Comparison of exponential smoothing methods in forecasting global prices of main metals

Abstract

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 and production policies of countries. The paper presents the application of various exponential smoothing methods to metal spot price forecasting. Aluminum, copper, lead, iron, nickel, tin, and zinc prices were analyzed by using yearly data from 1990 to 2021. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) values of the models were obtained and their performances were compared to determine the appropriate model for each metal price. These metal prices were forecasted up to 2030 by using the best-fitted models.