This study aims to use a monthly dataset from 1991 to 2021 to predict West Texas
Intermediate (WTI) oil price dynamics using US macroeconomic and financial factors, as well …

The volatility of the crude oil market and its effects on the global economy increased the
concerns of individual investors, states/governments, and corporations. Forecasting the …

The paper proposes a machine-learning approach to predict oil price. Market participants
can forecast prices using such factors as: US key rate, US dollar index, S and P500 index …

This study aims to predict oil prices during the 2019 novel coronavirus (COVID-19)
pandemic by looking into green energy resources, global environmental indexes (ESG), and …

Crude oil is an indispensable energy resource. With the establishment of the local crude oil
futures market in China, providing accurate forecasts for crude oil futures price is urgent. To …

Crude oil is one of the most important types of energy for the global economy, and hence it is
very attractive to understand the movement of crude oil prices. However, the sequences of …

There has been a renewed interest in accurately forecasting the price of crude oil and its
fluctuations. That said, this paper aims to study whether the price of crude oil in the United …

Crude oil price series are nonlinear and highly volatile, making it difficult to obtain
satisfactory performance for traditional statistical-based forecasting methods. To improve …

As the price of crude oil has nonlinearity, instability, and randomness, capturing its behavior
precisely is significantly challenging and leads to difficulties in forecasting. This study …

In light of the central role of crude oil in the economy and the complex mechanisms involved
in forecasting crude oil prices, this study proposes a two-stage model that optimally selects …