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

  • Shawkat M. Hammoudeh

    (Lebow College of Business, Drexel University)

  • Yuan Yuan

    (Lebow College of Business, Drexel University)

  • Michael McAleer

    (Erasmus University Rotterdam, Tinbergen Institute, The Netherlands, and Institute of Economic Research, Kyoto University)

This paper examines volatility, volatility spillovers, optimal portfolio weights and hedging for systems that include the dollar/euro exchange rate together with four important and highly traded commodities - aluminum, copper, gold and oil - by utilizing four 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. The model that includes copper displays more direct and indirect transmissions than the one that includes aluminum which displays the high interactions with oil. Optimal portfolio weights suggest that investors should hold more of aluminum, copper and gold and less of oil in those portfolios. Hedging ratios indicate that the most effective way of hedging long commodity and euro positions is shorting them with oil positions.

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File URL: http://www.kier.kyoto-u.ac.jp/DP/DP751.pdf
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Paper provided by Kyoto University, Institute of Economic Research in its series KIER Working Papers with number 751.

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Length: 53pages
Date of creation: Dec 2010
Date of revision:
Handle: RePEc:kyo:wpaper:751
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  1. Shiqing Ling & Michael McAleer, 2001. "Asymptotic Theory for a Vector ARMA-GARCH Model," ISER Discussion Paper 0549, Institute of Social and Economic Research, Osaka University.
  2. Massimiliano Caporin & Michael McAleer, 2010. "Do We Really Need Both BEKK and DCC? A Tale of Two Multivariate GARCH Models," Working Papers in Economics 10/06, University of Canterbury, Department of Economics and Finance.
  3. Moschini, GianCarlo & Myers, Robert J., 2002. "Testing for Constant Hedge Ratios in Commodity Markets: A Multivariate Garch Approach," Staff General Research Papers 1945, Iowa State University, Department of Economics.
  4. 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.
  5. 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.
  6. 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, 04.
  7. 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.
  8. Massimiliano Caporin & Michael McAleer, 2008. "Scalar BEKK and indirect DCC," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(6), pages 537-549.
  9. Massimiliano Caporin & Michael McAleer, 2009. "Do We Really Need Both BEKK and DCC? A Tale of Two Covariance Models," Documentos de Trabajo del ICAE 0904, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
  10. 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.
  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. 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.
  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. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February.
  15. 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.
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