Forecasting Malaysia Bulk Latex Prices Using Autoregressive Integrated Moving Average (ARIMA) and Exponential Smoothing


  • Mong Cheong Fu Universiti Teknologi Malaysia
  • Shariffah Suhaila Syed Jamaludin Universiti Teknologi Malaysia



natural rubber, time series, forecasting, ARIMA, Exponential Smoothing.


Natural rubber is an important component of many developed countries' socioeconomic structures because it is frequently used to manufacture essential consumer goods such as tires and latex gloves. The natural rubber industry is heavily affected by the volatility and unpredictability of the natural bulk latex markets. Forecasting natural rubber prices is critical for rubber industry in procurement decisions and marketing strategies. This study aims to model monthly bulk latex prices in Malaysia using Autoregressive Integrated Moving Averages (ARIMA) and Exponential Smoothing. The models performance are measured using the Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE). The Malaysian Rubber Board has 132 historical prices for the latex in Malaysia from January 2010 to December 2020. They are used for training and testing in determining the forecasting accuracy. Overall finding show that ARIMA (1,1,0) provides the most accurate prediction. With a MAPE of 8.59 percent and an RMSE of 69.78 sen per kilogram, this model is considered the best and highly accurate.


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