of sanctions pressure, limited access to external financing, and the growing importance of private capital's behavioural sensitivity to state economic policy instruments.
