What is the Intrinsic Value of the Dow

We model the time-series relation between price and intrinsic value as a cointegrated system, so that price and value are long-term convergent. In this framework, we compare the performance of alternative estimates of intrinsic value for the Dow 30 stocks. During 1963-1996, traditional market multiples (e.g., B/P, E/P, and D/P ratios) have little predictive power. However, a V/P ratio, where V is based on a residual income valuation model, has statistically reliable predictive power. Further analysis shows time-varying interest rates and analyst forecasts are important to the success of V Alternative forecast horizons and risk premia are less important. MOSTFINANCIAL ECONOMISTS AGREE that a stock's intrinsic value is the present value of its expected future dividends (or cash flows) to common shareholders, based on currently available information. However, few academic studies have focused on the practical problem of measuring intrinsic va1ue.l Perhaps the scant attention paid to this important topic reflects the standard academic view that a security's price is the best available estimate of intrinsic value. Consequently, many researchers regard fundamental analysis, the study of public financial information to arrive at an independent measure of intrinsic value, as a futile exercise. The case for the equality of price and value is based on an assumption of insignificant arbitrage costs.2 When information and trading costs are trivial, stock prices should be bid and offered to the point where they fully re' X e e and Swaminathan are at the Johnson Graduate School of Management, Cornell University. Myers is a t the University of Washington. We appreciate the helpful comments from Bill Beaver, Peter Easton, Jim Ohlson, Stephen Penman, Jay Ritter, Terry Shevlin, Robert Shiller, Ren6 Stulz (editor), Dan Thornton, an anonymous referee, and workshop participants at the University of Chicago, Cornell University, Dartmouth College, the University of Florida, N.B.E.R. Behavioral Finance Workshop, the London Business School, the Massachusetts Institute of Technology, Northwestern University, Stanford University, the University of Utah, the University of Washington, and the 1997 Western Finance Association. Ken French kindly provided the industrial portfolio and the factor portfolio returns. Financial analyst earnings forecasts were obtained from I/B/E/S Inc. Some of this work was completed during Lee's tenure as 1995-96 Visiting Economist a t the New York Stock Exchange. Exceptions we discuss later include Penman and Sougiannis (1997), Abarbanell and Bernard (1995), Frankel and Lee (1997, 1998), Kaplan and Ruback (1995), and Campbell and Shiller (1988). See Shleifer and Vishny (1997) for a discussion of the limits of arbitrage. 1694 The Journal of Finance flect intrinsic values. However, when intrinsic values are difficult to measure and/or when trading costs are significant, the process by which price adjusts to intrinsic value requires time, and price does not always perfectly reflect intrinsic value. In such a world, a more realistic depiction of the relation between price and value is one of continuous convergence rather than static e q ~ a l i t y . ~ Once we admit the possibility that price may diverge from value, the measurement of intrinsic value becomes paramount. Aside from an emerging set of studies in the accounting literature which we discuss later, few academic studies to date have directly addressed the many practical problems associated with implementing a comprehensive valuation model. Nor has much attention been paid to the appropriate empirical benchmark(s) for assessing alternative empirical value estimates when price itself is a noisy measure of intrinsic value. In this study, we empirically evaluate several alternative measures for the intrinsic value of the 30 stocks in the Dow Jones Industrial Average (DJIA). As a departure from the current literature, we do not require price to equal intrinsic value a t all times.4 Instead, we model the time-series relation between price and value as a cointegrated system, so that price and value are long-term ~onvergen t . ~ In this framework, we compare alternative empirical estimates of intrinsic value using two criteria: (i) their relative ability to track price variation in the DJIA over time, and (ii) their ability to predict market returns. We show that, under reasonable assumptions, superior empirical estimates of intrinsic value can perform better on either, or even both, dimensions. The ability to predict market returns is important in tactical asset allocation decisions, in which portfolio weights across broad asset classes are determined on the basis of their relative value. The ability to track price variations over time is also important, because it captures the responsiveness of the valuation model to economic forces that affect prices of publicly traded stocks. Valuation models with superior tracking ability can be applied