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Dynamic spillovers and dependencies between iron ore prices, industry bond yields, and steel prices

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  • Ma, Yiqun

Abstract

We examine the spillovers and dependencies between iron ore prices, bond yields of mechanical equipment, infrastructure construction and housing, and car industries, and steel prices by using the spillover index and copula model over the period 2011–2021. Our results show that compared with bond yields, iron ore prices are primary contributors of price spillovers and highly comparable with China's steel prices. Notably, the magnitudes of correlations and risk transmissions from bond yields of related industries to steel prices shifts over the period before the implementation of China's policy to cut overcapacity in steelmaking, after the policy implementation and before the outbreak of coronavirus, and after the outbreak of coronavirus. Because of high price spillovers from iron ore to steel prices and iron ore-steel relationship, policymakers in the steel industry should consider more supply-side policies to mitigate market risks. Meanwhile, risk-averse investors should increase the share of bonds of related industries.

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  • Ma, Yiqun, 2021. "Dynamic spillovers and dependencies between iron ore prices, industry bond yields, and steel prices," Resources Policy, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:jrpoli:v:74:y:2021:i:c:s0301420721004396
    DOI: 10.1016/j.resourpol.2021.102430
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    as
    1. Yu, Ip-Wing & Fung, Kang-Por & Tam, Chi-Sang, 2010. "Assessing financial market integration in Asia - Equity markets," Journal of Banking & Finance, Elsevier, vol. 34(12), pages 2874-2885, December.
    2. Engle, Robert F & Ng, Victor K, 1993. "Time-Varying Volatility and the Dynamic Behavior of the Term Structure," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 25(3), pages 336-349, August.
    3. Whitney K. Newey & Kenneth D. West, 1994. "Automatic Lag Selection in Covariance Matrix Estimation," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 61(4), pages 631-653.
    4. Aloui, Riadh & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2013. "A time-varying copula approach to oil and stock market dependence: The case of transition economies," Energy Economics, Elsevier, vol. 39(C), pages 208-221.
    5. Brahmasrene, Tantatape & Huang, Jui-Chi & Sissoko, Yaya, 2014. "Crude oil prices and exchange rates: Causality, variance decomposition and impulse response," Energy Economics, Elsevier, vol. 44(C), pages 407-412.
    6. Omura, Akihiro & Todorova, Neda & Li, Bin & Chung, Richard, 2016. "Steel scrap and equity market in Japan," Resources Policy, Elsevier, vol. 47(C), pages 115-124.
    7. Tule, Moses K. & Ndako, Umar B. & Onipede, Samuel F., 2017. "Oil price shocks and volatility spillovers in the Nigerian sovereign bond market," Review of Financial Economics, Elsevier, vol. 35(C), pages 57-65.
    8. Fenech, Jean-Pierre & Vosgha, Hamed, 2019. "Oil price and Gulf Corporation Council stock indices: New evidence from time-varying copula models," Economic Modelling, Elsevier, vol. 77(C), pages 81-91.
    9. Jorrit Gosens, 2020. "China’s post-COVID-19 stimulus: no Green New Deal in sight," CCEP Working Papers 2006, Centre for Climate & Energy Policy, Crawford School of Public Policy, The Australian National University.
    10. Lin, Boqiang & Su, Tong, 2020. "The linkages between oil market uncertainty and Islamic stock markets: Evidence from quantile-on-quantile approach," Energy Economics, Elsevier, vol. 88(C).
    11. Ma, Yiqun & Wang, Junhao, 2019. "Co-movement between oil, gas, coal, and iron ore prices, the Australian dollar, and the Chinese RMB exchange rates: A copula approach," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    12. Husain, Shaiara & Tiwari, Aviral Kumar & Sohag, Kazi & Shahbaz, Muhammad, 2019. "Connectedness among crude oil prices, stock index and metal prices: An application of network approach in the USA," Resources Policy, Elsevier, vol. 62(C), pages 57-65.
