IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v77y2022ics0301420722001568.html
   My bibliography  Save this article

Dynamic multiscale analysis of causality among mining stock prices

Author

Listed:
  • Wang, Xiaoxuan
  • Gao, Xiangyun
  • Wu, Tao
  • Sun, Xiaotian

Abstract

This paper combines the ensemble empirical mode decomposition(EEMD) method, the transfer entropy(TE) method and complex network theory to analyze the causal relationships among Chinese mining stock prices on multiple time scales. The results show that the strength of the causal relationship among mining stocks increases with cycle growth and that the causal relationship between stocks and subindustries is asymmetric and time-varying. On the three time scales, the weighted in-degree, weighted out-degree and weighted betweenness centrality of the five subindustries all show a trend of increasing and decreasing at the same time. In addition, we construct high and low transfer entropy portfolios and find that the high transfer entropy portfolio has higher investment returns when the stock market is good, and the low transfer entropy portfolio has less investment loss when the stock market is bad. Investors are advised to pay attention to the stocks included in the high transfer entropy portfolio when the market is good, and vice versa when the market is bad. Regulators are advised to pay attention to the subindustries with heavy positions in the high transfer entropy portfolio.

Suggested Citation

  • Wang, Xiaoxuan & Gao, Xiangyun & Wu, Tao & Sun, Xiaotian, 2022. "Dynamic multiscale analysis of causality among mining stock prices," Resources Policy, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:jrpoli:v:77:y:2022:i:c:s0301420722001568
    DOI: 10.1016/j.resourpol.2022.102708
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420722001568
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2022.102708?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. Liu, Chang & Sun, Xiaolei & Wang, Jun & Li, Jianping & Chen, Jianming, 2021. "Multiscale information transmission between commodity markets: An EMD-Based transfer entropy network," Research in International Business and Finance, Elsevier, vol. 55(C).
    2. Chen, Yufeng & Li, Wenqi & Qu, Fang, 2019. "Dynamic asymmetric spillovers and volatility interdependence on China’s stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 825-838.
    3. Shahzad, Syed Jawad Hussain & Bouri, Elie & Ahmad, Tanveer & Naeem, Muhammad Abubakr, 2022. "Extreme tail network analysis of cryptocurrencies and trading strategies," Finance Research Letters, Elsevier, vol. 44(C).
    4. 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.
    5. Xiao, Di & Wang, Jun, 2020. "Dynamic complexity and causality of crude oil and major stock markets," Energy, Elsevier, vol. 193(C).
    6. Lei, Yalin & Cui, Na & Pan, Dongyang, 2013. "Economic and social effects analysis of mineral development in China and policy implications," Resources Policy, Elsevier, vol. 38(4), pages 448-457.
    7. Huang, Shupei & An, Haizhong & Gao, Xiangyun & Huang, Xuan, 2016. "Time–frequency featured co-movement between the stock and prices of crude oil and gold," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 985-995.
    8. Bao, Dun, 2020. "Dynamics and correlation of platinum-group metals spot prices," Resources Policy, Elsevier, vol. 68(C).
    9. Wang, Lu & Ma, Feng & Niu, Tianjiao & He, Chengting, 2020. "Crude oil and BRICS stock markets under extreme shocks: New evidence," Economic Modelling, Elsevier, vol. 86(C), pages 54-68.
    10. Bekiros, Stelios & Nguyen, Duc Khuong & Sandoval Junior, Leonidas & Uddin, Gazi Salah, 2017. "Information diffusion, cluster formation and entropy-based network dynamics in equity and commodity markets," European Journal of Operational Research, Elsevier, vol. 256(3), pages 945-961.
