  Correlations between asset returns are important in many financial
applications. In recent years, multivariate volatility models have been used to
describe the time-varying feature of the correlations. However, the curse of
dimensionality quickly becomes an issue as the number of correlations is
$k(k-1)/2$ for $k$ assets. In this paper, we review some of the commonly used
models for multivariate volatility and propose a simple approach that is
parsimonious and satisfies the positive definite constraints of the
time-varying correlation matrix. Real examples are used to demonstrate the
proposed model.
