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A Bivariate Markov Regime Switching GARCH Approach to Estimate Time Varying Minimum Variance Hedge Ratios

  • Hsiang-Tai Lee

    (Washington State University)

  • Jonathan Yoder

    (Washington State University)

This paper develops a new bivariate Markov regime switching BEKK-GARCH (RS-BEKK-GARCH) model. The model is a state-dependent bivariate BEKK- GARCH model, and an extension of Gray’s univariate generalized regime- switching (GRS) model to the bivariate case. To solve the path- dependency problem inherent in the bivariate regime switching BEKK-GARCH model, we propose a recombining method for the covariance term in the conditional variance-covariance matrix. The model is applied to estimate time-varying minimum variance hedge ratios for corn and nickel spot and futures prices. Out-of-sample point estimates of hedging portfolio variance show that compared to the state-independent BEKK-GARCH model, the RS-BEKK-GARCH model improves out-of-sample hedging effectiveness for both corn and nickel data. We perform White’s (2000) data-snooping reality check to test for predictive superiority of RS-BEKK-GARCH over the benchmark model, and find that the difference in variance reduction between BEKK-GARCH and RS-BEKK-GARCH is not statistically significant for either data set at conventional confidence levels.

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File URL: http://econwpa.repec.org/eps/em/papers/0506/0506009.pdf
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Paper provided by EconWPA in its series Econometrics with number 0506009.

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Length: 33 pages
Date of creation: 28 Jun 2005
Date of revision:
Handle: RePEc:wpa:wuwpem:0506009
Note: Type of Document - pdf; pages: 33
Contact details of provider: Web page: http://econwpa.repec.org

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  1. H. N. E. BystrOm, 2003. "The hedging performance of electricity futures on the Nordic power exchange," Applied Economics, Taylor & Francis Journals, vol. 35(1), pages 1-11.
  2. Anil K. Bera & Philip Garcia & Jae-Sun Roh, 1997. "Estimation of Time-Varying Hedge Ratios for Corn and Soybeans: BGARCH and Random Coefficient Approaches," Finance 9712007, EconWPA.
  3. Figlewski, Stephen, 1984. " Hedging Performance and Basis Risk in Stock Index Futures," Journal of Finance, American Finance Association, vol. 39(3), pages 657-69, July.
  4. Baillie, Richard T & Myers, Robert J, 1991. "Bivariate GARCH Estimation of the Optimal Commodity Futures Hedge," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(2), pages 109-24, April-Jun.
  5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  6. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333.
  7. Ederington, Louis H, 1979. "The Hedging Performance of the New Futures Markets," Journal of Finance, American Finance Association, vol. 34(1), pages 157-70, March.
  8. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
  9. repec:cup:etheor:v:11:y:1995:i:1:p:122-50 is not listed on IDEAS
  10. Alizadeh, Amir H. & Nomikos, Nikos K. & Pouliasis, Panos K., 2008. "A Markov regime switching approach for hedging energy commodities," Journal of Banking & Finance, Elsevier, vol. 32(9), pages 1970-1983, September.
  11. Chris Brooks & Olan T. Henry & Gita Persand, 2002. "The Effect of Asymmetries on Optimal Hedge Ratios," The Journal of Business, University of Chicago Press, vol. 75(2), pages 333-352, April.
  12. Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February.
  13. Gagnon, Louis & Lypny, Gregory J. & McCurdy, Thomas H., 1998. "Hedging foreign currency portfolios," Journal of Empirical Finance, Elsevier, vol. 5(3), pages 197-220, September.
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