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Hybrid Stochastic-Grey Model to Forecast the Behavior of Metal Price in the Mining Industry

Author

Listed:
  • Zoran Gligorić

    (Faculty of Mining and Geology, University of Belgrade, Đušina 7, 11 000 Belgrade, Serbia)

  • Miloš Gligorić

    (Faculty of Mining and Geology, University of Belgrade, Đušina 7, 11 000 Belgrade, Serbia)

  • Dževdet Halilović

    (Faculty of Mining and Geology, University of Belgrade, Đušina 7, 11 000 Belgrade, Serbia)

  • Čedomir Beljić

    (Faculty of Mining and Geology, University of Belgrade, Đušina 7, 11 000 Belgrade, Serbia)

  • Katarina Urošević

    (Faculty of Mining and Geology, University of Belgrade, Đušina 7, 11 000 Belgrade, Serbia)

Abstract

Accurate metal price forecasting is the precondition for optimal and sustainable mine production planning. This paper combined two methods for time series analysis. The developed model represents the combination of the Grey System Theory and a Stochastic differential equation. More precisely, we added stochastic term to the first-order whitenization differential equation. Solution of this equation represents the time response function which is capable of creating artificial evolving paths of the metal price. The simulation process resulted in a distribution and adequate expected value at every single point. Further, model efficiency was increased by adding residuals modeled by the Singular Spectrum Analysis method. The model was tested on the monthly lead metal price series. Mean absolute percentage error is 4.37% and the model can be classified as a high-performance model.

Suggested Citation

  • Zoran Gligorić & Miloš Gligorić & Dževdet Halilović & Čedomir Beljić & Katarina Urošević, 2020. "Hybrid Stochastic-Grey Model to Forecast the Behavior of Metal Price in the Mining Industry," Sustainability, MDPI, vol. 12(16), pages 1-21, August.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:16:p:6533-:d:398268
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    References listed on IDEAS

    as
    1. Hassani, Hossein, 2007. "Singular Spectrum Analysis: Methodology and Comparison," MPRA Paper 4991, University Library of Munich, Germany.
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    Cited by:

    1. Han Khanh Nguyen, 2021. "Application of Mathematical Models to Assess the Impact of the COVID-19 Pandemic on Logistics Businesses and Recovery Solutions for Sustainable Development," Mathematics, MDPI, vol. 9(16), pages 1-21, August.
    2. Du, Pei & Guo, Ju’e & Sun, Shaolong & Wang, Shouyang & Wu, Jing, 2021. "Multi-step metal prices forecasting based on a data preprocessing method and an optimized extreme learning machine by marine predators algorithm," Resources Policy, Elsevier, vol. 74(C).

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