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The Accuracy and Bias of Equity Values Inferred from Analysts' Earnings Forecasts
Abstract
We evaluate the extent to which unbiased and accurate estimates of equity value can be derived from three multi-period accounting-based valuation models using consensus analysts' earnings forecasts over a four-year horizon. The models are: (a) the earnings capitalization model, (b) the residual income model without a terminal value, and (c) the residual income model with a terminal value that assumes residual income will grow beyond the horizon at a constant rate determined from the expected residual income growth rate over the forecast horizon. Our analysis is based on valuation errors that are calculated by comparing estimated prices to actual prices. We find that, on average, analysts' earnings forecasts convey information about value beyond that conveyed by current earnings, book values and dividends. Each of the models that we used has valuation errors that decline monotonically as the horizon increases, implying that earnings forecasts at each horizon convey new value relevant information. We cannot find a clear advantage to using firm specific growth rates instead of a constant rate of 4% across all sample firms. In addition, only 17% of the imputed growth rates could be used in terminal value calculations. The residual income model with a terminal value shows the best performance on average, but it values more accurately only 48% of our sample firms. The earnings capitalization model and the residual income model without a terminal calculation value more accurately 18% and 13% of the sample firms, respectively. The remaining 21% of firms are more accurately valued using only reported current earnings and book values of equity. Thus, different models are appropriate for different firms. The conditions under which given models work best relate to ex-ante growth indicators such as the current book-to-market, earnings-to-price, the present value of the expected residual income over the forecast horizon, the growth rate in expected earnings, and firm size, but not to industry membership. In all models estimated prices are, on average, downward biased and inaccurate and they explain at best 70% of the variation in market prices. We examined the quality of the earnings forecasts and the quality of the GAAP earnings as two possible reasons for the biased and inaccurate results. Our tests provide evidence consistent with both of these reasons. Thus, we conclude that the poor model performance is due to information missing from the forecasts and to the practice of conservative accounting.
... Bradshaw (2004) finds that analysts use their long-term earnings growth forecasts in formulating stock recommendations. Moreover, prior studies plug in up to five years of analysts' earnings forecasts into earningsbased valuation models to infer the implied cost of capital (e.g., Botosan & Plumlee, 2005; Claus & Thomas, 2001; P. Easton, Taylor, Shroff, & Sougiannis, 2002) or assess firms' intrinsic values (e.g., Frankel & Lee, 1998; Sougiannis & Yaekura, 2001). When earnings forecasts serve as inputs to valuation models, the accuracy of the earnings forecasts directly affects the estimates of cost of capital and intrinsic values. ...
... P. Easton and Monahan (2005) show that cost of capital derived from analysts' earnings forecasts is negatively correlated with realized returns after controlling for proxies for cash flow news and discount rate news. Similarly, prior studies (e.g., Francis, Olsson, & Oswald, 2000; Sougiannis & Yaekura, 2001) find large valuation errors from valuation models that use analysts' forecasts as a proxy for future earnings. Evidence in P. Easton and Monahan (2005) and Sougiannis and Yaekura (2001) suggests that their aforementioned findings are partially due to problems with analyst earnings forecast quality. ...
... Similarly, prior studies (e.g., Francis, Olsson, & Oswald, 2000; Sougiannis & Yaekura, 2001) find large valuation errors from valuation models that use analysts' forecasts as a proxy for future earnings. Evidence in P. Easton and Monahan (2005) and Sougiannis and Yaekura (2001) suggests that their aforementioned findings are partially due to problems with analyst earnings forecast quality. Therefore, it is important to examine the performance of analysts' forecasts against alternative sources of earnings forecasts such as statistical models. ...
We evaluate the performance of financial analysts versus naïve models in making long-term earnings forecasts. Long-term earnings forecasts are generally defined as third-, fourth-, and fifth-year earnings forecasts. We find that for the fourth and fifth years, analysts' forecasts are no more accurate than naïve random walk (RW) forecasts or naïve RW with economic growth forecasts. Furthermore, naïve model forecasts contain a large amount of incremental information over analysts' long-term forecasts in explaining future actual earnings. Tests based on subsamples show that the performance of analysts' long-term forecasts declines relative to naïve model forecasts for firms with high past earnings growth and low analyst coverage. Furthermore, a model that combines a naïve benchmark (last year's earnings) with the analyst long-term earnings growth forecast does not perform better than analysts' forecasts or naïve model forecasts. Our findings suggest that analysts' long-term earnings forecasts should be used with caution by researchers and practitioners. Also, when analysts' earnings forecasts are unavailable, naïve model earnings forecasts may be sufficient for measuring long-term earnings expectations.
