Oleh Kolodiziev

Banks select environmentally and socially safe projects for investment and lending. The ESG reporting system developed in the EU for the implementation of ESG standards can be applied in Ukraine and other countries, with an emphasis on the disclosure of credit and investment aspects. At the same time, achieving full standardization of information on the consideration of ESG components in the system of internal banking management and controlling remains a pressing issue. Therefore, this article is aimed at: creating a landscape of ESG factors with the allocation of a new concept of OperESG related to operational activities; analyzing four European banks that practice comprehensive disclosure of ESG information; and developing templates for aggregation of ESG indicators that can be useful for researchers, practitioners, and supervisory authorities, respectively. The results are presented in the context of the features of the application of ESG financial management and controlling tools. A matrix of the impact of ESG factors on the operational efficiency of banks is proposed for four segments of OperESG: direct environmental, indirect environmental, social, and managerial. Based on expert assessment, 27 components of OperESG were identified. Correlation analysis between ESG ratings and selected economic indicators – assets, profit before tax, return on assets and equity, and financial leverage – was conducted on a sample of 33 banks worldwide, the results of which may be useful for investors. A methodological approach to systematizing costs, forming eco-budgets, and developing a template for assessing key ESG performance indicators, as well as creating a single metric for plan/fact analysis in order to monitor the achievement of sustainable development goals by all economic agents, is proposed.

The aim of the article is to develop theoretical and methodological approaches to assessing the turbulence of financial markets and to substantiate the criteria for its measurement based on an empirical analysis of their dynamics. The article examines the peculiarities of the functioning and development dynamics of financial markets under conditions of global instability, increased geopolitical risks, and martial law. Theoretical approaches to interpreting the essence of turbulence in capital markets are generalized and systematized, which allowed clarifying its content as a complex phenomenon associated with sharp changes in volatility, liquidity, risks, and correlation interconnections between financial instruments. A system of criteria for assessing the turbulence of financial markets is proposed, which includes indicators of volatility, liquidity, yield spreads, as well as indicators of geopolitical tension. The advisability of integrating heterogeneous indicators within a single analytical approach is substantiated, which allows increasing the accuracy of assessing the state of financial markets. The key methodological limitations of existing approaches to measuring turbulence have been identified, and directions for overcoming them have been outlined. An empirical analysis of financial market dynamics has been conducted using modern econometric tools, which made it possible to identify the key determinants of turbulence and assess the strength of their impact. Within the framework of the study, an integrated financial market turbulence index has been developed, which is based on a multidimensional approach to aggregating indicators of volatility, liquidity, risk, correlation dependencies, and geopolitical factors. To ensure the statistical comparability of variables, a standardization procedure (Z-transformation) was applied, which allowed for neutralizing the influence of different measurement scales and increasing the accuracy of indicator integration. The proposed index serves as an efficient tool for identifying phases of turbulence and financial market stability, as well as providing the possibility for a formalized assessment of the level of financial instability. The decisive impact of the wartime factor and geopolitical shocks on the behavior of financial market participants has been substantiated. Based on the obtained results, practical recommendations have been developed aimed at increasing the resilience of financial systems and adapting to conditions of growing uncertainty.

The financial technology industry and its individual segments have been investigated in this study. The task addressed relates to the insufficient development of methodological tools for quantitatively determining the role of maturity of key technologies as a factor of investment attractiveness, as well as the fragmentation of the analysis of technological drivers of investment activity in FinTech segments. The methodological basis of this study is the Gartner Hype Cycle model. The information basis is data from global rating and research agencies. The global investment dynamics for 2018–2024 were analyzed, as well as their parameters in the context of individual sectors, which made it possible to identify the main patterns of investment activity. Based on the rule-based approach, methods for determining score estimates for investment activity and for the technology maturity factor have been proposed. They make it possible to eliminate the nonlinearity critical for the use of correlation analysis, which is inherent in the Gartner model. The results of the analysis of investment activity and maturity factors of key technologies confirmed a high positive correlation (r = 0.8615) between the indicated indicators. It was determined that the main driver for increasing investment activity is the implementation of key technologies that are near the “peak of inflated expectations” in the Gartner model. It was established that at present such technologies are often associated with artificial intelligence. Thus, taking into account the stages of technology maturity allows one to better explain investor behavior and predict changes in investment activity in FinTech segments. The results also extend to other sectors of the digital economy with a high share of intangible assets, fast cycles of updating and scaling, network effects, and a global sales model

