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A bivariate Markov regime switching GARCH approach to estimate time varying minimum variance hedge ratios

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Author Info
Hsiang-Tai Lee
Jonathan K. Yoder

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Abstract

This article develops a new bivariate Markov regime switching BEKK-Generalized Autoregressive Conditional Heteroscedasticity (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://www.informaworld.com/openurl?genre=article&doi=10.1080/00036840500438970&magic=repec&7C&7C8674ECAB8BB840C6AD35DC6213A474B5
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Article provided by Taylor and Francis Journals in its journal Applied Economics.

Volume (Year): 39 (2007)
Issue (Month): 10 ()
Pages: 1253-1265
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Handle: RePEc:taf:applec:v:39:y:2007:i:10:p:1253-1265

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  1. 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. [Downloadable!] (restricted)
  2. H.N.E. BystrÖm, 2003. "The hedging performance of electricity futures on the Nordic power exchange," Applied Economics, Taylor and Francis Journals, vol. 35(1), pages 1-11, January. [Downloadable!] (restricted)
  3. 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. [Downloadable!] (restricted)
  4. 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. [Downloadable!] (restricted)
  5. 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. [Downloadable!] (restricted)
  6. repec:cup:etheor:v:11:y:1995:i:1:p:122-50 is not listed on IDEAS
  7. Hamilton, James D. & Susmel, Raul, 1994. "Autoregressive conditional heteroskedasticity and changes in regime," Journal of Econometrics, Elsevier, vol. 64(1-2), pages 307-333. [Downloadable!] (restricted)
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  8. Chris Brooks & Olan T. Henry & Gita Persand, 2002. "The Effect of Asymmetries on Optimal Hedge Ratios," Journal of Business, University of Chicago Press, vol. 75(2), pages 333-352, April. [Downloadable!]
  9. 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. [Downloadable!]
  10. 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. [Downloadable!] (restricted)
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