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Realized volatility spillovers in the non-ferrous metal futures market

Author

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  • Todorova, Neda
  • Worthington, Andrew
  • Souček, Michael

Abstract

In contrast to energy and precious metals commodities, relatively little is known about the volatility dynamics of base (or industrial) metals commodities. To address this deficiency, this paper employs a multivariate heterogeneous autoregressive (HAR) model to consider the volatility spillovers between the five of the most liquid and important non-ferrous metals contracts (aluminium, copper, lead, nickel, and zinc) traded on the London Metal Exchange using intraday data over the period June 2006–December 2012. This period encompasses both the surge in commodities prices associated with the burgeoning industrial demand of many emerging economies, especially China, resulting in market peaks in May 2007 and April 2008 and the subsequent negative reaction of base metals markets to the collapse of stock markets during the recent global financial crisis. The results show that the volatility series of other industrial metals appear to contain useful incremental information for future price volatility. However, the own dynamics are often sufficient for describing most future daily and weekly volatility, with the most pronounced volatility spillovers identified in the longer term. Combined together, the results in this study provide useful findings for exporter and importer countries dealing with the continuing volatility in these industrially important commodity markets.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:jrpoli:v:39:y:2014:i:c:p:21-31
    DOI: 10.1016/j.resourpol.2013.10.008
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    as
    1. Fulvio Corsi & Stefan Mittnik & Christian Pigorsch & Uta Pigorsch, 2008. "The Volatility of Realized Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 46-78.
    2. Humphreys, David, 2010. "The great metals boom: A retrospective," Resources Policy, Elsevier, vol. 35(1), pages 1-13, March.
    3. Fulvio Corsi & Roberto Renò, 2012. "Discrete-Time Volatility Forecasting With Persistent Leverage Effect and the Link With Continuous-Time Volatility Modeling," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(3), pages 368-380, January.
    4. Donald Lien & Li Yang, 2009. "Intraday return and volatility spill‐over across international copper futures markets," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 5(1), pages 135-149, February.
    5. Ole E. Barndorff-Nielsen & Peter Reinhard Hansen & Asger Lunde & Neil Shephard, 2008. "Designing Realized Kernels to Measure the ex post Variation of Equity Prices in the Presence of Noise," Econometrica, Econometric Society, vol. 76(6), pages 1481-1536, November.
    6. 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.
    7. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    8. Bubák, Vít & Kocenda, Evzen & Zikes, Filip, 2011. "Volatility transmission in emerging European foreign exchange markets," Journal of Banking & Finance, Elsevier, vol. 35(11), pages 2829-2841, November.
    9. Wu, Feng, 2011. "Testing for Volatility Changes in Grain Markets," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103388, Agricultural and Applied Economics Association.
    10. Bauer, Gregory H. & Vorkink, Keith, 2011. "Forecasting multivariate realized stock market volatility," Journal of Econometrics, Elsevier, vol. 160(1), pages 93-101, January.
    11. Bandi, Federico M. & Russell, Jeffrey R., 2006. "Separating microstructure noise from volatility," Journal of Financial Economics, Elsevier, vol. 79(3), pages 655-692, March.
    12. Hammoudeh, Shawkat & Yuan, Yuan, 2008. "Metal volatility in presence of oil and interest rate shocks," Energy Economics, Elsevier, vol. 30(2), pages 606-620, March.
    13. A. Khalifa & S. Hammoudeh & E. Otranto & S. Ramchander, 2012. "Volatility Transmission across Currency, Commodity and Equity Markets under Multi-Chain Regime Switching: Implications for Hedging and Portfolio Allocation," Working Paper CRENoS 201214, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    14. Hansen, Peter R. & Lunde, Asger, 2006. "Realized Variance and Market Microstructure Noise," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 127-161, April.
    15. repec:dau:papers:123456789/4598 is not listed on IDEAS
    16. Geman, Hélyette & Smith, William O., 2013. "Theory of storage, inventory and volatility in the LME base metals," Resources Policy, Elsevier, vol. 38(1), pages 18-28.
    17. Roel C. A. Oomen, 2005. "Properties of Bias-Corrected Realized Variance Under Alternative Sampling Schemes," Journal of Financial Econometrics, Oxford University Press, vol. 3(4), pages 555-577.
    18. Zhou, Bin, 1996. "High-Frequency Data and Volatility in Foreign-Exchange Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 45-52, January.
    19. Clinton Watkins & Michael McAleer, 2004. "Econometric modelling of non‐ferrous metal prices," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 651-701, December.
    20. 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.
    21. 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.
    22. Shawkat M. Hammoudeh & Yuan Yuan & Michael McAleer, 2009. "Modeling Exchange Rate and Industrial Commodity Volatility Transmissions," "Marco Fanno" Working Papers 0096, Dipartimento di Scienze Economiche "Marco Fanno".
    23. Liu, Xiangli & Cheng, Siwei & Wang, Shouyang & Hong, Yongmiao & Li, Yi, 2008. "An empirical study on information spillover effects between the Chinese copper futures market and spot market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(4), pages 899-914.
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    JEL classification:

    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G1 - Financial Economics - - General Financial Markets
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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