IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v143y2015icp96-109.html
   My bibliography  Save this article

Interpreting the crude oil price movements: Evidence from the Markov regime switching model

Author

Listed:
  • Zhang, Yue-Jun
  • Zhang, Lu

Abstract

Since 2009, global financial crisis has eased gradually and world economy has begun to recover slowly. Meanwhile, both Brent and WTI (West Texas Intermediate) crude oil prices have entered into a new round of increase and volatility, and the abnormal price spreads between them have been identified. Under this circumstance, this paper employs the Markov regime switching model with dynamic autoregressive coefficients to explore the price regimes of Brent and WTI after the financial crisis. Then it analyzes the causes of the abnormal spreads between the two benchmark crude oil prices based on the statistical observations of their typical regime differences. The results show that there are three main regimes in both Brent and WTI crude oil price returns, i.e., sharply downward, slightly downward and sharply upward regimes for Brent whilst sharply downward, relatively stable and sharply upward regimes for WTI. Meanwhile, the typical price regimes of Brent and WTI are the “sharply upward” and “relatively stable” regimes after the financial crisis, respectively. Besides, their different movement regimes in recent years are mainly attributed to their different market fundamental situations and the dynamics in crude oil markets, which also lead to the occurrence of their abnormal price spreads.

Suggested Citation

  • Zhang, Yue-Jun & Zhang, Lu, 2015. "Interpreting the crude oil price movements: Evidence from the Markov regime switching model," Applied Energy, Elsevier, vol. 143(C), pages 96-109.
  • Handle: RePEc:eee:appene:v:143:y:2015:i:c:p:96-109
    DOI: 10.1016/j.apenergy.2015.01.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915000112
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2015.01.005?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
    ---><---

