Equity Valuation Using Multiples: An Empirical Investigation

Literature review 17information, enterprise value to sales (EV/SA) multiples, adjusted by differences insales growth and profitability (i.e., operating cash flow to sales), work reasonablywell.Lie & Lie (2002) examine the valuation accuracy of a conventional list ofmultiples for the universe of companies within the Compustat North America database.In line with the studies we already examined, Lie & Lie (2002) report superiorperformance of forward-looking P/E multiples compared to all other multiples.They also show that for trailing multiples, book values yield more accurate predictionsthan measures from the income statement (i.e., sales, EBITDA, earnings beforeinterest and taxes (EBIT), and earnings) within their sample. This result, however,conflicts with Liu, Nissim & Thomas (2002a) and Kim & Ritter (1999), wherethe cross-sectional performance of book values is relatively poor.Taken together, the empirical findings in favor of forward-looking multiplesare persuasive. Other results, however, are quite diverse, which is likely caused bydifferent research settings.2.2.3 Identification of comparable firmsNone of the studies above addresses the choice of comparable firms beyondnoting the usefulness of industry groupings. Boatsman & Baskin (1981) comparethe accuracy of P/E multiples from the same industry. They show that relative torandomly chosen firms, valuation errors are smaller when comparable firms arematched on the basis of similar historical earnings growth.Alford (1992) uses P/E multiples to test the effects of different methods ofidentifying comparables based on industry membership and proxies for growth andrisk on the precision of valuation estimates. He finds that while valuation accuracyincreases when the fineness of the industry definition used to identify comparablefirms is narrowed from broad 1-digit Standard Industrial Classification (SIC) codesto 2-digit and 3-digit SIC codes, there are no further improvements when 4-digitSIC codes are considered. He also finds that adding controls for earnings growth,leverage, and size does not significantly reduce valuation errors.Bhojraj & Lee (2002) revive the idea of Alford (1992) of matching comparablefirms based on underlying economic variables, instead of industry membership.To do so, they first develop a multiple regression model to predict a “warranted”