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A multi-model approach for describing crude oil price dynamics

Author

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  • Bernabe, Araceli
  • Martina, Esteban
  • Alvarez-Ramirez, Jose
  • Ibarra-Valdez, Carlos

Abstract

This paper develops a stochastic multi-model approach to describe the dynamics of crude oil prices. Based on the hypothesis that crude oil price dynamics reflects the activity of a competitive market with multiple equilibria, a mean-reversion multi-model incorporating two competitive processes with corresponding drifts and volatilities is investigated. Regimen-switching between the two standard stochastic processes is modeled as a simple process that describes extreme (e.g., social, political, etc.) events occurring scarcely but influencing on the market evolution.

Suggested Citation

  • Bernabe, Araceli & Martina, Esteban & Alvarez-Ramirez, Jose & Ibarra-Valdez, Carlos, 2004. "A multi-model approach for describing crude oil price dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(3), pages 567-584.
    • Handle: RePEc:eee:phsmap:v:338:y:2004:i:3:p:567-584
    DOI: 10.1016/j.physa.2004.03.007
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    Cited by:

    1. Alvarez-Ramirez, Jose & Rodriguez, Eduardo & Echeverria, Juan Carlos & Puebla, Hector, 2008. "Correlation analysis of chaotic trajectories from Chua’s system," Chaos, Solitons & Fractals, Elsevier, vol. 36(5), pages 1157-1169.
    2. García-Carranco, Sergio M. & Bory-Reyes, Juan & Balankin, Alexander S., 2016. "The crude oil price bubbling and universal scaling dynamics of price volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 60-68.
    3. Krzysztof Drachal, 2018. "Determining Time-Varying Drivers of Spot Oil Price in a Dynamic Model Averaging Framework," Energies, MDPI, vol. 11(5), pages 1-24, May.
    4. Mari, Carlo, 2006. "Regime-switching characterization of electricity prices dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 552-564.
    5. Jammazi, Rania & Aloui, Chaker, 2012. "Crude oil price forecasting: Experimental evidence from wavelet decomposition and neural network modeling," Energy Economics, Elsevier, vol. 34(3), pages 828-841.
    6. 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.
    7. Alvarez-Ramirez, Jose & Ibarra-Valdez, Carlos & Bernabe, Araceli & Rodriguez, Eduardo, 2005. "Power-law periodicity in the 2003–2004 crude oil price dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 349(3), pages 625-640.
    8. Lu-Tao Zhao & Guan-Rong Zeng & Ling-Yun He & Ya Meng, 2020. "Forecasting Short-Term Oil Price with a Generalised Pattern Matching Model Based on Empirical Genetic Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 55(4), pages 1151-1169, April.
    9. He, Ling-Yun & Chen, Shu-Peng, 2010. "Are crude oil markets multifractal? Evidence from MF-DFA and MF-SSA perspectives," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(16), pages 3218-3229.
    10. Drachal, Krzysztof, 2016. "Forecasting spot oil price in a dynamic model averaging framework — Have the determinants changed over time?," Energy Economics, Elsevier, vol. 60(C), pages 35-46.
    11. Ivan Damnjanovic & Xue Zhou, 2009. "Impact of crude oil market behaviour on unit bid prices: the evidence from the highway construction sector," Construction Management and Economics, Taylor & Francis Journals, vol. 27(9), pages 881-890.
    12. Toto Gunarto & Rialdi Azhar & Novita Tresiana & Supriyanto Supriyanto & Ayi Ahadiat, 2020. "Accurate Estimated Model of Volatility Crude Oil Price," International Journal of Energy Economics and Policy, Econjournals, vol. 10(5), pages 228-233.
    13. Fan, Ying & Liang, Qiang & Wei, Yi-Ming, 2008. "A generalized pattern matching approach for multi-step prediction of crude oil price," Energy Economics, Elsevier, vol. 30(3), pages 889-904, May.
    14. E, Jianwei & Bao, Yanling & Ye, Jimin, 2017. "Crude oil price analysis and forecasting based on variational mode decomposition and independent component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 484(C), pages 412-427.
    15. Mohsin, Muhammad & Jamaani, Fouad, 2023. "Green finance and the socio-politico-economic factors’ impact on the future oil prices: Evidence from machine learning," Resources Policy, Elsevier, vol. 85(PA).
    16. van Ruijven, Bas & van Vuuren, Detlef P., 2009. "Oil and natural gas prices and greenhouse gas emission mitigation," Energy Policy, Elsevier, vol. 37(11), pages 4797-4808, November.
    17. Guliyev, Hasraddin & Mustafayev, Eldayag, 2022. "Predicting the changes in the WTI crude oil price dynamics using machine learning models," Resources Policy, Elsevier, vol. 77(C).

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