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In the context of growing economic uncertainty, capital structure optimization is becoming a critical tool for minimizing financial risks, providing companies with the necessary stability and adaptability in modern conditions. This paper aims to develop theoretical foundations for the existing capital structure optimization methods and elaborate an optimal capital structure formation strategy to ensure companies’ financial stability and flexibility in conditions of high financial uncertainty. The article offers a stabilization-flexible approach to optimizing companies’ capital structure in financial instability and crises, making it possible to ensure the companies’ financial stability while preserving their ability to adapt to a volatile environment quickly. The main idea of the approach is the balanced use of equity capital and long-term and short-term liabilities to finance various components of assets, which helps to minimize risks and increase the efficiency of financial management. A roadmap for the implementation of the stabilization-flexible approach to optimizing the capital structure has been formed, the basis of which is the construction of a logical chain of actions, including the definition of companies’ goals, the assessment of available financial resources and risks, and the development of financing strategies, their implementation, further control and monitoring of results. The study results can be helpful for financial managers, analysts, and investors seeking to improve the efficiency of capital management and reduce the impact of external and internal risks on the financial condition of companies.

During the war, threats to national security related to illegal financial transactions with the aggressor country, circumvention of sanctions, fraud in the distribution of investment and humanitarian aid, earmarked funds for the reconstruction of destroyed infrastructure, and new schemes for legalizing dirty money are becoming more acute. Therefore, the study of the risks of illegal financial transactions at the regional level in Ukraine is a primary step towards understanding the specifics of corruption, identifying the main factors that shape them, and developing targeted measures to overcome them. To analyze corruption risks in the regions of Ukraine and the city of Kyiv, this article uses a base of 10 indicators covering key aspects of financial support, economic activity, public opinion, trust in government, and digital transformation to provide a holistic picture of regional security and development. Clustering by the level of corruption risk, which was implemented using Kohonen's self-organizing maps, allowed to identify 4 groups of Ukrainian regions with similar characteristics: Cluster 1 (Vinnytsia, Lviv and Ternopil regions) – regions with a high level of development and medium corruption risks; Cluster 2 (Volyn, Dnipropetrovs'k, Donetsk, Zhytomyr, Ivano-Frankivsk, Kharkiv, Khmelnytskyi and Chernihiv regions) – regions with an average level of development and moderate corruption risks; Cluster 3 (Zakarpattia, Kirovohrad, and Rivne regions) - regions with an average level of development and problems in governance; Cluster 4 (Zaporizhzhia, Kyiv, Luhansk, Mykolaiv, Odesa, Poltava, Sumy, Kherson, Cherkasy, Chernivtsi regions and the city of Kyiv) – regions with high corruption risks. The implemented clustering facilitates the development of individualized and targeted anti-corruption strategies for each group of regions. The results of the study allow us to focus anti-corruption efforts on the most problematic areas and develop targeted programs to effectively reduce corruption risks.

The emergence of cryptocurrencies as a form of digital payments has contributed to the emergence of numerous opportunities for the implementation of effective and efficient financial transactions, however, new fraud and money laundering schemes have emerged, as the anonymity and decentralization inherent in cryptocurrencies complicate the process of monitoring transactions and control by governments and law enforcement agencies. This study aims to develop a mechanism for analyzing transactions in the Ethereum cryptocurrency using a Bayesian classifier to identify potentially suspicious transactions that may be related to terrorist financing and money laundering. The Bayesian approach makes it possible to consider the probabilistic characteristics of transactions and their interrelationships to increase the accuracy of detecting anomalous and potentially illegal transactions. For the analysis, data on transactions of the Ethereum currency from June 2020 to December 2022 were taken. The developed mechanism involves determining a set of characteristics of transaction graph nodes that identify the potential for their use in illegal financial transactions and forming intervals of their permissible values. The article presents cryptocurrency transactions as an oriented graph, with the nodes being the entities conducting transactions and the arcs being the transactions between the nodes. In assessing the risks of using cryptocurrencies in money laundering, the number/amount of transactions to and from the respective node, the balance of these transactions (absolute value), and the type of node were considered. The analysis showed that among the 100 largest nodes in the network, 11 were identified as having a «critical» risk level, and the most closely connected nodes were identified. This methodology can be used not only to analyze the Ethereum cryptocurrency but also for other cryptocurrencies and similar networks.

