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Bivariate mixed normal GARCH models and out-of-sample hedge performances

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  • Chung, Sang-Kuck

Abstract

This study compares bivariate mixed normal GARCH models with standard bivariate GARCH models in terms of the percentage variance reduction of the out-of-sample hedged portfolio and also statistical significance tests of performance improvements using Superior Predictive Ability statistics. All competing models are applied to corn and wheat futures and empirical results demonstrate that the standard BEKK-GARCH model significantly outperforms the other competing GARCH models at shorter horizons. However, as the hedge horizon is extended to longer than 10Â days, it is evident that the mixed normal BEKK-GARCH model is the best at the usual significance level of 5%.

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  • Chung, Sang-Kuck, 2009. "Bivariate mixed normal GARCH models and out-of-sample hedge performances," Finance Research Letters, Elsevier, vol. 6(3), pages 130-137, September.
    • Handle: RePEc:eee:finlet:v:6:y:2009:i:3:p:130-137
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    1. Asger Lunde & Peter R. Hansen, 2005. "A forecast comparison of volatility models: does anything beat a GARCH(1,1)?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(7), pages 873-889.
    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. Bauwens, L. & Hafner, C.M. & Rombouts, J.V.K., 2007. "Multivariate mixed normal conditional heteroskedasticity," Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3551-3566, April.
    4. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2006. "Multivariate normal mixture GARCH," CFS Working Paper Series 2006/09, Center for Financial Studies (CFS).
    5. Andrew J. Patton, 2004. "On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation," Journal of Financial Econometrics, Oxford University Press, vol. 2(1), pages 130-168.
    6. Emese Lazar & Carol Alexander, 2006. "Normal mixture GARCH(1,1): applications to exchange rate modelling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(3), pages 307-336.
    7. Markus Haas, 2004. "Mixed Normal Conditional Heteroskedasticity," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 211-250.
    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.
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    Cited by:

    1. Zhipeng, Yan & Shenghong, Li, 2018. "Hedge ratio on Markov regime-switching diagonal Bekk–Garch model," Finance Research Letters, Elsevier, vol. 24(C), pages 49-55.
    2. Haas, Markus, 2010. "Covariance forecasts and long-run correlations in a Markov-switching model for dynamic correlations," Finance Research Letters, Elsevier, vol. 7(2), pages 86-97, June.

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