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A separate reduced‐form volatility forecasting model for nonferrous metal market: Evidence from copper and aluminum

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  • Hongwei Zhang
  • Xuehong Zhu
  • Yaoqi Guo
  • Haibo Liu

Abstract

This article extends the HAR‐CJN model proposed by Andersen, Bollerslev, and Huang (Journal of Econometrics, 2011, 160, 176–189) and explores the role of overnight information and leverage effects in improving volatility forecasting. To explore the interaction between different components of daily volatility, this paper attempts to separately model the dynamics of continuous variation, the discontinuous jump, and the overnight return variance by including leverage effects. The findings show that lagged continuous and discontinuous jump variations generate significant impacts on future continuous segments, discontinuous jump segments, and the overnight return variance. Furthermore, in addition to the usual leverage effects, additional leverage effects with respect to overnight returns are found to play a significant role in volatility forecasting. Finally, out‐of‐sample forecasts are investigated; the results show that the new HAR‐CJN model can describe and predict daily volatility more accurately than other HAR models.

Suggested Citation

  • Hongwei Zhang & Xuehong Zhu & Yaoqi Guo & Haibo Liu, 2018. "A separate reduced‐form volatility forecasting model for nonferrous metal market: Evidence from copper and aluminum," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(7), pages 754-766, November.
    • Handle: RePEc:wly:jforec:v:37:y:2018:i:7:p:754-766
    DOI: 10.1002/for.2523
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    Cited by:

    1. Klein, Tony & Todorova, Neda, 2021. "Night trading with futures in China: The case of Aluminum and Copper," Resources Policy, Elsevier, vol. 73(C).
    2. Wen, Fenghua & Wu, Nan & Gong, Xu, 2020. "China's carbon emissions trading and stock returns," Energy Economics, Elsevier, vol. 86(C).
    3. Huang, Jianbai & Tang, Jing & Zhang, Hongwei, 2020. "The effect of investors’ information search behaviors on rebar market return dynamics using high frequency data," Resources Policy, Elsevier, vol. 66(C).
    4. Yaojie Zhang & Yudong Wang & Feng Ma, 2021. "Forecasting US stock market volatility: How to use international volatility information," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 733-768, August.
    5. Shahani, Rakesh & Paliwal, Riya, 2020. "An empirical analysis of the Co-movement of Crude, Gold, Rupee-Dollar Exchange rate and Nifty 50 Stock Index during Sub-prime and Coronavirus crisis periods," MPRA Paper 103568, University Library of Munich, Germany.
    6. Yang, Cai & Gong, Xu & Zhang, Hongwei, 2019. "Volatility forecasting of crude oil futures: The role of investor sentiment and leverage effect," Resources Policy, Elsevier, vol. 61(C), pages 548-563.
    7. Zhu, Xuehong & Zheng, Weihang & Zhang, Hongwei & Guo, Yaoqi, 2019. "Time-varying international market power for the Chinese iron ore markets," Resources Policy, Elsevier, vol. 64(C).
    8. Liu, Yuanyuan & Niu, Zibo & Suleman, Muhammad Tahir & Yin, Libo & Zhang, Hongwei, 2022. "Forecasting the volatility of crude oil futures: The role of oil investor attention and its regime switching characteristics under a high-frequency framework," Energy, Elsevier, vol. 238(PA).
    9. Klein, Tony & Todorova, Neda, 2019. "Night Trading with Futures in China: The Case of Aluminum and Copper," QBS Working Paper Series 2019/06, Queen's University Belfast, Queen's Business School.
    10. Jia, Nanfei & An, Haizhong & Gao, Xiangyun & Liu, Donghui & Chang, Hao, 2023. "The main transmission paths of price fluctuations for tungsten products along the industry chain," Resources Policy, Elsevier, vol. 80(C).
    11. Niu, Zibo & Liu, Yuanyuan & Gao, Wang & Zhang, Hongwei, 2021. "The role of coronavirus news in the volatility forecasting of crude oil futures markets: Evidence from China," Resources Policy, Elsevier, vol. 73(C).
    12. Zhu, Xuehong & Li, Xinyuan & Zhang, Hongwei & Huang, Jianbai, 2019. "International market power analysis of China’s tungsten export market -- from the perspective of tungsten export policies," Resources Policy, Elsevier, vol. 61(C), pages 643-652.
    13. Shao, Liuguo & Zhang, Hua, 2020. "The impact of oil price on the clean energy metal prices: A multi-scale perspective," Resources Policy, Elsevier, vol. 68(C).
    14. Wen, Fenghua & Zhao, Cong & Hu, Chunyan, 2019. "Time-varying effects of international copper price shocks on China's producer price index," Resources Policy, Elsevier, vol. 62(C), pages 507-514.

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