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Pricing of Non-ferrous Metals Futures on the London Metal Exchange

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  • Clinton Watkins

    (Department of Economics, University of Western Australia)

  • Michael McAleer

    (Department of Economics, University of Western Australia)

Abstract

The London Metal Exchange (LME) is the most important centre for spot and futures trading in the main industrially-used non-ferrous metals. In this paper, data on 3-month futures contracts for aluminium, aluminium alloy, copper, lead, nickel, tin and zinc are analysed. The risk premium hypothesis and the cost-of-carry model are the standard theoretical models for pricing futures contracts, but these two models have rarely been estimated within a unified framework for metals futures. Single equation versions of the risk premium hypothesis and the cost-of-carry model are nested within a more general model. If the spot price, futures price, interest rate and stock level variables contain stochastic trends, long run versions of the general model can be estimated within a cointegration framework. Various long run pricing models are estimated using daily LME price data for the period 1 February 1986 to 30 September 1998. Likelihood ratio tests are used to test restrictions on the general model to examine the validity of alternative nested specifications.

Suggested Citation

  • Clinton Watkins & Michael McAleer, 2003. "Pricing of Non-ferrous Metals Futures on the London Metal Exchange," CIRJE F-Series CIRJE-F-213, CIRJE, Faculty of Economics, University of Tokyo.
  • Handle: RePEc:tky:fseres:2003cf213
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    Cited by:

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    3. Fernandez, Viviana, 2020. "The predictive power of convenience yields," Resources Policy, Elsevier, vol. 65(C).
    4. Cummins, Mark & Dowling, Michael & Lucey, Brian M., 2015. "Behavioral influences in non-ferrous metals prices," Resources Policy, Elsevier, vol. 45(C), pages 9-22.
    5. Barry A. Goss & S. Gulay Avsar, 2013. "Simultaneity, Forecasting and Profits in London Copper Futures," Australian Economic Papers, Wiley Blackwell, vol. 52(2), pages 79-96, June.
    6. Lien, Donald & Yang, Li, 2008. "Hedging with Chinese metal futures," Global Finance Journal, Elsevier, vol. 19(2), pages 123-138.
    7. Arouri, Mohamed El Hedi & Hammoudeh, Shawkat & Lahiani, Amine & Nguyen, Duc Khuong, 2013. "On the short- and long-run efficiency of energy and precious metal markets," Energy Economics, Elsevier, vol. 40(C), pages 832-844.
    8. Hu, Haiqing & Chen, Di & Sui, Bo & Zhang, Lang & Wang, Yinyin, 2020. "Price volatility spillovers between supply chain and innovation of financial pledges in China," Economic Modelling, Elsevier, vol. 89(C), pages 397-413.
    9. 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.
    10. Watkins, Clinton & McAleer, Michael, 2008. "How has volatility in metals markets changed?," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 237-249.
    11. Han, Xuyuan & Liu, Zhenya & Wang, Shixuan, 2022. "An R-vine copula analysis of non-ferrous metal futures with application in Value-at-Risk forecasting," Journal of Commodity Markets, Elsevier, vol. 25(C).
    12. Fernandez, Viviana, 2017. "A historical perspective of the informational content of commodity futures," Resources Policy, Elsevier, vol. 51(C), pages 135-150.
    13. Mohamed El Hedi Arouri & Fredj Jawadi & Prosper Mouak, 2013. "Testing the efficiency of the aluminium market: evidence from London metal exchange," Applied Financial Economics, Taylor & Francis Journals, vol. 23(6), pages 483-493, March.
    14. Nidhi Choudhary & Girish K. Nair & Harsh Purohit, 2015. "Volatility In Copper Prices In India," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 1-26, December.
    15. Claudio-Quiroga, Gloria & Gil-Alana, Luis A. & Maiza-Larrarte, Andoni, 2023. "Mineral prices persistence and the development of a new energy vehicle industry in China: A fractional integration approach," Resources Policy, Elsevier, vol. 82(C).
    16. Stepanek, Christian & Walter, Matthias & Rathgeber, Andreas, 2013. "Is the convenience yield a good indicator of a commodity's supply risk?," Resources Policy, Elsevier, vol. 38(3), pages 395-405.
    17. Kshitij Kakade & Aswini Kumar Mishra & Kshitish Ghate & Shivang Gupta, 2022. "Forecasting Commodity Market Returns Volatility: A Hybrid Ensemble Learning GARCH‐LSTM based Approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(2), pages 103-117, April.
    18. Etoundi Atenga, Eric Martial, 2014. "Asymmetric shocks, persistence in volatility and spillover effects between non ferrous metals on the LME spot market," MPRA Paper 61017, University Library of Munich, Germany.
    19. Omura, Akihiro & Todorova, Neda & Li, Bin & Chung, Richard, 2015. "Convenience yield and inventory accessibility: Impact of regional market conditions," Resources Policy, Elsevier, vol. 44(C), pages 1-11.
    20. Todorova, Neda, 2015. "The course of realized volatility in the LME non-ferrous metal market," Economic Modelling, Elsevier, vol. 51(C), pages 1-12.
    21. 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).
    22. Chen, Xiangyu & Tongurai, Jittima, 2022. "Spillovers and interdependency across base metals: Evidence from China's futures and spot markets," Resources Policy, Elsevier, vol. 75(C).
    23. Morales, Lucía & Andreosso-O'Callaghan, Bernadette, 2011. "Comparative analysis on the effects of the Asian and global financial crises on precious metal markets," Research in International Business and Finance, Elsevier, vol. 25(2), pages 203-227, June.
    24. Sanidas, Elias, 2014. "Four harmonic cycles explain and predict commodity currencies' wide long term fluctuations," Technological Forecasting and Social Change, Elsevier, vol. 87(C), pages 135-151.

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