Forecasting Energy Prices Using Data Mining Methods

Energy prices have been playing an increasingly significant role in the world economy since all elements involved in this area are considered as a major input for the production. The energy prices as it affect economic variables in the world, is influenced by economic activities of great countries. Indicatively, oil prices which are a major energy index globally are affected by economic activities of great countries, and when such activities are on the decrease, the economy of the industrial countries slips into recession. The energy market is a complex market which does not follow the random walk process. There are many reasons behind the complexity of the energy market such as political situation, etc. Therefore prediction of this type of market is a difficult task. This study aims to investigate, model and forecast the whole US energy market as an important energy market in the world using different machine learning methods. Besides that, the effect of the US inflation on the volatility of the energy market has as well examined. Keywords: Forecasting, Neural Networks, US Energy Market, LPPL Models, Data mining methods