... The Residual Income Model (RIM) is a widely used theoretical framework for equity valuation based on accounting data (Peasnell 1982, Ohlson 1995, Penman and Sougiannis 1998, Frankel and Lee 1998, DeChow et al. 1999, Myers 1999, Francis et al. 2000, Sougiannis and Yaekura 2001, Baginsky and Wahlen 2003, Choi et al. 2006). In the RIM, the stock price of a single firm is a function of book value, a series of abnormal earnings, and other information captured via t v. Prior research has applied the RIM using annual earnings, but not quarterly earnings, presumably to avoid seasonality in quarterly data. ...
... Specifically, I define abnormal earnings as the difference between analyst forward earnings forecast (best knowledge of actual earnings) and the earnings number achieved under growth of book value at the normal discount rate. This approach recognizes analyst forecasts as essential signals of firm valuation (Frankel and Lee 1998, Francis et al. 2000, Sougiannis and Yaekura 2001Besides using new data, this paper also discusses a new view of the theoretical RIM, specifically the role of other information captured in t v. In prior research, t v is modeled as impacting future abnormal earnings, but this creates an intermediate step in forecasting stock price because future earnings must be estimated first to estimate stock price. ...
... Focusing on SP500 industrial firms,For a brief review of prior forecast results, prior valuation studies based on the RIM have obtained very large forecast errors, although the RIM is found to produce more accurate forecasts than alternatives such as the dividend discount model and the free cash flow model (Penman andSougiannis 1998, Francis et al. 2000). Forecast errors are disturbingly large, and valuations tend to understate stock price (Choi et al. 2006, Sougiannis and Yaekura 2001, Frankel and Lee 1998, DeChow et al. 1999, Myers 1999).Myers (1999), summarizing studies using in-sample forecasts, state that value estimates understate stock price by 10 to 40 percent on average. The errors are larger with out-ofSection 4 describes the results of estimating jointly the RIM regressions and the time series models of t v , and discusses the forecast results. ...
... 4 This result is consistent with the notion that VL terminal price forecasts contain bias/ measurement error. Finally, Sougiannis and Yaekura (1997) explore the valuation errors associated with several GAAP-based RIM valuation models using I/B/E/S rather than VL forecast data. For RIM with conventional non price-based terminal value expressions at a horizon five years hence, they obtain median signed (absolute) valuation errors of -26 (35) percent. ...
... For RIM with conventional non price-based terminal value expressions at a horizon five years hence, they obtain median signed (absolute) valuation errors of -26 (35) percent. As we will see later, the magnitudes of these errors are comparable to our RIM 5 The version of our RIM models that is closest to Sougiannis and Yaekura (1997) is RIM2, which assumes a 2 percent growth rate. As reported in Section 5.1, the signed and absolute median valuation errors for that model are - 29.00% and 32.72%, respectively, comparable to those documented by Sougiannis and Yaekura (1997) using I/B/E/S data. ...
... As we will see later, the magnitudes of these errors are comparable to our RIM 5 The version of our RIM models that is closest to Sougiannis and Yaekura (1997) is RIM2, which assumes a 2 percent growth rate. As reported in Section 5.1, the signed and absolute median valuation errors for that model are - 29.00% and 32.72%, respectively, comparable to those documented by Sougiannis and Yaekura (1997) using I/B/E/S data. 8 errors for valuation estimates that do not employ VL terminal stock price forecasts. ...
Recently, Penman and Sougiannis (1998) and Francis, Olsson and Oswald (1999) compared the bias and accuracy of the dividend discount model (DDM), discounted cash flow model (DCF), and Edwards-Bell-Ohlson residual income model (RIM) in explaining the relation between value estimates and observed stock prices. Both studies report that, with non price-based terminal values, RIM outperforms DCF and DDM. Our primary research objective is to explore whether, over a five-year valuation horizon, DDM, DCF and RIM are empirically equivalent when Penman's (1998) theoretically "ideal" terminal value expressions are employed in each model. Using Value Line terminal stock price forecasts at the horizon to proxy for such values, we find empirical support for the prediction of equivalence between these three price-based valuation models. Our secondary research objective is to demonstrate that, within each class of the DCF and RIM valuation models, the model that employs Value Line forecasted price in the terminal value expression will generate the lowest pricing errors, compared to models that employ non price-based terminal value under an arbitrary growth assumption. Results indicate that, for both DCF and RIM, price-based valuation models outperform the corresponding non price-based models by a wide margin. We also revisit the issue of the apparent superiority of RIM, and find that this result does not hold in a level playing field where an approximation of ideal terminal values is employed. In fact, the price-based RIM model is marginally outperformed by the price-based DCF and DDM models, in terms of pricing errors as well as its ability to explain current market price.
