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Commodities inventory effect

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  • CARPANTIER, Jean - François

    () (Université catholique de Louvain, CORE, B-1348 Louvain-la-Neuve, Belgium)

Abstract

Asymmetric GARCH models were developped for equity stocks to take into account the larger response of the conditional variance to negative price shocks. We show that these asymmetric GARCH models are also relevant for modelling commodity prices. Contrary to the equity case, positive shocks are the main contributors to the conditional variance of commodity prices. The theory of storage, by relating the state of the inventories of a commodity to its conditional variance, is a serious candidate to explain the phenomenon, as positive price shocks for commodities usually serve as proxies for the deterioration of the inventories. We find that this inverse leverage effect, or “inventory effect”, is relatively robust, for different subsamples, for diverse types of commodities and for different ways of specifying the asymmetry, though weaker than the leverage effect for equity stocks. Appropriately specifying the asymmetric conditional variance of commodities could improve risk management, hedging strategies or Value-at-Risk estimates. Incidentally, the inventory effect sheds some new light on the debate about the origin of the leverage effect.

Suggested Citation

  • CARPANTIER, Jean - François, 2010. "Commodities inventory effect," CORE Discussion Papers 2010040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  • Handle: RePEc:cor:louvco:2010040
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    Cited by:

    1. 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.
    2. BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," CORE Discussion Papers 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. 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.
    4. 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.
    5. 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.
    6. PIERRET, Diane, 2013. "The systemic risk of energy markets," CORE Discussion Papers 2013018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. 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.

    More about this item

    Keywords

    GARCH; asymmetries; leverage effect; inventory; commodities; Value-at-Risk;

    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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