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首页> 外文期刊>Procedia Computer Science >The Performance of ARIMAX Model and Vector Autoregressive (VAR) Model in Forecasting Strategic Commodity Price in Indonesia
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The Performance of ARIMAX Model and Vector Autoregressive (VAR) Model in Forecasting Strategic Commodity Price in Indonesia

机译:ARIMAX模型与载体自回归(VAR)模型在预测印度尼西亚战略商品价格中的表现

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Rice as one of the strategic commodities has an important role in the life of Indonesian society. This is cause of rice is the main food of the Indonesian nation. Therefore, the stabilization of food prices is one of the priorities of the Indonesian government’s policy. It can minimize the impact of the global financial crisis such as inflation and purchasing power of the poor. The sta bility price can be maintained by price forecasting for several periods ahead. It can be used to set up the anticipatory action. In this research, ARIMAX model and VAR model used to forecast the rice price. This model involves several variables including consumer rice price (HKB), production (PROD), dry milled rice (GKP), harvested area (LP), and rice price in Thailand (HD). The results show that ARIMAX model can predict the rice consumer price with MAPE 0.15%. This is 15.27 % better than VAR model. The GKP variable did not significantly affect to the rice price. This is indicated by the MAPE difference between model with GKP and model without GKP is less than 0.01%.
机译:米饭作为战略商品之一在印度尼西亚社会的生活中具有重要作用。这是米饭的原因是印度尼西亚国家的主要食物。因此,食品价格的稳定是印度尼西亚政府政策的优先事项之一。它可以最大限度地减少全球金融危机的影响,例如穷人的通货膨胀和购买力。 STA Bility价格可以通过价格预测的价格预测来维护。它可用于建立预期的行动。在本研究中,ARIMAX模型和VAR模型用于预测米价格。该模型涉及多个变量,包括消费米价格(HKB),生产(产品),干磨米(GKP),收获区(LP)和泰国的米价格(HD)。结果表明,ARIMAX模型可以预测米饭消费品,MAPE 0.15%。这比VAR模型好15.27%。 GKP变量对米价格没有显着影响。这由模型与GKP和没有GKP的模型之间的MAPE差异表示的表示指示小于0.01%。

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