DOI: 10.1016/j.eneco.2020.104721
论文题名: Crude oil price analysis and forecasting: A perspective of “new triangle”
作者: Lu Q. ; Li Y. ; Chai J. ; Wang S.
刊名: Energy Economics
ISSN: 1409883
出版年: 2020
卷: 87 语种: 英语
英文关键词: Bayesian model average
; Crude oil
; Dynamic Bayesian structural time series model
; Google trend
; Kalman filtering
; Spike and slab prior
Scopus关键词: Bayesian networks
; Costs
; Crude oil
; Economics
; Forecasting
; Petroleum analysis
; Search engines
; Time series
; Bayesian
; Bayesian model
; Google trends
; Kalman-filtering
; Spike and slab prior
; Crude oil price
; Bayesian analysis
; crude oil
; forecasting method
; Kalman filter
; price dynamics
; time series analysis
; trend analysis
英文摘要: In this paper, the new structural characteristics and core influencing factors of the crude oil prices are summarized based on previous representative research results. Firstly, a newly dynamic Bayesian structural time series model (DBSTS) is developed to investigate the oil prices. In particular, Google trend is introduced as an indicator to reflect the impact of search data on the oil price. Secondly, the spike and slab method is employed to select core influence factors. Finally, the Bayesian model average (BMA) is utilized to predict the oil price. Experimental results confirm that the supply and demand of global crude oil and the financial market are still the main factors affecting the oil price. Furthermore, Google trend can reflect the changes in the crude oil price to a certain extent. Moreover, the impact of shale oil production on the oil price is gradually increasing, yet remains relatively small. In addition, the DBSTS model can identify turning points in historical data (such as the 2008 financial crisis). Finally, the findings suggest the DBSTS model has good predictive capabilities in short-term prediction, making it suitable for analyzing the crude oil prices. © 2020 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/159113
Appears in Collections: 气候变化与战略
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作者单位: School of Economics and Management, University of Chinese Academy of Sciences, Beijing, 100190, China; Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China; School of Mathematical Science, University of Chinese Academy of Sciences, Beijing, 110190, China; School of Economics and Management, Xidian University, Xi'an, 710126, China
Recommended Citation:
Lu Q.,Li Y.,Chai J.,et al. Crude oil price analysis and forecasting: A perspective of “new triangle”[J]. Energy Economics,2020-01-01,87