Trends, Cycles and Seasonal Variations of Ukrainian Gross Domestic Product

The article attempts to study trends, seasonal variations and cyclical fluctuations of Ukraine's quarterly GDP at current prices. The period of the study is from the first quarter of 2010 to the first quarter of 2020. The methodological support of the study includes an approach based on the Hamilton regression filter, the Hodrick-Prescott filter and the asymmetric filter model of Cristiano and Fitzgerald. Based on the use of a Hamilton regression filter, which clearly gives one complete cycle with a peak and a depression, the study substantiates that the seasonally adjusted series of GDP has a slight difference with the remainder, but its seasonal fluctuations are homogeneous and have the shape of the letter V, which allowed us to draw the following conclusions: seasonal fluctuations in GDP are confirmed by the ACF and PACF models during the study period; the filter is very different from the Hamilton filter in terms of trend and cycle, but has common features in the context of asymmetry in time with the random walk filter of Cristiano and Fitzgerald. The paper substantiates the conclusions about stable and stationary series of GDP by volatility (leading to a decrease) of cyclical fluctuations based on the used forecast model ARIMA (4,0,4) for 2020-2030, which passed through the Hamilton regression filter. Based on the results of the study, the author provides recommendations on the need to introduce a new monetary and fiscal policy, including reform measures, which should be balanced with current trends in the functioning and development of international financial institutions and organizations. Such changes will be a motivating lever for the growth of the share of agriculture and related activities, production, transport, real estate, capital formation and other macroeconomic indicators of Ukraine's economy, respectively, during the period of GDP decline.