Why does it make sense to use single-period Markowitz mean-variance optimization techniques when we're trying to figure out asset allocation across multiple asset classes (bonds, stocks, REITs, etc)?
Minimizing the variance for a target expected return makes sense to me if you're considering a portfolio of equities. However, including bonds for example complicates things - they have systematic differences from equities such as fixed maturities, periodic coupon payments/reinvestment, depend on interest rate expectations etc. Bonds with a maturity shorter than the investment horizon wouldn't exist at the terminal time in the model. These considerations would naturally be amplified if you're including even more heterogenous asset classes into your portfolio and your optimization problem. The return dynamics would obviously be very different from equities and this seems to be glossed over by the model.
However, I frequently see the standard MVO techniques used to determine asset allocations across equities, fixed income and other classes. Is this theoretically valid? Are there superior techniques for optimizing mixed portfolios?