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Prediction of Oil Price using ARMA Method for Years 2003 to 2011

  • Abdalali Monsef

    ()

    (Payame Noor University)

  • Amir Hortmani

    ()

    (Islamic Azad University)

  • Khadijeh Hamzeh

    ()

    (Payame Noor University)

Registered author(s):

    One main purpose of economic analysis is prediction of economic variables. For this reason, various methods have been developed in this context. One important challenge in prediction of time series is precise prediction without any computational complexities. It is usually assumed that autoregressive moving-average (ARMA) models have this ability with a high accuracy. In this study, ARMA method has been used to predict time series of oil price. To determine the order of this process Akaike and Schwartz’s Bayesian criteria have been used. The results show that the best answers are obtained by ARMA (1,0) model for static predictions and ARMA (3,2) model for dynamic predictions.

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    Article provided by Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences in its journal International Journal of Academic Research in Accounting, Finance and Management Sciences.

    Volume (Year): 3 (2013)
    Issue (Month): 1 (January)
    Pages: 271-279

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    Handle: RePEc:hur:ijaraf:v:3:y:2013:i:1:p:271-279
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    1. Buchanan, W. K. & Hodges, P. & Theis, J., 2001. "Which way the natural gas price: an attempt to predict the direction of natural gas spot price movements using trader positions," Energy Economics, Elsevier, vol. 23(3), pages 279-293, May.
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