IDEAS home Printed from https://ideas.repec.org/a/sae/enejou/v30y2009i3p81-90.html
   My bibliography  Save this article

Modelling and Forecasting Oil Prices: The Role of Asymmetric Cycles

Author

Listed:
  • Jesus Crespo Cuaresma
  • Adusei Jumah
  • Sohbet Karbuz

Abstract

Using a simple unobserved components model, we show that explicitly modelling asymmetric cycles on crude oil prices improves the forecast ability of univariate time series models of the oil price.

Suggested Citation

  • Jesus Crespo Cuaresma & Adusei Jumah & Sohbet Karbuz, 2009. "Modelling and Forecasting Oil Prices: The Role of Asymmetric Cycles," The Energy Journal, , vol. 30(3), pages 81-90, July.
    • Handle: RePEc:sae:enejou:v:30:y:2009:i:3:p:81-90
    DOI: 10.5547/ISSN0195-6574-EJ-Vol30-No3-4
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.5547/ISSN0195-6574-EJ-Vol30-No3-4
    Download Restriction: no
    File URL: https://libkey.io/10.5547/ISSN0195-6574-EJ-Vol30-No3-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Clements, Michael P. & Smith, Jeremy, 1997. "The performance of alternative forecasting methods for SETAR models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 463-475, December.
    2. Carmen M. Reinhart & Peter Wickham, 1994. "Commodity Prices: Cyclical Weakness or Secular Decline?," IMF Staff Papers, Palgrave Macmillan, vol. 41(2), pages 175-213, June.
    3. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    4. Knut Anton Mork & Oystein Olsen & Hans Terje Mysen, 1994. "Macroeconomic Responses to Oil Price Increases and Decreases in Seven OECD Countries," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 19-36.
    5. Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-227, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jesus Crespo Cuaresma & Adusei Jumah & Sohbet Karbuz, 2009. "Modelling and Forecasting Oil Prices: The Role of Asymmetric Cycles," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 81-90.
    2. de Albuquerquemello, Vinícius Phillipe & de Medeiros, Rennan Kertlly & da Nóbrega Besarria, Cássio & Maia, Sinézio Fernandes, 2018. "Forecasting crude oil price: Does exist an optimal econometric model?," Energy, Elsevier, vol. 155(C), pages 578-591.
    3. Günes Kamber & James Morley & Benjamin Wong, 2018. "Intuitive and Reliable Estimates of the Output Gap from a Beveridge-Nelson Filter," The Review of Economics and Statistics, MIT Press, vol. 100(3), pages 550-566, July.
    4. Asea, Patrick K & Reinhart, Carmen M, 1996. "Economic Growth and Economic Consequences of External Shocks in Sub-Saharan Africa: Introduction," Journal of African Economies, Centre for the Study of African Economies, vol. 5(3), pages 1-6, October.
    5. Thomas Hasenzagl & Filippo Pellegrino & Lucrezia Reichlin & Giovanni Ricco, 2022. "A Model of the Fed's View on Inflation," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 686-704, October.
    6. Milena Hoyos & Mario Galindo, 2011. "Comparación de los modelos SETAR y STAR para el índice de empleo industrial colombiano," Documentos de Trabajo, Escuela de Economía 8347, Universidad Nacional de Colombia, FCE, CID.
    7. Guglielmo Maria Caporale & Juncal Cuñado & Luis A. Gil-Alana, 2013. "Modelling long-run trends and cycles in financial time series data," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(3), pages 405-421, May.
    8. René Lalonde & Zhenhua Zhu & Frédérick Demers, 2003. "Forecasting and Analyzing World Commodity Prices," Money Affairs, CEMLA, vol. 0(1), pages 1-30, January-J.
    9. Ozdemir, Zeynel Abidin & Gokmenoglu, Korhan & Ekinci, Cagdas, 2013. "Persistence in crude oil spot and futures prices," Energy, Elsevier, vol. 59(C), pages 29-37.
    10. Orphanides, Athanasios & van Norden, Simon, 2005. "The Reliability of Inflation Forecasts Based on Output Gap Estimates in Real Time," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 583-601, June.
    11. Luis Uzeda, 2022. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 25-53, Emerald Group Publishing Limited.
    12. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    13. Dick van Dijk & Philip Hans Franses & Michael P. Clements & Jeremy Smith, 2003. "On SETAR non-linearity and forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(5), pages 359-375.
    14. Duarte, A. & Venetis, I. & Payá, I., 2004. "Curva de rendimientos y crecimiento de la producción real en la UEM: eficiencia y estabilidad predictiva./Yield Curve and Real Output Growth in the EMU: Efficiency and Predictive Stability," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 22, pages 1-21, Abril.
    15. Hui Feng & Jia Liu, 2003. "A SETAR model for Canadian GDP: non-linearities and forecast comparisons," Applied Economics, Taylor & Francis Journals, vol. 35(18), pages 1957-1964.
    16. Dueker, Michael J. & Sola, Martin & Spagnolo, Fabio, 2007. "Contemporaneous threshold autoregressive models: Estimation, testing and forecasting," Journal of Econometrics, Elsevier, vol. 141(2), pages 517-547, December.
    17. Labys, W C & Lesourd, J B & Badillo, D, 1998. "The existence of metal price cycles," Resources Policy, Elsevier, vol. 24(3), pages 147-155, September.
    18. Nibbering, Didier & Paap, Richard & van der Wel, Michel, 2018. "What do professional forecasters actually predict?," International Journal of Forecasting, Elsevier, vol. 34(2), pages 288-311.
    19. Juan Antolin-Diaz & Thomas Drechsel & Ivan Petrella, 2017. "Tracking the Slowdown in Long-Run GDP Growth," The Review of Economics and Statistics, MIT Press, vol. 99(2), pages 343-356, May.
    20. Ramis Khabibullin, 2019. "What measures of real economic activity slack are helpful for forecasting Russian inflation?," Bank of Russia Working Paper Series wps50, Bank of Russia.

    Corrections

    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:sae:enejou:v:30:y:2009:i:3:p:81-90. See general information about how to correct material in RePEc.

    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 bibliographic 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.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.