    11. Li, Yong & Vilela, André L.M. & Stanley, H. Eugene, 2020. "The institutional characteristics of multifractal spectrum of China’s stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    12. Wang, Xunxiao & Wang, Yudong, 2019. "Volatility spillovers between crude oil and Chinese sectoral equity markets: Evidence from a frequency dynamics perspective," Energy Economics, Elsevier, vol. 80(C), pages 995-1009.
    13. Wang, Ze & Gao, Xiangyun & An, Haizhong & Tang, Renwu & Sun, Qingru, 2020. "Identifying influential energy stocks based on spillover network," International Review of Financial Analysis, Elsevier, vol. 68(C).
    14. Mokni, Khaled & Hammoudeh, Shawkat & Ajmi, Ahdi Noomen & Youssef, Manel, 2020. "Does economic policy uncertainty drive the dynamic connectedness between oil price shocks and gold price?," Resources Policy, Elsevier, vol. 69(C).
    15. 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.
    16. Liow, Kim Hiang & Song, Jeongseop, 2020. "Dynamic interdependence of ASEAN5 with G5 stock markets," Emerging Markets Review, Elsevier, vol. 45(C).
    17. Xi, Xian & Gao, Xiangyun & Zhou, Jinsheng & Zheng, Huiling & Ding, Jiazheng & Si, Jingjian, 2021. "Uncovering the impacts of structural similarity of financial indicators on stock returns at different quantile levels," International Review of Financial Analysis, Elsevier, vol. 76(C).
    18. Li, Ranran & Hu, Yucai & Heng, Jiani & Chen, Xueli, 2021. "A novel multiscale forecasting model for crude oil price time series," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
    19. Chand, Pushpendu & Thakkar, Jitesh J. & Ghosh, Kunal Kanti, 2020. "Analysis of supply chain performance metrics for Indian mining & earthmoving equipment manufacturing companies using hybrid MCDM model," Resources Policy, Elsevier, vol. 68(C).
    20. Feng, Sida & Huang, Shupei & Qi, Yabin & Liu, Xueyong & Sun, Qingru & Wen, Shaobo, 2018. "Network features of sector indexes spillover effects in China: A multi-scale view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 496(C), pages 461-473.
    21. Peng Yue & Yaodong Fan & Jonathan A. Batten & Wei-Xing Zhou, 2020. "Information transfer between stock market sectors: A comparison between the USA and China," Papers 2004.07612, arXiv.org.
    22. Hu, Min & Zhang, Dayong & Ji, Qiang & Wei, Lijian, 2020. "Macro factors and the realized volatility of commodities: A dynamic network analysis," Resources Policy, Elsevier, vol. 68(C).
    23. 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).
    24. Ashfaq, Saleha & Tang, Yong & Maqbool, Rashid, 2020. "Dynamics of spillover network among oil and leading Asian oil trading countries’ stock markets," Energy, Elsevier, vol. 207(C).
    25. Niu, Hongli & Hu, Ziang, 2021. "Information transmission and entropy-based network between Chinese stock market and commodity futures market," Resources Policy, Elsevier, vol. 74(C).
    26. Ur Rahman, Zia & Iqbal Khattak, Shoukat & Ahmad, Manzoor & Khan, Anwar, 2020. "A disaggregated-level analysis of the relationship among energy production, energy consumption and economic growth: Evidence from China," Energy, Elsevier, vol. 194(C).
    27. Modak, Mousumi & Pathak, Khanindra & Ghosh, Kunal Kanti, 2017. "Performance evaluation of outsourcing decision using a BSC and Fuzzy AHP approach: A case of the Indian coal mining organization," Resources Policy, Elsevier, vol. 52(C), pages 181-191.
    28. Shao, Liuguo & Hu, Wenqin & Yang, Danhui, 2020. "The price relationship between main-byproduct metals from a multiscale nonlinear Granger causality perspective," Resources Policy, Elsevier, vol. 69(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhou, Yang & Xie, Chi & Wang, Gang-Jin & Gong, Jue & Li, Zhao-Chen & Zhu, You, 2024. "Who dominate the information flowing between innovative and traditional financial assets? A multiscale entropy-based approach," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 329-358.
    2. Wu, Tao & Gao, Xiangyun & An, Feng & Xu, Xin & Kurths, Jürgen, 2024. "Forecasting the dynamics of correlations in complex systems," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).

