IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v83y2023ics0301420723004385.html
   My bibliography  Save this article

Research on price transmission in Chinese mining stock market: Based on industry

Author

Listed:
  • Zhu, Mingxue
  • Zhang, Hua
  • Xing, Wanli
  • Zhou, Xuanru
  • Wang, Lu
  • Sun, Haoyu

Abstract

The strong impact of COVID-19 on the global mining market has caused severe fluctuations in the prices of mineral products and mining stocks. Meanwhile, geopolitical conflicts have exacerbated risks in minerals trade and mining stock transactions. In the face of uncertainties in the international economic landscape and volatility of stock prices, China, as the world's major mineral trading country, has become increasingly linked between its stock market and the mining economy. To clarify the characteristics of mining stock price fluctuations and the evolution of the transmission relationships, and identify the key nodes and main paths of price transmission, we select 100 Chinese mining stocks from January 2019 to October 2022, distinguish them according to the industry category, and use Granger causality test, minimum spanning tree model and complex network analysis method to study. The results show that: (1) Chinese mining stock prices have risen significantly since 2020, and there has been a “decoupling” phenomenon within the stock market, that is, the linkage between some mining stocks has weakened. (2) The stock price fluctuation characteristics and transmission effects of different mining industries are obviously different. Precious metal minerals (PM) have the most dramatic changes in price fluctuations, the most prominent hedging characteristics, and the rapid price response ability, which is the first to accept price transmission. rare earth and rare metal minerals (RE) are sensitive to price fluctuations and are usually the “leader” of the transmission path. Bulk non-ferrous minerals (BNFM) have the most stable price fluctuations and are closely related to other stocks, which is a “transit warehouse” in the transmission path. (3) The price transmission mechanism of Chinese mining stock market has gradually stabilized, and the main transmission paths of “Coal→Agricultural minerals (Agri)→BNFM→Steel” and “PM, Core minerals for new energy (NEM), and RE→BNFM” have been formed in 2022.

