Forecasting the Malaysian crude palm oil price during COVID-19 pandemic - Megat Muainuddin, Megat Muhammad Afif; Abu, Noratikah (GBMR Journal, 2021)
Purpose: Commodities forecasting can lead to an important element in commodities industry to ensure that each investment by individuals, companies and government was worth it. This study applied exponential smoothing models for analysis and forecasting the crude palm oil (CPO) price in Malaysia during COVID-19 pandemic. Design/methodology/approach: The data used in this study is daily data of CPO price from March 2020 until May 2021. Findings: Results obtained by applying exponential smoothing models and numerical calculation shows that it is effective for forecasting the number of CPO price. The best models are single exponential smoothing model were chosen by selecting the lowest value of forecast errors using mean absolute percentage error (MAPE), mean absolute deviation (MAD) and mean square deviation (MSD) as forecast evaluation. As a conclusion, single exponential model gives significant result to be the best model to forecast compared to exponential smoothing models. Research limitations/implications: The analysis on the comparison between others commodity could be an analysis for future study. Practical implications: This study contribute to the literature on the impact of COVID-19 towards palm oil industries in Malaysia. Originality/value: This study will provide an understanding on forecasting crude palm oil price in Malaysia and this study is among the pioneerstudy in Malaysia that focus on the impact of COVID-19 towards crude palm oil price. Paper type: Research paper