Forecasting crude palm oil price using Univariate and Box-Jenkins techniques / Nurul 'Adila Arrifin, Wan Syaniza Zainal Abidin and Mohamad Naqib Zulkarnain

• Main Authors: Arrifin, Nurul 'Adila, Zainal Abidin, Wan Syaniza, Zulkarnain, Mohamad Naqib
• Format: Student Project
• Language: English
• Published: 2019
• Subjects: Mathematical statistics. Probabilities; Multivariate analysis. Cluster analysis. Longitudinal method; Analytical methods used in the solution of physical problems
• Online Access: http://ir.uitm.edu.my/id/eprint/39355/1/39355.pdf; http://ir.uitm.edu.my/id/eprint/39355/

In Malaysia, crude palm oil price forecasts represented fundamental and valuable infonnation to traders who are involved directly or indirectly in the fat and oil markets. It has been widely accepted that the price of oil is one of the reasons of the world economy. Therefore, reliable crude oil forecasts are important for assessing economic fluctuations and improving economic policy. In this research has used BoxJenkins and Univariate Modelling Technique to analyse the problem of there are lack of researchers that make studies on the accuracy between the Univariate and BoxJenkins Techniques in forecasting the future CPO price of Malaysia with the minimum error. Besides that, there are not much of studies using SARIMA method. The objective of this study is to compare the model between Single Exponential Smoothing, Double Exponential Smoothing and SARIMA model by measure the model using Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Geometric Root Mean Squared Error (GRMSE), and also to forecast the future crude palm oil price using the best model. The best method in this study we can assume that Single Exponential Smoothing is the suitable method for the forecasting the CPO prices.