Ensuring the financial stability of the banking system is a key prerequisite for macroeconomic resilience and sustainable economic development, particularly under conditions of military conflict and increasing European integration commitments. The article examines methodological approaches to ensuring the stability of the banking system of Ukraine under martial law and macroeconomic uncertainty. Despite the extensive literature on banking stability, the combined influence of military risks, macrofinancial shocks, and regulatory convergence with the European Union remains insufficiently explored. The study is based on official statistical data of the National Bank of Ukraine, the IMF, and international financial institutions for the period 2015–2024. The methodological framework includes methods of analysis and synthesis, comparative analysis of regulatory convergence, construction of an integral financial stability index, and multifactor regression modelling to assess the impact of internal and external determinants of banking stability. The results indicate that key internal determinants include capitalization (CAR), liquidity indicators (LCR, NSFR), profitability (ROA, ROE), and credit risk (NPL ratio). External factors such as GDP dynamics (5.3% growth in 2023), inflation (12.9%), exchange rate volatility, and geopolitical risks significantly influence the stability index. Regression estimates confirm the statistically significant impact of both banking and macrofinancial indicators. The study contributes to methodological approaches for assessing banking system stability under wartime conditions by integrating macrofinancial and institutional determinants into a unified framework. The results may support regulators in improving macroprudential policy, developing stress-testing scenarios, and adapting Ukrainian banking regulation to EU standards.

Debate persists over whether classical econometric or modern machine learning (ML) approaches provide superior forecasts for volatile monthly price series. Despite extensive research, no systematic cross-domain comparison exists to guide model selection across diverse asset types. In this study, we compare traditional econometric models with classical ML baselines and hybrid approaches across financial assets, futures, commodities, and market index domains. Universal Python-based forecasting tools include month-end preprocessing, automated ARIMA order selection, Fourier terms for seasonality, circular terms, and ML frameworks for forecasting and residual corrections. Performance is assessed via anchored rolling-origin backtests with expanding windows and a fixed 12-month horizon. MAPE comparisons show that ARIMA-based models provide stable, transparent benchmarks but often fail to capture the nonlinear structure of high-volatility series. ML tools can enhance accuracy in these cases, but they are susceptible to stability and overfitting on monthly histories. The most accurate and reliable forecasts come from models that combine ARIMA-based methods with Fourier transformation and a slight enhancement using machine learning residual correction. ARIMA-based approaches achieve about 30% lower forecast errors than pure ML (18.5% vs. 26.2% average MAPE and 11.6% vs. 16.8% median MAPE), with hybrid models offering only marginal gains (0.1 pp median improvement) at significantly higher computational cost. This work demonstrates the domain-specific nature of model performance, clarifying when hybridization is effective and providing reproducible Python pipelines suited for economic security applications.

The study aims to examine the impact of international trade on the sustainability of regional ecosystems in Ukraine, particularly amid the ongoing Russia-Ukraine war. The paper applies econometric modeling, factor analysis, cluster analysis, and geographic information systems (GIS) for spatial analysis. Sustainability indicators include environmental resilience indicators (carbon emissions, water quality), economic stability metrics (GDP per capita, investment in green technologies), and social sustainability factors (employment rate, access to education and healthcare). Results indicate that a 1% increase in exports enhances sustainability indicators by 0.9%, while a 1% rise in imports or demographic density reduces these indices by 0.94% and 0.75%, respectively. Cluster analysis identifies five groups of regions with varying ecological resilience, revealing critical vulnerabilities in southern and eastern Ukraine where resilience indices are below 0.5. War actions exacerbate these issues, causing infrastructure destruction, soil and water degradation, and pollutant emissions ranging from 152.5 to 16,311.4 thousand tons. Recommendations include scaling up environmental protection investments by 20% (from the current 5,965–165,228 thousand UAH) and integrating sustainability standards into international trade policies to harmonize economic activities with environmental management in crisis and post-war recovery contexts.

