References

• 2018A Comparison of ARIMA and LSTM in Forecasting Time Series1,382 cited
• 2018Forecasting the volatility of stock price index: A hybrid model integrating LSTM with multiple GARCH-type models786 cited
• 2020On relationships between the Pearson and the distance correlation coefficients348 cited
• 2013An improved wavelet–ARIMA approach for forecasting metal prices175 cited
• 2020A hybrid deep learning approach by integrating LSTM-ANN networks with GARCH model for copper price volatility prediction156 cited
• 2022RETRACTED: Financial Risk, Renewable Energy Technology Budgets, and Environmental Sustainability: Is Going Green Possible?87 cited
• 2018An adaptive forecasting approach for copper price volatility through hybrid and non-hybrid models75 cited
• 2019Predictive analytics of the copper spot price by utilizing complex network and artificial neural network techniques70 cited
• 2020Bankruptcy or Success? The Effective Prediction of a Company’s Financial Development Using LSTM62 cited
• 2021Development of copper price from July 1959 and predicted development till the end of year 202240 cited
• 2018The Composite Coincident Indicator (CCI) for Business Cycles37 cited
• 2018On resource depletion and productivity: The case of the Chilean copper industry31 cited

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