The main task for the Central Bank is ensuring the stability of the national currency. For this purpose, it tends to use traditional monetary regulation instruments. There are interest rates regulation, currencies intervention, administrative restriction, money supply adjustment and so on. A significant number of these traditional tools are effective. However, it is very difficult to assess the effectiveness of the regulators influence. Therefore, the purpose of the work is to define the theoretical substantiation of the basic monetary regulation instruments effectiveness and estimate its influence on the economy growth indicators in Ukraine. This article is based on the theoretical principles and methods of macroeconomic analysis; the system approach methods to define the main monetary regulation instruments of finance system and economy. The study presents a regression models with paired and multiple variables. For these models R-Studio instruments are the main tools of quality estimation and results interpretation. The article shows the results of statistical analysis of national currency rate and consumer price index which is based on open data of Ukraine economy trends for the period from 2007 till 2019. Traditionally econometric methods are used to find out long run relationships between basic economy indicators (agriculture and industry outputs, average salary, stock index growth etc.) and both monetary information and regulation instruments. Authors develop the regressive models of influence of Central Bank regulation instruments of monetary and economic stability. The paper presents conclusions regarding trends and problems in the implementation of Ukraine's monetary policy, it's influences on the currency stability and economic growth trends. Implementation of the proposed measures will increase monetary policy effectiveness and define the directions of the further research in forecasting inflationary and course-forming factors of the development of the national economy and financial system of Ukraine. The key focus of further research is to define an adequate indicator that determines the real level of inflation, which must evaluate a whole range of factors reducing the real value of money.

The correlation between macroeconomic dynamics and the inflation rate is the subject of many economic studies. The principles of monetary policy are developed in classical economics studies, which are based on the theories of Keynes, Phillips, Campbell, etc. However, classic approaches require practical validation, especially with regard to modern economic trends in times of crisis and emerging economies. Therefore, the purpose of the paper is to investigate and summarize the impact of inflation targeting and other key monetary policy instruments on fundamental economic indicators in Ukraine during periods of stability and crises. An empirical analysis is based on official statistics from Ukraine for 2011–2019. This study uses econometric methods (multivariate regression and simultaneous equation model), which are applied for the general and transmission impact of inflation on the estimation of economic growth. The results prove that inflation does not affect (less than 0.46 linear correlation) fundamental economic indicators during periods of real GDP growth and a quarterly CPI level of less than 2%. On the other hand, there are significant simultaneous regressions (more than 0.8 coefficients of determination) between unemployed, spending on real final consumption, hryvnia exchange rate and monetary policy instruments (discount rate, international reserves, amount of government bonds, M3 monetary aggregate) for periods when the quarterly CPI (consumer price index) is more than 2%. Therefore, the traditional monetary policy implications are discussed for emerging economies.

The paper investigates discretionary budget expenditure and determines its role in the system of regulation of country’s socio-economic development. In a very difficult political and socio-economic situation, Ukraine faces an urgent need to finda balance between the amount of functions performed by the state and the level of their financial support. The analysis of the State Budget of Ukraine expenditure according to the functional classification in 2014–2017 has been carried out. In particular, the discretionary budget expenditures (on state functions, economic activity, defense budget expenditures, budget expenditure on public order, security and judiciary; environmental protection, housing and utilities) are carefully analyzed. The purpose of the article is to study trends in financing discretionary budget expenditure and determine their impact on the socio-economic development of a country. Discretionary budget expenditures are the study object. It is determined that socio-economic development of a country requires government to apply progressive forms, methods and principles of expenditure management between the budget system levels. This need is due to the objective necessity to achieve sustainable development of economy and population welfare. The main problems that reduce budget discretionary expenditure effectiveness in the current conditions are investigated and the main directions to improve their financing are offered. The obtained results indicate the need to revise the funding of discretionary budget expenditures depending on the state policy priorities.

Abstract. The first cryptocurrency was born in 2008. Already today, virtual financial assets and tokens are a significant part of trading in global financial markets. The cryptocurrency market capitalization currently exceeds 600 billion U.S. dollars. However, there is a lot of discussion about cryptocurrency functions and the correlation between Bitcoin prices and the basic economic indices. Therefore, the purpose of the paper is to define the statistical substantiation of the influence of fundamental economic indicators on the market of virtual financial assets and the possibility of using cryptocurrency as the investment assets. This article is based on the theoretical principles and methods of econometric analysis; the system approach methods to define the main vehicles and trends of the international financial market. The study presents correlation analysis, regression models with paired and multiple variables. For these models, R-Studio instruments are the main tools of quality estimation and results interpretation. The article shows the results of the correlation analysis of Bitcoin’s U.S. dollar price dynamics and changes in the main stock, monetary market indicators, cryptocurrencies market tendency, levels of the United States fundamental economic indicators for the period from 2014 to 2021. Traditional multifactorial regression models are used to determine the level and the impact of individual indicators of the world stock market at the U.S. dollar price of Bitcoin. A comparison of the level of volatility of key investment financial assets in the market of cryptocurrencies and stock markets is carried out. The authors determine the level of correlation dependence and make a regression model of the impact of fundamental economic indicators and stock market trends on the dynamics of U.S. dollar prices for key cryptocurrencies. The article presents conclusions on trends and problems of using cryptocurrencies as an investment asset, considering volatility and profitability. Implementation of the results allows to clarify the economic essence of cryptocurrencies as a specific financial vehicle, as well as improving the existing models of investment management, considering the statistical characteristics of the virtual financial assets. The main direction of further research is to build models of medium-term prediction of prices for the main cryptocurrencies as an investment asset in conditions of changes in global financial markets, which must consider the fundamental economic indicators of the world economy and trends on key stock and commodity markets. Keywords: virtual financial asset, cryptocurrency, bitcoin, econometric model, financial market, economic indicator, investment asset. JEL Classification D53, E44, G15, C58 Formulas: 3; fig.: 3; tabl.: 3; bibl.: 31.