This study aims to conduct a bibliometric analysis on the topic of public policy and financial regulation in preventing and combating financial fraud using a variety of bibliometric methods and tools, including the in-built tools of Scopus by Elsevier (SciVal) and Web of Science by Clarivate Analytics, as well as VOSviewer software. The most relevant publications related to the search terms were identified. Based on the results, a map illustrating the interrelationships of concepts such as “financial fraud,” “public policy,” and “financial regulation” with other categories was created, allowing for the identification of five clusters, each of which was characterized in detail. The results of the evolutionary and temporal analysis of scientific research showed that before 2000, scholars focused on the legislative aspects of combating financial fraud; from 2000 to 2015, on risk management and the impact of financial fraud on economic growth; from 2016 to the present, on the search for methods and tools to detect and combat financial fraud. The spatial analysis confirmed a predominantly intercontinental connection between researchers. The comparison of subject areas demonstrated the interdisciplinary nature of the study, with a predominant focus on the fields of “computer science” and “economics, econometrics, and finance,” which is logical considering the economic nature and the ongoing technological transformation of financial fraud. The results can be utilized to develop new strategies, policies, and legislative initiatives to ensure financial integrity and increase confidence in financial systems. AcknowledgmentThis study is funded by the Ministry of Education and Science of Ukraine and contains the results of the projects No. 0123U101945 “National security of Ukraine through prevention of financial fraud and money laundering: War and post-war challenges”, 0121U109559 “National security through the convergence of financial monitoring systems and cyber security: Intelligent modelling of financial market regulation mechanisms” and by the Vega Agency No. 1/0638/23.

Forecasting external public debt under conditions of uncertainty is important as it allows the country to respond adequately to economic and financial challenges, promotes efficient management of financial resources, formation of a stable financial policy and ensures the country's external debt security, which are critical elements for ensuring economic sustainability and sustainable development. The article's main purpose is to critically analyze and apply existing time-series forecasting methodologies to determine the future values of Ukraine's external public debt in conditions of uncertainty caused by the still unresolved consequences of the COVID-19 pandemic and russia's invasion and full-scale war in Ukraine. Using three forecasting methods, namely trendline extrapolation, exponential smoothing, and autoregressive and moving average models, the paper forecasts the volume of external public debt until 2029 and presents a graphical representation of the debt dynamics from 2011 to 2029. The most pessimistic forecast for the growth of external public debt was revealed when applying the method of data extrapolation based on the trendline. A comparative analysis of the forecast values for the three forecasting methods has revealed common trends in the growth of public debt, as well as the key advantages and disadvantages inherent in each model. Importantly, the article emphasizes the common risks identified in forecasting Ukraine's external debt using time series analysis models, including the problem of achieving only short-term forecasting accuracy and insufficient flexibility taking into account complex and unexpected changes that may arise in conditions of uncertainty and economic instability. The results of the study provide valuable information for policymakers and stakeholders trying to navigate the complexities of managing external public debt under uncertainty.

The purpose of this study is to substantiate the theoretical provisions on the accounting support for sustainability reporting and develop practical recommendations for improving the mechanisms for generating fragments of non-financial reporting based on accounting data. The study is conducted on the example of Ukraine. The paper provides a bibliometric analysis of scientific publications on the reporting in the field of sustainable development. Generalizing the results of the content-context block of the bibliometric analysis allowed identifying seven clusters. In the context of the study, the most relevant is the fourth cluster, which reflects the relationship between sustainability reporting and accounting. To create an effective mechanism for building sustainability reporting, a five-step sequence of actions based on accounting data was proposed, and tables were created to simplify the search for the necessary information to fill out fragments of a sustainability report and assess social and environmental security based on accounting data.

