Prediction prices of Basrah light oil using artificial neural networks

Abstract

The global economy is assured to be very sensitive to the volatility of the oil market. The beneficial of oil price collapse are both consumers and developed countries. Iraq's economy is a one-sided economy that completely depends on oil revenue to charge economic activity. Hence, the current decline in oil prices will produce serious concerns. Some factors stopped most investment projects, rationalize the recurrent outflow, and decreasethe development of the economic activity. The predicate oil prices are considered among the most complex studies because of the different dynamic variables that affect the strategic goods. The subject of forecasting has been extremely developing during recent years and some modern methods have been appeared in this regard, for example, Artificial Neural Networks. In this study, an artificial neural network (RFFNN) is adopted to extractthe complex relationships among divergent parameters that have the abilities to predict oil prices serving as an inputs to the network data collected in this research represent monthly time series data are Oil prices series in (US dollars) over a period of 11 years (2008-2018) in Iraq.