Crude oil plays a very important role in the development of the world getting faster and faster. Since it is not renewable, people significantly care about this precious and limited resource that occurs everywhere in their daily lives. In recent years, the fluctuation of crude oil prices varied frequently. Therefore, what the oil price will change in the future becomes a very big problem that people care about. Among plenty of models, this paper will use the Bayesian structural time series (BSTS) model to forecast the future trend of crude oil prices within the next 12 months and the possible factors that could cause this trend. Based on the analysis by employing the BSTS model, the forecasting result of the future oil price shows that the crude oil price might increase at a relatively slow rate. Based on this trend, all the factors that could cause the oil price to rise are possible to happen, meaning that considering these factors when making decisions such as investment is important.
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Yuxi Wang (2024) studied this question.
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