Analysis of the time series of Brent oil prices

fluctuations in oil prices are one of the most important factors determining sustainable economic development. Such macroeconomic indicators as economic growth, trade balance, and consumer demand depend on this variable. Forecasting oil prices is a complex task, the solution to which can be implemented using various econometric approaches. One effective approach to solving the oil price forecasting problem is time series analysis. The purpose is to carry out the forecast of prices for a barrel of Brent oil for the period 2014-2025 for the period 2026-2029. Materials and methods: the construction of regression models and the graphical representation of modeling results are implemented in the Statistica software package (v.10), designed for data analysis and statistical processing of open resource data. Results and discussions: a seasonal decomposition of the time series of prices was carried out, it was established that the main component of this series is the trend-cyclical one, while the seasonal factor can be neglected. It is shown that the forecast data obtained using the exponential smoothing model have statistical significance and greater reliability than those obtained within the framework of the moving average autoregression model. Conclusion: it is shown that during the forecasted period of time, the price of a barrel of Brent oil will fluctuate around the average value of $73.

oil, price, forecast, exponential smoothing, ARIMA