Forecasting rare earth stock prices with machine learning
I Henriques, P Sadorsky - Resources Policy, 2023 - Elsevier
Rare earth elements (REEs) are indispensable for producing green technologies and
electronics. Demand for REEs in clean energy technologies in 2040 are projected to be …
electronics. Demand for REEs in clean energy technologies in 2040 are projected to be …
A novel non-ferrous metal price hybrid forecasting model based on data preprocessing and error correction
Z He, J Huang - Resources Policy, 2023 - Elsevier
Accurately forecasting the price of non-ferrous metals is of great significance for traders to
avoid risks, enterprises to arrange production plans, and countries to formulate economic …
avoid risks, enterprises to arrange production plans, and countries to formulate economic …
Forecasting on metal resource spot settlement price: New evidence from the machine learning model
T Shi, C Li, W Zhang, Y Zhang - Resources Policy, 2023 - Elsevier
Accurate prediction of the price of metal mineral resources is of great practical significance
for guiding the production of non-renewable resource enterprises and maintaining the …
for guiding the production of non-renewable resource enterprises and maintaining the …
Copper price prediction using support vector regression technique
Predicting copper price is essential for making decisions that can affect companies and
governments dependent on the copper mining industry. Copper prices follow a time series …
governments dependent on the copper mining industry. Copper prices follow a time series …
A random walk through the trees: Forecasting copper prices using decision learning methods
We investigate the accuracy of copper price forecasts produced by three decision learning
methods. Prior evidence (Liu et al. Resources Policy, 2017) shows that a regression tree, a …
methods. Prior evidence (Liu et al. Resources Policy, 2017) shows that a regression tree, a …
“Watch your tone!”: Forecasting mining industry commodity prices with financial report tone
This paper presents robust evidence indicating that the tone of financial reports from the US
mining industry firms can predict certain mining commodity returns. We assess this …
mining industry firms can predict certain mining commodity returns. We assess this …
Comparison of exponential smoothing methods in forecasting global prices of main metals
E Kahraman, O Akay - Mineral Economics, 2023 - Springer
Metals are indispensable raw materials for industry and have strategic importance in
economic development. The price forecasting of metals is crucial for the production sector …
economic development. The price forecasting of metals is crucial for the production sector …
Forecasting commodity prices: Looking for a benchmark
M Kwas, M Rubaszek - Forecasting, 2021 - mdpi.com
The random walk, no-change forecast is a customary benchmark in the literature on
forecasting commodity prices. We challenge this custom by examining whether alternative …
forecasting commodity prices. We challenge this custom by examining whether alternative …
Common factors and the dynamics of industrial metal prices. A forecasting perspective
This study aims to analyze the suitability of factor models in describing the dynamics of real
prices for four main non-ferrous industrial metals: aluminium, copper, nickel and zinc. For …
prices for four main non-ferrous industrial metals: aluminium, copper, nickel and zinc. For …
Generating affordable protection of high seas biodiversity through cross-sectoral spatial planning
L Fourchault, F Dahdouh-Guebas, DC Dunn… - One Earth, 2024 - cell.com
Over the past 20 years, industrial activities have accelerated in the open ocean. Fishing,
shipping, and deep-sea mining are major drivers of this" blue acceleration," with each …
shipping, and deep-sea mining are major drivers of this" blue acceleration," with each …