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

Hlouskova, Jaroslava; Schmidheiny, Kurt; Wagner, Martin (November 2002). Multistep Predictions from Multivariate ARMA-GARCH Models and their Value for Portfolio Management (Diskussionsschriften 02-12). Bern: Universität Bern Volkswirtschaftliches Institut

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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.

Item Type:

Working Paper

Division/Institute:

03 Faculty of Business, Economics and Social Sciences > Department of Economics

UniBE Contributor:

Wagner, Martin

Subjects:

300 Social sciences, sociology & anthropology > 330 Economics

Series:

Diskussionsschriften

Publisher:

Universität Bern Volkswirtschaftliches Institut

Language:

English

Submitter:

Aline Lehnherr

Date Deposited:

11 Jun 2020 16:23

Last Modified:

06 Aug 2020 14:18

Additional Information:

This work has been supported by OLZ and Partners Asset and Liability Management AG.

JEL Classification:

C32, C61, G11

BORIS DOI:

10.7892/boris.143991

URI:

https://boris.unibe.ch/id/eprint/143991

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