Using Economic Value Added as a Portfolio Separation Criterion

Introduction Given a particular buy list of stocks, it would be useful to ascertain if one portfolio formed as a subset of the buy list should be expected to outperform another subset portfolio. In other words, is there an economic, financial, or accounting criterion that will allow the buy list to be separated into well-performing versus poorly performing portfolios? Following Cary et al. (2004), we call the process of differentiating between portfolios that are expected to perform well from a buy list and portfolios that are expected to perform poorly from the same list a portfolio separation test. The difficulty, of course, lies in finding an economic, financial, or accounting criterion that results in successful portfolio separation. De Bondt and Thaler (1987) form winner and loser portfolios based on stock performance over the previous five years. They find that the loser portfolios outperform the winner portfolios over the next three years. Chopra, Lakonishok, and Ritter (1992) find similar reversal results where poorly (well) performing stocks in one period tend to outperform (underperform) in following periods. Several studies, including Stewart (1994) and Lehn and Makhija (1996), find that there is a positive correlation between market value added (MVA) and stock price performance. MVA is the difference between the market value of a company and the capital contributed by both stockholders and bondholders. A positive MVA shows that firm management has generated wealth for the firm's shareholders over the life of the firm. Noting the positive correlation between MVA and stock price, Cary et al. (2004) hypothesize that portfolios that are selected based on changes in MVA over the course of a year can be used to separate higher and lower performing portfolios. Testing this hypothesis empirically, they find that ranking their buy list by the change in MVA as a percentage of market capitalization successfully separates portfolios formed from the top 100 (the winner portfolio) and bottom 100 (the loser portfolio) stocks in the buy list. They find that winner portfolios outperform loser portfolios. In addition, Cary et al. (2004) test to see if the difference in cumulative returns between the winner and loser portfolios is statistically significant, and they find that it is. Testing to see if the cumulative difference in returns between the two portfolios is statistically significant is an important extension of current practice. In Cary et al. (2004) it shows that MVA is an economically useful criterion for portfolio separation. This is an interesting finding, but it raises the question of whether other criteria can be used in a portfolio separation test and if another criterion can do a better job of portfolio separation than MVA. Therefore, this paper uses the methodology developed in Cary et al. (2004) and extends their work by looking at economic value added (EVA) rather than MVA as a portfolio separation criterion. We also extend the work in Cary et al. (2004) by including data from the bear market from 2000 through 2002. The Cary et al. (2004) data come from the primarily bull market period of 1990 to 1999. Theoretical Background Obviously, MVA is not the only criterion that can be used to test for portfolio separation. But the success of MVA when used for portfolio separation suggests that a criterion similar to MVA also might be effective (or perhaps even more effective) as a portfolio separator. Theoretically, MVA is equal to the present value of the yearly EVA that a firm is expected to generate. Given that MVA can be used for portfolio separation, the close theoretical relationship between MVA and EVA suggests that EVA also might be an effective criterion for portfolio separation. EVA was developed and promoted by the consulting firm Stem Stewart & Co. Stewart (1991) gives a detailed description of the theoretical underpinnings of EVA and also shows many examples of how to estimate EVA empirically. …