Abstract
This article is the first to study, simulate and forecast the monthly dynamics of the trade balance between Ukraine and the European Union for the period from 2005 to 2019. In the presented work, three types of models were used for modeling and forecasting: Automated Neural Networks, additive models ARIMA *ARIMAS (Autoregressive integrated moving average with season component) and Holts model with a damped trend. When modeling using the Automated Neural Networks module, various ensembles of networks and neuron activation functions in hidden layers were used. It turned out that Automated Neural Networks have poor prognostic ability (as in the case considered by us, when modeling insufficiently long series of dynamics). Therefore, when modeling and forecasting the dynamics of the Ukraine-EU trade balance, classical (so-called Box-Jenkins) time series models were used. In this case, the time series is divided into several components (in our case, terms): the main trend is the trend, the seasonal component and the random component (the so-called white noise). By smoothing the initial series, a trend was found, and an analysis of the autocorrelation functions revealed a one-year seasonality. Eliminating the trend and the seasonal component, we obtained a random component, which has a Gaussian distribution. This made it possible to apply first the ARIMA* ARIMAS additive model, and then the Holt model of exponential smoothing with a damped trend. Adequate models of Ukraine-EU trade balance dynamics have been obtained, according to which the forecast has been made. A comparative analysis of the models used. The best model was chosen for forecasting, which allowed to get a good forecast (in comparison with actual data).
Highlights
IntroductionInternational trade has begun to attract the close attention of many scientists
In recent years, international trade has begun to attract the close attention of many scientists
In the work [6], BoxJenkins models were compared with Automated Neural Networks when modeling the dynamics of Czech GDP
Summary
International trade has begun to attract the close attention of many scientists. We note publication [1], which explores the dynamics of the trade balance between the EU and China. Economists around the world have always paid close attention to the study, modeling and forecasting of the dynamics of economic processes. A rapid development of modeling and forecasting using time series models began after the release of the classic Box-Jenkins book [3]. Note that these methods have not lost relevance at present. The relevance of this study is indisputable, since the EU has become the largest trading partner of Ukraine in recent years
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