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.

Effectiveness of Single and Double Exponential Smoothing: SES, ARRSES and Holt’s Linear for Time Series Data Prediction with Trend and Non-seasonal Characteristic (Covid-19 Vaccinate Case)

“…Pamungkas dkk [8] meneliti mengenai komparasi metode exponential smoothing dalam bidang perikanan dan kelautan, yang mana hasil dari penelitiannya metode terbaik adalah exponential smoothing jenis Holt's yang memperoleh nilai peramalan dengan kesalahan 37,878%. Penelitian Kahraman dan Akay [5] membandingkan metode exponential smoothing untuk kasus data harga logam diperoleh hasil bahwa model terbaik untuk memprediksi untuk alumunium, tembaga, timah dan besi adalah damped trend, model Holt's untuk harga logam nikel dan seng, dan model Brown untuk harga logam timah.…”

Determination of iron procurement strategy for manufacturing companies

“…iron price fluctuations (Lv et al, 2022;Kolková, & Ključnikov, 2021;Kolkova & Rozehnal, 2022). A time series includes statistical data on various quantitative indicators of economic and social phenomena in a time sequence, and methods based on time series analysis comprise various estimation techniques (Landmesser, 2021;Fiszeder & Małecka, 2022), where the most important technique is the exponential smoothing estimation method (Kahraman & Akay, 2022). Ten years time series analysis was used by Jeremić et al (2022) in their research on agricultural development in Serbia, examining the relationship between crude oil and gold and the price of iron, concluding that changes in the price of steel cause a gradual increase in the price of agricultural machinery, which significantly increases the cost of agricultural production.…”