Advanced Search
MyIDEAS: Login to save this paper or follow this series

Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models

Contents:

Author Info

  • Mohamed El Hedi Arouri

    ()
    (LEO, University of Orleans and EDHEC Business School Rue de Blois - BP 6739, 45067 Orléans Cedex 2, France)

  • Amine Lahiani

    ()
    (LEO, University of Orleans and EDHEC Business School Rue de Blois - BP 6739, 45067 Orléans Cedex 2, France)

  • Khuong Nguyen Duc

    ()
    (Professor of Finance, ISC Paris School of Management 22 Boulevard du Fort de Vaux, 75848 Paris cedex 17, France)

Abstract

This paper investigates whether structural breaks and long memory are relevant features in modeling and forecasting the conditional volatility of oil spot and futures prices using three GARCH-type models, i.e., linear GARCH, GARCH with structural breaks and FIGARCH. By relying on a modified version of Inclan and Tiao (1994)’s iterated cumulative sum of squares (ICSS) algorithm, our results can be summarized as follows. First, we provide evidence of parameter instability in five out of twelve GARCH-based conditional volatility processes for energy prices. Second, long memory is effectively present in all the series considered and a FIGARCH model seems to better fit the data, but the degree of volatility persistence diminishes significantly after adjusting for structural breaks. Finally, the out-of-sample analysis shows that forecasting models accommodating for structural break characteristics of the data often outperform the commonly used short-memory linear volatility models. It is however worth no at the long memory evidence found in the in-sample period is not strongly supported by the out-of-sample forecasting exercise.

Download Info

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.depocenwp.org/upload/pubs/NguyenDucKhuong/Forecastingtheconditionalvolatilityofoilspotandfutures_WP.pdf
Our checks indicate that this address may not be valid because: 404 Not Found. If this is indeed the case, please notify (Doan Quang Hung)
Download Restriction: no

Bibliographic Info

Paper provided by Development and Policies Research Center (DEPOCEN), Vietnam in its series Working Papers with number 13.

as in new window
Length: 34 pages
Date of creation: 2010
Date of revision:
Handle: RePEc:dpc:wpaper:1310

Contact details of provider:
Postal: 8-9 2nd Floor, 216 Tran Quang Khai Street, Hanoi
Phone: 844-3935-1419
Fax: 844-3935-1418
Email:
Web page: http://www.depocenwp.org
More information through EDIRC

Related research

Keywords: oil markets; volatility forecasting; long memory; structural breaks; GARCH; RiskMetrics;

Other versions of this item:

Find related papers by JEL classification:

