چكيده به لاتين
Abstract:
The portfolio selection (stock) is one of the most important issues in the field of investment management. The first model is based on risk and return to the issues raised by Markowitz in 1952 that is known to the mean-variance.The problem of dynamic portfolio choice with transaction costs is often addressed by constructing a Markov Chain approximation of the continuous time price processes. Using this approximation,we present an efficient numerical method to determine optimal portfolio strategies under time-and 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 exponentialutility 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.
Keywords: Dynamic programming,Markov Chain approximation,Numerical methods,State-dependent drift,Transaction costs
