Prospect theory based portfolio optimization problem with imprecise forecasts

In this paper we propose a novel interval optimization approach for portfolio selection when imprecise forecasts are available. We consider investors acting their choices according to the prospect theory, where scenarios are provided in the form of approximate numbers. The resulting constrained nonlinear interval optimization problem is converted into two nonlinear programming problems using a total order relation between intervals. Static and dynamic analysis of portfolios involving assets from the Croatian market illustrate the potential of the method with respect to the standard procedure.