    13. Mensi, Walid & Rehman, Mobeen Ur & Al-Yahyaee, Khamis Hamed, 2020. "Time-frequency co-movements between oil prices and interest rates: Evidence from a wavelet-based approach," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    14. Prasad Bal, Debi & Narayan Rath, Badri, 2015. "Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India," Energy Economics, Elsevier, vol. 51(C), pages 149-156.
    15. Reboredo, Juan C. & Rivera-Castro, Miguel A., 2013. "A wavelet decomposition approach to crude oil price and exchange rate dependence," Economic Modelling, Elsevier, vol. 32(C), pages 42-57.
    16. Dai, Zhifeng & Kang, Jie, 2021. "Bond yield and crude oil prices predictability," Energy Economics, Elsevier, vol. 97(C).
    17. Hamao, Yasushi & Masulis, Ronald W & Ng, Victor, 1990. "Correlations in Price Changes and Volatility across International Stock Markets," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 281-307.
    18. Peng, Cheng & Zhu, Huiming & Guo, Yawei & Chen, Xiuyun, 2018. "Risk spillover of international crude oil to China's firms: Evidence from granger causality across quantile," Energy Economics, Elsevier, vol. 72(C), pages 188-199.
    19. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    20. 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.
    21. Keay, Ian & Redish, Angela, 2004. "The micro-economic effects of financial market structure: evidence from 20th century North American steel firms," Explorations in Economic History, Elsevier, vol. 41(4), pages 377-403, October.
    22. Zihui Yang & Yinggang Zhou, 2017. "Quantitative Easing and Volatility Spillovers Across Countries and Asset Classes," Management Science, INFORMS, vol. 63(2), pages 333-354, February.
    23. Mensi, Walid & Hamed Al-Yahyaee, Khamis & Vinh Vo, Xuan & Hoon Kang, Sang, 2021. "Dynamic spillover and connectedness between oil futures and European bonds," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).
    24. Ma, Yiqun, 2021. "Do iron ore, scrap steel, carbon emission allowance, and seaborne transportation prices drive steel price fluctuations?," Resources Policy, Elsevier, vol. 72(C).
    25. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
    26. Sadorsky, Perry, 2006. "Modeling and forecasting petroleum futures volatility," Energy Economics, Elsevier, vol. 28(4), pages 467-488, July.
    27. Li, Xiao-Ping & Zhou, Chun-Yang & Wu, Chong-Feng, 2017. "Jump spillover between oil prices and exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 656-667.
    28. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    29. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    30. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    31. Bondia, Ripsy & Ghosh, Sajal & Kanjilal, Kakali, 2016. "International crude oil prices and the stock prices of clean energy and technology companies: Evidence from non-linear cointegration tests with unknown structural breaks," Energy, Elsevier, vol. 101(C), pages 558-565.
    32. Mu, Xiaoyi, 2007. "Weather, storage, and natural gas price dynamics: Fundamentals and volatility," Energy Economics, Elsevier, vol. 29(1), pages 46-63, January.
    33. King, Mervyn & Sentana, Enrique & Wadhwani, Sushil, 1994. "Volatility and Links between National Stock Markets," Econometrica, Econometric Society, vol. 62(4), pages 901-933, July.
    34. Nam T. Hoang & Bao H. Nguyen, 2018. "Oil and Iron Ore Price Shocks: What Are the Different Economic Effects in Australia?," The Economic Record, The Economic Society of Australia, vol. 94(305), pages 186-203, June.
    35. Xiaolu Hu & Haoyi Luo & Zijin Xu & Jiang Li, 2021. "Intra‐industry spill‐over effect of default: Evidence from the Chinese bond market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4703-4740, September.
    36. Ma, Yiqun, 2013. "Iron ore spot price volatility and change in forward pricing mechanism," Resources Policy, Elsevier, vol. 38(4), pages 621-627.
    37. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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