AN APPLICATION OF DATA ENVELOPMENT ANALYSIS IN RELATIVE VALUATION OF EQUITIES

Abstract

Data envelopment analysis (DEA) has been widely used in efficiency evaluation among various organisations since the late 70s. In this research, DEA method is firstly applied to value shares that are traded in the financial market. Then the facet analysis is developed to further match two sub-groups generated in initial DEA analysis, efficient group and inefficient one, with three traditional market valuations, namely, overvalued, fairly valued, and undervalued. After the DEA modeling two DEA models, the Additive DEA model and the Stochastic DEA model are applied to companies listed in real stock markets. The results are verified by checking their market performances in the following year, and are compared with that of the traditional PIE (price/earning) ratio method. Two groups of market data from the Shanghai Securities Exchange (SSE) and the Stock Exchange of Singapore (SES) are chosen as research samples. The results show that the Additive DEA model is the best among the three methods. Thus, it is concluded that the Additive DEA is valuable for equity valuation.