... Abnormal earning is defined as the difference between analyst earnings forecast (best knowledge of actual earnings) and the earnings number achieved under growth of book value at a normal discount rate. Underlying this definition are the ideas that analyst earnings forecasts are essential signals of firm valuation (following Frankel and Lee 1998, Francis et al. 2000, and Sougiannis and Yaekura 2001), that analyst information is fully and quickly reflected in stock price (see Yen and Lee 2008 for a thorough discussion of the efficient market hypothesis), and that time series information are useful (Dopuch et al. 2008). Next, I demonstrate how to improve the implementation of the RIM. ...
... The errors are larger with out-ofsample forecasts, because the new observations to be forecasted are farther from the center of the estimation sample. The large errors could be due to many factors, including inappropriate terminal values, discount rates, growth rate (Lundholm and O'Keefe 2001, and Sougiannis and Yaekura 2001), model specification (Tsay et al. 2008), and autocorrelation as argued in this paper. This paper discusses how to address the autocorrelation factor to improve RIM-based stock price forecasts. ...
... The theoretical RIM could be mis - specified , for example due to violation of the clean - surplus assumption , or due to non - linear relationships between price and accounting variables ( Morel 2003 ) . Also , the cost of capital is likely measured with error , resulting in large errors in price forecasts ( Sougiannis and Yaekura 2001 ) . Therefore , future research addressing these issues may yield more accurate price forecasts . ...
The main purpose of this paper is to demonstrate a method to forecast stock price using analyst earnings forecasts as essential
signals of firm valuation. The demonstrated method is based on the residual income model (RIM), with adjustment for autocorrelation.
Over the past decade, the RIM has been widely accepted as a theoretical framework for equity valuation based on fundamental
information from financial reports. This paper shows how to implement the RIM for forecasting and how to address autocorrelation
to improve forecast accuracy. Overall, this paper provides a method to forecast stock price that blends fundamental data with
mechanical analyses of past time series.
KeywordsFinancial analyst–Earnings forecast–Forecasting model–Price forecast–Residual income model–Valuation
... Specifically, I define abnormal earnings as the difference between analyst forward earnings forecast (best knowledge of actual earnings) and the earnings number achieved under growth of book value at the normal discount rate. This approach recognizes analyst earnings forecasts as essential signals of firm valuation (following Frankel andLee 1998, andSougiannis andYaekura 2001), that analyst information is fully and quickly reflected in stock price (see Yen and Lee 2008 for a thorough discussion of the efficient market hypothesis), and that time series information are useful (Dopuch et al. 2008). ...
... Specifically, I define abnormal earnings as the difference between analyst forward earnings forecast (best knowledge of actual earnings) and the earnings number achieved under growth of book value at the normal discount rate. This approach recognizes analyst earnings forecasts as essential signals of firm valuation (following Frankel andLee 1998, andSougiannis andYaekura 2001), that analyst information is fully and quickly reflected in stock price (see Yen and Lee 2008 for a thorough discussion of the efficient market hypothesis), and that time series information are useful (Dopuch et al. 2008). ...
... The Residual Income Model (RIM) is widely used as a framework for accounting-based equity valuation (Ohlson, 1995). However, empirical implementations of the RIM yield very large forecast errors, casting doubt on the theoretical model (Myers, 1999; DeChow et al., 1999; Sougiannis and Yaekura, 2001). In this paper, we use Bayesian statistics to improve the accuracy of stock price forecasts based on the RIM. ...
... Although the Residual Income Model (RIM) has been embraced enthusiastically as a theoretical framework for equity valuation (Ohlson, 1995), it has not fared well in empirical testing (Myers, 1999; DeChow et al., 1999; Sougiannis & Yaekura, 2001). Many implementations of the model have yielded high valuation errors. ...
