Artificial Neural Networks Based Oil Price Forecasting: A Decade Review of the Literature
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2016, Vol 4, Issue 9
Abstract
Crude oil plays an important role in the development of financial markets and the global economy. Oil price forecasts are of immediate interest and importance to central banks, various industries and international organisations. Hence proactive knowledge of its future price can lead to better decision making at various levels. A number of efforts have been made by researchers towards developing efficient methods for forecasting oil prices. The non linear, volatile and chaotic nature of international oil prices coupled with a large number of factors that affect the oil prices makes prediction of oil prices a challenging and difficult task. In the recent past Artificial Neural Networks have gained popularity as an effective tool for forecasting purposes. Artificial Neural Networks have been successfully employed to forecast oil prices by various researchers across the world. Various models have been developed for this purpose. This paper presents a comprehensive review of use of artificial neural networks for forecasting oil prices from 2005 to 2016. It reviews the various factors considered by the various researchers in these eleven years for developing various ANN models for forecasting prices of oil.
Authors and Affiliations
Mandeep Kaur, Parminder Kaur
Keywords
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