Multistep predictions for multivariate GARCH models: Closed form solution and the value for portfolio management

Hlouskova, Jaroslava and Schmidheiny, Kurt and Wagner, Martin (2009) Multistep predictions for multivariate GARCH models: Closed form solution and the value for portfolio management. Journal of Empirical Finance, 16 (2). pp. 330-336.

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Abstract or Table of Contents

This 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.

Item Type: Article in Academic Journal
Keywords: Multivariate GARCH models, Volatility forecasts, Portfolio optimization, Minimum variance portfolio
Classification Codes (e.g. JEL): C32, C61, G11
Status: Published
Date Deposited: 26 May 2015 08:19
Last Modified: 01 Apr 2016 14:19
URI: http://irihs.ihs.ac.at/id/eprint/3379

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