IDEAS home Printed from https://ideas.repec.org/p/pre/wpaper/202180.html
   My bibliography  Save this paper

Realized Volatility Spillovers between Energy and Metal Markets: A Time-Varying Connectedness Approach

Author

Listed:
  • Juncal Cunado

    (Department of Economics, University of Navarra, Pamplona, Spain)

  • David Gabauer

    (Data Analysis Systems, Software Competence Center Hagenberg, Hagenberg, Austria)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)

Abstract

This paper analyzes the degree of dynamic connectedness between energy and metal commodity prices in the pre and post COVID-19 era, using the TVP-VAR based connectedness approach of Antonakakis et al. (2020). The results suggest that market interconnectedness slightly increased following the outbreak of COVID-19, although this increase was lower and less persistent than that observed after the Global Financial Crisis of 2008. Furthermore, we find that crude oil was the main transmitter of shocks during the period prior to COVID-19 while heating oil, gold and silver became the main transmitters of shocks during the COVID-19 pandemic. On the contrary, natural gas and palladium have been the main receivers of shocks during the whole sample period, making these two commodities attractive hedging and safe-haven options for investors during the pandemic crisis. The implications of our findings for portfolio diversification and energy transition policies are discussed.

Suggested Citation

  • Juncal Cunado & David Gabauer & Rangan Gupta, 2021. "Realized Volatility Spillovers between Energy and Metal Markets: A Time-Varying Connectedness Approach," Working Papers 202180, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:202180
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Chatziantoniou, Ioannis & Gabauer, David, 2021. "EMU risk-synchronisation and financial fragility through the prism of dynamic connectedness," The Quarterly Review of Economics and Finance, Elsevier, vol. 79(C), pages 1-14.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Tan, Xueping & Geng, Yong & Vivian, Andrew & Wang, Xinyu, 2021. "Measuring risk spillovers between oil and clean energy stocks: Evidence from a systematic framework," Resources Policy, Elsevier, vol. 74(C).
    4. 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.
    5. Gabauer, David, 2021. "Dynamic measures of asymmetric & pairwise connectedness within an optimal currency area: Evidence from the ERM I system," Journal of Multinational Financial Management, Elsevier, vol. 60(C).
    6. Zhang, Dayong & Broadstock, David C., 2020. "Global financial crisis and rising connectedness in the international commodity markets," International Review of Financial Analysis, Elsevier, vol. 68(C).
    7. Xiu, Dacheng, 2010. "Quasi-maximum likelihood estimation of volatility with high frequency data," Journal of Econometrics, Elsevier, vol. 159(1), pages 235-250, November.
    8. Umar, Zaghum & Gubareva, Mariya & Teplova, Tamara, 2021. "The impact of Covid-19 on commodity markets volatility: Analyzing time-frequency relations between commodity prices and coronavirus panic levels," Resources Policy, Elsevier, vol. 73(C).
    9. Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Commodity Connectedness," Central Banking, Analysis, and Economic Policies Book Series, in: Enrique G. Mendoza & Ernesto Pastén & Diego Saravia (ed.),Monetary Policy and Global Spillovers: Mechanisms, Effects and Policy Measures, edition 1, volume 25, chapter 4, pages 097-136, Central Bank of Chile.
    10. Shehzad, Khurram & Xiaoxing, Liu & Kazouz, Hayfa, 2020. "COVID-19’s disasters are perilous than Global Financial Crisis: A rumor or fact?," Finance Research Letters, Elsevier, vol. 36(C).
    11. Umar, Zaghum & Nasreen, Samia & Solarin, Sakiru Adebola & Tiwari, Aviral Kumar, 2019. "Exploring the time and frequency domain connectedness of oil prices and metal prices," Resources Policy, Elsevier, vol. 64(C).
    12. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    13. Francis X. Diebold & Kamil Yilmaz, 2009. "Measuring Financial Asset Return and Volatility Spillovers, with Application to Global Equity Markets," Economic Journal, Royal Economic Society, vol. 119(534), pages 158-171, January.
    14. Rehman, Mobeen Ur & Vo, Xuan Vinh, 2021. "Energy commodities, precious metals and industrial metal markets: A nexus across different investment horizons and market conditions," Resources Policy, Elsevier, vol. 70(C).
