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Price Dynamics of Crude Oil in the Short and Long Term

Author

Listed:
  • Sa d Benbachir

    (Department of Management Sciences, FSJES-Agdal, Mohammed 5 University, Morocco,)

  • Sihame Lembarki

    (Center for Doctoral Studies Law and Economics. Department of Management Sciences, Faculty of Law Agdal, Mohammed 5 University, Morocco.)

Abstract

The drop in the price of crude oil in 2014 left no one indifferent, and motivated several researchers to analyse the nature of the relationship between the physical and the financial market of this commodity. This article discusses the issue of Spot and Futures price dynamics of crude oil in the short and long term. The originality of the present work is that we will proceed to a double analysis of the stochastic processes of the two variables Spot and Futures - with and without break - for the period from February 2015 to December 2017, using the models VAR and VECM. This last allows to understand short-term price dynamics while the VAR makes it possible to understand it in the long term. The results obtained estimate that there is a bidirectional causality between the two variables, and that their long-term dynamics undergo the same changes together. The Spot and Futures prices hold the fall of their prices on the same date of January 2016 (common break date for the 2 series), which distinguishes between two sub-periods and consequently two distinct regimes: "Tension" and "return to the average" regime. In the short term, the first one cannot reject the theory of normal backwardation, while the storage theory reasonably explains the return to the path of the equilibrium of the prices of the oil markets.

Suggested Citation

  • Sa d Benbachir & Sihame Lembarki, 2018. "Price Dynamics of Crude Oil in the Short and Long Term," International Journal of Economics and Financial Issues, Econjournals, vol. 8(5), pages 103-114.
  • Handle: RePEc:eco:journ1:2018-05-16
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    References listed on IDEAS

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    4. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    5. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    6. Nicolas Carnot & Caterine Hagège, 2004. "Le marché pétrolier," Economie & Prévision, La Documentation Française, vol. 166(5), pages 127-136.
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    Cited by:

    1. Galán-Gutiérrez, Juan Antonio & Martín-García, Rodrigo, 2021. "Cointegration between the structure of copper futures prices and Brexit," Resources Policy, Elsevier, vol. 71(C).
    2. Juan Antonio Galán-Gutiérrez & Rodrigo Martín-García, 2022. "Fundamentals vs. Financialization during Extreme Events: From Backwardation to Contango, a Copper Market Analysis during the COVID-19 Pandemic," Mathematics, MDPI, vol. 10(4), pages 1-23, February.
    3. Galán-Gutiérrez, Juan Antonio & Labeaga, José M. & Martín-García, Rodrigo, 2023. "Cointegration between high base metals prices and backwardation: Getting ready for the metals super-cycle," Resources Policy, Elsevier, vol. 81(C).

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    More about this item

    Keywords

    Spot & Futures markets; Cointegration; Autoregressive vector model (VAR); Vector error correction model (VECM);
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices

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