Abstract
In a group decision method on ranking a large number of stocks, multiple stocks are re-grouped into subgroups, and each stock in every subgroup is evaluated based on information of each stock to generate a ranking number for each stock in every subgroup. Then, a normalized score for each stock in every subgroup is determined. After a number of iterations of re-grouping, evaluation, and ranking, an average normalized score for each stock is generated, so as to increase the accuracy of ranking stocks in a large scale evaluation process.