    15. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    16. Efraim Benmelech & Nitzan Tzur-Ilan, 2020. "The Determinants of Fiscal and Monetary Policies During the Covid-19 Crisis," NBER Working Papers 27461, National Bureau of Economic Research, Inc.
    17. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    18. Hammoudeh, Shawkat & Mokni, Khaled & Ben-Salha, Ousama & Ajmi, Ahdi Noomen, 2021. "Distributional predictability between oil prices and renewable energy stocks: Is there a role for the COVID-19 pandemic?," Energy Economics, Elsevier, vol. 103(C).
    19. Zhang, Yue-Jun & Wei, Yi-Ming, 2010. "The crude oil market and the gold market: Evidence for cointegration, causality and price discovery," Resources Policy, Elsevier, vol. 35(3), pages 168-177, September.
    20. Luo, Jiawen & Ji, Qiang, 2018. "High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets," Energy Economics, Elsevier, vol. 76(C), pages 424-438.
    21. Sari, Ramazan & Hammoudeh, Shawkat & Soytas, Ugur, 2010. "Dynamics of oil price, precious metal prices, and exchange rate," Energy Economics, Elsevier, vol. 32(2), pages 351-362, March.
    22. Salisu, Afees A. & Vo, Xuan Vinh & Lawal, Adedoyin, 2021. "Hedging oil price risk with gold during COVID-19 pandemic," Resources Policy, Elsevier, vol. 70(C).
    23. Lin, Boqiang & Su, Tong, 2021. "Does COVID-19 open a Pandora's box of changing the connectedness in energy commodities?," Research in International Business and Finance, Elsevier, vol. 56(C).
    24. Hung, Ngo Thai, 2021. "Oil prices and agricultural commodity markets: Evidence from pre and during COVID-19 outbreak," Resources Policy, Elsevier, vol. 73(C).
    25. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    26. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    27. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    28. Farid, Saqib & Kayani, Ghulam Mujtaba & Naeem, Muhammad Abubakr & Shahzad, Syed Jawad Hussain, 2021. "Intraday volatility transmission among precious metals, energy and stocks during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 72(C).
    29. Wheeler,Collette Mari & Baffes,John & Kabundi,Alain Ntumba & Kindberg-Hanlon,Gene & Nagle,Peter Stephen Oliver & Ohnsorge,Franziska Lieselotte, 2020. "Adding Fuel to the Fire : Cheap Oil during the COVID-19 Pandemic," Policy Research Working Paper Series 9320, The World Bank.
    30. Kang, Sang Hoon & McIver, Ron & Yoon, Seong-Min, 2017. "Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets," Energy Economics, Elsevier, vol. 62(C), pages 19-32.
    31. Lahiani, Amine & Mefteh-Wali, Salma & Vasbieva, Dinara G., 2021. "The safe-haven property of precious metal commodities in the COVID-19 era," Resources Policy, Elsevier, vol. 74(C).
    32. Wei, Xiaoyun & Han, Liyan, 2021. "The impact of COVID-19 pandemic on transmission of monetary policy to financial markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
    33. Chen, Hsuan-Chi & Yeh, Chia-Wei, 2021. "Global financial crisis and COVID-19: Industrial reactions," Finance Research Letters, Elsevier, vol. 42(C).
    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. Sisa Shiba & Juncal Cunado & Rangan Gupta, 2022. "Predictability of the Realised Volatility of International Stock Markets Amid Uncertainty Related to Infectious Diseases," JRFM, MDPI, vol. 15(1), pages 1-18, January.
    2. Ali, Shoaib & Ijaz, Muhammad Shahzad & Yousaf, Imran, 2023. "Dynamic spillovers and portfolio risk management between defi and metals: Empirical evidence from the Covid-19," Resources Policy, Elsevier, vol. 83(C).
    3. Younis, Ijaz & Du, Anna Min & Gupta, Himani & Shah, Waheed Ullah, 2024. "Dynamic spillover effects and interconnectedness of DeFi assets, commodities, and Islamic stock markets during crises," International Review of Financial Analysis, Elsevier, vol. 96(PA).
    4. Ghosh, Bikramaditya & Pham, Linh & Teplova, Tamara & Umar, Zaghum, 2023. "COVID-19 and the quantile connectedness between energy and metal markets," Energy Economics, Elsevier, vol. 117(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. Chen, Ruoyu & Iqbal, Najaf & Irfan, Muhammad & Shahzad, Farrukh & Fareed, Zeeshan, 2022. "Does financial stress wreak havoc on banking, insurance, oil, and gold markets? New empirics from the extended joint connectedness of TVP-VAR model," Resources Policy, Elsevier, vol. 77(C).
    2. Juncal Cunado & David Gabauer & Rangan Gupta & Chien-Chiang Lee, 2025. "On the propagation mechanism of international real interest rate spillovers: evidence from more than 200 years of data," Applied Economics, Taylor & Francis Journals, vol. 57(7), pages 790-804, February.
