Ex ante performance from ex post models of global equity market correlations

Analysis of ex post returns reveals the time series properties of correlations, but ex ante correlations are required for efficient diversification. We find that a time-varying parameter model offers the best fit to ex post global equity market correlations, suggesting changing mean correlations and changing rates of adjustment back to the means. Nevertheless, we do not find improved forecast performance from time-varying parameter models in holdout periods. The added complexity of time-varying models does not translate into lower forecast errors.