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Time-frequency connectedness between energy and nonenergy commodity markets during COVID-19: Evidence from China

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  • Chen, Hao
  • Xu, Chao
  • Peng, Yun

Abstract

We aim to investigate the static and dynamic time-frequency connectedness between energy and nonenergy commodity markets in China during COVID-19 based on Baruník and Křehlík (2018) method. First, in this paper, we find that the short-term connectedness dominates the long-term one, and the total connectedness increases after the COVID-19 outbreak. Second, the energy commodity is the receiver and is influenced much by the spillovers of non-energy commodity markets (e.g. chemical commodities and non-ferrous metals) in the short run. At the same time, the impact is less at the long-term investment horizons. In addition, chemical commodities and soft commodities are the primary transmitters in this system in the short run. In contrast, chemical commodities and coal steel iron commodities are the main long-run primary transmitters. Third, the spillover role varies with the time-frequency domain during COVID-19. To be more specific, the energy commodity shows a net receiver role in the short and long run before the COVID-19 pandemic, but after it, the role of the net transmitter can be seen in the long run with ease. Finally, we show that COVID can reduce the hedging effectiveness at different investment horizons. The mineral policymakers should note our dynamic empirical results between energy and nonenergy commodity.

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  • Chen, Hao & Xu, Chao & Peng, Yun, 2022. "Time-frequency connectedness between energy and nonenergy commodity markets during COVID-19: Evidence from China," Resources Policy, Elsevier, vol. 78(C).
    • Handle: RePEc:eee:jrpoli:v:78:y:2022:i:c:s0301420722003191
    DOI: 10.1016/j.resourpol.2022.102874
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    as
    1. Bouri, Elie & Cepni, Oguzhan & Gabauer, David & Gupta, Rangan, 2021. "Return connectedness across asset classes around the COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 73(C).
    2. Marianne P. Bitler & Hilary W. Hoynes & Diane Whitmore Schanzenbach, 2020. "The Social Safety Net in the Wake of COVID-19," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 51(2 (Summer), pages 119-158.
    3. 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.
    4. Bannigidadmath, Deepa & Narayan, Paresh Kumar, 2022. "Economic importance of correlations for energy and other commodities," Energy Economics, Elsevier, vol. 107(C).
    5. Shah, Adil Ahmad & Dar, Arif Billah, 2021. "Exploring diversification opportunities across commodities and financial markets: Evidence from time-frequency based spillovers," Resources Policy, Elsevier, vol. 74(C).
    6. Jiang, Yonghong & Nie, He & Monginsidi, Joe Yohanes, 2017. "Co-movement of ASEAN stock markets: New evidence from wavelet and VMD-based copula tests," Economic Modelling, Elsevier, vol. 64(C), pages 384-398.
    7. Chen, Yufeng & Zheng, Biao & Qu, Fang, 2020. "Modeling the nexus of crude oil, new energy and rare earth in China: An asymmetric VAR-BEKK (DCC)-GARCH approach," Resources Policy, Elsevier, vol. 65(C).
    8. Li, Zijian & Meng, Qiaoyu, 2022. "Time and frequency connectedness and portfolio diversification between cryptocurrencies and renewable energy stock markets during COVID-19," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    9. Antonakakis, Nikolaos & Gabauer, David & Gupta, Rangan & Plakandaras, Vasilios, 2018. "Dynamic connectedness of uncertainty across developed economies: A time-varying approach," Economics Letters, Elsevier, vol. 166(C), pages 63-75.
    10. Yonghong JIANG & Juan MENG & He NIE, 2018. "Visiting the Economic Policy Uncertainty Shocks - Economic Growth Relationship: Wavelet-based Granger-Causality in Quantiles Approac," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 80-94, December.
    11. Antonakakis, Nikolaos & Breitenlechner, Max & Scharler, Johann, 2015. "Business cycle and financial cycle spillovers in the G7 countries," The Quarterly Review of Economics and Finance, Elsevier, vol. 58(C), pages 154-162.
    12. Akyildirim, Erdinc & Cepni, Oguzhan & Molnár, Peter & Uddin, Gazi Salah, 2022. "Connectedness of energy markets around the world during the COVID-19 pandemic," Energy Economics, Elsevier, vol. 109(C).