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

    References listed on IDEAS

    as
    1. Arouri, Mohamed El Hédi & Lahiani, Amine & Lévy, Aldo & Nguyen, Duc Khuong, 2012. "Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models," Energy Economics, Elsevier, vol. 34(1), pages 283-293.
    2. Jammazi, Rania, 2012. "Oil shock transmission to stock market returns: Wavelet-multivariate Markov switching GARCH approach," Energy, Elsevier, vol. 37(1), pages 430-454.
    3. Sévi, Benoît, 2014. "Forecasting the volatility of crude oil futures using intraday data," European Journal of Operational Research, Elsevier, vol. 235(3), pages 643-659.
    4. Narayan, Paresh Kumar & Narayan, Seema, 2007. "Modelling oil price volatility," Energy Policy, Elsevier, vol. 35(12), pages 6549-6553, December.
    5. 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.
    6. Chang, Chia-Lin & McAleer, Michael & Tansuchat, Roengchai, 2013. "Conditional correlations and volatility spillovers between crude oil and stock index returns," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 116-138.
    7. Fan, Ying & Zhang, Yue-Jun & Tsai, Hsien-Tang & Wei, Yi-Ming, 2008. "Estimating 'Value at Risk' of crude oil price and its spillover effect using the GED-GARCH approach," Energy Economics, Elsevier, vol. 30(6), pages 3156-3171, November.
    8. Ripple, Ronald D. & Moosa, Imad A., 2009. "The effect of maturity, trading volume, and open interest on crude oil futures price range-based volatility," Global Finance Journal, Elsevier, vol. 20(3), pages 209-219.
    9. Vo, Minh T., 2009. "Regime-switching stochastic volatility: Evidence from the crude oil market," Energy Economics, Elsevier, vol. 31(5), pages 779-788, September.
    10. 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.
    11. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    12. Naifar, Nader & Al Dohaiman, Mohammed Saleh, 2013. "Nonlinear analysis among crude oil prices, stock markets' return and macroeconomic variables," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 416-431.
    13. Hung, Jui-Cheng & Yi-Hsien Wang, & Chang, Matthew C. & Shih, Kuang-Hsun & Hsiu-Hsueh Kao,, 2011. "Minimum variance hedging with bivariate regime-switching model for WTI crude oil," Energy, Elsevier, vol. 36(5), pages 3050-3057.
    14. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    15. Regnier, Eva, 2007. "Oil and energy price volatility," Energy Economics, Elsevier, vol. 29(3), pages 405-427, May.
    16. Larsson, Karl & Nossman, Marcus, 2011. "Jumps and stochastic volatility in oil prices: Time series evidence," Energy Economics, Elsevier, vol. 33(3), pages 504-514, May.
    17. Ali Ahmed, Huson Joher & Bashar, Omar H.M.N. & Wadud, I.K.M. Mokhtarul, 2012. "The transitory and permanent volatility of oil prices: What implications are there for the US industrial production?," Applied Energy, Elsevier, vol. 92(C), pages 447-455.
    18. 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.
    19. Mollick, André Varella & Assefa, Tibebe Abebe, 2013. "U.S. stock returns and oil prices: The tale from daily data and the 2008–2009 financial crisis," Energy Economics, Elsevier, vol. 36(C), pages 1-18.
    20. Wu, Gang & Zhang, Yue-Jun, 2014. "Does China factor matter? An econometric analysis of international crude oil prices," Energy Policy, Elsevier, vol. 72(C), pages 78-86.
    21. Zhang, Yue-Jun, 2013. "Speculative trading and WTI crude oil futures price movement: An empirical analysis," Applied Energy, Elsevier, vol. 107(C), pages 394-402.
    22. repec:ipg:wpaper:2014-053 is not listed on IDEAS
    23. Gallo, Andres & Mason, Paul & Shapiro, Steve & Fabritius, Michael, 2010. "What is behind the increase in oil prices? Analyzing oil consumption and supply relationship with oil price," Energy, Elsevier, vol. 35(10), pages 4126-4141.
    24. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    25. Bhar, Ramaprasad & Malliaris, A.G., 2011. "Oil prices and the impact of the financial crisis of 2007–2009," Energy Economics, Elsevier, vol. 33(6), pages 1049-1054.
    26. Chang, Kuang-Liang, 2012. "Volatility regimes, asymmetric basis effects and forecasting performance: An empirical investigation of the WTI crude oil futures market," Energy Economics, Elsevier, vol. 34(1), pages 294-306.
    27. Liu, Li & Wan, Jieqiu, 2012. "A study of Shanghai fuel oil futures price volatility based on high frequency data: Long-range dependence, modeling and forecasting," Economic Modelling, Elsevier, vol. 29(6), pages 2245-2253.
    28. Hou, Aijun & Suardi, Sandy, 2012. "A nonparametric GARCH model of crude oil price return volatility," Energy Economics, Elsevier, vol. 34(2), pages 618-626.
    29. Zhang, Yue-Jun & Wang, Jing, 2015. "Exploring the WTI crude oil price bubble process using the Markov regime switching model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 377-387.
    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. ebrahimi, mohsen & babaei agh esmaili, Majid & kafili, vahid, 2017. "بررسی رژیم های قیمتی دو شاخص عمده بازار جهانی نفت(برنت و Wti) قبل و بعد از بحران مالی:کاربردی از رویکرد مارکف سوئیچینگ [Investigate price regimes of two prime index in the world oil market(Brent an," MPRA Paper 98739, University Library of Munich, Germany.
    2. Nonejad, Nima, 2017. "Parameter instability, stochastic volatility and estimation based on simulated likelihood: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 61(C), pages 388-408.
    3. Walid Matar & Saud M. Al-Fattah & Tarek Atallah & Axel Pierru, 2013. "An introduction to oil market volatility analysis," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 37(3), pages 247-269, September.
    4. Zhang, Yue-Jun & Yao, Ting & He, Ling-Yun & Ripple, Ronald, 2019. "Volatility forecasting of crude oil market: Can the regime switching GARCH model beat the single-regime GARCH models?," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 302-317.
    5. Lin, Boqiang & Wesseh, Presley K., 2013. "What causes price volatility and regime shifts in the natural gas market," Energy, Elsevier, vol. 55(C), pages 553-563.
    6. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
    7. Zhang, Jin-Liang & Zhang, Yue-Jun & Zhang, Lu, 2015. "A novel hybrid method for crude oil price forecasting," Energy Economics, Elsevier, vol. 49(C), pages 649-659.
    8. Urom, Christian & Onwuka, Kevin O. & Uma, Kalu E. & Yuni, Denis N., 2020. "Regime dependent effects and cyclical volatility spillover between crude oil price movements and stock returns," International Economics, Elsevier, vol. 161(C), pages 10-29.
    9. Apergis, Nicholas & Payne, James E., 2017. "Volatility Modeling of U.S. Metropolitan Retail Gasoline Prices: An Empirical Note," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 48(2), September.
    10. Wang, Yudong & Liu, Li & Ma, Feng & Wu, Chongfeng, 2016. "What the investors need to know about forecasting oil futures return volatility," Energy Economics, Elsevier, vol. 57(C), pages 128-139.
    11. Wen, Fenghua & Gong, Xu & Cai, Shenghua, 2016. "Forecasting the volatility of crude oil futures using HAR-type models with structural breaks," Energy Economics, Elsevier, vol. 59(C), pages 400-413.
    12. Yue-Jun Zhang & Ting Yao & Ling-Yun He, 2015. "Forecasting crude oil market volatility: can the Regime Switching GARCH model beat the single-regime GARCH models?," Papers 1512.01676, arXiv.org.
    13. Ma, Feng & Wahab, M.I.M. & Huang, Dengshi & Xu, Weiju, 2017. "Forecasting the realized volatility of the oil futures market: A regime switching approach," Energy Economics, Elsevier, vol. 67(C), pages 136-145.
    14. Wang, Yudong & Wu, Chongfeng, 2012. "Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?," Energy Economics, Elsevier, vol. 34(6), pages 2167-2181.
    15. Liu, Yuanyuan & Niu, Zibo & Suleman, Muhammad Tahir & Yin, Libo & Zhang, Hongwei, 2022. "Forecasting the volatility of crude oil futures: The role of oil investor attention and its regime switching characteristics under a high-frequency framework," Energy, Elsevier, vol. 238(PA).
    16. Gong, Xu & Lin, Boqiang, 2017. "Forecasting the good and bad uncertainties of crude oil prices using a HAR framework," Energy Economics, Elsevier, vol. 67(C), pages 315-327.
    17. Alizadeh, Amir H. & Huang, Chih-Yueh & Marsh, Ian W., 2021. "Modelling the volatility of TOCOM energy futures: A regime switching realised volatility approach," Energy Economics, Elsevier, vol. 93(C).
    18. Drachal, Krzysztof, 2016. "Forecasting spot oil price in a dynamic model averaging framework — Have the determinants changed over time?," Energy Economics, Elsevier, vol. 60(C), pages 35-46.
    19. Lin, Yu & Xiao, Yang & Li, Fuxing, 2020. "Forecasting crude oil price volatility via a HM-EGARCH model," Energy Economics, Elsevier, vol. 87(C).
    20. Charles, Amélie & Darné, Olivier, 2014. "Volatility persistence in crude oil markets," Energy Policy, Elsevier, vol. 65(C), pages 729-742.

    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:eee:appene:v:143:y:2015:i:c:p:96-109. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.