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Modeling Commodity Price Dynamics

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  • David Lee

    (FinPricing)

Abstract

The random component of commodity future prices can be generally broken down into major contributors or factors. These are known as principal components. In this paper, we present a multifactor framework for modeling commodity price dynamics. We develop a generic procedure for the model calibration. The calibration procedure consists of an offline step and an online step. Empirical and numeric study shows that the model prices fluctuate randomly around the market prices, indicating prima facie that the model performs quite well.

Suggested Citation

  • David Lee, 2022. "Modeling Commodity Price Dynamics," Working Papers hal-03758093, HAL.
    • Handle: RePEc:hal:wpaper:hal-03758093
    Note: View the original document on HAL open archive server: https://hal.science/hal-03758093
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    References listed on IDEAS

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    1. Eduardo Schwartz & James E. Smith, 2000. "Short-Term Variations and Long-Term Dynamics in Commodity Prices," Management Science, INFORMS, vol. 46(7), pages 893-911, July.
    2. Fred Espen Benth & Jūratė Šaltytė-Benth, 2004. "The Normal Inverse Gaussian Distribution And Spot Price Modelling In Energy Markets," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 7(02), pages 177-192.
    3. Schwartz, Eduardo S, 1997. "The Stochastic Behavior of Commodity Prices: Implications for Valuation and Hedging," Journal of Finance, American Finance Association, vol. 52(3), pages 923-973, July.
    4. Ladokhin, Sergiy & Borovkova, Svetlana, 2021. "Three-factor commodity forward curve model and its joint P and Q dynamics," Energy Economics, Elsevier, vol. 101(C).
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