with greater confidence to nontraded stocks-for example, in valuing initial public offerings, or mergers and acquisitions. Perhaps the most direct evidence on the inequality of value and price for equity securities comes from the closed-end fund literature (e.g., Lee, Shleifer, and Thaler (1991), Swaminathan (1996)). The stock prices of these funds clearly do not equal their net asset value, even though net asset values are computed and reported weekly. The evidence instead shows that the price and value of closed-end funds converge over time, so that the fund discount is mean-reverting. * Not all academic studies embrace the equality of price and value. Earlier studies that question this view include Shiller (1984), Summers (1986), DeBondt and Thaler (1987), and Lakonishok, Shleifer, and Vishny (1994). Two nonstationary time series are cointegrated if they are tied together in a long-run equilibrium relation. Formally, if any linear combination of two nonstationary time series can be shown to be a stationary process, then the two time series are said to be cointegrated (Hamilton (1994), Chap. 19). What is the Intrinsic Value of the Dow? This study is related to two streams of literature in accounting and finance. First, our work extends prior studies in finance that examine the relation between market multiples such as the book-to-market ratio (B/P) or the dividend yield (D/P) and subsequent market returns (e.g., Rozeff (1984), Fama and French (1988a, 1989), Campbell and Shiller (1988), Hodrick (1992), MacBeth and Emanuel(1993), and Kothari and Shanken (1997)). These studies evaluate the predictability of market returns using simple valuation heuristics, and they focus on return forecasting rather than valuation issues. The evidence suggests that these simple valuation heuristics may not hold in recent years. For example, the price-to-book ratio (P/B) for the Dow stocks increased from an average of approximately 1.0 in 1979 to more than 3.2 by June 1996. The dividend yield on the Dow stocks has decreased from more than 6 percent to less than 2 percent over the same time period. Whether these trends are due to structural changes (such as lower interest rates, decreased dividend payouts, or growth expectations), or are indicative of market mispricings, is difficult to determine without a more complete valuation model. We use a richer valuation model to address this question. Our results show that time-varying interest rates are an essential part of valuation models in time-series applications. In the post-1963 period, traditional market ratios that omit time-varying interest rates (such as B/P, D/P, and E/P ratios) do not predict U.S. market returns. However, during the same time period, a V/P ratio, in which "V" is estimated using a residual income formula, has reliable predictive power for U.S. market returns. Using a vectorautoregressive (VAR) simulation technique, we show that this result is robust to the inclusion of many factors in the regression, including B/P, D/P, and E/P, as well as the short-term interest rate, the ex ante default risk premium, the ex ante term structure risk premium, and past market returns. Our study is also related to a recent line of research in the accounting literature that explores the empirical properties of the residual-income formula. The valuation equation we implement in this paper is similar to models appearing in recent studies by Abarbanell and Bernard (1995), Frankel and Lee (1997, 1998), Penman and Sougiannis (1997), and Dechow, Hutton, and Sloan (1997). However, these empirical studies examine the ability of the model to explain cross-sectional prices and/or expected returns, whereas our investigation focuses on the time-series relation between value and price. We provide evidence on the sensitivity of this valuation model to various key input parameters for time-series applications. Specifically, we document the effect of altering the forecast horizon (3 years to 18 years), the choice of earnings forecasting method (a historical time-series model versus a model based on analyst consensus forecasts), the choice of risk premia (a marketwide time-varying risk premium, a Fama-French one-factor industry risk premium, or a Fama-French three-factor industry risk premium), and the choice of the riskless rate (short-term T-bill yield versus the long-term Treasury bond yield). 1696 The Journal of Finance Our results show that the inclusion of a time-varying discount rate component is essential to the success of V. Intrinsic value estimates that do not include time-varying discount rates have little predictive power for returns. The choice of the riskless rate is also important. Specifically, value estimates based on short-term T-bill rates outperform value estimates based on long-term Treasury bond rates. Once time-varying interest rates have been incorporated into the estimation process, the addition of analyst forecasts further improves the performance of the value estimate. Specifically,