    3. Balcilar, Mehmet & Gabauer, David & Umar, Zaghum, 2021. "Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach," Resources Policy, Elsevier, vol. 73(C).
    4. Zhou, Xiaoran & Enilov, Martin & Parhi, Mamata, 2024. "Does oil spin the commodity wheel? Quantile connectedness with a common factor error structure across energy and agricultural markets," Energy Economics, Elsevier, vol. 132(C).
    5. Farid, Saqib & Naeem, Muhammad Abubakr & Paltrinieri, Andrea & Nepal, Rabindra, 2022. "Impact of COVID-19 on the quantile connectedness between energy, metals and agriculture commodities," Energy Economics, Elsevier, vol. 109(C).
    6. Chatziantoniou, Ioannis & Elsayed, Ahmed H. & Gabauer, David & Gozgor, Giray, 2023. "Oil price shocks and exchange rate dynamics: Evidence from decomposed and partial connectedness measures for oil importing and exporting economies," Energy Economics, Elsevier, vol. 120(C).
    7. Umar, Zaghum & Jareño, Francisco & Escribano, Ana, 2021. "Oil price shocks and the return and volatility spillover between industrial and precious metals," Energy Economics, Elsevier, vol. 99(C).
    8. Cunado, Juncal & Chatziantoniou, Ioannis & Gabauer, David & de Gracia, Fernando Perez & Hardik, Marfatia, 2023. "Dynamic spillovers across precious metals and oil realized volatilities: Evidence from quantile extended joint connectedness measures," Journal of Commodity Markets, Elsevier, vol. 30(C).
    9. Stenfors, Alexis & Chatziantoniou, Ioannis & Gabauer, David, 2022. "Independent policy, dependent outcomes: A game of cross-country dominoes across European yield curves," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    10. Cui, Jinxin & Maghyereh, Aktham, 2023. "Higher-order moment risk connectedness and optimal investment strategies between international oil and commodity futures markets: Insights from the COVID-19 pandemic and Russia-Ukraine conflict," International Review of Financial Analysis, Elsevier, vol. 86(C).
    11. Chen, Huayi & Shi, Huai-Long & Zhou, Wei-Xing, 2024. "Carbon volatility connectedness and the role of external uncertainties: Evidence from China," Journal of Commodity Markets, Elsevier, vol. 33(C).
    12. Naeem, Muhammad Abubakr & Chatziantoniou, Ioannis & Gabauer, David & Karim, Sitara, 2024. "Measuring the G20 stock market return transmission mechanism: Evidence from the R2 connectedness approach," International Review of Financial Analysis, Elsevier, vol. 91(C).
    13. Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Gabauer, David & Dwumfour, Richard Adjei, 2022. "Dynamic spillover effects among green bond, renewable energy stocks and carbon markets during COVID-19 pandemic: Implications for hedging and investments strategies," Global Finance Journal, Elsevier, vol. 51(C).
    14. Antonakakis, Nikolaos & Cunado, Juncal & Filis, George & Gabauer, David & de Gracia, Fernando Perez, 2023. "Dynamic connectedness among the implied volatilities of oil prices and financial assets: New evidence of the COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 114-123.
    15. Nasreen, Samia & Tiwari, Aviral Kumar & Goodell, John W. & Tedeschi, Marco, 2024. "Asymmetric and frequency-domain spillover effects among industrial metals, precious metals, and energy futures markets," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 1556-1592.
    16. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    17. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    18. Balli, Faruk & Balli, Hatice Ozer & Dang, Tam Hoang Nhat & Gabauer, David, 2023. "Contemporaneous and lagged R2 decomposed connectedness approach: New evidence from the energy futures market," Finance Research Letters, Elsevier, vol. 57(C).
    19. Alomari, Mohammad & Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Extreme return spillovers and connectedness between crude oil and precious metals futures markets: Implications for portfolio management," Resources Policy, Elsevier, vol. 79(C).
    20. Bhattacherjee, Purba & Mishra, Sibanjan & Kang, Sang Hoon, 2024. "Extreme time-frequency connectedness across U.S. sector stock and commodity futures markets," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 1176-1197.

    More about this item

    Keywords

    Realized volatilities; energy market; metal market; TVP-VAR; dynamic connectedness;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:pre:wpaper:202180. 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: Rangan Gupta (email available below). General contact details of provider: https://edirc.repec.org/data/decupza.html .

    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.