This paper investigates the degree of persistence in the financial markets' data during different days of the week over the last twenty years. This allows taking a brand new look on the day-of-the-week effect and providing additional evidence against the efficient market hypothesis. The variety of the financial markets includes developed and emerging stock markets, FOREX, commodity and cryptocurrency markets. To measure the level of persistence the R/S analysis is used. The findings indicate that the level of persistence is different for different days of the week. This is inconsistent with the Efficient Market Hypothesis: data do not follow a random walk; and there can be indirect evidence in favor of the day-of-the-week effect. Conclusions on non-randomness of the data are important, because they allow choosing the best model to describe price dynamics so that to increase the predictive power of the existing models. Differences in the long-memory properties of the market data during different days of the week is an important finding that can lead to better understanding of the behavior of financial markets. High level of persistence implies data predictability, and therefore suggests that trend following technics can be applied to make profits from trading.

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.

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.

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.