Over the past decade of accounting and finance research, the Residual Income Model (RIM) as proposed by Ohlson (1995) has often been applied as a framework for equity valuation. In this paper, we apply transformations and Bayesian statistics to the RIM, and evaluate improvement in predictive power. Specifically, focusing on SP500 firms, we use 23 quarters of data starting in Q1 1999 to estimate the prediction models, which we then use to predict stock price in Q4 of 2004. We use two types of estimation approaches, maximum likelihood as commonly used in prior research and Bayesian statistics. We find that our maximum likelihood forecast errors are comparable to prior results. Our Bayesian analyses result in significantly smaller predictive errors than our maximum likelihood analyses. We perform several transformations, however transformations of the maximum likelihood models do not outweigh the usefulness of applying Bayesian statistics. In sum, we propose methods to improve the implementation of the RIM, and our methods yield more accurate price forecasts than commonly-used methods based on the RIM.
... Abnormal earning is defined as the difference between analyst earnings forecast (best knowledge of actual earnings) and the earnings number achieved under growth of book value at a normal discount rate. Underlying this definition are the ideas that analyst earnings forecasts are essential signals of firm valuation (following Frankel and Lee 1998; Francis et al. 2000; Sougiannis and Yaekura 2001), that analyst information is fully and quickly reflected in stock price (see Yen and Lee 2008 for a thorough discussion of the efficient market hypothesis), and that time series information are useful (Dopuch et al. 2008). Next, I demonstrate how to improve the implementation of the RIM. ...
... The theoretical RIM could be mis-specified, for example due to violation of the clean-surplus assumption, or due to non-linear relationships between price and accounting variables (Morel 2003). Also, the cost of capital is likely measured with error, resulting in large errors in price forecasts (Sougiannis and Yaekura 2001). Therefore, future research addressing these issues may yield more accurate price forecasts. ...
Over the past decade of accounting and finance research, the Ohlson model has been often examined as a framework for equity valuation. In this paper, we apply Bayesian statistics to the Ohlson model, and evaluate improvement in predictive power. Specifically, focusing on SP500 firms, we use 23 quarters of data starting in Q1 1999 to estimate the prediction models, which we then use to predict stock price in Q4 of 2004. We use two types of estimation approaches, maximum likelihood and Bayesian statistics. We find that Bayesian analyses generally result in smaller predictive errors than maximum likelihood analyses. We perform several transformations, however transformations of the maximum likelihood models do not outweigh the usefulness of applying Bayesian statistics. We conclude that applying Bayesian statistics is a fruitful way to improve the Ohlson's classical framework for equity valuation.
... Moreover, firm managers also pay attention to analysts' forecast to learn the market expectation to their firms and adjust their business operations accordingly. Financial analysts apply their domain knowledge to generate their earnings forecast using large sets of information, such as proxy statements, published financial reports, conference calls, management communications, behavioral assumptions, and macro-economic conditions [4], [5]. Therefore, analysts' earnings forecast has a superior value in the field of finance. ...
... For instance, in the case of a stock, the intrinsic value from a financial traditional approach is the time discounted value of the free cash flow of the company [5], [6]. There are several issues regarding the intrinsic value approach, such as the need to forecast the cash flows of the company for several years into the future [7] which makes estimates rather challenging. Another issue, from an investor point of view, is that the intrinsic value of the stock and the actual value of the stock, i.e., its price, are not the same. ...
Stock price forecasting is a relevant and challenging problem that has attracted a lot of interest from engineers and scientists. In this paper we apply two techniques for stock price and price intervals forecasting. Both techniques, derived from previous works by the authors, are based on the use of local data extracted from a database. These data are those that correspond to similar market states to the current one. The first technique uses these local data to compute a price forecast by finding an optimal combination of past states that equals the current state. The price forecast is then obtained by combining the past actual prices associated to the past market states. The second technique can be used to forecast prices but its main use is to forecast price intervals that will contain the real future price with a guaranteed probability. This is accomplished by building a probability distribution for the forecasted price and then setting the intervals by a choice of desired percentiles. Thus, this technique can be used in financial risk management. Both techniques are purely data driven and do not need a theoretical description or model of the price trend being forecasted. The proposed techniques adapt very easily to market changes because they use only the subset of the database that it is closer to the current state. Furthermore, the database can be updated as new data is available. Finally, both approaches are highly parallelizable, thus making possible to manage large data sets. As a case study, the proposed approaches have been applied to the k-step forecasting of the Dow Jones Industrial Average index. The results have been validated in relation with some baseline approaches, such as martingale and neural network predictors and quantile regression for the interval forecasting.
