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Price linkages in the copper futures, primary, and scrap markets

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  • Aruga, Kentaka
  • Managi, Shunsuke

Abstract

This study investigates how markets for different levels of copper purity are interrelated by testing the long-run price linkage and causalities among the copper futures, primary, copper scrap, and brass scrap markets. It is expected that copper markets that deal with high purity levels, such as the futures, primary, and copper scrap markets, have a long-run relationship. However, brass scrap markets where copper with a lower purity is traded may not have a price linkage with other copper markets. The results reveal that a long-run relationship holds between the futures, primary, and copper scrap markets but the brass scrap market does not have a long-run relationship with the other markets. From the short-run and long-run causality tests, we determine that the futures market plays an important role in transmitting price information to other copper markets while such information flow is not found for the brass scrap market.

Suggested Citation

  • Aruga, Kentaka & Managi, Shunsuke, 2011. "Price linkages in the copper futures, primary, and scrap markets," Resources, Conservation & Recycling, Elsevier, vol. 56(1), pages 43-47.
    • Handle: RePEc:eee:recore:v:56:y:2011:i:1:p:43-47
    DOI: 10.1016/j.resconrec.2011.08.010
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    Cited by:

    1. Ding, Yinghui & Chen, Shan & Li, Haoran & Sun, Qingru & Chen, Hanyu & Yu, Hui, 2023. "Causality inference among base metal, rare metal and precious metal markets," Resources Policy, Elsevier, vol. 85(PB).
    2. Tomas Brabenec & Josef Montag, 2016. "Criminals and the Price System: Evidence from Czech Metal Thieves," CERGE-EI Working Papers wp558, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    3. Donghua Wang & Yang Xin & Xiaohui Chang & Xingze Su, 2021. "Realized volatility forecasting and volatility spillovers: Evidence from Chinese non‐ferrous metals futures," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2713-2731, April.
    4. Rivera, Nilza & Guzmán, Juan Ignacio & Jara, José Joaquín & Lagos, Gustavo, 2021. "Evaluation of econometric models of secondary refined copper supply," Resources Policy, Elsevier, vol. 73(C).
    5. Shaoqiang Ma & Min Fang & Xin Zhou, 2023. "China’s Embodied Copper Flow from the Demand-Side and Production-Side Perspectives," Sustainability, MDPI, vol. 15(3), pages 1-18, January.
    6. Buncic, Daniel & Moretto, Carlo, 2015. "Forecasting copper prices with dynamic averaging and selection models," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
    7. Simic, Vladimir & Dimitrijevic, Branka, 2013. "Risk explicit interval linear programming model for long-term planning of vehicle recycling in the EU legislative context under uncertainty," Resources, Conservation & Recycling, Elsevier, vol. 73(C), pages 197-210.
    8. Todorova, Neda & Worthington, Andrew & Souček, Michael, 2014. "Realized volatility spillovers in the non-ferrous metal futures market," Resources Policy, Elsevier, vol. 39(C), pages 21-31.
    9. Nilza Rivera & Juan Ignacio Guzmán, 2024. "Dynamic relationship between refined and scrap copper prices," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 37(2), pages 381-392, June.
    10. Todorova, Neda, 2015. "The course of realized volatility in the LME non-ferrous metal market," Economic Modelling, Elsevier, vol. 51(C), pages 1-12.
    11. Ciner, Cetin & Lucey, Brian & Yarovaya, Larisa, 2020. "Spillovers, integration and causality in LME non-ferrous metal markets," Journal of Commodity Markets, Elsevier, vol. 17(C).
    12. Arık, Evren & Mutlu, Elif, 2014. "Chinese steel market in the post-futures period," Resources Policy, Elsevier, vol. 42(C), pages 10-17.

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    More about this item

    Keywords

    Futures market; Copper scrap; Brass scrap; Cointegration; Causality;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • L61 - Industrial Organization - - Industry Studies: Manufacturing - - - Metals and Metal Products; Cement; Glass; Ceramics

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