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Non-Gaussian Regime-Switching Model in Application to the Commodity Price Description

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Nonstationary Systems: Theory and Applications (WNSTA 2021)

Part of the book series: Applied Condition Monitoring ((ACM,volume 18))

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Abstract

Regime-switching models have been recently becoming increasingly important as they allow structural changes to be taken into account in modelling financial data. Application of such models to describe prices behaviour is especially valuable in commodities markets, where China’s industrialisation in the past three decades, created a huge demand for metals and energy, changing fundamentals of the market and affecting commodity prices. Moreover, in the financial time series very often we observe the non-Gaussian behaviour, which is manifested by large observations related to the market conditions. Considering the mentioned features of the financial data (especially commodity prices) in this paper we propose a stochastic model which takes under consideration the possible regime changes, the non-Gaussian character of the data and finally, the non-constant in time characteristics (like the mean function). We describe the main properties of the considered model and introduce a novel estimation procedure for the estimation of its parameters. Finally, we apply the proposed model to the real data describing the copper prices, one of the main risk factor for the KGHM mining company.

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Authors and Affiliations

  1. Faculty of Pure and Applied Mathematics, Hugo Steinhaus Center Wrocław University of Science and Technology, Wrocław, Poland

    Dawid Szarek & Agnieszka Wyłomańska

  2. KGHM Polska Miedz S.A., M. Sklodowskiej-Curie 48, 59-301, Lubin, Poland

    Łukasz Bielak

Authors
  1. Dawid Szarek
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  2. Łukasz Bielak
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  3. Agnieszka Wyłomańska
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Corresponding author

Correspondence to Dawid Szarek .

Editor information

Editors and Affiliations

  1. National School of Engineers of Sfax, Sfax, Tunisia

    Fakher Chaari

  2. College of Telecommunications and Computer Science, Cracow University of Technology, Cracow, Poland

    Jacek Leskow

  3. Institute of Mining Engineering, Wroclaw University of Technology, Wrocław, Poland

    Agnieszka Wylomanska

  4. Faculty of GeoEngineering, Mining and Geology, Wroclaw University of Technology, Wrocław, Poland

    Radoslaw Zimroz

  5. Centro Direzionale di Napoli, Napoli, Italy

    Antonio Napolitano

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Szarek, D., Bielak, Ł., Wyłomańska, A. (2022). Non-Gaussian Regime-Switching Model in Application to the Commodity Price Description. In: Chaari, F., Leskow, J., Wylomanska, A., Zimroz, R., Napolitano, A. (eds) Nonstationary Systems: Theory and Applications. WNSTA 2021. Applied Condition Monitoring, vol 18. Springer, Cham. https://doi.org/10.1007/978-3-030-82110-4_6

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  • DOI: https://doi.org/10.1007/978-3-030-82110-4_6

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