A python-based multicriteria portfolio selection DSS

Our purpose in this article is to develop an integrated portfolio management decision support system, which takes into account the inherent multidimensional nature of problem, while allowing DM, i.e . investor, incorporate his/her preferences process. The proposed DSS has been developed Python programming language and consists two components: first component associated with security selection phase, second optimization phase. In four discrete multicriteria methods are employed; PROMETHEE II, ELECTRE III, MAUT TOPSIS. After cumulative integration results, a series mathematical models applied that optimization; mixed-integer quadratic model, goal genetic algorithm multiobjective flow model. Finally, approach tested through large-scale illustrative application several stock markets various sectors, analyzing simultaneously very large number securities.