Bivariate mixed normal GARCH models and out-of-sample hedge performances
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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- Andrew J. Patton, 2002.
"On the out-of-sample importance of skewness and asymetric dependence for asset allocation,"
LSE Research Online Documents on Economics
24951, London School of Economics and Political Science, LSE Library.
- Andrew J. Patton, 2004. "On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(1), pages 130-168.
- BAUWENS, Luc & HAFNER, Christian & ROMBOUTS, Jeroen, 2006.
"Multivariate mixed normal conditional heteroskedasticity,"
CORE Discussion Papers
2006012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- 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.
- BAUWENS, Luc & HAFNER, Christian M. & ROMBOUTS, Jeroen VK, . "Multivariate mixed normal conditional heteroskedasticity," CORE Discussion Papers RP -1906, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Luc, BAUWENS & C.M., HAFNER & J.V.K., ROMBOUTS, 2006. "Multivariate mixed normal conditional heteroskedasticity," Discussion Papers (ECON - Département des Sciences Economiques) 2006007, Université catholique de Louvain, Département des Sciences Economiques.
- Asger Lunde & Peter Reinhard Hansen, 2001.
"A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?,"
2001-04, Brown University, Department of Economics.
- 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.
- Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2002.
"Mixed normal conditional heteroskedasticity,"
CFS Working Paper Series
2002/10, Center for Financial Studies (CFS).
- 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.
- Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2006. "Multivariate normal mixture GARCH," CFS Working Paper Series 2006/09, Center for Financial Studies (CFS).
- Engle, Robert F. & Kroner, Kenneth F., 1995. "Multivariate Simultaneous Generalized ARCH," Econometric Theory, Cambridge University Press, vol. 11(01), pages 122-150, February.
- 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.
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