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Modeling and Forecasting Crude Oil Price with an Autoregressive Integrated Moving Average (ARIMA) Model
Journal: Iranian Journal of Business and Economics
Issue: Iranian Journal of Business and Economics (Volume: 5, Issue: 4)
Author: Ramezan Rezaeyan , Milad Taghizadeh
Keywords : time series , ARIMA , modeling , Monthly forecast of crude oil prices
Abstract:

Oil is very important as the largest energy consumer in the world due to its role in the economies of producing countries. Therefore, it is necessary to determine different parameters affecting the oil market for these countries. In this context, this paper forecasts the global market for oil prices as an important variable using ARIMA approach. It should be noted that this forecast is more dynamic. In this study, using ARIMA model, time series and a 7-year period from January 2009 to December in 2015, price of a single shipment of Iranian light crude oil was used.

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