Forecasting correlations during the late-2000s financial crisis: short-run component, long-run component, and structural breaks

Abstract

We empirically investigate the predictive power of the various components affecting correlations that have been recently introduced in the literature. We focus on models allowing for a flexible specification of the short-run component of correlations as well as the long-run component. Moreover, we also allow the correlation dynamics to be subjected to regime-shift caused by threshold-based structural breaks of a different nature. Our results indicate that in some cases there may be a superimposition of the long- and short-term movements in correlations. Therefore, care is called for in interpretations when estimating the two components. Testing the forecasting accuracy of correlations during the late-2000s financial crisis yields mixed results. In general component models allowing for a richer correlation specification possess a (marginally) increased predictive accuracy. Economically speaking, no relevant gains are found by allowing for more flexibility in the correlation dynamics.Correlation forecasting; Component models; Threshold regime-switching models; Mixed data sampling; Performance evaluation