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The Study of Different Factors Effects on the Oil Futures Price by Applying Agent-based Model

Author

Listed:
  • Mohammad sadegh Karimi

    (Department of Energy Engineering, Sharif University of Technology, Azadi St, Tehran, Iran,)

  • Abbas Maleki

    (Department of Energy Engineering, Sharif University of Technology, Iran.)

Abstract

An agent-based model is employed for simulating the price of oil futures. The model proceeds as follows: On each time step agents choose their rule for price expectation formation. Next, they bid and ask based on their price and trend expectations. The new price is formed using the market mechanism . Finally, the time steps forward and the process is repeated in the next day. The agents use 6 different rules to make price and trend expectations. Brent future prices in a 2-year-period (2010 to 2011) and in 2012 are used for model calibration and validation, respectively. It was shown that market participants weigh U.S. stocks data more than other factors, while OECD stock s data were not that important for the market. It was also inferred that the market does not weigh the technical aspects of the oil price as much as the fundamental aspects.

Suggested Citation

  • Mohammad sadegh Karimi & Abbas Maleki, 2018. "The Study of Different Factors Effects on the Oil Futures Price by Applying Agent-based Model," International Journal of Energy Economics and Policy, Econjournals, vol. 8(3), pages 76-81.
    • Handle: RePEc:eco:journ2:2018-03-11
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    References listed on IDEAS

    as
    1. Alquist, Ron & Kilian, Lutz & Vigfusson, Robert J., 2013. "Forecasting the Price of Oil," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 427-507, Elsevier.
    2. De Santis, Roberto A., 2003. "Crude oil price fluctuations and Saudi Arabia's behaviour," Energy Economics, Elsevier, vol. 25(2), pages 155-173, March.
    3. Blitzer, Charles & Meeraus, Alex & Stoutjesdijk, Ardy, 1975. "A dynamic model of OPEC trade and production," Journal of Development Economics, Elsevier, vol. 2(4), pages 319-335, December.
    4. Amano, Akihiro, 1987. "A small forecasting model of the world oil market," Journal of Policy Modeling, Elsevier, vol. 9(4), pages 615-635.
    5. W. Brian Arthur & Paul Tayler, "undated". "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Computing in Economics and Finance 1997 57, Society for Computational Economics.
    6. Richard Bookstaber, 2012. "Using Agent-Based Models for Analyzing Threats to Financial Stability," Working Papers 12-03, Office of Financial Research, US Department of the Treasury.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Agent-based model; oil price; technical/fundamental rule;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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