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Commonality in the LME aluminum and copper volatility processes through a FIGARCH lens

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  • Isabel Figuerola‐Ferretti
  • Christopher L. Gilbert

Abstract

Dynamic representation of spot and three‐month aluminum and copper volatilities is considered. Aluminum and copper are the two most important metals traded in the London Metal Exchange. They share common business cycle factors and are traded under identical contract specifications. The bivariate FIGARCH model, which allows parsimonious representation of long memory volatility processes, is applied. The results show that spot and three‐month aluminum and copper volatilities follow long memory processes, that they exhibit a common degree of fractional integration and that the processes are symmetric. However, there is no evidence that the processes are fractionally cointegrated. This high degree of commonality may result from the common LME trading process. © 2008 Wiley Periodicals, Inc. Jrl Fut Mark 28:935–962, 2008

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  • Isabel Figuerola‐Ferretti & Christopher L. Gilbert, 2008. "Commonality in the LME aluminum and copper volatility processes through a FIGARCH lens," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 28(10), pages 935-962, October.
    • Handle: RePEc:wly:jfutmk:v:28:y:2008:i:10:p:935-962
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    Cited by:

    1. Jaehwan Park, 2019. "Effect of Speculators’ Position Changes on the LME Futures Market," IJFS, MDPI, vol. 7(2), pages 1-9, June.
    2. Byungkwon Lim & Hyeon Sook Kim & Jaehwan Park, 2020. "Direct Effect of TC on the LME Copper Prices," Economies, MDPI, vol. 8(2), pages 1-9, May.
    3. Gilles Truchis & Benjamin Keddad, 2016. "Long-Run Comovements in East Asian Stock Market Volatility," Open Economies Review, Springer, vol. 27(5), pages 969-986, November.
    4. Tapia, Carlos & Coulton, Jeff & Saydam, Serkan, 2020. "Using entropy to assess dynamic behaviour of long-term copper price," Resources Policy, Elsevier, vol. 66(C).
    5. Wahab, Bashir A. & Adewuyi, Adeolu O., 2021. "Analysis of major properties of metal prices using new methods: Structural breaks, non-linearity, stationarity and bubbles," Resources Policy, Elsevier, vol. 74(C).
    6. Tangyong Liu & Xu Gong & Boqiang Lin, 2021. "Analyzing the frequency dynamics of volatility spillovers across precious and industrial metal markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(9), pages 1375-1396, September.
    7. Kang, Boda & Nikitopoulos, Christina Sklibosios & Prokopczuk, Marcel, 2020. "Economic determinants of oil futures volatility: A term structure perspective," Energy Economics, Elsevier, vol. 88(C).
    8. Jaehwan Park, 2018. "Volatility Transmission between Oil and LME Futures," Applied Economics and Finance, Redfame publishing, vol. 5(2), pages 65-72, March.
    9. 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.
    10. Jaehwan Park & Byungkwon Lim, 2018. "Testing Efficiency of the London Metal Exchange: New Evidence," IJFS, MDPI, vol. 6(1), pages 1-10, March.

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