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A Methodology for the Choice of the Best Fitting Continuous-Time Stochastic Models of Crude Oil Price: The Case of Russia

Author

Listed:
  • Hamidreza Mostafaei

    (Department of Statistics, Tehran North Branch, Islamic Azad University, Tehran, Iran)

  • Ali Akbar Rahimzadeh Sani

    (Department of Mathematics, Teacher Training University of Tehran, IRAN)

  • Samira Askari

    (M.Sc Statistics, Tehran North Branch, Islamic Azad University)

Abstract

In this study, it has been attempted to select the best continuous- time stochastic model, in order to describe and forecast the oil price of Russia, by information and statistics about oil price that has been available for oil price in the past. For this purpose, method of The Maximum Likelihood Estimation is implemented for estimation of the parameters of continuous-time stochastic processes. The result of unit root test with a structural break, reveals that time series of the crude oil price is a stationary series. The simulation of continuous-time stochastic processes and the mean square error between the simulated prices and the market ones shows that the Geometric Brownian Motion is the best model for the Russian crude oil price.

Suggested Citation

  • Hamidreza Mostafaei & Ali Akbar Rahimzadeh Sani & Samira Askari, 2013. "A Methodology for the Choice of the Best Fitting Continuous-Time Stochastic Models of Crude Oil Price: The Case of Russia," International Journal of Energy Economics and Policy, Econjournals, vol. 3(2), pages 137-142.
    • Handle: RePEc:eco:journ2:2013-02-3
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    References listed on IDEAS

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    1. Kaffel, Bilel & Abid, Fathi, 2009. "A methodology for the choice of the best fitting continuous-time stochastic models of crude oil price," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(3), pages 971-1000, August.
    2. Robert S. Pindyck, 1999. "The Long-Run Evolutions of Energy Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 1-27.
    3. Perron, Pierre, 1997. "Further evidence on breaking trend functions in macroeconomic variables," Journal of Econometrics, Elsevier, vol. 80(2), pages 355-385, October.
    4. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
    5. Postali, Fernando A.S. & Picchetti, Paulo, 2006. "Geometric Brownian Motion and structural breaks in oil prices: A quantitative analysis," Energy Economics, Elsevier, vol. 28(4), pages 506-522, July.
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    Cited by:

    1. Chen, Ruoran & Deng, Tianhu & Huang, Simin & Qin, Ruwen, 2015. "Optimal crude oil procurement under fluctuating price in an oil refinery," European Journal of Operational Research, Elsevier, vol. 245(2), pages 438-445.

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    More about this item

    Keywords

    Stochastic processes; Crude oil price; Unit root test; Structural break; MLE estimation; Simulation;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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