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Understanding Dynamic Conditional Correlations between Oil, Natural Gas and Non-Energy Commodity Futures Markets

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  • Niaz Bashiri Behmiri, Matteo Manera, and Marcella Nicolini

Abstract

We look at the dynamic conditional correlations (DCCs) between oil, natural gas and other non-energy commodity futures markets, obtained from a DCC-GARCH model over the period 1998-2014. They are positive and display a sharp increase around year 2008 and a subsequent decrease. The DCCs between energy and metals are larger than the energy-agriculture ones. To understand how macroeconomic and financial factors, as well as speculative activity, influence them, we estimate an ARDL(1,1) model, adopting a pooled mean group (PMG) estimator. We observe that macroeconomic and financial variables are significantly correlated with the energy-agriculture and energy-metals DCCs. Speculative activity contributes to explain the

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  • Niaz Bashiri Behmiri, Matteo Manera, and Marcella Nicolini, 2019. "Understanding Dynamic Conditional Correlations between Oil, Natural Gas and Non-Energy Commodity Futures Markets," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
  • Handle: RePEc:aen:journl:ej40-2-manera
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    1. Philippe Charlot & Vêlayoudom Marimoutou, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Post-Print hal-01474252, HAL.
    2. Peter R. Hartley and Kenneth B. Medlock III, 2014. "The Relationship between Crude Oil and Natural Gas Prices: The Role of the Exchange Rate," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    3. Charlot, Philippe & Marimoutou, Vêlayoudom, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Energy Economics, Elsevier, vol. 44(C), pages 456-467.
    4. Levin, Andrew & Lin, Chien-Fu & James Chu, Chia-Shang, 2002. "Unit root tests in panel data: asymptotic and finite-sample properties," Journal of Econometrics, Elsevier, vol. 108(1), pages 1-24, May.
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