This paper examines the dynamics of the covariance matrix of return rates for securitized real estate, other company stocks, and government bonds for a cross-section of eight countries. In-sample analysis establishes that in all countries the covariance matrix is time-varying and reacts stronger to bad than to good news. Using a realistic out-of-sample exercise, we find that portfolios selected with a forecasted dynamic covariance matrix are less risky than portfolios constructed with the static matrix. However, benefits of using the dynamic covariance matrix for active portfolio management are mostly offset by rebalancing cost. Passive buy-and-hold investors benefit, because the forecasted dynamic covariance matrix provides better risk assessment.
- dynamic conditional correlation
- portfolio allocation
- forecast evaluation