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Forecasting Crude Oil Price Using Artificial Neural Networks: A Literature Survey

Author

Listed:
  • Manel Hamdi

    () (International Finance Group Tunisia, El Manar University, Tunisia)

  • Chaker Aloui

    () (College of business Administration, King Saud University, Riyadh, Saudi Arabia)

Abstract

The literature on forecasting the « black gold » price is vast. This paper provides a literature review on the various techniques that have been used to forecast crude oil price. We mainly focused on the researches that have utilized artificial neural network models in their forecasting study. Therefore, a detailed description of this model will be presented in this paper.

Suggested Citation

  • Manel Hamdi & Chaker Aloui, 2015. "Forecasting Crude Oil Price Using Artificial Neural Networks: A Literature Survey," Economics Bulletin, AccessEcon, vol. 35(2), pages 1339-1359.
  • Handle: RePEc:ebl:ecbull:eb-14-00800
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    References listed on IDEAS

    as
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    Cited by:

    1. repec:eee:energy:v:148:y:2018:i:c:p:49-58 is not listed on IDEAS
    2. Gori, Fabio, 2016. "Mass and energy-capital conservation equations to forecast the oil price evolution with accumulation or depletion of the resources," Energy, Elsevier, vol. 116(P1), pages 746-760.
    3. repec:gam:jsusta:v:10:y:2018:i:8:p:2801-:d:162455 is not listed on IDEAS

    More about this item

    Keywords

    Crude oil price; Forecasting; Artificial neural networks;

    JEL classification:

    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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