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Exchange Rate and Industrial Commodity Volatility Transmissions and Hedging Strategies

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  • Shawkat M. Hammoudeh

    (Lebow College of Business, Drexel University)

  • Yuan Yuan

    (Lebow College of Business, Drexel University)

  • Michael McAleer

    (Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam and Tinbergen Institute and Center for International Research on the Japanese Economy (CIRJE), Faculty of Economics, University of Tokyo)

Abstract

This paper examines the inclusion of the dollar/euro exchange rate together with important commodities in two different BEKK, or multivariate conditional covariance, models. Such inclusion increases the significant direct and indirect past shock and volatility effects on future volatility between the commodities, as compared with their effects in the all-commodity basic model (Model 1), which includes the highly-traded aluminum, copper, gold and oil. Model 2, which includes copper, gold, oil and exchange rate, displays more direct and indirect transmission than does Model 3, which replaces the business cycle-sensitive copper with the highly energy-intensive aluminum. Optimal portfolios should have more Euro than commodities, and more copper and gold than oil. The multivariate conditional volatility models reveal greater volatility spillovers than their univariate counterparts.

Suggested Citation

  • Shawkat M. Hammoudeh & Yuan Yuan & Michael McAleer, 2009. "Exchange Rate and Industrial Commodity Volatility Transmissions and Hedging Strategies," CARF F-Series CARF-F-172, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    • Handle: RePEc:cfi:fseres:cf172
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    References listed on IDEAS

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    1. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(2), pages 280-310, April.
    2. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(1), pages 122-150, February.
    3. Hammoudeh, Shawkat & Dibooglu, Sel & Aleisa, Eisa, 2004. "Relationships among U.S. oil prices and oil industry equity indices," International Review of Economics & Finance, Elsevier, vol. 13(4), pages 427-453.
    4. Massimiliano Caporin & Michael McAleer, 2009. "Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models," CIRJE F-Series CIRJE-F-638, CIRJE, Faculty of Economics, University of Tokyo.
    5. Smith, Kenneth L & Bracker, Kevin, 2003. "Forecasting Changes in Copper Futures Volatility with GARCH Models Using an Iterated Algorithm," Review of Quantitative Finance and Accounting, Springer, vol. 20(3), pages 245-265, May.
    6. Moschini, GianCarlo & Myers, Robert J., 2002. "Testing for constant hedge ratios in commodity markets: a multivariate GARCH approach," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 589-603, December.
    7. Bollerslev, Tim & Engle, Robert F & Wooldridge, Jeffrey M, 1988. "A Capital Asset Pricing Model with Time-Varying Covariances," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 116-131, February.
    8. Bhar, Ramaprasad & Hammoudeh, Shawkat & Thompson, Mark A., 2008. "Component structure for nonstationary time series: Application to benchmark oil prices," International Review of Financial Analysis, Elsevier, vol. 17(5), pages 971-983, December.
    9. Massimiliano Caporin & Michael McAleer, 2008. "Scalar BEKK and indirect DCC," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 537-549.
    10. Kroner, Kenneth F. & Sultan, Jahangir, 1993. "Time-Varying Distributions and Dynamic Hedging with Foreign Currency Futures," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(4), pages 535-551, December.
    11. Seung‐Ryong Yang & B. Wade Brorsen, 1993. "Nonlinear dynamics of daily futures prices: Conditional heteroskedasticity or chaos?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 13(2), pages 175-191, April.
    12. 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.
    13. Tully, Edel & Lucey, Brian M., 2007. "A power GARCH examination of the gold market," Research in International Business and Finance, Elsevier, vol. 21(2), pages 316-325, June.
    14. Plourde, André & Watkins, G. C., 1998. "Crude oil prices between 1985 and 1994: how volatile in relation to other commodities?," Resource and Energy Economics, Elsevier, vol. 20(3), pages 245-262, September.
    15. Ewing, Bradley T. & Malik, Farooq & Ozfidan, Ozkan, 2002. "Volatility transmission in the oil and natural gas markets," Energy Economics, Elsevier, vol. 24(6), pages 525-538, November.
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    Cited by:

    1. Ahmadi, Maryam & Bashiri Behmiri, Niaz & Manera, Matteo, 2016. "How is volatility in commodity markets linked to oil price shocks?," Energy Economics, Elsevier, vol. 59(C), pages 11-23.
    2. Balcilar, Mehmet & Hammoudeh, Shawkat & Asaba, Nwin-Anefo Fru, 2015. "A regime-dependent assessment of the information transmission dynamics between oil prices, precious metal prices and exchange rates," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 72-89.

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