Forecasting the lithium mineral resources prices in China: Evidence with Facebook Prophet (Fb-P) and Artificial Neural Networks (ANN) methods

Author:

Li Xiaobin,Sengupta Tuhin,Si Mohammed KamelORCID,Jamaani Fouad

Publisher

Elsevier BV

Subject

Law,Management, Monitoring, Policy and Law,Economics and Econometrics,Sociology and Political Science

Reference52 articles.

1. Deep learning framework for predictive modeling of crude oil price for sustainable management in oil markets;Ali Salamai;Expert Syst. Appl.,2023

2. Production Cuts Will Rebalance the Lithium Market;Analytica,2020

3. Cross-correlations between economic policy uncertainty and precious and industrial metals: a multifractal cross-correlation analysis;Aslam;Res. Pol.,2022

4. Comparison of prediction performances of artificial neural network (ANN) and vector autoregressive (VAR) Models by using the macroeconomic variables of gold prices, Borsa Istanbul (BIST) 100 index and US Dollar-Turkish Lira (USD/TRY) exchange rates;Aydin;Procedia Econ. Finance,2015

5. The future of lithium-ion batteries: exploring expert conceptions, market trends, and price scenarios;Bajolle;Energy Res. Social Sci.,2022

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