Volatility-dependent correlations: further evidence of when, where and how

This paper expands on the usefulness of conditioning correlations on market volatility to generate forecasts of the covariance matrix in two contexts: within a single market and between several international markets. The dynamic conditional correlation family provides an illustration of the relationship between volatility and correlation. We use a portfolio allocation problem to compare covariance forecasts over a range of portfolio sizes and sub-samples of high and low market volatility. Findings confirm recent results for these models in comparable examples and extend these results through the two comprehensive out-of-sample analyses including large dimensional and international settings. This study furthers our understanding of the linkage between volatility and correlations and provides guidance for exploiting correlation’s dependence on volatility, emphasising its importance for differing market states and portfolio characteristics.