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

Jaroslava Hlouskova, Kurt Schmidheiny and Martin Wagner

Journal of Empirical Finance, 2009, vol. 16, issue 2, 330-336

Abstract: 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.

Keywords: Multivariate; GARCH; models; Volatility; forecasts; Portfolio; optimization; Minimum; variance; portfolio (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (5)

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Working Paper: Multistep Predictions for Multivariate GARCH Models: Closed Form Solution and the Value for Portfolio Management (2004)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:16:y:2009:i:2:p:330-336

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