Application of fuzzy multiple attribute decision making on company analysis for stock selection

The investor has to consider many factors when making a decision on which stock(s) to buy. However, judgements on these factors are usually linguistic, fuzzy, and conflicting. Therefore, selection of stocks is one of the fuzzy multiple attribute decision making (FMADM) problems. In this paper, A hierarchical composite structure for factors and subfactors is developed for company analysis. A weight model is presented. Values of each subfactor are assumed to have normal distribution in order to build up the membership function of the ascending half-trapezoid. By multiplying weight matrix with the corresponding fuzzy judgement matrix for each factor and calculating the weighted summation of weighted matrices, we make the fuzzy decision by grades. A numerical example of selecting the first priority stock among seven listed companies of cement industry in Taiwan's stock market is applied to verify this model.