IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1808.04150.html
   My bibliography  Save this paper

A Predictive Model for Oil Market under Uncertainty: Data-Driven System Dynamics Approach

Author

Listed:
  • Sina Aghaei
  • Amirreza Safari Langroudi
  • Masoud Fekri

Abstract

In recent years, there have been a lot of sharp changes in the oil price. These rapid changes cause the traditional models to fail in predicting the price behavior. The main reason for the failure of the traditional models is that they consider the actual value of parameters instead of their expectational ones. In this paper, we propose a system dynamics model that incorporates expectational variables in determining the oil price. In our model, the oil price is determined by the expected demand and supply vs. their actual values. Our core model is based upon regression analysis on several historic time series and adjusted by adding many casual loops in the oil market. The proposed model in simulated in different scenarios that have happened in the past and our results comply with the trends of the oil price in each of the scenarios.

Suggested Citation

  • Sina Aghaei & Amirreza Safari Langroudi & Masoud Fekri, 2018. "A Predictive Model for Oil Market under Uncertainty: Data-Driven System Dynamics Approach," Papers 1808.04150, arXiv.org.
    • Handle: RePEc:arx:papers:1808.04150
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1808.04150
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Krichene, Noureddine, 2002. "World crude oil and natural gas: a demand and supply model," Energy Economics, Elsevier, vol. 24(6), pages 557-576, November.
    2. James D. Hamilton, 2009. "Causes and Consequences of the Oil Shock of 2007-08," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 40(1 (Spring), pages 215-283.
    3. Roe, Brian & Teisl, Mario F. & Levy, Alan & Russell, Matthew, 2001. "US consumers' willingness to pay for green electricity," Energy Policy, Elsevier, vol. 29(11), pages 917-925, September.
    4. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2010. "Market Efficiency of Oil Spot and Futures: A Stochastic Dominance Approach," CIRJE F-Series CIRJE-F-705, CIRJE, Faculty of Economics, University of Tokyo.
    5. Basher, Syed A. & Sadorsky, Perry, 2006. "Oil price risk and emerging stock markets," Global Finance Journal, Elsevier, vol. 17(2), pages 224-251, December.
    6. Lean, Hooi Hooi & McAleer, Michael & Wong, Wing-Keung, 2010. "Market efficiency of oil spot and futures: A mean-variance and stochastic dominance approach," Energy Economics, Elsevier, vol. 32(5), pages 979-986, September.
    7. Hallock, John L. & Tharakan, Pradeep J. & Hall, Charles A.S. & Jefferson, Michael & Wu, Wei, 2004. "Forecasting the limits to the availability and diversity of global conventional oil supply," Energy, Elsevier, vol. 29(11), pages 1673-1696.
    8. Lutz Kilian & Daniel P. Murphy, 2012. "Why Agnostic Sign Restrictions Are Not Enough: Understanding The Dynamics Of Oil Market Var Models," Journal of the European Economic Association, European Economic Association, vol. 10(5), pages 1166-1188, October.
    9. Gately, Dermot, 1984. "A Ten-Year Retrospective: OPEC and the World Oil Market," Journal of Economic Literature, American Economic Association, vol. 22(3), pages 1100-1114, September.
    10. Lutz Kilian, 2009. "Not All Oil Price Shocks Are Alike: Disentangling Demand and Supply Shocks in the Crude Oil Market," American Economic Review, American Economic Association, vol. 99(3), pages 1053-1069, June.
    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. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    2. Christiane Baumeister & Gert Peersman, 2013. "Time-Varying Effects of Oil Supply Shocks on the US Economy," American Economic Journal: Macroeconomics, American Economic Association, vol. 5(4), pages 1-28, October.
    3. Güntner, Jochen H.F., 2014. "How do oil producers respond to oil demand shocks?," Energy Economics, Elsevier, vol. 44(C), pages 1-13.
    4. Miroslava Zavadska & Lucía Morales & Joseph Coughlan, 2018. "The Lead–Lag Relationship between Oil Futures and Spot Prices—A Literature Review," IJFS, MDPI, vol. 6(4), pages 1-22, October.
    5. Ortiz-Cruz, Alejandro & Rodriguez, Eduardo & Ibarra-Valdez, Carlos & Alvarez-Ramirez, Jose, 2012. "Efficiency of crude oil markets: Evidences from informational entropy analysis," Energy Policy, Elsevier, vol. 41(C), pages 365-373.
    6. Basher, Syed Abul & Haug, Alfred A. & Sadorsky, Perry, 2012. "Oil prices, exchange rates and emerging stock markets," Energy Economics, Elsevier, vol. 34(1), pages 227-240.
    7. 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.
    8. Jean-Pierre Allegret & Cécile Couharde & Valérie Mignon & Tovonony Razafindrabe, 2017. "Oil currencies in the face of oil shocks: what can be learned from time-varying specifications?," Applied Economics, Taylor & Francis Journals, vol. 49(18), pages 1774-1793, April.
    9. Radosław Puka & Bartosz Łamasz & Marek Michalski, 2021. "Effectiveness of Artificial Neural Networks in Hedging against WTI Crude Oil Price Risk," Energies, MDPI, vol. 14(11), pages 1-26, June.
    10. Caldara, Dario & Cavallo, Michele & Iacoviello, Matteo, 2019. "Oil price elasticities and oil price fluctuations," Journal of Monetary Economics, Elsevier, vol. 103(C), pages 1-20.
    11. Selien De Schryder & Gert Peersman, 2016. "The U.S. Dollar Exchange Rate and the Demand for Oil," The Energy Journal, , vol. 37(1), pages 90-114, January.
    12. Kilian, Lutz & Lee, Thomas K., 2014. "Quantifying the speculative component in the real price of oil: The role of global oil inventories," Journal of International Money and Finance, Elsevier, vol. 42(C), pages 71-87.
    13. Degiannakis, Stavros & Filis, George, 2018. "Forecasting oil prices: High-frequency financial data are indeed useful," Energy Economics, Elsevier, vol. 76(C), pages 388-402.
    14. Knut Are Aastveit & Hilde C. Bjørnland & Jamie L. Cross, 2023. "Inflation Expectations and the Pass-Through of Oil Prices," The Review of Economics and Statistics, MIT Press, vol. 105(3), pages 733-743, May.
    15. Kilian, Lutz, 2022. "Understanding the estimation of oil demand and oil supply elasticities," Energy Economics, Elsevier, vol. 107(C).
    16. Huiming Zhu & Xianfang Su & Wanhai You & Yinghua Ren, 2017. "Asymmetric effects of oil price shocks on stock returns: evidence from a two-stage Markov regime-switching approach," Applied Economics, Taylor & Francis Journals, vol. 49(25), pages 2491-2507, May.
    17. Gong, Xu & Chen, Liqiang & Lin, Boqiang, 2020. "Analyzing dynamic impacts of different oil shocks on oil price," Energy, Elsevier, vol. 198(C).
    18. Baumeister, Christiane & Hamilton, James, 2017. "Structural Interpretation of Vector Autoregressions with Incomplete Identification: Revisiting the Role of Oil Supply and Deman," CEPR Discussion Papers 12532, C.E.P.R. Discussion Papers.
    19. Cross, Jamie & Nguyen, Bao H., 2017. "The relationship between global oil price shocks and China's output: A time-varying analysis," Energy Economics, Elsevier, vol. 62(C), pages 79-91.
    20. Raghavan, Mala, 2020. "An analysis of the global oil market using SVARMA models," Energy Economics, Elsevier, vol. 86(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:arx:papers:1808.04150. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.