We solve the dynamic mean-variance portfolio problem and derive its time-consistent solution using dynamic programming. Previous literature, in contrast, only determines either myopic or precommitment (committing to follow the initially optimal policy) solutions. We provide a fully analytical simple characterization of the dynamically optimal mean-variance portfolios within a general incomplete-market economy. We also identify a probability measure that incorporates intertemporal hedging demands and facilitates tractability. We illustrate this by easily computing portfolios explicitly under various stochastic investment opportunities. A calibration exercise shows that the mean variance hedging demands are economically significant
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