  In this work we present a model for the solution of the multi-period
portfolio selection problem. The model is based on a time consistent dynamic
risk measure. We apply l1-regularization to stabilize the solution process and
to obtain sparse solutions, which allow one to reduce holding costs. The core
problem is a nonsmooth optimization one, with equality constraints. We present
an iterative procedure based on a modified Bregman iteration, that adaptively
sets the value of the regularization parameter in order to produce solutions
with desired financial properties. We validate the approach showing results of
tests performed on real data.
