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Risk connectedness between crude oil, gold and exchange rates in China: Implications of the COVID-19 pandemic

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  • Xu, Lei
  • Ma, Xueke
  • Qu, Fang
  • Wang, Li

Abstract

This study examined the risk connectedness and its asymmetry between oil, gold, and foreign exchange under the realized volatility, spillover index framework, and high-frequency data during the COVID-19 pandemic. It was found that: (1) At the beginning of the pandemic outbreak, the total volatility spillover in the system declined, which may indicate that the pandemic cuts the trading activities in the financial markets by inhibiting personnel mobility, then, the spillover experienced a short-term sharp rise due to panic. (2) The exchange rate had a significant risk connectedness with gold and international crude oil, but a restrict connectedness with domestic crude oil after the outbreak. These variations of risk transmission caused by the pandemic emerged later than the outbreak, reflecting a certain lag. (3) The impact of the pandemic on the asymmetric risk connectedness between oil, gold and the exchange rate was limited, and the risk transfer resulting from bad news was dominant during the sample period; however, gold was less affected by bad news than the oil and exchange rates. These findings suggested that the establishment of Chinese crude oil futures could restrain volatility spillovers from the exchange rate; the foreign exchange reserve structure should be optimized. Gold has been proved to have a hedging function with the crude oil, and its proportion in foreign exchange reserves should be appropriately increased.

Suggested Citation

  • Xu, Lei & Ma, Xueke & Qu, Fang & Wang, Li, 2023. "Risk connectedness between crude oil, gold and exchange rates in China: Implications of the COVID-19 pandemic," Resources Policy, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:jrpoli:v:83:y:2023:i:c:s0301420723004026
    DOI: 10.1016/j.resourpol.2023.103691
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    References listed on IDEAS

    as
    1. Liao, Yin & Pan, Zheyao, 2022. "Extreme risk connectedness among global major financial institutions: Links to globalization and emerging market fear," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    2. Andersen T. G & Bollerslev T. & Diebold F. X & Labys P., 2001. "The Distribution of Realized Exchange Rate Volatility," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 42-55, March.
    3. Jozef Baruník & Tomáš Křehlík, 2018. "Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 271-296.
    4. Liu, Jianing & Man, Yuanyuan & Dong, Xiuliang, 2023. "Tail dependence and risk spillover effects between China's carbon market and energy markets," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 553-567.
    5. Liu, Renren & Chen, Jianzhong & Wen, Fenghua, 2021. "The nonlinear effect of oil price shocks on financial stress: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    6. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers," Journal of Financial Markets, Elsevier, vol. 27(C), pages 55-78.
    7. El-Khatib, Youssef & Goutte, Stephane & Makumbe, Zororo S. & Vives, Josep, 2022. "Approximate pricing formula to capture leverage effect and stochastic volatility of a financial asset," Finance Research Letters, Elsevier, vol. 44(C).
    8. Singhal, Shelly & Choudhary, Sangita & Biswal, Pratap Chandra, 2019. "Return and volatility linkages among International crude oil price, gold price, exchange rate and stock markets: Evidence from Mexico," Resources Policy, Elsevier, vol. 60(C), pages 255-261.
    9. Baffes, John, 2007. "Oil spills on other commodities," Resources Policy, Elsevier, vol. 32(3), pages 126-134, September.
    10. Jia, Zhijie & Wen, Shiyan & Lin, Boqiang, 2021. "The effects and reacts of COVID-19 pandemic and international oil price on energy, economy, and environment in China," Applied Energy, Elsevier, vol. 302(C).
    11. Qi, Haozhi & Ma, Lijun & Peng, Pin & Chen, Hao & Li, Kang, 2022. "Dynamic connectedness between clean energy stock markets and energy commodity markets during times of COVID-19: Empirical evidence from China," Resources Policy, Elsevier, vol. 79(C).
    12. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    13. Chen, Yufeng & Qu, Fang, 2019. "Leverage effect and dynamics correlation between international crude oil and China’s precious metals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    14. Bedoui, Rihab & Braeik, Sana & Goutte, Stéphane & Guesmi, Khaled, 2018. "On the study of conditional dependence structure between oil, gold and USD exchange rates," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 134-146.
    15. Chang, Hsiao-Fen & Huang, Liang-Chou & Chin, Ming-Chin, 2013. "Interactive relationships between crude oil prices, gold prices, and the NT–US dollar exchange rate—A Taiwan study," Energy Policy, Elsevier, vol. 63(C), pages 441-448.
    16. Zhang, Chen & Yang, Yu & Yun, Po, 2020. "Risk measurement of international carbon market based on multiple risk factors heterogeneous dependence," Finance Research Letters, Elsevier, vol. 32(C).
    17. 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.
    18. 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.
    19. Tully, Edel & Lucey, Brian M., 2007. "A power GARCH examination of the gold market," Research in International Business and Finance, Elsevier, vol. 21(2), pages 316-325, June.
    20. Sadorsky, Perry, 2014. "Modeling volatility and conditional correlations between socially responsible investments, gold and oil," Economic Modelling, Elsevier, vol. 38(C), pages 609-618.
    21. Kumar, Suresh & Choudhary, Sangita & Singh, Gurcharan & Singhal, Shelly, 2021. "Crude oil, gold, natural gas, exchange rate and indian stock market: Evidence from the asymmetric nonlinear ARDL model," Resources Policy, Elsevier, vol. 73(C).
    22. Shahzad, Syed Jawad Hussain & Naeem, Muhammad Abubakr & Peng, Zhe & Bouri, Elie, 2021. "Asymmetric volatility spillover among Chinese sectors during COVID-19," International Review of Financial Analysis, Elsevier, vol. 75(C).
    23. Mensi, Walid & Al Rababa'a, Abdel Razzaq & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Asymmetric spillover and network connectedness between crude oil, gold, and Chinese sector stock markets," Energy Economics, Elsevier, vol. 98(C).
    24. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    25. Ciner, Cetin & Gurdgiev, Constantin & Lucey, Brian M., 2013. "Hedges and safe havens: An examination of stocks, bonds, gold, oil and exchange rates," International Review of Financial Analysis, Elsevier, vol. 29(C), pages 202-211.
    26. Guan, Lu & Zhang, Wei-Wei & Ahmad, Ferhana & Naqvi, Bushra, 2021. "The volatility of natural resource prices and its impact on the economic growth for natural resource-dependent economies: A comparison of oil and gold dependent economies," Resources Policy, Elsevier, vol. 72(C).
    27. Li, Wenqi, 2021. "COVID-19 and asymmetric volatility spillovers across global stock markets," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    28. Georgiadis, Georgios & Zhu, Feng, 2021. "Foreign-currency exposures and the financial channel of exchange rates: Eroding monetary policy autonomy in small open economies?," Journal of International Money and Finance, Elsevier, vol. 110(C).
    29. Song, Malin & Fisher, Ron & Kwoh, Yusen, 2019. "Technological challenges of green innovation and sustainable resource management with large scale data," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 361-368.
    30. Gong, Xu & Xu, Jun, 2022. "Geopolitical risk and dynamic connectedness between commodity markets," Energy Economics, Elsevier, vol. 110(C).
    31. Song, Malin & Ma, Xiaowei & Shang, Yuping & Zhao, Xin, 2020. "Influences of land resource assets on economic growth and fluctuation in China," Resources Policy, Elsevier, vol. 68(C).
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