Abstract

For decision making, sugar basic identification can be used as a strategic tool. In this study, accessible forecast using ARMA (p,q) time series models comparing Indonesian sugar spot and ICE future markets. The study identified that in two cities of Indonesia, there exist synchronous high and low primary movement, and volatility with correlation coefficient of 0.70, showing positive higher magnitude, and descriptive statistics. The result shows that in the selected two cities, Jakarta showed higher compare to the other city. Comparing forecasting errors between ARMA (p,q) and SARMAX (p,q) models, the monthly sugar basis model for Bande Aache is SARMAX (1,0). For Jakarta, the forecasted model is ARMA (2,0). Additionally, the Bande Aache sugar basis breakpoint month is 2008M09 and for Bande Aache, breakpoint month is 2011M11. A closer analysis suggests that the breaking points coinciding with the identifiable sugar basis level and the volatility trends in the examined period. Both forecasted models are easier and implementable and can provide informational input for efficient allocative decisions by the Indonesian sugar supply chain.

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