Open AccessApplication of SARIMA model to forecasting the natural rubber price in the world market
Author(s) -
Nhien T. Pham
Publication year - 2018
Publication title -
the journal of agriculture and development/the journal of agriculture and develoment/nông nghiệp và phát triển
Language(s) - English
Resource type - Journals
eISSN - 2615-949X
pISSN - 2615-9503
DOI - 10.52997/jad.1.03.2018
Subject(s) - akaike information criterion , autoregressive integrated moving average , natural rubber , mean absolute percentage error , econometrics , statistics , economics , mean squared error , commodity , value (mathematics) , market price , agricultural economics , mathematics , time series , finance , chemistry , organic chemistry
This study was conducted to develop a forecasting model to predict the price natural rubber in the world market by using the Seasonal Autoregressive Integrated Moving Average (SARIMA). The dataset for model development was collected from series data of average monthly closing average prices in the natural rubber - Ribbed Smoked Sheet No.3 (RSS3) on the Tokyo Commodity Exchange (TOCOM) for the period of January 2007 - September 2018. The RSS3 price on the TOCOM provided the reference price for natural rubber in the world market. It resulted SARIMA(2,1,2)(1,1,1)12 model was selected as the best-fit model. The model achieved 0.000 for Probability value (P-value). 8.86 for Akaike Information Criterion (AIC) and 9.01 for Schwarz Information Criterion (SIC); 6.68% for Mean Absolute Percentage Error (MAPE) and 21.43 for Root Mean Square Error (RMSE). This model was used to forecast the world's natural rubber price during October 2018 - December 2020. This study may be helpful to the farmers, traders, and the governments of the world's important natural rubber producing countries to plan policies to reduce natural rubber production costs and stabilize the natural rubber price in the future, such as by setting suitable areas for natural rubber plantation in each country and defining appropriate and sustainable alternative crop areas in each country.