Applications of Neural Networks in modeling and forecasting volatility of crude oil markets:Evidences from US and China

摘要：

　　Previous researches on oil price volatility have been done with parametric models of GARCH types.In this work,we model volatility of crude oil price based on GARCH(p,q) by using Neural Network which is one of powerful classes of nonparametric models.The empirical analysis based on crude oil prices in US and China show that the proposed models significantly generate improved forecasting accuracy than the parametric model of normal GARCH(p,q).Among nine different combinations of hybrid models (for p =1,2,3 and q =1,2,3),it is found that NN-GARCH(1,1) and NN-GARCH(2,2) perform better than the others in US market whereas,NN-GARCH(1,1) and NN-GARCH(3,1) outperform in Chinese case.

关键词： Neural Network GARCH volatility oil price

作者: Phichhang Ou Hengshan Wang

作者单位: School of Business, University of Shanghai for Science and Technology Rm 101, International Exchange Center, No.516, Jun Gong Road, Shanghai 200093, China

会议类型: 国际会议

会议名称: the 2011 International Conference on Frontiers of Manufacturing Science and Measuring Technology (第一届制造科学与检测技术国际会议(ICFMM2011))

会议地点: 重庆

会议语种:英文

页码: 953-957

在线出版日期: 2011-06-23（万方平台首次上网日期，不代表论文的发表时间）