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Commodities Inventory Effect

Author

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  • Jean-François Carpantier

    (CERGAM - Centre d'Études et de Recherche en Gestion d'Aix-Marseille - AMU - Aix Marseille Université - UTLN - Université de Toulon)

  • Arnaud Dufays

Abstract

Does commodity price volatility increase when inventories are low? We are the first ones to document this relationship. To that aim, we estimate asym- metric volatility models for a large set of commodities over 1994-2011. Since inventories are hard to measure, especially for high frequency data, we use positive return shocks as a new original proxy for inventories and find that asymmetric GARCH models reveal a significant inventory effect for many commodities. The results look robust. They hold if we allow the uncondi- tional variance to vary over time and if we relax the parametric form.

Suggested Citation

  • Jean-François Carpantier & Arnaud Dufays, 2013. "Commodities Inventory Effect," Working Papers hal-01821144, HAL.
  • Handle: RePEc:hal:wpaper:hal-01821144
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    Citations

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    Cited by:

    1. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The role of outliers and oil price shocks on volatility of metal prices," Resources Policy, Elsevier, vol. 46(P2), pages 139-150.
    2. Ahmadi, Maryam & Bashiri Behmiri, Niaz & Manera, Matteo, 2016. "How is volatility in commodity markets linked to oil price shocks?," Energy Economics, Elsevier, vol. 59(C), pages 11-23.
    3. Jean‐Francois Carpantier & Besik Samkharadze, 2013. "The Asymmetric Commodity Inventory Effect on the Optimal Hedge Ratio," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(9), pages 868-888, September.
    4. Pierret, D., 2013. "The systemic risk of energy markets," LIDAM Discussion Papers ISBA 2013061, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Sercan Demiralay & Selcuk Bayraci & H. Gaye Gencer, 2019. "Time-varying diversification benefits of commodity futures," Empirical Economics, Springer, vol. 56(6), pages 1823-1853, June.
    7. Paraschiv, Florentina & Mudry, Pierre-Antoine & Andries, Alin Marius, 2015. "Stress-testing for portfolios of commodity futures," Economic Modelling, Elsevier, vol. 50(C), pages 9-18.
    8. Svetlana Borovkova & Diego Mahakena, 2015. "News, volatility and jumps: the case of natural gas futures," Quantitative Finance, Taylor & Francis Journals, vol. 15(7), pages 1217-1242, July.

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    More about this item

    Keywords

    Asymmetries; Commodities; Inventory; Spline GARCH; VaR.;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • Q14 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Finance

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