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Basis variations and regime shifts in the oil futures market

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  • Wai Mun Fong
  • Kim Hock See

Abstract

The conditional volatility of crude oil futures returns is modelled as a regime switching process. The model features transition probabilities that are functions of the basis. Consistent with the theory of storage, in volatile periods, an increase in backwardation is associated with an increase in the likellihood of switching to or remaining in the high-volatility state. Conditional on regimes, GARCH persistence is significantly reduced. Out-of-sample tests show that incorporating regime shifts improves the accuracy of short-term volatility forecasts.

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  • Wai Mun Fong & Kim Hock See, 2003. "Basis variations and regime shifts in the oil futures market," The European Journal of Finance, Taylor & Francis Journals, vol. 9(5), pages 499-513.
    • Handle: RePEc:taf:eurjfi:v:9:y:2003:i:5:p:499-513
    DOI: 10.1080/1351847032000082808
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    References listed on IDEAS

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    Cited by:

    1. Charles, Amélie & Darné, Olivier, 2014. "Volatility persistence in crude oil markets," Energy Policy, Elsevier, vol. 65(C), pages 729-742.
    2. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2013. "Risk-averse and Risk-seeking Investor Preferences for Oil Spot and Futures," Documentos de Trabajo del ICAE 2013-31, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Aug 2013.
    3. Almansour, Abdullah, 2016. "Convenience yield in commodity price modeling: A regime switching approach," Energy Economics, Elsevier, vol. 53(C), pages 238-247.
    4. Lean, H.H. & McAleer, M.J. & Wong, W.-K., 2010. "Investor preferences for oil spot and futures based on mean-variance and stochastic dominance," Econometric Institute Research Papers EI 2010-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    5. Nomikos, Nikos K. & Pouliasis, Panos K., 2011. "Forecasting petroleum futures markets volatility: The role of regimes and market conditions," Energy Economics, Elsevier, vol. 33(2), pages 321-337, March.
    6. Panos K. Pouliasis & Christos Bentsos, 2024. "Oil price uncertainty and the relation to tanker shipping," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 2472-2494, April.
    7. Lean, Hooi Hooi & McAleer, Michael & Wong, Wing-Keung, 2015. "Preferences of risk-averse and risk-seeking investors for oil spot and futures before, during and after the Global Financial Crisis," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 204-216.
    8. Elliott, Robert J. & Siu, Tak Kuen & Badescu, Alexandru, 2011. "On pricing and hedging options in regime-switching models with feedback effect," Journal of Economic Dynamics and Control, Elsevier, vol. 35(5), pages 694-713, May.
    9. Chang, Kuang-Liang & Lee, Chingnun, 2020. "The asymmetric spillover effect of the Markov switching mechanism from the futures market to the spot market," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 374-388.
    10. Lean, Hooi Hooi & McAleer, Michael & Wong, Wing-Keung, 2010. "Market efficiency of oil spot and futures: A mean-variance and stochastic dominance approach," Energy Economics, Elsevier, vol. 32(5), pages 979-986, September.
    11. Chang, Kuang-Liang, 2016. "Does the return-state-varying relationship between risk and return matter in modeling the time series process of stock return?," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 72-87.
    12. Qian, Lihua & Zeng, Qing & Li, Tao, 2022. "Geopolitical risk and oil price volatility: Evidence from Markov-switching model," International Review of Economics & Finance, Elsevier, vol. 81(C), pages 29-38.
    13. Vo, Minh T., 2009. "Regime-switching stochastic volatility: Evidence from the crude oil market," Energy Economics, Elsevier, vol. 31(5), pages 779-788, September.
    14. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2010. "Market Efficiency of Oil Spot and Futures: A Stochastic Dominance Approach," CIRJE F-Series CIRJE-F-705, CIRJE, Faculty of Economics, University of Tokyo.
    15. Li, Sufang & Zhang, Hu & Yuan, Di, 2019. "Investor attention and crude oil prices: Evidence from nonlinear Granger causality tests," Energy Economics, Elsevier, vol. 84(C).
    16. Alizadeh, Amir H. & Nomikos, Nikos K. & Pouliasis, Panos K., 2008. "A Markov regime switching approach for hedging energy commodities," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1970-1983, September.
    17. Alzahrani, Mohammed & Masih, Mansur & Al-Titi, Omar, 2014. "Linear and non-linear Granger causality between oil spot and futures prices: A wavelet based test," Journal of International Money and Finance, Elsevier, vol. 48(PA), pages 175-201.
    18. 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.
    19. 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.
    20. 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.

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