Article ID: | iaor2009429 |
Country: | Netherlands |
Volume: | 179 |
Issue: | 1 |
Start Page Number: | 186 |
End Page Number: | 202 |
Publication Date: | May 2007 |
Journal: | European Journal of Operational Research |
Authors: | zekici S., elikyurt U. |
Keywords: | markov processes, optimization |
We consider several multiperiod portfolio optimization models where the market consists of a riskless asset and several risky assets. The returns in any period are random with a mean vector and a covariance matrix that depend on the prevailing economic conditions in the market during that period. An important feature of our model is that the stochastic evolution of the market is described by a Markov chain with perfectly observable states. Various models involving the safety-first approach, coefficient of variation and quadratic utility functions are considered where the objective functions depend only on the mean and the variance of the final wealth. An auxiliary problem that generates the same efficient frontier as our formulations is solved using dynamic programming to identify optimal portfolio management policies for each problem.