The Crimea annexation and the military aggression of the Russian Federation, which first began in some territories of the Donetsk and Luhansk regions in 2014 and escalated into a full-scale war on February 24, 2022, resulted in heavy losses of life and a humanitarian crisis, exacerbating economic, political and social instability. To restore Ukraine’s economy, all businesses, including hospitality (hotel and restaurant business) sector, should continue functioning, though it is a challenging but crucial task. The paper aims to analyze the state of the hospitality market in the current war conditions in Ukraine and assess the possibilities of its restoration and development. An online survey was conducted among 282 representatives of the hospitality business in Kyiv, Sumy, Chernihiv, Dnipropetrovsk, Kharkiv, Poltava, Ivano-Frankivsk, Lviv, Ternopil, and Zakarpattia regions. Based on the results, in 2022, almost 23% of hospitality industry representatives suspended their activities, and 54% functioned only partially. Many surveyed hotels and restaurants (36%) have gradually changed and adapted their business strategies. For more than half of the hospitality representatives, expenses increased by 20-50%, and profits dropped by more than 20%. The critical consequences of the full-scale war for the Ukrainian hospitality market are as follows: disruption of supply chains, reduction in consumers’ purchasing power, changes in consumer demand, shortage of certain types of products, shortage of personnel, and business unprofitability.

Public debt can attract funds to finance public needs and stabilize the country’s economic development. This study aims to analyze the relationship between public debt and economic development considering the war actions in Ukraine. This paper uses bibliometric analysis, comprising in-built Scopus and WoS instruments, VosViewer, and Google Trends tools. The overall results show the close relationship between public debt, economic development, and war (armed conflict) concepts. The publications were examined according to key features: containing the keywords from the green and red clusters; covering the period 2015–2018 and 2022; and discussing public debt in Central and South-Eastern Europe. This improved the theoretical and methodological approach to the bibliometric analysis of public debt. Moreover, the study identified risks (based on selected scientific publications) to which the primary attention should be paid during the war and post-war periods in Ukraine: currency and demographic risks. Key recommendations were provided to ensure debt security during the war and post-war periods. However, the given recommendations should be implemented within the framework of the Recovery Plan of Ukraine, which would improve the credit rating and reliability of the state.

Sovereign wealth funds accumulate the largest resources to bridge the financial gap under the Sustainable Development Goals. The basic mechanism for accelerating sustainability progress is the effort of sovereign wealth funds to incorporate environmental, social, governance and ethical criteria and targets of these Goals disclosed in their sustainability reports. This study aims to develop a methodology for assessing the Sustainability Transparency Index in a sample of sovereign wealth funds, as well as to investigate how this transparency is influenced by the size of funds’ assets and sustainability progress with a cross-regional comparison. Five groups of sustainability disclosure metrics, such as the main pillars of novel Sustainability Transparency Index, were tested and analyzed for 91 funds using binary variables and normalization method. Three hypotheses regarding the statistical association of funds’ sustainability transparency index with the size of the funds’ assets, countries’ sustainability progress, and the region of a fund were checked for 87 funds using multiple regression. The overall results of the Sustainability Transparency Index show an insufficient level of funds’ transparency. Sustainability disclosure in 57% of funds surveyed should be fully enhanced in terms of greater sustainability transparency. There is strong evidence of the correlation between the volume of funds’ assets and sustainability transparency as well as the leadership of European funds in a cross-regional comparative study. However, data on the progress of the country’s sustainability and the funds’ Sustainability Transparency Index are limited and can be used as evidence of the insufficient role of fund transparency in promoting sustainability.

