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Modelling and forecasting Oman crude oil prices using Box-Jenkins techniques

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  • M.I. Ahmad

Abstract

The Box-Jenkins' Auto Regressive Integrated Moving Average (ARIMA) modelling approach has been applied for the time series analysis of monthly average prices of Oman crude oil taken over a period of 10 years. Several seasonal and non-seasonal ARIMA models were identified. These models were then estimated and compared for their adequacy using the significance of the parameter estimates, mean square errors and Modified Box-Pierce (Ljung-Box) Chi-Square statistic. Based on these criterion a multiplicative seasonal model of the form ARIMA (1,1,5)x(1,1,1) was recommended for short term forecasting.

Suggested Citation

  • M.I. Ahmad, 2012. "Modelling and forecasting Oman crude oil prices using Box-Jenkins techniques," International Journal of Trade and Global Markets, Inderscience Enterprises Ltd, vol. 5(1), pages 24-30.
    • Handle: RePEc:ids:ijtrgm:v:5:y:2012:i:1:p:24-30
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    References listed on IDEAS

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    1. Dées, Stéphane & Gasteuil, Audrey & Kaufmann, Robert K. & Mann, Michael, 2008. "Assessing the factors behind oil price changes," Working Paper Series 855, European Central Bank.
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    Cited by:

    1. Hasnain Iftikhar & Aimel Zafar & Josue E. Turpo-Chaparro & Paulo Canas Rodrigues & Javier Linkolk López-Gonzales, 2023. "Forecasting Day-Ahead Brent Crude Oil Prices Using Hybrid Combinations of Time Series Models," Mathematics, MDPI, vol. 11(16), pages 1-19, August.
    2. Asit Kumar Das & Debahuti Mishra & Kaberi Das & Pradeep Kumar Mallick & Sachin Kumar & Mikhail Zymbler & Hesham El-Sayed, 2022. "Prophesying the Short-Term Dynamics of the Crude Oil Future Price by Adopting the Survival of the Fittest Principle of Improved Grey Optimization and Extreme Learning Machine," Mathematics, MDPI, vol. 10(7), pages 1-33, March.

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