Machine learning in energy economics and finance: A review
Abstract Machine learning (ML) is generating new opportunities for innovative research in
energy economics and finance. We critically review the burgeoning literature dedicated to …
energy economics and finance. We critically review the burgeoning literature dedicated to …
Forecasting crude oil prices based on variational mode decomposition and random sparse Bayesian learning
Accurately forecasting crude oil prices has drawn much attention from researchers,
investors, producers, and consumers. However, the complexity of crude oil prices makes it a …
investors, producers, and consumers. However, the complexity of crude oil prices makes it a …
A deep learning ensemble approach for crude oil price forecasting
Y Zhao, J Li, L Yu - Energy Economics, 2017 - Elsevier
As crude oil price is influenced by numerous factors, capturing its behavior precisely is quite
challenging, and thus leads to the difficulty of forecasting. In this study, a deep learning …
challenging, and thus leads to the difficulty of forecasting. In this study, a deep learning …
Multi-step-ahead crude oil price forecasting based on two-layer decomposition technique and extreme learning machine optimized by the particle swarm optimization …
T Zhang, Z Tang, J Wu, X Du, K Chen - Energy, 2021 - Elsevier
The prediction of crude oil prices has important research significance. The paper contributes
to the literature of hybrid models for forecasting crude oil prices. We apply ensemble …
to the literature of hybrid models for forecasting crude oil prices. We apply ensemble …
Oil price forecasting using a hybrid model
A Safari, M Davallou - Energy, 2018 - Elsevier
Forecasting oil prices is an important and challenging matter, because of its impact on many
economic and non-economic factors. Because factors such as economic growth, political …
economic and non-economic factors. Because factors such as economic growth, political …
A novel hybrid model for forecasting crude oil price based on time series decomposition
H Abdollahi - Applied energy, 2020 - Elsevier
Oil price forecasting has received a prodigious attention by scholars and policymakers due
to its significant effect on various economic sectors and markets. Incentivized by this issue …
to its significant effect on various economic sectors and markets. Incentivized by this issue …
Deep learning framework for predictive modeling of crude oil price for sustainable management in oil markets
AA Salamai - Expert Systems with Applications, 2023 - Elsevier
Crude oil price predictability has continually been considered as a fundamental argument of
finance literature, given its critical propositions for risk management, investment decisions …
finance literature, given its critical propositions for risk management, investment decisions …
A new hybrid model for forecasting Brent crude oil price
H Abdollahi, SB Ebrahimi - Energy, 2020 - Elsevier
Received a plethora of attention by both practitioners and researchers, oil price forecasting
remains a challenging issue due to the particular characteristics of oil price and its …
remains a challenging issue due to the particular characteristics of oil price and its …
Artificial intelligence methods for oil price forecasting: a review and evaluation
Artificial intelligent methods are being extensively used for oil price forecasting as an
alternate approach to conventional techniques. There has been a whole spectrum of …
alternate approach to conventional techniques. There has been a whole spectrum of …
A novel hybrid method of forecasting crude oil prices using complex network science and artificial intelligence algorithms
Forecasting the price of crude oil is a challenging task. To improve this forecasting, this
paper proposes a novel hybrid method that uses an integrated data fluctuation network …
paper proposes a novel hybrid method that uses an integrated data fluctuation network …