An extension of Data Envelopment analysis to equity valuation

Abstract

Data envelopment analysis (DEA) has been widely used in efficiency evaluation since the late 1970s. In this study, we apply the DEA method for the first time to the relative valuation of equities in financial markets from the perspective of investors. We propose a general framework and a specific method, called efficient facet analysis, to classify shares into three categories. We further choose input and output variables and use shares listed in Shanghai and Singapore as example to demonstrate its capacity in identifying overvalued and undervalued shares. Comparing with the widely used P/E (price/earning) ratio method and the newly developed PE/growth ratio method, we find that the results from the DEA method are better in the equity valuation, especially in identifying undervalued shares. We highlight both benefits and limitations of DEA application to equity valuation as well as future research direction.