Multistep predictions for multivariate GARCH models: Closed form solution and the value for portfolio management
AbstractThis paper derives the closed form solution for multistep predictions of the conditional means and covariances for multivariate ARMA-GARCH models. These predictions are useful e.g. in mean-variance portfolio analysis when the rebalancing frequency is lower than the data frequency. In this situation the conditional mean and the conditional covariance matrix of the cumulated higher frequency returns are required as inputs in the mean-variance portfolio problem. The empirical value of the result is evaluated by comparing the performance of quarterly and monthly rebalanced portfolios using monthly MSCI index data across a large set of GARCH models. Using correct multistep predictions generally results in lower risk and higher returns.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Empirical Finance.
Volume (Year): 16 (2009)
Issue (Month): 2 (March)
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Web page: http://www.elsevier.com/locate/jempfin
Multivariate GARCH models Volatility forecasts Portfolio optimization Minimum variance portfolio;
Other versions of this item:
- Jaroslava HLOUSKOVA & Kurt SCHMIDHEINY & Martin WAGNER, 2004. "Multistep Predictions for Multivariate GARCH Models: Closed Form Solution and the Value for Portfolio Management," Cahiers de Recherches Economiques du DÃ©partement d'EconomÃ©trie et d'Economie politique (DEEP) 04.10, Université de Lausanne, Faculté des HEC, DEEP.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
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