Investigating Efficiency Stock Ranking Based on CANSLIM Analysis Criteria Using Fuzzy Multiple Attribute Decision Model

Investors mostly rely on fundamental and technical analysis in applying past and present information to choose the optimum stock and its future trend in an attempt to increase returns. The present study investigates the relationship factors ranking of CANSLIM model in synthetic fundamental-technical model by Fuzzy Multiple Attribute Decision method with stock return using econometric models. The variables of the CANSLIM model include the percentage of seasonal earnings, the percent of change in annual profit, the new price, level Free Float Stock, the leading, the support of institutional investors, and the direction of the market (changes in the total index). The study also weighs stock by the Fuzzy-AHP using CANSLIM criteria, and measures its efficiency using TOPSIS technique is ranked annually. Population of the study includes 73 companies listed at stock exchange during 2010-2017 Multi-variable regression analysis based on synthetic and panel data was used. Results of testing hypotheses revealed direct effects of rating factors: percent of seasonal earnings change, percentage of annual profit changes, industry leading companies, free float stocks, CANSLIM model on stock returns.