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Exploring the WTI crude oil price bubble process using the Markov regime switching model

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  • Zhang, Yue-Jun
  • Wang, Jing

Abstract

The sharp volatility of West Texas Intermediate (WTI) crude oil price in the past decade triggers us to investigate the price bubbles and their evolving process. Empirical results indicate that the fundamental price of WTI crude oil appears relatively more stable than that of the market-trading price, which verifies the existence of oil price bubbles during the sample period. Besides, by allowing the WTI crude oil price bubble process to switch between two states (regimes) according to a first-order Markov chain, we are able to statistically discriminate upheaval from stable states in the crude oil price bubble process; and in most of time, the stable state dominates the WTI crude oil price bubbles while the upheaval state usually proves short-lived and accompanies unexpected market events.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:phsmap:v:421:y:2015:i:c:p:377-387
    DOI: 10.1016/j.physa.2014.11.051
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    Cited by:

    1. Zhang, Yue-Jun & Yao, Ting, 2016. "Interpreting the movement of oil prices: Driven by fundamentals or bubbles?," Economic Modelling, Elsevier, vol. 55(C), pages 226-240.
    2. García-Carranco, Sergio M. & Bory-Reyes, Juan & Balankin, Alexander S., 2016. "The crude oil price bubbling and universal scaling dynamics of price volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 60-68.
    3. Rashidi Ranjbar, Hedieh & Seifi, Abbas, 2015. "A path-independent method for barrier option pricing in hidden Markov models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 440(C), pages 1-8.
    4. Jung, Sean S. & Chang, Woojin, 2016. "Clustering stocks using partial correlation coefficients," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 410-420.
    5. Su, Chi-Wei & Li, Zheng-Zheng & Chang, Hsu-Ling & Lobonţ, Oana-Ramona, 2017. "When Will Occur the Crude Oil Bubbles?," Energy Policy, Elsevier, vol. 102(C), pages 1-6.
    6. Pal, Debdatta & Mitra, Subrata K., 2016. "Asymmetric oil product pricing in India: Evidence from a multiple threshold nonlinear ARDL model," Economic Modelling, Elsevier, vol. 59(C), pages 314-328.
    7. Ju, Keyi & Su, Bin & Zhou, Dequn & Wu, Junmin & Liu, Lifan, 2016. "Macroeconomic performance of oil price shocks: Outlier evidence from nineteen major oil-related countries/regions," Energy Economics, Elsevier, vol. 60(C), pages 325-332.
    8. 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.
    9. Ftiti, Zied & Fatnassi, Ibrahim & Tiwari, Aviral Kumar, 2016. "Neoclassical finance, behavioral finance and noise traders: Assessment of gold–oil markets," Finance Research Letters, Elsevier, vol. 17(C), pages 33-40.

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