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A dynamic model of hedging and speculation in the commodity futures markets

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  • Cifarelli, Giulio
  • Paladino, Giovanna

Abstract

Over the 1990–2010 time period, a dynamic interaction between spot and futures returns in five commodity markets (copper, cotton, oil, silver, and soybeans) is empirically validated. An error correction relationship for the cash returns and a non-linear parameterization of the corresponding futures returns are combined with a bivariate CCC-GARCH representation of the conditional variances. Hedgers and speculators are contemporaneously at work in the futures markets, the role of the latter being far from negligible. In order to capture the consequences of the growing turbulence of these markets, a two-state regime-switching model for futures returns is developed. In this way financial traders׳ time-varying risk appetites are allowed to interact with hedgers׳ demand in determining both future and spot prices.

Suggested Citation

  • Cifarelli, Giulio & Paladino, Giovanna, 2015. "A dynamic model of hedging and speculation in the commodity futures markets," Journal of Financial Markets, Elsevier, vol. 25(C), pages 1-15.
    • Handle: RePEc:eee:finmar:v:25:y:2015:i:c:p:1-15
    DOI: 10.1016/j.finmar.2015.07.002
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    3. Juan Ignacio Guzmán & Enrique Silva, 2018. "Copper price determination: fundamentals versus non-fundamentals," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 31(3), pages 283-300, October.
    4. Wu, Lei & Zeng, Hongchao, 2019. "The impact of liquidity constraints on the cash-futures basis dynamics: Evidence from the Chinese market," Economic Modelling, Elsevier, vol. 83(C), pages 96-110.
    5. Elina Pradkhan, 2016. "Information Content of Trading Activity in Precious Metals Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 36(5), pages 421-456, May.
    6. Billio, Monica & Casarin, Roberto & Osuntuyi, Anthony, 2018. "Markov switching GARCH models for Bayesian hedging on energy futures markets," Energy Economics, Elsevier, vol. 70(C), pages 545-562.
    7. Vigne, Samuel A. & Lucey, Brian M. & O’Connor, Fergal A. & Yarovaya, Larisa, 2017. "The financial economics of white precious metals — A survey," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 292-308.
    8. Vedenov, Dmitry & Power, Gabriel J., 2022. "We don't need no fancy hedges! Or do we?," International Review of Financial Analysis, Elsevier, vol. 81(C).
    9. K. Abhaya Kumar & Prakash Pinto & Iqbal Thonse Hawaldar & K. G. Ramesh, 2021. "Can Crude Oil Futures be the Good Hedging Tool for Tyre Equities? Evidence from India," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 523-537.
    10. Lee, Hsiang-Tai & Lee, Chien-Chiang, 2022. "A regime-switching real-time copula GARCH model for optimal futures hedging," International Review of Financial Analysis, Elsevier, vol. 84(C).
    11. Čech, František & Zítek, Michal, 2022. "Marine fuel hedging under the sulfur cap regulations," Energy Economics, Elsevier, vol. 113(C).
    12. Donald Lien & Hsiang‐Tai Lee & Her‐Jiun Sheu, 2018. "Hedging systematic risk in the commodity market with a regime‐switching multivariate rotated generalized autoregressive conditional heteroskedasticity model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(12), pages 1514-1532, December.
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    14. Hsiang‐Tai Lee, 2022. "A Markov regime‐switching Cholesky GARCH model for directly estimating the dynamic of optimal hedge ratio," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(3), pages 389-412, March.

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    More about this item

    Keywords

    Commodity spot and futures markets; Dynamic hedging; Speculation; Non-linear GARCH; Markov regime switching;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting

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