Different Probability Distributions for Portfolio Selection in the Chance Constrained Compromise Programming Model
The Chance Constrained Compromise Programming model has been utilized for the multi-attributes financial portfolio selection where several conflicting and incommensurable objectives are optimized simultaneously. This model is based on the assumption that the aspiration levels of the objectives are normally distributed with known means and variances. The aim of this paper is to extend this model to other probability distributions such as uniform, triangular and skew triangular. The different formulations will be illustrated through twenty five securities from the Toronto stock exchange market.
chance constrained compromise programming model multi-attribute financial portfolio selection stochastic modelling