    13. Lao, Jiashun & Nie, He & Jiang, Yonghong, 2018. "Revisiting the investor sentiment–stock returns relationship: A multi-scale perspective using wavelets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 499(C), pages 420-427.
    14. 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).
    15. Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    16. Jiang, Yonghong & Lie, Jiayi & Wang, Jieru & Mu, Jinqi, 2021. "Revisiting the roles of cryptocurrencies in stock markets: A quantile coherency perspective," Economic Modelling, Elsevier, vol. 95(C), pages 21-34.
    17. Saeed, Tareq & Bouri, Elie & Alsulami, Hamed, 2021. "Extreme return connectedness and its determinants between clean/green and dirty energy investments," Energy Economics, Elsevier, vol. 96(C).
    18. Liu, Yuntong & Wei, Yu & Wang, Qian & Liu, Yi, 2022. "International stock market risk contagion during the COVID-19 pandemic," Finance Research Letters, Elsevier, vol. 45(C).
    19. He Nie & Yonghong Jiang & Baoqing Yang, 2018. "Do different time horizons in the volatility of the US stock market significantly affect the China ETF market?," Applied Economics Letters, Taylor & Francis Journals, vol. 25(11), pages 747-751, June.
    20. Yang, Dong-Xiao & Wu, Bi-Bo & Tong, Jing-Yang, 2021. "Dynamics and causality of oil price shocks on commodities: Quantile-on-quantile and causality-in-quantiles methods," Resources Policy, Elsevier, vol. 74(C).
    21. Mensi, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Yoon, Seong-Min, 2014. "Dynamic spillovers among major energy and cereal commodity prices," Energy Economics, Elsevier, vol. 43(C), pages 225-243.
    22. Ji, Qiang & Fan, Ying, 2016. "How do China's oil markets affect other commodity markets both domestically and internationally?," Finance Research Letters, Elsevier, vol. 19(C), pages 247-254.
    23. Antonakakis, Nikolaos & Gabauer, David, 2017. "Refined Measures of Dynamic Connectedness based on TVP-VAR," MPRA Paper 78282, University Library of Munich, Germany.
    24. Jiang, Yonghong & Wu, Lanxin & Tian, Gengyu & Nie, He, 2021. "Do cryptocurrencies hedge against EPU and the equity market volatility during COVID-19? – New evidence from quantile coherency analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    25. Kroner, Kenneth F. & Sultan, Jahangir, 1993. "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(4), pages 535-551, December.
    26. Helena Chuliá & Dolores Furió & Jorge M. Uribe, 2019. "Volatility Spillovers in Energy Markets," The Energy Journal, , vol. 40(3), pages 173-198, May.
    27. Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Time and frequency connectedness and network across the precious metal and stock markets: Evidence from top precious metal importers and exporters," Resources Policy, Elsevier, vol. 72(C).
    28. Liu, Tangyong & Gong, Xu, 2020. "Analyzing time-varying volatility spillovers between the crude oil markets using a new method," Energy Economics, Elsevier, vol. 87(C).
    29. Khalfaoui, Rabeh & Baumöhl, Eduard & Sarwar, Suleman & Výrost, Tomáš, 2021. "Connectedness between energy and nonenergy commodity markets: Evidence from quantile coherency networks," Resources Policy, Elsevier, vol. 74(C).
    30. Xiarchos, Irene M. & Burnett, J. Wesley, 2018. "Dynamic Volatility Spillovers Between Agricultural And Energy Commodities," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 50(3), pages 291-318, August.
    31. Green, Rikard & Larsson, Karl & Lunina, Veronika & Nilsson, Birger, 2018. "Cross-commodity news transmission and volatility spillovers in the German energy markets," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 231-243.
    32. Umar, Muhammad & Farid, Saqib & Naeem, Muhammad Abubakr, 2022. "Time-frequency connectedness among clean-energy stocks and fossil fuel markets: Comparison between financial, oil and pandemic crisis," Energy, Elsevier, vol. 240(C).
    33. Albulescu, Claudiu Tiberiu, 2021. "COVID-19 and the United States financial markets’ volatility," Finance Research Letters, Elsevier, vol. 38(C).
    34. 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).
    35. Wasim Ahmad & Shirin Rais, 2018. "Time-Varying Spillover and the Portfolio Diversification Implications of Clean Energy Equity with Commodities and Financial Assets," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 54(8), pages 1837-1855, June.
