Stochastic correlation across international stock markets

This paper examines the correlation across a number of international stock market indices. As correlation is not observable, we assume it to be a latent variable whose dynamics must be estimated using data on observables. To do so, we use filtering methods to extract stochastic correlation from returns data. We find evidence that the estimated correlation structure is dynamically changing over time. We also investigate the link between stochastic correlation and volatility. In general, stochastic correlation tends to increase in response to higher volatility but the effect is by no means consistent. These results have important implications for portfolio theory as well as risk management.