The Role of Correlation Dynamics in Sector Allocation

This paper assesses the role of correlation dynamics in mean-variance sector allocation. A correlation timing framework is deployed to evaluate dynamic strategies against a static constant covariance strategy and the nonparametric RiskMetrics covariance model. We find using sector portfolios in three equity markets that correlation timing is rewarding. We document time-variation, asymmetry and a structural break in sector correlations and show that the predictability of conditional correlation models capturing such features is economically relevant. The incremental value of correlation timing is more pronounced for monthly rather than daily rebalancing and the gains of such strategies are not eroded by transaction costs. Risk-averse monthly investors are willing to pay up to 1000 bp per annum for switching from a static strategy to a dynamic correlation strategy. In contrast, the RiskMetrics proves relatively trade intensive and sustains no net performance gains