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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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    2. Scarcioffolo, Alexandre R. & Etienne, Xiaoli L., 2021. "Regime-switching energy price volatility: The role of economic policy uncertainty," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 336-356.
    3. Marco Tronzano, 2020. "Safe-Haven Assets, Financial Crises, and Macroeconomic Variables: Evidence from the Last Two Decades (2000–2018)," JRFM, MDPI, vol. 13(3), pages 1-21, February.
    4. Chen, Xiangyu & Tongurai, Jittima, 2022. "Spillovers and interdependency across base metals: Evidence from China's futures and spot markets," Resources Policy, Elsevier, vol. 75(C).
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    8. Yip, Pick Schen & Brooks, Robert & Do, Hung Xuan & Nguyen, Duc Khuong, 2020. "Dynamic volatility spillover effects between oil and agricultural products," International Review of Financial Analysis, Elsevier, vol. 69(C).
    9. Karanasos, M. & Yfanti, S., 2021. "On the Economic fundamentals behind the Dynamic Equicorrelations among Asset classes: Global evidence from Equities, Real estate, and Commodities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
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    11. Halser, Christoph & Paraschiv, Florentina & Russo, Marianna, 2023. "Oil–gas price relationships on three continents: Disruptions and equilibria," Journal of Commodity Markets, Elsevier, vol. 31(C).
    12. Gong, Xu & Liu, Yun & Wang, Xiong, 2021. "Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method," International Review of Financial Analysis, Elsevier, vol. 76(C).
    13. Zhu, Huiming & Meng, Liang & Ge, Yajing & Hau, Liya, 2020. "Dependent relationships between Chinese commodity markets and the international financial market: Evidence from quantile time-frequency analysis," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    14. Algirdas Justinas Staugaitis & Bernardas Vaznonis, 2022. "Short-Term Speculation Effects on Agricultural Commodity Returns and Volatility in the European Market Prior to and during the Pandemic," Agriculture, MDPI, vol. 12(5), pages 1-26, April.
    15. Ruiwen Yang & Pathairat Pastpipatkul & Chaiwat Nimanussornkul, 2020. "Dynamic Volatility Spillover Among Chinese Black Series Futures Under Structural Breaks," International Journal of Business and Administrative Studies, Professor Dr. Bahaudin G. Mujtaba, vol. 6(5), pages 236-246.
    16. Pu, Yingjian & Yang, Baochen, 2022. "The commodity futures' historical basis in trading strategy and portfolio investment," Energy Economics, Elsevier, vol. 105(C).

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