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A Cointegrated Regime-Switching Model Approach with Jumps Applied to Natural Gas Futures Prices

Author

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  • Daniel Leonhardt

    (Chair of Financial Mathematics, Technical University Munich, 80333 München, Germany
    These authors contributed equally to this work.)

  • Antony Ware

    (Department of Mathematics and Statistics, University of Calgary, Calgary, AB T2N 1N4, Canada
    These authors contributed equally to this work.)

  • Rudi Zagst

    (Chair of Financial Mathematics, Technical University Munich, 80333 München, Germany
    These authors contributed equally to this work.)

Abstract

Energy commodities and their futures naturally show cointegrated price movements. However, there is empirical evidence that the prices of futures with different maturities might have, e.g., different jump behaviours in different market situations. Observing commodity futures over time, there is also evidence for different states of the underlying volatility of the futures. In this paper, we therefore allow for cointegration of the term structure within a multi-factor model, which includes seasonality, as well as joint and individual jumps in the price processes of futures with different maturities. The seasonality in this model is realized via a deterministic function, and the jumps are represented with thinned-out compound Poisson processes. The model also includes a regime-switching approach that is modelled through a Markov chain and extends the class of geometric models. We show how the model can be calibrated to empirical data and give some practical applications.

Suggested Citation

  • Daniel Leonhardt & Antony Ware & Rudi Zagst, 2017. "A Cointegrated Regime-Switching Model Approach with Jumps Applied to Natural Gas Futures Prices," Risks, MDPI, vol. 5(3), pages 1-19, September.
    • Handle: RePEc:gam:jrisks:v:5:y:2017:i:3:p:48-:d:111674
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    References listed on IDEAS

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    Cited by:

    1. Oleksandr Castello & Marina Resta, 2023. "A Machine-Learning-Based Approach for Natural Gas Futures Curve Modeling," Energies, MDPI, vol. 16(12), pages 1-22, June.

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