Multistep Predictions from Multivariate ARMA-GARCH: Models and their Value for Portfolio Management

Hlouskova, Jaroslava and Schmidheiny, Kurt and Wagner, Martin. (2009) Multistep Predictions from Multivariate ARMA-GARCH: Models and their Value for Portfolio Management. Journal of Empirical Finance, 16. pp. 330-336.

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In this paper we derive the closed form solution for multistep predictions of the conditional means and their covariances from multivariate ARMA-GARCH models. These 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 covariance matrix of the sum of the higher frequency returns until the next rebalancing period is required as input in the mean variance portfolio problem. The closed form solution for this quantity is derived as well. We assess the empirical value of the result by evaluating and comparing the performance of quarterly and monthly rebalanced portfolios using monthly MSCI index data across a large set of ARMA-GARCH models. The results forcefully demonstrate the substantial value of multistep predictions for portfolio management.
Faculties and Departments:06 Faculty of Business and Economics > Departement Wirtschaftswissenschaften > Professuren Wirtschaftswissenschaften > Angewandte ├ľkonometrie (Schmidheiny)
UniBasel Contributors:Schmidheiny, Kurt
Item Type:Article, refereed
Article Subtype:Research Article
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:24 Jan 2024 16:09
Deposited On:10 Apr 2017 11:39

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