Accurate Estimated Model of Volatility Crude Oil Price

Toto Gunarto, Rialdi Azhar, Novita Tresiana, Supriyanto Supriyanto, Ayi Ahadiat


Crude oil price (COP) data are time-series data that are assessed as having both volatility and heteroscedasticity variance. One of the best models that can be applied to address the heteroscedasticity problem is GARCH (generalized autoregressive conditional heteroscedasticity) model. The purpose of this study is to construct the best-fitted model to forecast daily COP as well as to discuss the prepared recommendation for reducing the impact of daily COP movement. Daily COP data are observed for the last decade, i.e., from 2009 to 2018. The finding with the error of less than 0.0001 is AR (1) – GARCH (1,1). The implementation of the model is applicable for both predicting the next 90 days for the COP and its anticipated impact in the future. Because of the increasing prediction, it is recommended that policymakers convert energy use to renewable energy to reduce the cost of oil use.

Keywords: Crude Oil Price, Heteroscedasticity, Subsidy, GARCH Model

JEL Classifications: C5, C53, O4, O42, Q4, Q42


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