Forecasting crude oil spot price using OECD petroleum inventory levels

被引:9
|
作者
Ye M. [1 ]
Zyren J. [2 ]
Shore J. [2 ]
机构
[1] St. Mary's College of Maryland,
[2] Department of Energy,undefined
关键词
Price Change; Petroleum Production; Market Behavior; Forecast Price; Demand Change;
D O I
10.1007/BF02295507
中图分类号
学科分类号
摘要
This paper presents a short-term monthly forecasting model of West Texas Intermediate crude oil spot price using OECD petroleum inventory levels. Theoretically, petroleum inventory levels are a measure of the balance, or imbalance, between petroleum production and demand, and thus provide a good market barometer of crude oil price change. Based on an understanding of petroleum market fundamentals and observed market behavior during the post-Gulf War period, the model was developed with the objectives of being both simple and practical, with required data readily available. As a result, the model is useful to industry and government decision-makers in forecasting price and investigating the impacts of changes on price, should inventories, production, imports, or demand change. (JEL Q40, C53).
引用
收藏
页码:324 / 333
页数:9
相关论文
共 50 条
  • [41] FORECASTING CRUDE OIL PRICE MOVEMENTS WITH OIL-SENSITIVE STOCKS
    Chen, Shiu-sheng
    ECONOMIC INQUIRY, 2014, 52 (02) : 830 - 844
  • [42] Futures Prices are Useful Predictors of the Spot Price of Crude Oil
    Ellwanger, Reinhard
    Snudden, Stephen
    ENERGY JOURNAL, 2023, 44 (04): : 65 - 82
  • [43] Improved EEMD-based crude oil price forecasting using LSTM networks
    Wu, Yu-Xi
    Wu, Qing-Biao
    Zhu, Jia-Qi
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2019, 516 : 114 - 124
  • [44] Crude oil price forecasting based on internet concern using an extreme learning machine
    Wang, Jue
    Athanasopoulos, George
    Hyndman, Rob J.
    Wang, Shouyang
    INTERNATIONAL JOURNAL OF FORECASTING, 2018, 34 (04) : 665 - 677
  • [45] A novel crude oil price forecasting model using decomposition and deep learning networks
    Dong, Yao
    Jiang, He
    Guo, Yunting
    Wang, Jianzhou
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2024, 133
  • [46] Forecasting the price of crude oil via convenience yield predictions
    Knetsch, Thomas A.
    JOURNAL OF FORECASTING, 2007, 26 (07) : 527 - 549
  • [47] Forecasting Crude Oil Price with Multiscale Denoising Ensemble Model
    Li, Xia
    He, Kaijian
    Lai, Kin Keung
    Zou, Yingchao
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2014, 2014
  • [48] A VAR-SVM model for crude oil price forecasting
    Zhao, Lutao
    Cheng, Lei
    Wan, Yongtao
    Zhang, Hao
    Zhang, Zhigang
    INTERNATIONAL JOURNAL OF GLOBAL ENERGY ISSUES, 2015, 38 (1-3) : 126 - 144
  • [49] Interval decomposition ensemble approach for crude oil price forecasting
    Sun, Shaolong
    Sun, Yuying
    Wang, Shouyang
    Wei, Yunjie
    ENERGY ECONOMICS, 2018, 76 : 274 - 287
  • [50] CRUDE OIL PRICE FORECASTING WITH TEI@I METHODOLOGY
    WANG Shouyang (Institute of Systems Science
    School of Management
    College of Business Administration
    JournalofSystemsScienceandComplexity, 2005, (02) : 145 - 166