Suggested Citation

  • Zhu, Mingxue & Zhang, Hua & Xing, Wanli & Zhou, Xuanru & Wang, Lu & Sun, Haoyu, 2023. "Research on price transmission in Chinese mining stock market: Based on industry," Resources Policy, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:jrpoli:v:83:y:2023:i:c:s0301420723004385
    DOI: 10.1016/j.resourpol.2023.103727
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420723004385
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2023.103727?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jain, Anshul & Biswal, P.C., 2016. "Dynamic linkages among oil price, gold price, exchange rate, and stock market in India," Resources Policy, Elsevier, vol. 49(C), pages 179-185.
    2. Thorbecke, Willem, 2019. "How oil prices affect East and Southeast Asian economies: Evidence from financial markets and implications for energy security," Energy Policy, Elsevier, vol. 128(C), pages 628-638.
    3. Mishra, Aswini Kumar & Ghate, Kshitish, 2022. "Dynamic connectedness in non-ferrous commodity markets: Evidence from India using TVP-VAR and DCC-GARCH approaches," Resources Policy, Elsevier, vol. 76(C).
    4. Ma, Yan-Ran & Zhang, Dayong & Ji, Qiang & Pan, Jiaofeng, 2019. "Spillovers between oil and stock returns in the US energy sector: Does idiosyncratic information matter?," Energy Economics, Elsevier, vol. 81(C), pages 536-544.
    5. Karali, Berna & Ramirez, Octavio A., 2014. "Macro determinants of volatility and volatility spillover in energy markets," Energy Economics, Elsevier, vol. 46(C), pages 413-421.
    6. Zheng, Biao & Zhang, Yuquan & Chen, Yufeng, 2021. "Asymmetric connectedness and dynamic spillovers between renewable energy and rare earth markets in China: Evidence from firms’ high-frequency data," Resources Policy, Elsevier, vol. 71(C).
    7. Singh, Vipul Kumar & Nishant, Shreyank & Kumar, Pawan, 2018. "Dynamic and directional network connectedness of crude oil and currencies: Evidence from implied volatility," Energy Economics, Elsevier, vol. 76(C), pages 48-63.
    8. Thu Thuy Nguyen & Van Chien Nguyen & Trong Nguyen Tran & David McMillan, 2020. "Oil price shocks against stock return of oil- and gas-related firms in the economic depression: A new evidence from a copula approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1799908-179, January.
    9. Katarzyna Czech & Michał Wielechowski, 2021. "Is the Alternative Energy Sector COVID-19 Resistant? Comparison with the Conventional Energy Sector: Markov-Switching Model Analysis of Stock Market Indices of Energy Companies," Energies, MDPI, vol. 14(4), pages 1-17, February.
    10. Pinglin He & Yulong Sun & Ying Zhang & Tao Li, 2020. "COVID–19’s Impact on Stock Prices Across Different Sectors—An Event Study Based on the Chinese Stock Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(10), pages 2198-2212, August.
    11. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    12. Esmaeilpour Moghadam, Hadi & Mohammadi, Teymour & Feghhi Kashani, Mohammad & Shakeri, Abbas, 2019. "Complex networks analysis in Iran stock market: The application of centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 531(C).
    13. Nguyen, Thu Thuy & Tran, T.N. & Nguyen, V.C., 2020. "Oil price shocks against stock return of oil- and gas-related firms in the economic depression: A new evidence from a copula approach," OSF Preprints 4cm7b, Center for Open Science.
    14. Zhou, Xuanru & Zhang, Hua & Zheng, Shuxian & Xing, Wanli & Yang, Hanshi & Zhao, Yifan, 2023. "A study on the transmission of trade behavior of global nickel products from the perspective of the industrial chain," Resources Policy, Elsevier, vol. 81(C).
    15. Baur, Dirk G. & Prange, Philipp & Schweikert, Karsten, 2021. "Flight to quality – Gold mining shares versus gold bullion," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    16. Jia, Zhijie & Lin, Boqiang, 2021. "How to achieve the first step of the carbon-neutrality 2060 target in China: The coal substitution perspective," Energy, Elsevier, vol. 233(C).
    17. Dar, Arif Billah & Bhanja, Niyati & Paul, Manas, 2019. "Do gold mining stocks behave like gold or equities? Evidence from the UK and the US," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 369-384.
    18. An, Sufang & Gao, Xiangyun & An, Haizhong & Liu, Siyao & Sun, Qingru & Jia, Nanfei, 2020. "Dynamic volatility spillovers among bulk mineral commodities: A network method," Resources Policy, Elsevier, vol. 66(C).
    19. Lv, Xin & Lien, Donald & Yu, Chang, 2020. "Who affects who? Oil price against the stock return of oil-related companies: Evidence from the U.S. and China," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 85-100.
    20. Ouyang, Ruolan & Zhuang, Chengkai & Wang, Tingting & Zhang, Xuan, 2022. "Network analysis of risk transmission among energy futures: An industrial chain perspective," Energy Economics, Elsevier, vol. 107(C).
    21. Asadi, Mehrad & Roubaud, David & Tiwari, Aviral Kumar, 2022. "Volatility spillovers amid crude oil, natural gas, coal, stock, and currency markets in the US and China based on time and frequency domain connectedness," Energy Economics, Elsevier, vol. 109(C).
    22. J.-P. Onnela & K. Kaski & J. Kertész, 2004. "Clustering and information in correlation based financial networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 353-362, March.
    23. Muneer M. Alshater & Osama F. Atayah & Ashraf Khan, 2022. "What do we know about business and economics research during COVID-19: a bibliometric review," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 35(1), pages 1884-1912, December.
    24. Li, Baihua & Li, Huajiao & Ren, Shuai & Liu, Haiping & Wang, Gang, 2023. "Commodity supply risk assessment of China's copper industrial chain: The perspective of trade network," Resources Policy, Elsevier, vol. 81(C).
    25. Nerlinger, Martin & Utz, Sebastian, 2022. "The impact of the Russia-Ukraine conflict on energy firms: A capital market perspective," Finance Research Letters, Elsevier, vol. 50(C).
    26. Liu, Wei & Ma, Qianting & Liu, Xiaoxing, 2022. "Research on the dynamic evolution and its influencing factors of stock correlation network in the Chinese new energy market," Finance Research Letters, Elsevier, vol. 45(C).
    27. Tong, Yuan & Wan, Ning & Dai, Xingyu & Bi, Xiaoyi & Wang, Qunwei, 2022. "China's energy stock market jumps: To what extent does the COVID-19 pandemic play a part?," Energy Economics, Elsevier, vol. 109(C).
    28. Wu, Fei & Zhao, Wan-Li & Ji, Qiang & Zhang, Dayong, 2020. "Dependency, centrality and dynamic networks for international commodity futures prices," International Review of Economics & Finance, Elsevier, vol. 67(C), pages 118-132.
    29. Yanjing Jia & Chao Ding & Zhiliang Dong, 2021. "Transmission Mechanism of Stock Price Fluctuation in the Rare Earth Industry Chain," Sustainability, MDPI, vol. 13(22), pages 1-21, November.
    30. Adam Duda & Gregorio Fidalgo Valverde, 2021. "The Economics of Coking Coal Mining: A Fossil Fuel Still Needed for Steel Production," Energies, MDPI, vol. 14(22), pages 1-12, November.
    31. Duque, Valentina & Gilraine, Michael, 2022. "Coal use, air pollution, and student performance," Journal of Public Economics, Elsevier, vol. 213(C).
    32. Hong Cheng & Yunqing Wang & Yihong Wang & Tinggan Yang, 2022. "Inferring Causal Interactions in Financial Markets Using Conditional Granger Causality Based on Quantile Regression," Computational Economics, Springer;Society for Computational Economics, vol. 59(2), pages 719-748, February.
    33. Alfredo Mendiola & Luis Chavez-Bedoya & Thilo Wallenstein, 2022. "Analyzing the Reaction of Mining Stocks to the Development of Copper Prices," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 58(1), pages 244-266, January.
    34. Ping Zhang & Jieying Gao & Xingchao Li, 2021. "Stock Liquidity and Firm Value in the Time of COVID-19 Pandemic," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(6), pages 1578-1591, May.
    35. Samitas, Aristeidis & Kampouris, Elias & Polyzos, Stathis, 2022. "Covid-19 pandemic and spillover effects in stock markets: A financial network approach," International Review of Financial Analysis, Elsevier, vol. 80(C).
    Full references (including those not matched with items on IDEAS)

