Authors: Liwei Fan; Huiping Li
Addresses: School of Business, Hohai University, Nanjing 211100, China ' College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Abstract: Accurate forecasting of crude oil prices plays a significant role for supporting policy and decision making at economy and firm levels. The successive developments in econometric and artificial intelligence models provide opportunities to analyse crude oil market in depth and improve the accuracy of oil price forecasting. Past years have seen an increasing number of studies on the volatility analysis and forecasting of crude oil prices by different techniques such as econometric and artificial intelligence models. This paper aims to present a systematic review of existing tools used to model the volatility of crude oil prices. It is found that the integration of time series models with artificial intelligence models has received increasing attention in oil price forecasting owing to its satisfactory prediction performance. Also, feature extraction of oil price series with appropriate multivariate statistical analysis techniques plays an important role in improving the prediction performance.
Keywords: crude oil prices; volatility analysis; price forecasting; energy markets; time series models; artificial intelligence; feature extraction; multivariate statistics; modelling.
International Journal of Global Energy Issues, 2015 Vol.38 No.1/2/3, pp.5 - 17
Available online: 18 May 2015 *Full-text access for editors Access for subscribers Purchase this article Comment on this article