IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Log in (now much improved!) to save this article

International evidence on crude oil price dynamics: Applications of ARIMA-GARCH models

  • Mohammadi, Hassan
  • Su, Lixian
Registered author(s):

    We examine the usefulness of several ARIMA-GARCH models for modeling and forecasting the conditional mean and volatility of weekly crude oil spot prices in eleven international markets over the 1/2/1997-10/3/2009 period. In particular, we investigate the out-of-sample forecasting performance of four volatility models -- GARCH, EGARCH and APARCH and FIGARCH over January 2009 to October 2009. Forecasting results are somewhat mixed, but in most cases, the APARCH model outperforms the others. Also, conditional standard deviation captures the volatility in oil returns better than the traditional conditional variance. Finally, shocks to conditional volatility dissipate at an exponential rate, which is consistent with the covariance-stationary GARCH models than the slow hyperbolic rate implied by the FIGARCH alternative.

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

    File URL: http://www.sciencedirect.com/science/article/pii/S0140-9883(10)00065-4
    Download Restriction: Full text for ScienceDirect subscribers only

    As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.

    Article provided by Elsevier in its journal Energy Economics.

    Volume (Year): 32 (2010)
    Issue (Month): 5 (September)
    Pages: 1001-1008

    as
    in new window

    Handle: RePEc:eee:eneeco:v:32:y:2010:i:5:p:1001-1008
    Contact details of provider: Web page: http://www.elsevier.com/locate/eneco

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

    as in new window
    1. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    2. Newey, Whitney K & West, Kenneth D, 1987. "A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix," Econometrica, Econometric Society, vol. 55(3), pages 703-08, May.
    3. Ben S. Bernanke, 1983. "Irreversibility, Uncertainty, and Cyclical Investment," The Quarterly Journal of Economics, Oxford University Press, vol. 98(1), pages 85-106.
    4. Bernanke, Ben S. & Gertler, Mark & Waston, Mark, 1997. "Systematic Monetary Policy and the Effects of Oil Price Shocks," Working Papers 97-25, C.V. Starr Center for Applied Economics, New York University.
    5. Kang, Sang Hoon & Kang, Sang-Mok & Yoon, Seong-Min, 2009. "Forecasting volatility of crude oil markets," Energy Economics, Elsevier, vol. 31(1), pages 119-125, January.
    6. Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
    7. Agnolucci, Paolo, 2009. "Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models," Energy Economics, Elsevier, vol. 31(2), pages 316-321, March.
    8. Elder, John & Serletis, Apostolos, 2009. "Oil price uncertainty in Canada," Energy Economics, Elsevier, vol. 31(6), pages 852-856, November.
    9. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-47, August.
    10. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    11. Mohammadi, Hassan, 2009. "Electricity prices and fuel costs: Long-run relations and short-run dynamics," Energy Economics, Elsevier, vol. 31(3), pages 503-509, May.
    12. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    13. Peter Ferderer, J., 1996. "Oil price volatility and the macroeconomy," Journal of Macroeconomics, Elsevier, vol. 18(1), pages 1-26.
    14. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
    15. 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.
    16. Kausik Chaudhuri, 2001. "Long-run prices of primary commodities and oil prices," Applied Economics, Taylor & Francis Journals, vol. 33(4), pages 531-538.
    17. Bowden, Nicholas & Payne, James E., 2008. "Short term forecasting of electricity prices for MISO hubs: Evidence from ARIMA-EGARCH models," Energy Economics, Elsevier, vol. 30(6), pages 3186-3197, November.
    18. Rotemberg, Julio J & Woodford, Michael, 1996. "Imperfect Competition and the Effects of Energy Price Increases on Economic Activity," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 28(4), pages 550-77, November.
    19. Michael Bruno & Jeffrey Sachs, 1982. "Energy and Resource Allocation: A Dynamic Model of the "Dutch Disease"," NBER Working Papers 0852, National Bureau of Economic Research, Inc.
    20. Hamilton, James D & Herrera, Ana Maria, 2004. "Oil Shocks and Aggregate Macroeconomic Behavior: The Role of Monetary Policy: Comment," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 36(2), pages 265-86, April.
    21. Michael Bruno & Jeffrey Sachs, 1982. "Energy and Resource Allocation: A Dynamic Model of the "Dutch Disease"," Review of Economic Studies, Oxford University Press, vol. 49(5), pages 845-859.
    22. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    23. Yang, C. W. & Hwang, M. J. & Huang, B. N., 2002. "An analysis of factors affecting price volatility of the US oil market," Energy Economics, Elsevier, vol. 24(2), pages 107-119, March.
    24. Sadorsky, Perry, 2006. "Modeling and forecasting petroleum futures volatility," Energy Economics, Elsevier, vol. 28(4), pages 467-488, July.
    25. Edwards, Sebastian & Aoki, Masanao, 1983. "Oil export boom and Dutch-disease : A dynamic analysis," Resources and Energy, Elsevier, vol. 5(3), pages 219-242, September.
    26. Iikka Korhonen & Tuuli Juurikkala, 2009. "Equilibrium exchange rates in oil-exporting countries," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 33(1), pages 71-79, January.
    27. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    28. Mohammad R. Jahan-Parvar & Hassan Mohammadi, 2009. "Oil prices and competitiveness: time series evidence from six oil-producing countries," Journal of Economic Studies, Emerald Group Publishing, vol. 36(1), pages 98-118, January.
    29. Hsieh, David A, 1989. "Modeling Heteroscedasticity in Daily Foreign-Exchange Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 7(3), pages 307-17, July.
    30. Mork, Knut Anton, 1989. "Oil and Macroeconomy When Prices Go Up and Down: An Extension of Hamilton's Results," Journal of Political Economy, University of Chicago Press, vol. 97(3), pages 740-44, June.
    31. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
    Full references (including those not matched with items on IDEAS)

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    When requesting a correction, please mention this item's handle: RePEc:eee:eneeco:v:32:y:2010:i:5:p:1001-1008. 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: (Shamier, Wendy)

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.

    This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.