References

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. 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.
  2. Elder, John & Serletis, Apostolos, 2008. "Long memory in energy futures prices," Review of Financial Economics, Elsevier, vol. 17(2), pages 146-155.
  3. Robinson, P.M. & Henry, M., 1999. "Long And Short Memory Conditional Heteroskedasticity In Estimating The Memory Parameter Of Levels," Econometric Theory, Cambridge University Press, vol. 15(03), pages 299-336, June.
  4. Plourde, André & Watkins, G. C., 1998. "Crude oil prices between 1985 and 1994: how volatile in relation to other commodities?," Resource and Energy Economics, Elsevier, vol. 20(3), pages 245-262, September.
  5. Regnier, Eva, 2007. "Oil and energy price volatility," Energy Economics, Elsevier, vol. 29(3), pages 405-427, May.
  6. Matteo Manera & Alessandro Cologni, 2005. "Oil Prices, Inflation and Interest Rates in a Structural Cointegrated VAR Model for the G-7 Countries," Working Papers 2005.101, Fondazione Eni Enrico Mattei.
  7. Wei, Yu & Wang, Yudong & Huang, Dengshi, 2010. "Forecasting crude oil market volatility: Further evidence using GARCH-class models," Energy Economics, Elsevier, vol. 32(6), pages 1477-1484, November.
  8. Lee, Yen-Hsien & Hu, Hsu-Ning & Chiou, Jer-Shiou, 2010. "Jump dynamics with structural breaks for crude oil prices," Energy Economics, Elsevier, vol. 32(2), pages 343-350, March.
  9. Kyongwook Choi & Shawkat Hammoudeh, 2009. "Long Memory in Oil and Refined Products Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 97-116.
  10. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  11. repec:att:wimass:9317 is not listed on IDEAS
  12. Ciner Cetin, 2001. "Energy Shocks and Financial Markets: Nonlinear Linkages," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(3), pages 1-11, October.
  13. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
  14. West, K.D. & Cho, D., 1993. "The Predictive Ability of Several Models of Exchange Rate Volatility," Working papers 9317r, Wisconsin Madison - Social Systems.
  15. Hamilton, James D, 1983. "Oil and the Macroeconomy since World War II," Journal of Political Economy, University of Chicago Press, vol. 91(2), pages 228-48, April.
  16. Kenneth D. West & Whitney K. Newey, 1995. "Automatic Lag Selection in Covariance Matrix Estimation," NBER Technical Working Papers 0144, National Bureau of Economic Research, Inc.
  17. Amélie Charles & Olivier Darne, 2009. "The efficiency of the crude oil markets: Evidence from variance ratio tests," Post-Print hal-00771081, HAL.
  18. 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.
  19. Jones, Charles M & Kaul, Gautam, 1996. " Oil and the Stock Markets," Journal of Finance, American Finance Association, vol. 51(2), pages 463-91, June.
  20. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
  21. Sadorsky, Perry, 2006. "Modeling and forecasting petroleum futures volatility," Energy Economics, Elsevier, vol. 28(4), pages 467-488, July.
  22. Cheong, Chin Wen, 2009. "Modeling and forecasting crude oil markets using ARCH-type models," Energy Policy, Elsevier, vol. 37(6), pages 2346-2355, June.
  23. Lardic, Sandrine & Mignon, Valérie, 2008. "Oil prices and economic activity: An asymmetric cointegration approach," Energy Economics, Elsevier, vol. 30(3), pages 847-855, May.
  24. Hedi Arouri, Mohamed El & Khuong Nguyen, Duc, 2010. "Oil prices, stock markets and portfolio investment: Evidence from sector analysis in Europe over the last decade," Energy Policy, Elsevier, vol. 38(8), pages 4528-4539, August.
  25. 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.
  26. Tabak, Benjamin M. & Cajueiro, Daniel O., 2007. "Are the crude oil markets becoming weakly efficient over time? A test for time-varying long-range dependence in prices and volatility," Energy Economics, Elsevier, vol. 29(1), pages 28-36, January.
  27. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
  28. Fong, Wai Mun & See, Kim Hock, 2002. "A Markov switching model of the conditional volatility of crude oil futures prices," Energy Economics, Elsevier, vol. 24(1), pages 71-95, January.
  29. Thomas Mikosch & Cătălin Stărică, 2004. "Nonstationarities in Financial Time Series, the Long-Range Dependence, and the IGARCH Effects," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 378-390, February.
  30. Hillebrand, Eric, 2005. "Neglecting parameter changes in GARCH models," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 121-138.
  31. Nandha, Mohan & Faff, Robert, 2008. "Does oil move equity prices? A global view," Energy Economics, Elsevier, vol. 30(3), pages 986-997, May.
  32. Catalin Starica & Stefano Herzel & Tomas Nord, 2005. "Why does the GARCH(1,1) model fail to provide sensible longer- horizon volatility forecasts?," Econometrics 0508003, EconWPA.
  33. Narayan, Paresh Kumar & Narayan, Seema, 2007. "Modelling oil price volatility," Energy Policy, Elsevier, vol. 35(12), pages 6549-6553, December.
  34. Boyer, M. Martin & Filion, Didier, 2007. "Common and fundamental factors in stock returns of Canadian oil and gas companies," Energy Economics, Elsevier, vol. 29(3), pages 428-453, May.
  35. Sowell, Fallaw, 1992. "Maximum likelihood estimation of stationary univariate fractionally integrated time series models," Journal of Econometrics, Elsevier, vol. 53(1-3), pages 165-188.
  36. Lee, Chien-Chiang & Lee, Jun-De, 2009. "Energy prices, multiple structural breaks, and efficient market hypothesis," Applied Energy, Elsevier, vol. 86(4), pages 466-479, April.
Full references (including those not matched with items on IDEAS)

Citations

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

Cited by:
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page.

Lists

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

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:dpc:wpaper:1310. 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: (Doan Quang Hung).

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.