A fuzzy-MCDM based value investing method for banking stocks evaluation

Stock investing decisions are always made under a dynamic, complex and risky environment. In the long run, investors must rely on the invested companies´ financial outcomes to share with their equity shareholders. Thus, in the stock market, Arms´ financial statements should be scrutinized and diagnosed before making investment decisions, which is so-called fundamental analysis. Although scholars and investment professionals have proposed some investing rules to outperform market, few robust methods are available to meet this goal. Among previous studies, the accounting-based fundamental analysis (F-Score) [1] has been a widely accepted model for value investing. However, the manner which is based on financial information and traditional regression models would face difficulty of acquiring implicit knowledge and interactive considerations of senior experts. To improve the applicability of F-Score system, this research integrates fuzzy set theory and decision method for multiple criteria to propose an innovative model for distinguishing strong financial prospect stocks among high book-to-market (B/M) banking stocks. Our empirical study shows the practicability of the proposed model.