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Exchange Rate and Industrial Commodity Volatility Transmissions, Asymmetries and Hedging Strategies

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  • Hammoudeh, S.M.
  • Yuan, Y.
  • McAleer, M.J.

Abstract

This paper examines the inclusion of the dollar/euro exchange rate together with four important and highly traded commodities - aluminum, copper, gold and oil- in symmetric and asymmetric multivariate GARCH and DCC models. The inclusion of exchange rate increases the significant direct and indirect past shock and volatility effects on future volatility between the commodities in all the models. Model 2, which includes the business cycle industrial metal copper and not aluminum, displays more direct and indirect transmissions than does Model 3, which replaces the business cycle-sensitive copper with the highly energy-intensive aluminum. The asymmetric effects are the greatest in Model 3 because of the high interactions between oil and aluminum. Optimal portfolios should have more euro currency than commodities, and more copper and gold than oil.

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Bibliographic Info

Paper provided by Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute in its series Econometric Institute Research Papers with number EI 2010-35.

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Date of creation: 11 May 2010
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Handle: RePEc:ems:eureir:19449

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Keywords: MGARCH; asymmetries; hedging; shocks; transmission; volatility;

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  1. 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.
  2. 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.
  3. Massimiliano Caporin & Michael McAleer, 2009. "Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models," Documentos del Instituto Complutense de Análisis Económico 0904, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales.
  4. Ling, Shiqing & McAleer, Michael, 2003. "Asymptotic Theory For A Vector Arma-Garch Model," Econometric Theory, Cambridge University Press, vol. 19(02), pages 280-310, April.
  5. Caporin, M. & McAleer, M.J., 2010. "Do We Really Need Both BEKK and DCC? A Tale of Two Multivariate GARCH Models," Econometric Institute Research Papers EI 2010-13, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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  7. 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 245-65, May.
  8. GianCarlo Moschini & Robert J. Myers, 2001. "Testing for Constant Hedge Ratios in Commodity Markets: A Multivariate GARCH Approach," Center for Agricultural and Rural Development (CARD) Publications 01-wp268, Center for Agricultural and Rural Development (CARD) at Iowa State University.
  9. 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.
  10. Massimiliano Caporin & Michael McAleer, 2008. "Scalar BEKK and indirect DCC," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 537-549.
  11. 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.
  12. 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 116-31, February.
  13. 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.
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Cited by:
  1. Halova Wolfe, Marketa & Rosenman, Robert, 2014. "Bidirectional causality in oil and gas markets," Energy Economics, Elsevier, vol. 42(C), pages 325-331.

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