IDEAS home Printed from https://ideas.repec.org/a/sae/enejou/v40y2019i2p55-76.html
   My bibliography  Save this article

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

Author

Listed:
  • Niaz Bashiri Behmiri
  • Matteo Manera
  • 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 energy-agriculture DCCs but not those of the energy-metals.

Suggested Citation

  • Niaz Bashiri Behmiri & Matteo Manera & Marcella Nicolini, 2019. "Understanding Dynamic Conditional Correlations between Oil, Natural Gas and Non-Energy Commodity Futures Markets," The Energy Journal, , vol. 40(2), pages 55-76, March.
    • Handle: RePEc:sae:enejou:v:40:y:2019:i:2:p:55-76
    DOI: 10.5547/01956574.40.2.nbeh
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.5547/01956574.40.2.nbeh
    Download Restriction: no
    File URL: https://libkey.io/10.5547/01956574.40.2.nbeh?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    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. 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).
    4. Pu, Yingjian & Yang, Baochen, 2022. "The commodity futures' historical basis in trading strategy and portfolio investment," Energy Economics, Elsevier, vol. 105(C).
    5. Marco Tronzano, 2024. "What Drives Asset Returns Comovements? Some Empirical Evidence from US Dollar and Global Stock Returns (2000–2023)," JRFM, MDPI, vol. 17(4), pages 1-26, April.
    6. 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).
    7. 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.
    8. 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.
    9. U, Tony Sio-Chong & Lin, Yongjia & Wang, Yizhi, 2024. "The impact of the Russia–Ukraine war on volatility spillovers," International Review of Financial Analysis, Elsevier, vol. 93(C).
    10. Ma, Yan-Ran & Ji, Qiang & Wu, Fei & Pan, Jiaofeng, 2021. "Financialization, idiosyncratic information and commodity co-movements," Energy Economics, Elsevier, vol. 94(C).
    11. 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).
    12. Fiszeder, Piotr & Fałdziński, Marcin & Molnár, Peter, 2023. "Attention to oil prices and its impact on the oil, gold and stock markets and their covariance," Energy Economics, Elsevier, vol. 120(C).
    13. 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).
    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. Kocaarslan, Baris & Mushtaq, Rizwan, 2024. "The impact of liquidity conditions on the time-varying link between U.S. municipal green bonds and major risky markets during the COVID-19 crisis: A machine learning approach," Energy Policy, Elsevier, vol. 184(C).
    16. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Raza, Syed Ali & Masood, Amna & Benkraiem, Ramzi & Urom, Christian, 2023. "Forecasting the volatility of precious metals prices with global economic policy uncertainty in pre and during the COVID-19 period: Novel evidence from the GARCH-MIDAS approach," Energy Economics, Elsevier, vol. 120(C).
    2. 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.
    3. Davide, Marinella & Vesco, Paola, 2016. "Alternative Approaches for Rating INDCs: a Comparative Analysis," MITP: Mitigation, Innovation and Transformation Pathways 232716, Fondazione Eni Enrico Mattei (FEEM).
    4. Bao, Dun, 2020. "Dynamics and correlation of platinum-group metals spot prices," Resources Policy, Elsevier, vol. 68(C).
    5. Pu, Yingjian & Yang, Baochen, 2022. "The commodity futures' historical basis in trading strategy and portfolio investment," Energy Economics, Elsevier, vol. 105(C).
    6. Li, Wenlan & Cheng, Yuxiang & Fang, Qiang, 2020. "Forecast on silver futures linked with structural breaks and day-of-the-week effect," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    7. Kuruppuarachchi, Duminda & Premachandra, I.M., 2016. "Information spillover dynamics of the energy futures market sector: A novel common factor approach," Energy Economics, Elsevier, vol. 57(C), pages 277-294.
    8. Wang, Yang & Cao, Xinbang & Sui, Xiuping & Zhao, Wenxi, 2019. "How do black swan events go global? -Evidence from US reserves effects on TOCOM gold futures prices," Finance Research Letters, Elsevier, vol. 31(C).
    9. Yaqoob, Tanzeela & Maqsood, Arfa, 2024. "The potency of time series outliers in volatile models: An empirical analysis of fintech, and mineral resources," Resources Policy, Elsevier, vol. 89(C).
    10. 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.
    11. Das, Debojyoti & Kannadhasan, M., 2020. "The asymmetric oil price and policy uncertainty shock exposure of emerging market sectoral equity returns: A quantile regression approach," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 563-581.
    12. 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.
    13. Khalfaoui, Rabeh & Tiwari, Aviral Kumar & Kablan, Sandrine & Hammoudeh, Shawkat, 2021. "Interdependence and lead-lag relationships between the oil price and metal markets: Fresh insights from the wavelet and quantile coherency approaches," Energy Economics, Elsevier, vol. 101(C).
    14. Rehman, Mobeen Ur & Zeitun, Rami & Mardani, Abbas & Vo, Xuan Vinh & Eraslan, Veysel, 2022. "Asymmetric pass through of energy commodities to US sectoral returns," Resources Policy, Elsevier, vol. 76(C).
    15. Díaz, Juan D. & Hansen, Erwin & Cabrera, Gabriel, 2020. "A random walk through the trees: Forecasting copper prices using decision learning methods," Resources Policy, Elsevier, vol. 69(C).
    16. Khaled Mokni, 2018. "Empirical Analysis Of The Relationship Between Oil And Precious Metals Markets," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(01), pages 1-20, March.
    17. Rehman, Mobeen Ur & Shahzad, Syed Jawad Hussain & Uddin, Gazi Salah & Hedström, Axel, 2018. "Precious metal returns and oil shocks: A time varying connectedness approach," Resources Policy, Elsevier, vol. 58(C), pages 77-89.
    18. Shelly Singhal & Pratap Chandra Biswal, 2021. "Dynamic Commodity Portfolio Management: A Regime-switching VAR Model," Global Business Review, International Management Institute, vol. 22(2), pages 532-549, April.
    19. Zhang, Zitao & Qin, Yun, 2022. "Study on the nonlinear interactions among the international oil price, the RMB exchange rate and China's gold price," Resources Policy, Elsevier, vol. 77(C).
    20. Behmiri, Niaz Bashiri & Manera, Matteo & Nicolini, Marcella, 2016. "Understanding Dynamic Conditional Correlations between Commodities Futures Markets," ESP: Energy Scenarios and Policy 232223, Fondazione Eni Enrico Mattei (FEEM).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:enejou:v:40:y:2019:i:2:p:55-76. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.