One of the pressing problems in the modern development of the world financial system is an excessive increase in state debt, which has many negative consequences for the financial system of any country. At the same time, special attention should be paid to developing an effective state debt management system based on its forecast values. The paper is aimed at determining the level of persistence and forecasting future values of state debt in the short term using time series analysis, i.e., an ARIMA model. The study covers the time series of Ukraine’s state debt data for the period from December 2004 to November 2020. A visual analysis of the dynamics of state debt led to the conclusion about the unstable debt situation in Ukraine and a significant increase in debt over the past six years. Using the Hurst exponent, the paper provides the calculated value of the level of persistence in time series data. Based on the obtained indicator, a conclusion was made on the confirmation of expediency to use autoregressive models for predicting future dynamics of Ukraine’s state debt. Using the EViews software, the procedure for forecasting Ukraine’s state debt by utilizing the ARIMA model was illustrated, i.e., the series was tested for stationarity, the time series of monthly state debt data were converted to stationary, the model parameters were determined and, as a result, the most optimal specification of the ARIMA model was selected.

The paper explores theoretical and practical aspects of forecasting the government debt in Ukraine. A visual analysis of changes in the amount of government debt was conducted, which has made it possible to conclude about the deepening of the debt crisis in the country. The autoregressive integrated moving average (ARIMA) is considered as the basic forecasting model; besides, the model work and its diagnostics are estimated. The EViews software package illustrates the procedure for forecasting the Ukrainian government debt for the ARIMA model: the series for stationarity was tested, the time series of monthly government debt was converted into stationary by making a number of transformations and determining model parameters; as a result, the most optimal specification for the ARIMA model was chosen.Based on the simulated time series, it is concluded that ARIMA tools can be used to predict the government debt values.

Purpose: To substantiate the place and role of the responsible investment in the structure of the stock exchange market. Methods: Structure-functional in order to form an idea of the structure of the stock exchange market, determining the place and role of responsible investment elements in the stock market organization; systematic analysis to identify current trends and patterns in the functioning of the socially responsible investment segment by geographical regions of the world; statistical and graphical methods for quantitative and visual presentation of the results of the stock market sectors analysis, represented by responsible investment elements. Findings: The definition of «responsible investment» and «stock market» has been clarified; a number of subjects, objects and forms of responsible investment, which are elements of the stock market, are singled out and substantiated; the generalization of activities of stock exchanges in the field of responsible investing is carried out; the dynamics of stock market sector indicators, which are represented by elements of responsible investment, are analyzed; key reporting standards used by stock exchanges in disclosing ESG issues are analyzed. Theoretical Implications: A comprehensive assessment of the functioning of socially responsible investment segment as part of the stock market is carried out, the place and role of responsible investing in the stock market structure are substantiated, which creates a basis for the development of effective measures to increase the stock market efficiency of Ukraine and its transformation into an effective and stable source of investment resources. Future Research: The results can be used in the context of further study of the stock market transformation in Ukraine on the basis of a socially responsible trajectory and fractal analysis. Paper Type: Theoretical. The study was performed within the state budget research «Fractal model of the stock market transformation in Ukraine: socially responsible investment to achieve the Sustainable Development Goals» № 0121U100473.

Nowadays one of the relevant problems of economic development of Ukraine is the excessive increasing of the public debt that has a number of negative consequences for the financial system of the country. The article is devoted to the research of state’s debt sustainability concept. Special attention is paid to the development of an effective system of debt sustainability management. The aim of the article is to study the theoretical bases of the state’s debt sustainability, investigate scientific and methodological approaches to its management, analyze the public debt and debt sustainability of Ukraine. In order to achieve that goal, the following scientific methods were used: analysis and generalization, decomposition analysis, comparison and compilation. The authors analyzed the structure of the debt sustainability management system: objects, subjects, key principles, objectives, methods, instruments, etc. The list of key indicators of debt sustainability was substantiated and the authors compared their normative values in Ukraine and in world practice. Besides, the state and structure of public debt and the ratio of government debt to GDP were scrutinized. The obtained results proved the debt crisis deepening in Ukraine.