In a typical tactical asset allocation setup, managers generally make their choices with the aim of beating a benchmark portfolio. In this context, the pure Markowitz (1959) strategy does not take two aspects into account: asset returns often show changes in volatility and managers’ decisions depend on private information. This paper provides an empirical model for large-scale tactical asset allocation with multivariate GARCH estimates, given a tracking error constraint. Moreover, the Black and Litterman (1991) approach makes it possible to tactically manage the selected portfolio by combining information taken from the time-varying volatility model with some personal ‘views’ about asset returns.

Multivariate GARCH Models and Black-Litterman Approach for Tracking Error Constrained Portfolios: An Empirical Analysis

PALOMBA, Giulio
2008-01-01

Abstract

In a typical tactical asset allocation setup, managers generally make their choices with the aim of beating a benchmark portfolio. In this context, the pure Markowitz (1959) strategy does not take two aspects into account: asset returns often show changes in volatility and managers’ decisions depend on private information. This paper provides an empirical model for large-scale tactical asset allocation with multivariate GARCH estimates, given a tracking error constraint. Moreover, the Black and Litterman (1991) approach makes it possible to tactically manage the selected portfolio by combining information taken from the time-varying volatility model with some personal ‘views’ about asset returns.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/36031
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