    36. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    37. Mo, Bin & Meng, Juan & Zheng, Liping, 2022. "Time and frequency dynamics of connectedness between cryptocurrencies and commodity markets," Resources Policy, Elsevier, vol. 77(C).
    38. Xia, Tongshui & Yao, Chen-Xi & Geng, Jiang-Bo, 2020. "Dynamic and frequency-domain spillover among economic policy uncertainty, stock and housing markets in China," International Review of Financial Analysis, Elsevier, vol. 67(C).
    39. Asl, Mahdi Ghaemi & Canarella, Giorgio & Miller, Stephen M., 2021. "Dynamic asymmetric optimal portfolio allocation between energy stocks and energy commodities: Evidence from clean energy and oil and gas companies," Resources Policy, Elsevier, vol. 71(C).
    40. Kroner, Kenneth F & Ng, Victor K, 1998. "Modeling Asymmetric Comovements of Asset Returns," The Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 817-844.
    41. Tan, Xueping & Sirichand, Kavita & Vivian, Andrew & Wang, Xinyu, 2020. "How connected is the carbon market to energy and financial markets? A systematic analysis of spillovers and dynamics," Energy Economics, Elsevier, vol. 90(C).
    42. Jiang, Yonghong & Zhu, Zixuan & Tian, Gengyu & Nie, He, 2019. "Determinants of within and cross-country economic policy uncertainty spillovers: Evidence from US and China," Finance Research Letters, Elsevier, vol. 31(C).
    43. Akkoc, Ugur & Civcir, Irfan, 2019. "Dynamic linkages between strategic commodities and stock market in Turkey: Evidence from SVAR-DCC-GARCH model," Resources Policy, Elsevier, vol. 62(C), pages 231-239.
    44. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    45. 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.
    46. Jiang, Wei & Chen, Yunfei, 2022. "The time-frequency connectedness among carbon, traditional/new energy and material markets of China in pre- and post-COVID-19 outbreak periods," Energy, Elsevier, vol. 246(C).
    47. Meng, Juan & Nie, He & Mo, Bin & Jiang, Yonghong, 2020. "Risk spillover effects from global crude oil market to China’s commodity sectors," Energy, Elsevier, vol. 202(C).
    48. Barbaglia, Luca & Croux, Christophe & Wilms, Ines, 2020. "Volatility spillovers in commodity markets: A large t-vector autoregressive approach," Energy Economics, Elsevier, vol. 85(C).
    49. Mo, Bin & Chen, Cuiqiong & Nie, He & Jiang, Yonghong, 2019. "Visiting effects of crude oil price on economic growth in BRICS countries: Fresh evidence from wavelet-based quantile-on-quantile tests," Energy, Elsevier, vol. 178(C), pages 234-251.
    50. Costa, Antonio & Matos, Paulo & da Silva, Cristiano, 2022. "Sectoral connectedness: New evidence from US stock market during COVID-19 pandemics," Finance Research Letters, Elsevier, vol. 45(C).
    51. Chen, Peng & He, Limin & Yang, Xuan, 2021. "On interdependence structure of China's commodity market," Resources Policy, Elsevier, vol. 74(C).
    52. Zhang, Yue-Jun & Chen, Ming-Ying, 2018. "Evaluating the dynamic performance of energy portfolios: Empirical evidence from the DEA directional distance function," European Journal of Operational Research, Elsevier, vol. 269(1), pages 64-78.
    53. Magkonis, Georgios & Tsouknidis, Dimitris A., 2017. "Dynamic spillover effects across petroleum spot and futures volatilities, trading volume and open interest," International Review of Financial Analysis, Elsevier, vol. 52(C), pages 104-118.
    54. Rehman, Mobeen Ur & Bouri, Elie & Eraslan, Veysel & Kumar, Satish, 2019. "Energy and non-energy commodities: An asymmetric approach towards portfolio diversification in the commodity market," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    55. Jiang, Yonghong & Jiang, Cheng & Nie, He & Mo, Bin, 2019. "The time-varying linkages between global oil market and China's commodity sectors: Evidence from DCC-GJR-GARCH analyses," Energy, Elsevier, vol. 166(C), pages 577-586.
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