A Novel Grey Relation Method with Analytic Hierarchy Process for Stock Selection

Abstract

This paper presents a multiple criteria decision support approach in order to build a ranking and suggest a best choice1 on a set of alternatives. The decision of how to choose a group of optimal stocks in the stock market is a basic problem in the stock investment process. This research describes a AHP (analytic hierarchy process) to determine the weighting of subjective judgments and a synthetic evaluation system is proposed on the basis of a novel grey multi-hierarchy decision method to select stocks based on their qualitative and quantitative data. The developed tool can be used for in depth analysis of the stock market. First, Analytic hierarchy process (AHP) is using for the decision of weight of multi-hierarchy and multi-facto. Second, fuzzy set theory is used to deal with quantification of qualitative data. Third, the general selection method selects the optimal value or the idealized value from these original data values as the reference data values. Finally, a novel grey relational coefficient calculated reflects the relational degree between single data and reference data. The order of grey relational grades of the aim layer is just the superior and inferior sequence of these stocks. Then the evaluation system is applied to an example. The results show that the evaluation system can overcome the errors of expert's subjective judgment.