    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. Wu, Fei & Xiao, Xuanqi & Zhou, Xinyu & Zhang, Dayong & Ji, Qiang, 2022. "Complex risk contagions among large international energy firms: A multi-layer network analysis," Energy Economics, Elsevier, vol. 114(C).
    2. Ouyang, Ruolan & Zhuang, Chengkai & Wang, Tingting & Zhang, Xuan, 2022. "Network analysis of risk transmission among energy futures: An industrial chain perspective," Energy Economics, Elsevier, vol. 107(C).
    3. Asadi, Mehrad & Roudari, Soheil & Tiwari, Aviral Kumar & Roubaud, David, 2023. "Scrutinizing commodity markets by quantile spillovers: A case study of the Australian economy," Energy Economics, Elsevier, vol. 118(C).
    4. Shi, Huai-Long & Chen, Huayi, 2024. "Understanding co-movements based on heterogeneous information associations," International Review of Financial Analysis, Elsevier, vol. 94(C).
    5. Chen, Ning & Li, Shaofang & Lu, Shuai, 2023. "The extreme risk connectedness of the global financial system: G7 and BRICS evidence," Journal of Multinational Financial Management, Elsevier, vol. 69(C).
    6. Deng, Jing & Xu, Zihan & Xing, Xiaoyun, 2024. "Extreme risk contagions among fossil energy companies in China: Insights from a multilayer dynamic network analysis," Energy, Elsevier, vol. 306(C).
    7. Hoque, Mohammad Enamul & Soo-Wah, Low & Billah, Mabruk, 2023. "Time-frequency connectedness and spillover among carbon, climate, and energy futures: Determinants and portfolio risk management implications," Energy Economics, Elsevier, vol. 127(PB).
    8. Peng Liu, 2024. "Antinetwork among China A-shares," Papers 2404.00028, arXiv.org.
    9. He, Chengying & Huang, Ke & Lin, Jianwu & Wang, Tianqi & Zhang, Zuominyang, 2023. "Explain systemic risk of commodity futures market by dynamic network," International Review of Financial Analysis, Elsevier, vol. 88(C).
    10. Deng, Jing & Xu, Zihan & Xing, Xiaoyun, 2023. "Dynamic spillovers between clean energy and non-ferrous metals markets in China: A network-based analysis during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 83(C).
    11. Zhang, Jiahao & Chen, Xiaodan & Wei, Yu & Bai, Lan, 2023. "Does the connectedness among fossil energy returns matter for renewable energy stock returns? Fresh insights from the Cross-Quantilogram analysis," International Review of Financial Analysis, Elsevier, vol. 88(C).
    12. Sebastiano Michele Zema & Giorgio Fagiolo & Tiziano Squartini & Diego Garlaschelli, 2021. "Mesoscopic Structure of the Stock Market and Portfolio Optimization," Papers 2112.06544, arXiv.org.
    13. Navarre, Jeremy T. & Frazier, Jeremy A., 2022. "Econometric analysis of factors influencing commercial helicopter operators’ stock returns in the gulf of Mexico," Journal of Air Transport Management, Elsevier, vol. 99(C).
    14. Paulus, Michal & Kristoufek, Ladislav, 2015. "Worldwide clustering of the corruption perception," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 428(C), pages 351-358.
    15. Cagli, Efe Caglar, 2023. "The volatility spillover between battery metals and future mobility stocks: Evidence from the time-varying frequency connectedness approach," Resources Policy, Elsevier, vol. 86(PA).
    16. Peng Yue & Qing Cai & Wanfeng Yan & Wei-Xing Zhou, 2020. "Information flow networks of Chinese stock market sectors," Papers 2004.08759, arXiv.org.
    17. Wu, Fei & Zhang, Dayong & Ji, Qiang, 2021. "Systemic risk and financial contagion across top global energy companies," Energy Economics, Elsevier, vol. 97(C).
    18. Sandoval, Leonidas, 2014. "To lag or not to lag? How to compare indices of stock markets that operate on different times," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 227-243.
    19. Liang, Chao & Xia, Zhenglan & Lai, Xiaodong & Wang, Lu, 2022. "Natural gas volatility prediction: Fresh evidence from extreme weather and extended GARCH-MIDAS-ES model," Energy Economics, Elsevier, vol. 116(C).
    20. Xie, Qichang & Luo, Chao & Cong, Xiaoping & Wang, Xu, 2024. "Volatility connectedness and its determinants of global energy stock markets," Economic Systems, Elsevier, vol. 48(2).

    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:eee:jrpoli:v:83:y:2023:i:c:s0301420723004385. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    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.