    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. Xi, Xian & Gao, Xiangyun & Zhou, Jinsheng & Zheng, Huiling & Ding, Jiazheng & Si, Jingjian, 2021. "Uncovering the impacts of structural similarity of financial indicators on stock returns at different quantile levels," International Review of Financial Analysis, Elsevier, vol. 76(C).
    2. Farid, Saqib & Kayani, Ghulam Mujtaba & Naeem, Muhammad Abubakr & Shahzad, Syed Jawad Hussain, 2021. "Intraday volatility transmission among precious metals, energy and stocks during the COVID-19 pandemic," Resources Policy, Elsevier, vol. 72(C).
    3. Chen, Yufeng & Xu, Jing & Hu, May, 2022. "Asymmetric volatility spillovers and dynamic correlations between crude oil price, exchange rate and gold price in BRICS," Resources Policy, Elsevier, vol. 78(C).
    4. Ngo Thai Hung, 2020. "Analysis of the Time-frequency Connectedness between Gold Prices, Oil Prices and Hungarian Financial Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 10(4), pages 51-59.
    5. Wen, Danyan & Wang, Yudong, 2021. "Volatility linkages between stock and commodity markets revisited: Industry perspective and portfolio implications," Resources Policy, Elsevier, vol. 74(C).
    6. Hung, Ngo Thai & Vo, Xuan Vinh, 2021. "Directional spillover effects and time-frequency nexus between oil, gold and stock markets: Evidence from pre and during COVID-19 outbreak," International Review of Financial Analysis, Elsevier, vol. 76(C).
    7. Liu, Chang & Sun, Xiaolei & Wang, Jun & Li, Jianping & Chen, Jianming, 2021. "Multiscale information transmission between commodity markets: An EMD-Based transfer entropy network," Research in International Business and Finance, Elsevier, vol. 55(C).
    8. Ding, Qian & Huang, Jianbai & Chen, Jinyu, 2021. "Dynamic and frequency-domain risk spillovers among oil, gold, and foreign exchange markets: Evidence from implied volatility," Energy Economics, Elsevier, vol. 102(C).
    9. Wang, Xiangning & Huang, Qian & Zhang, Shuguang, 2023. "Effects of macroeconomic factors on stock prices for BRICS using the variational mode decomposition and quantile method," The North American Journal of Economics and Finance, Elsevier, vol. 67(C).
    10. Wen, Danyan & Wang, Yudong & Ma, Chaoqun & Zhang, Yaojie, 2020. "Information transmission between gold and financial assets: Mean, volatility, or risk spillovers?," Resources Policy, Elsevier, vol. 69(C).
    11. Alkathery, Mohammed A. & Chaudhuri, Kausik & Nasir, Muhammad Ali, 2023. "Dependence between the GCC energy equities, global clean energy and emission markets: Evidence from wavelet analysis," Energy Economics, Elsevier, vol. 121(C).
    12. Zhang, Zitao & Qin, Yun, 2022. "Study on the nonlinear interactions among the international oil price, the RMB exchange rate and China's gold price," Resources Policy, Elsevier, vol. 77(C).
    13. Hong, Yanran & Ma, Feng & Wang, Lu & Liang, Chao, 2022. "How does the COVID-19 outbreak affect the causality between gold and the stock market? New evidence from the extreme Granger causality test," Resources Policy, Elsevier, vol. 78(C).
    14. Zhou, Yang & Xie, Chi & Wang, Gang-Jin & Gong, Jue & Li, Zhao-Chen & Zhu, You, 2024. "Who dominate the information flowing between innovative and traditional financial assets? A multiscale entropy-based approach," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 329-358.
    15. Mensi, Walid & Rehman, Mobeen Ur & Vo, Xuan Vinh, 2022. "Spillovers and diversification benefits between oil futures and ASEAN stock markets," Resources Policy, Elsevier, vol. 79(C).
    16. Zhang, Hua & Chen, Jinyu & Shao, Liuguo, 2021. "Dynamic spillovers between energy and stock markets and their implications in the context of COVID-19," International Review of Financial Analysis, Elsevier, vol. 77(C).
    17. Bouri, Elie & Roubaud, David & Jammazi, Rania & Assaf, Ata, 2017. "Uncovering frequency domain causality between gold and the stock markets of China and India: Evidence from implied volatility indices," Finance Research Letters, Elsevier, vol. 23(C), pages 23-30.
    18. Tanin, Tauhidul Islam & Sarker, Ashutosh & Brooks, Robert & Do, Hung Xuan, 2022. "Does oil impact gold during COVID-19 and three other recent crises?," Energy Economics, Elsevier, vol. 108(C).
    19. Khan, Muhammad Imran & Teng, Jian-Zhou & Khan, Muhammad Kamran & Jadoon, Arshad Ullah & Khan, Muhammad Fayaz, 2021. "The impact of oil prices on stock market development in Pakistan: Evidence with a novel dynamic simulated ARDL approach," Resources Policy, Elsevier, vol. 70(C).
    20. Aamir Aijaz Syed & Muhammad Abdul Kamal, 2024. "Do cryptocurrency and commodities markets affect stock market performance in South Asia? An empirical investigation during the COVID-19 pandemic," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 27(4), pages 673-692.

    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:77:y:2022:i:c:s0301420722001568. 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.