We present a new method to obtain a conditional mean vector and a conditional covariance matrix when given an investor's view about return profiles of certain assets. The method extends earlier results that were limited to the conditional mean. The new method allows an investor to express views on return means, volatilities, and correlations. An application of our results illustrates how a single anticipated volatility shock spreads to other assets and increases the correlation coefficients among assets. Another application shows how a flight-to-quality event affects volatilities and correlations. Based on the conditional mean and covariance matrix, we then derive analytically an optimal mean–variance portfolio and discuss its implications for asset allocation.