IDEAS home Printed from
   My bibliography  Save this article

Forecasting short-run crude oil price using high- and low-inventory variables


  • Ye, Michael
  • Zyren, John
  • Shore, Joanne


No abstract is available for this item.

Suggested Citation

  • Ye, Michael & Zyren, John & Shore, Joanne, 2006. "Forecasting short-run crude oil price using high- and low-inventory variables," Energy Policy, Elsevier, vol. 34(17), pages 2736-2743, November.
  • Handle: RePEc:eee:enepol:v:34:y:2006:i:17:p:2736-2743

    Download full text from publisher

    File URL:
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    1. Robert S. Pindyck, 1994. "Inventories and the Short-Run Dynamics of Commodity Prices," RAND Journal of Economics, The RAND Corporation, vol. 25(1), pages 141-159, Spring.
    2. Williams,Jeffrey C. & Wright,Brian D., 2005. "Storage and Commodity Markets," Cambridge Books, Cambridge University Press, number 9780521023399, March.
    3. Bessembinder, Hendrik, et al, 1995. " Mean Reversion in Equilibrium Asset Prices: Evidence from the Futures Term Structure," Journal of Finance, American Finance Association, vol. 50(1), pages 361-375, March.
    4. Angus Deaton & Guy Laroque, 1992. "On the Behaviour of Commodity Prices," Review of Economic Studies, Oxford University Press, vol. 59(1), pages 1-23.
    5. Miranda, Mario J & Glauber, Joseph W, 1993. "Estimation of Dynamic Nonlinear Rational Expectations Models of Primary Commodity Markets with Private and Government Stockholding," The Review of Economics and Statistics, MIT Press, vol. 75(3), pages 463-470, August.
    6. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    7. Bryan R. Routledge & Duane J. Seppi & Chester S. Spatt, 2000. "Equilibrium Forward Curves for Commodities," Journal of Finance, American Finance Association, vol. 55(3), pages 1297-1338, June.
    8. Michaelides, Alexander & Ng, Serena, 2000. "Estimating the rational expectations model of speculative storage: A Monte Carlo comparison of three simulation estimators," Journal of Econometrics, Elsevier, vol. 96(2), pages 231-266, June.
    9. A. Arize, 2000. "U.S. petroleum consumption behavior and oil price uncertainty: Tests of cointegration and parameter instability," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 28(4), pages 463-477, December.
    10. Chambers, Marcus J & Bailey, Roy E, 1996. "A Theory of Commodity Price Fluctuations," Journal of Political Economy, University of Chicago Press, vol. 104(5), pages 924-957, October.
    11. Michael Ye & John Zyren & Joanne Shore, 2003. "Elasticity of demand for relative petroleum inventory in the short run," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 31(1), pages 87-102, March.
    12. Husted, Steven & Kollintzas, Tryphon, 1987. "Linear Rational Expectations Equilibrium Laws of Motion for Selected U.S. Raw Material Imports," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 28(3), pages 651-670, October.
    13. Robert S. Pindyck, 2001. "The Dynamics of Commodity Spot and Futures Markets: A Primer," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-30.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. Shiu-Sheng Chen, 2014. "Forecasting Crude Oil Price Movements With Oil-Sensitive Stocks," Economic Inquiry, Western Economic Association International, vol. 52(2), pages 830-844, April.
    2. Jeffrey A Frankel & Andrew K Rose, 2010. "Determinants of Agricultural and Mineral Commodity Prices," RBA Annual Conference Volume,in: Renée Fry & Callum Jones & Christopher Kent (ed.), Inflation in an Era of Relative Price Shocks Reserve Bank of Australia.
    3. He, Kaijian & Yu, Lean & Lai, Kin Keung, 2012. "Crude oil price analysis and forecasting using wavelet decomposed ensemble model," Energy, Elsevier, vol. 46(1), pages 564-574.
    4. Hongtao Chen & Lianghua Chen, 2015. "Multifractal spectrum analysis of Brent crude oil futures prices volatility in intercontinental exchange," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 38(1/2/3), pages 93-108.
    5. repec:eee:eneeco:v:66:y:2017:i:c:p:9-16 is not listed on IDEAS
    6. Wang, Yudong & Liu, Li & Diao, Xundi & Wu, Chongfeng, 2015. "Forecasting the real prices of crude oil under economic and statistical constraints," Energy Economics, Elsevier, vol. 51(C), pages 599-608.
    7. Xiong, Tao & Bao, Yukun & Hu, Zhongyi, 2013. "Beyond one-step-ahead forecasting: Evaluation of alternative multi-step-ahead forecasting models for crude oil prices," Energy Economics, Elsevier, vol. 40(C), pages 405-415.
    8. repec:eee:eneeco:v:66:y:2017:i:c:p:508-522 is not listed on IDEAS
    9. Giliola Frey & Matteo Manera & Anil Markandya & Elisa Scarpa, 2009. "Econometric Models for Oil Price Forecasting: A Critical Survey," CESifo Forum, Ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 10(1), pages 29-44, April.
    10. Meade, Nigel, 2010. "Oil prices -- Brownian motion or mean reversion? A study using a one year ahead density forecast criterion," Energy Economics, Elsevier, vol. 32(6), pages 1485-1498, November.
    11. Naser, Hanan, 2016. "Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach," Energy Economics, Elsevier, vol. 56(C), pages 75-87.
    12. Manel Hamdi & Chaker Aloui, 2015. "Forecasting Crude Oil Price Using Artificial Neural Networks: A Literature Survey," Economics Bulletin, AccessEcon, vol. 35(2), pages 1339-1359.
    13. Yu, Lean & Wang, Zishu & Tang, Ling, 2015. "A decomposition–ensemble model with data-characteristic-driven reconstruction for crude oil price forecasting," Applied Energy, Elsevier, vol. 156(C), pages 251-267.
    14. García-Martos, Carolina & Rodríguez, Julio & Sánchez, María Jesús, 2013. "Modelling and forecasting fossil fuels, CO2 and electricity prices and their volatilities," Applied Energy, Elsevier, vol. 101(C), pages 363-375.
    15. Chen, Shyh-Wei & Lin, Shih-Mo, 2014. "Non-linear dynamics in international resource markets: Evidence from regime switching approach," Research in International Business and Finance, Elsevier, vol. 30(C), pages 233-247.
    16. Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2008. "Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm," Energy Economics, Elsevier, vol. 30(5), pages 2623-2635, September.
    17. Frankel, Jeffrey A., 2014. "Effects of speculation and interest rates in a “carry trade” model of commodity prices," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 88-112.
    18. Fan, Ying & Liang, Qiang & Wei, Yi-Ming, 2008. "A generalized pattern matching approach for multi-step prediction of crude oil price," Energy Economics, Elsevier, vol. 30(3), pages 889-904, May.
    19. Zhang, Xun & Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method," Energy Economics, Elsevier, vol. 31(5), pages 768-778, September.
    20. repec:spr:eurasi:v:7:y:2017:i:3:d:10.1007_s40821-016-0058-0 is not listed on IDEAS
    21. Ai Han & Yanan He & Yongmiao Hong & Shouyang Wang, 2013. "Forecasting Interval-valued Crude Oil Prices via Autoregressive Conditional Interval Models," WISE Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    22. de Souza e Silva, Edmundo G. & Legey, Luiz F.L. & de Souza e Silva, Edmundo A., 2010. "Forecasting oil price trends using wavelets and hidden Markov models," Energy Economics, Elsevier, vol. 32(6), pages 1507-1519, November.

    More about this item


    Access and download statistics


    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:34:y:2006:i:17:p:2736-2743. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.