ANALISIS VOLATILITY FORECASTING SEMBILAN BAHAN POKOK MENGGUNAKAN METODE GARCH DENGAN PROGRAM R

  • Enggar Niken Larasati Universitas Negeri Semarang
  • Putriaji Hendikawati Universitas Negeri Semarang
  • Zaenuri Zaenuri Universitas Negeri Semarang
Keywords: ARIMA; GARCH; Heteroskedatik; Volatilitas

Abstract

commodities, namely oil, sugar, eggs, flour, rice, chili, milk, onions, and chicken with GARCH models using the program R 2.11.1.The first step is, to test the data stationary nine basic commodities price increases, stationary data already analyzed using ARIMA method. From the analysis using ARIMA, were estimated several models. To determine the best ARIMA model, conducted a comparison of some of the models that have been in the estimation of the model are then selected by a significant parameter value, the value of ^ 2 is the smallest, smallest AIC value and the largest value of log likelihood. The residual value of the best ARIMA model that will be used to determine the GARCH model to the data of nine price increases of basic commodities. Having obtained the best GARCH model, it will be forecasting the smallest value of standard error and approach the original data.Forecasting results on nine basic price increase in 2015 with the best ie GARCH GARCH (1,1) for the rise in oil prices, chili, onions, chicken and wheat flour, GARCH (2,1) for the price of sugar, milk, rice and eggs. Garch best models have a standard error values are smaller and tend to be closer to the original data. By using the GARCH method, it will be forecasting the rise in prices of daily necessities in 2015.

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Published
2017-02-27
Section
Articles