Copper Monthly Price Forecast with Time Series Models

Abstract

The research design was quantitative with a predictive scope, real information on monthly copper prices since September 2020 was used to August 2022. The models used as time series forecasting methods were moving average forecasting, weighted moving average, simple exponential smoothing, Holt exponential smoothing, and Winters exponential smoothing. The adjustment of the methods to the original model used the coefficient of determination (R2) and the mean absolute percentage error (MAPE) as a measure of precision. The result indicated that the best method is simple exponential smoothing, where the forecast copper price for September 2022 was $3.60/lb, the mean absolute percentage error (MAPE) was 4.4% and the coefficient of determination (R2) was 0.86. Finally, it is concluded that with the time series forecasting methods it is possible to forecast the price of copper.