Dynamic portfolio optimization with transaction costs and state-dependent drift

The problem of dynamic portfolio choice with transaction costs is often addressed by constructing a Markov Chain approximationof the continuous timeprice processes. Using this approximation,wepresent an efficient numerical method to determine optimal portfolio strategies under timeand state-dependent drift and proportional transaction costs. This scenario arises when investors have behavioral biases or the actual drift is unknown and needs to be estimated. Our numerical method solves dynamic optimal portfolio problems with an exponential utility function for time-horizons of up to 40 years. It is applied to measure the value of information and the loss from transaction costs using the indifference principle. © 2014 Elsevier B.V. All rights reserved.