Introduction The article is devoted to the systematization of existing approaches to the analysis of the impact of financial instruments and technologies on the development of the economy in modern conditions of martial law. Ukraine has significant potential for adaptation to modern economic challenges. Effective development of exports and imports in conditions of war and post-war recovery requires a comprehensive approach, which includes state support for business, modernization of logistics infrastructure, expansion of the circle of trading partners, digitalization and strengthening of industrial potential. Objective. The objective of the article is to generalization of approaches to ensuring the stability of economic agents, taking into account the peculiarities of the functioning of the economy under martial law. Methodology. The study employs methods of analysis and synthesis, formalized, abstraction and comparison. Results. The article systematizes approaches to analysing the impact of means and technologies on the development of the national economy in modern conditions, identifies key areas of influence of the results of the implementation of innovations with clarification of their content, directions of influence and significance. A basic scheme of interaction of participants according to the key characteristics of financial stability is presented and approaches to ensuring financial stability in conditions of turbulence in the capital markets are systematized. The understanding of the essence of the concepts of «financial stability» and «turbulence of capital markets» at the stage of development of the digitalized economy is clarified. It is proved that the innovative development of export-import activity is a determining factor in strengthening the competitiveness of enterprises and the national economy. In the conditions of globalization and rapid technological progress, the strategy of foreign economic activity must be constantly adapted by implementing modern solutions. Innovations in product diversification, digitalization of processes, optimization of logistics and improvement of customs regulation contribute to increasing the efficiency of foreign economic activity and ensure sustainable development. It has been determined that the main components of imports will be energy technologies, military equipment and industrial equipment. The conclusion of new economic agreements with partners will contribute to the transformation of the trade structure, in particular, to increasing the technological level of imports and increasing the share of products with high added value in exports. Mastering the complex of proposed approaches to ensuring financial stability will contribute to a deeper analysis of current trends in the conditions of instability of capital markets and will allow timely adoption of justified and effective investment decisions.

The russian aggression against Ukraine underscores the need to reassess regional strategies for digitalization and inclusivity. The study aims to identify strategies for enhancing these areas during wartime. Taxonomy and cluster and factor analysis methods have shown that regions with a higher level of digitalization have lower levels of poverty and unemployment. Specifically, regions in the top quartile of the digitalization index reported, on average, 12% lower unemployment rates compared to those in the bottom quartile. The analysis identifies distinct regional groupings: areas such as Zaporizhzhia, Kherson, Donetsk, and Luhansk are partially occupied and exhibiting low digitalization and inclusivity, in contrast with Mykolaiv and Kirovohrad that show moderate progress. Rural regions face a significant digital divide, with only 60% of rural households having stable internet access compared to 90% in urban areas. Factor analysis confirms that wartime conditions have accelerated digital transformation, evidenced by a 42% increase in Diia app usage from 2021 to 2023 and a rise in internet penetration from 62% in 2019 to 78% in 2023. Additionally, IT sector export revenues grew by 20% in 2022, and technology startups doubled between 2019 and 2023. The study proposes a strategic framework for regional adaptation: intensive digitalization and inclusivity for Zaporizhzhia, Kherson, Donetsk, and Luhansk regions; digitalization for Mykolaiv region; inclusivity for Kirovohrad and Zakarpattia regions; and balanced adaptation for Chernivtsi and Khmelnytskyi regions. Recommended measures include modernizing digital infrastructure, expanding educational opportunities, supporting startups, and aligning digital and social initiatives to foster regional resilience and development.

The paper is devoted to an under-researched topic of the international business community’s reaction to russia’s armed aggression against Ukraine. It aims to evaluate how G7 and EU financial sanctions, institutional pressure, ESG ratings, and asset value of multinational banks in russia influence their decisions to reduce activities in the invading country. The study used the Yale CELI database of companies leaving and staying in Russia for the classification tree method. The results show that none of the banks headquartered in G7 and EU member states that had no or relatively little assets in russia before the invasion are doing business there on a pre-war scale. Unlike banks headquartered in other countries, most either curtailed their presence in that market or exited the market. This indicates that financial sanctions imposed by G7 and EU member states and institutional pressure on banks in these countries to withdraw from the russian market have proven effective to a certain extent. However, these factors do not meaningfully influence the business of multinational banks with significant assets in russia. The study has not confirmed the hypothesis that a bank with higher ESG ratings is more likely to curtail its operations in the market of an aggressor country and withdraw. However, nearly all banks that scaled back significant activities or even pulled out of russia have better ESG indicators than the industry average. The results suggest the feasibility of improving the methodologies of ESG rating providers for accurately measuring business reactions to aggression and war crimes.