IDEAS home Printed from https://ideas.repec.org/a/eco/journ2/2018-03-11.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.econjournals.com/index.php/ijeep/article/download/6465/3680
    Download Restriction: no

    File URL: https://www.econjournals.com/index.php/ijeep/article/view/6465/3680
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. De Santis, Roberto A., 2003. "Crude oil price fluctuations and Saudi Arabia's behaviour," Energy Economics, Elsevier, vol. 25(2), pages 155-173, March.
    2. 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.
    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)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wirl, Franz, 2008. "Why do oil prices jump (or fall)?," Energy Policy, Elsevier, vol. 36(3), pages 1029-1043, March.
    2. Farzanegan, Mohammad Reza & Raeisian Parvari, Mozhgan, 2014. "Iranian-Oil-Free Zone and international oil prices," Energy Economics, Elsevier, vol. 45(C), pages 364-372.
    3. Llacay, Bàrbara & Peffer, Gilbert, 2017. "Impact of value-at-risk models on market stability," Journal of Economic Dynamics and Control, Elsevier, vol. 82(C), pages 223-256.
    4. Vincent Brémond & Emmanuel Hache & Tovonony Razafindrabe, 2016. "The Oil Price and Exchange Rate Relationship Revisited: A time-varying VAR parameter approach," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 13(1), pages 97-131, June.
    5. Papapostolou, Nikos C. & Pouliasis, Panos K. & Nomikos, Nikos K. & Kyriakou, Ioannis, 2016. "Shipping investor sentiment and international stock return predictability," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 96(C), pages 81-94.
    6. Ehrentreich, Norman, 2006. "Technical trading in the Santa Fe Institute Artificial Stock Market revisited," Journal of Economic Behavior & Organization, Elsevier, vol. 61(4), pages 599-616, December.
    7. Duc Huynh, Toan Luu & Burggraf, Tobias & Nasir, Muhammad Ali, 2020. "Financialisation of natural resources & instability caused by risk transfer in commodity markets," Resources Policy, Elsevier, vol. 66(C).
    8. Baumeister, Christiane & Kilian, Lutz & Lee, Thomas K., 2014. "Are there gains from pooling real-time oil price forecasts?," Energy Economics, Elsevier, vol. 46(S1), pages 33-43.
    9. Makarewicz, Tomasz, 2021. "Traders, forecasters and financial instability: A model of individual learning of anchor-and-adjustment heuristics," Journal of Economic Behavior & Organization, Elsevier, vol. 190(C), pages 626-673.
    10. Jacks, David S. & Stuermer, Martin, 2020. "What drives commodity price booms and busts?," Energy Economics, Elsevier, vol. 85(C).
    11. Wang, Yudong & Hao, Xianfeng, 2022. "Forecasting the real prices of crude oil: A robust weighted least squares approach," Energy Economics, Elsevier, vol. 116(C).
    12. Ferrari, Davide & Ravazzolo, Francesco & Vespignani, Joaquin, 2021. "Forecasting energy commodity prices: A large global dataset sparse approach," Energy Economics, Elsevier, vol. 98(C).
    13. Siddiqi, Hammad, 2007. "Rational Interacting Agents and Volatility Clustering: A New Approach," MPRA Paper 2984, University Library of Munich, Germany.
    14. Mann, Janelle & Sephton, Peter, 2016. "Global relationships across crude oil benchmarks," Journal of Commodity Markets, Elsevier, vol. 2(1), pages 1-5.
    15. Beckmann, Joscha & Czudaj, Robert L. & Arora, Vipin, 2020. "The relationship between oil prices and exchange rates: Revisiting theory and evidence," Energy Economics, Elsevier, vol. 88(C).
    16. Mileva, Elitza & Siegfried, Nikolaus, 2012. "Oil market structure, network effects and the choice of currency for oil invoicing," Energy Policy, Elsevier, vol. 44(C), pages 385-394.
    17. Fokin, Nikita, 2021. "The importance of modeling structural breaks in forecasting Russian GDP," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 63, pages 5-29.
    18. Joëts, Marc & Mignon, Valérie & Razafindrabe, Tovonony, 2017. "Does the volatility of commodity prices reflect macroeconomic uncertainty?," Energy Economics, Elsevier, vol. 68(C), pages 313-326.
    19. Bastianin, Andrea & Galeotti, Marzio & Manera, Matteo, 2014. "Forecasting the oil–gasoline price relationship: Do asymmetries help?," Energy Economics, Elsevier, vol. 46(S1), pages 44-56.
    20. Hommes, Cars & Huang, Hai & Wang, Duo, 2005. "A robust rational route to randomness in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 29(6), pages 1043-1072, June.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eco:journ2:2018-03-11. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ilhan Ozturk (email available below). General contact details of provider: http://www.econjournals.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.