IDEAS home Printed from
   My bibliography  Save this article

Futures versus univariate forecast of crude oil prices


  • Salah Abosedra


A simple univariate model is employed to generate an unbiased and (weakly) efficient forecast of the crude oil spot price. In terms of predictive information, however, this univariate forecast is inferior to the futures price for one-month-ahead contracts. This observation may suggest that the futures price of crude oil, while unbiased, tends to be semi-strongly efficient. Copyright 2005 Organization of the Petroleum Exporting Countries.

Suggested Citation

  • Salah Abosedra, 2005. "Futures versus univariate forecast of crude oil prices," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 29(4), pages 231-241, December.
  • Handle: RePEc:bla:opecrv:v:29:y:2005:i:4:p:231-241

    Download full text from publisher

    File URL:
    File Function: link to full text
    Download Restriction: Access to full text is restricted to subscribers.

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


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

    Cited by:

    1. Prat, Georges & Uctum, Remzi, 2011. "Modelling oil price expectations: Evidence from survey data," The Quarterly Review of Economics and Finance, Elsevier, vol. 51(3), pages 236-247, June.
    2. Matteo Manera & Chiara Longo & Anil Markandya & Elisa Scarpa, 2007. "Evaluating the Empirical Performance of Alternative Econometric Models for Oil Price Forecasting," Working Papers 2007.4, Fondazione Eni Enrico Mattei.
    3. 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.
    4. 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.
    5. 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.
    6. Juan Carlos Cuestas & Paulo Jose Regis, 2008. "Nonlinearities and the order of integration of oil prices," Working Papers 2008/15, Nottingham Trent University, Nottingham Business School, Economics Division.
    7. Arunanondchai, Panit & Senia, Mark C. & Capps, Oral Jr, 2017. "Can U.S. EIA Retail Gasoline Price Forecasts Be Improved Upon?," 2017 Annual Meeting, February 4-7, 2017, Mobile, Alabama 252717, Southern Agricultural Economics Association.
    8. 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.

    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:bla:opecrv:v:29:y:2005:i:4:p:231-241. 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: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). 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.

    We have no references for this item. You can help adding them by using 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.