Before revision: We develop an efficient method for solving dynamic portfolio selection problems in the presence of transaction cost, liquidity cost and market impact. Our method , based on least-squares Monte Carlo simulation, has no restriction on return dynamics, portfolio constraints, intermediate consumption and investor's objective. We model return dynamics as exogenous state variables and model portfolio weights, price dynamics and portfolio value as endogenous state variables .
After revision: We develop an efficient method for solving dynamic portfolio selection problems in the presence of general transaction costs, liquidity costs and market impacts. This method extends the classical least squares Monte Carlo algorithm to incorporate switching costs, corresponding to transaction costs and transient liquidity costs, as well as multiple endogenous state variables .