... " Among the topics not (adequately) covered by the original paper which we develop here are the following: dividend policy irrelevancy (DPI) and its central role in the model; properties of the primitive variable " x t " and reasons why it makes sense to label it earnings; how one extends the model to incorporate an underlying information dynamic in the spirit of Ohlson (1995); accounting rules and their influence on the model; the ways in which the model can be extended to reflect operating vs. financial activities much like Feltham and Ohlson (1995). Aside from the original OJ paper, and its companion Ohlson (2005), the analysis draws on Christensen and Feltham (2003), Fairfield (1994), Feltham and Ohlson (1995), Ohlson (1995, 1999a, 1999b), Ohlson et al. (2006), Ohlson and Zhang (1999), Olsson (2005), Ozair (2003), Penman (2005 Penman ( , 2006), Ryan (1986), Sougiannis and Yaekura (2001), and Yee (2005, 2006). Finally, we should note here that this paper will not discuss many empirical papers that have looked at, or used, the OJ model and similar valuation formulas (e.g., Botosan and Plumlee, 2005, Begley and Feltham, 2002, Cheng, 2005, Cheng et al., 2006, Daske, 2006, Easton, 2004, Easton, 2006, Easton and Monahan, 2005, Easton et al., 2002, Francis et al., 2004, Gebhardt et al., 2001, Gode and Mohanram, 2003, Hutton, 2000, Ohlson, 2001, Thomas and Zhang, 2006). ...
A recent paper by Ohlson and Juettner-Nauroth (2005) develops a model in which a firm's expected earnings and their growth determine its value. At least on its surface, the model appeals because it embeds the core principle used in investment practice and, further, generalizes the Constant Growth model (Gordon and Williams) without restricting the firm's dividend policy. This text reviews the valuation model and its properties. It also extends previous results by analyzing a number of issues not adequately covered in the original paper. These topics include the precise nature of dividend policy irrelevancy, how the model relates to other well-known valuation models, the role of accounting principles, and how it can be developed on the basis of an underlying information dynamics. A central result shows why the model should be accorded "benchmark" status.
... Note 4. The normalized level of FCF is needed for calculation of a firm's terminal value. We conduct sensitivity analyses for the firms' expected growth rate for perpetuity using various growth rates from 0% to 4% (see Sougiannis and Yaekura (2001)). We report here only the results based on 2% growth. ...
This paper examines the added value of expert valuations and their relationship to corporate governance. The analysis is based on a unique sample of 44 closely held public companies that were appraised by financial experts for transactions outside of the Exchange. Each valuation is examined on the basis of pre- and post-valuation data. Our key findings are: (1)expert valuations are 29% higher than market; (2) in the short-run investors respond cautiously to expert valuation; in the long-run, however, the over-valuation appears to be followed by destruction of their values; (3) both are influenced by the corporate governance structure.
... 27 Information asymmetry around intangibles is a potential source of information risk that disadvantages some firms (e.g., younger firms) by generating higher systematic risk (Clarkson and Thompson 1990). 28 Other evidence suggests the consequences of not identifying and measuring intangible investments may include insider trading (e.g., Aboody and Lev, 2000), mispricing of intangibles-intensive firms (e.g., Chambers, Jennings and Thompson, 2002), and mis-specification of equity valuation models (e.g., Kohlbeck and Warfield, 2007;Sougiannis and Yaekura, 2001). ...
This paper aims to show how firms account for expenditure on their intangible investments and how this influences their decision making processes. Evidence from our survey of 614 large Australian companies show that (1) firms do not systematically identify and separate expenditures on intangible investment from expenditures on tangible investment and operating expenditures; and (2) this leads to an information gap that adversely affects the firm's internal processes for evaluating the decision to invest in intangibles. The paper builds a deductive argument for the use of the general purpose financial reporting system (GAAP) to separate and report the expenditures on intangibles by corporations in a way that is consistent and comparable across firms and over time. Our evidence suggests that investment decisions by management and investors, where intangibles are involved, are likely to be based more on rules-of-thumb than objective evidence.
... Analysts may issue intentionally optimistic forecasts because of incentives to maintain access to managers' private information (Francis and Philbrick 1993; Krishnan and Sivaramakrishnan 1998; Lim 2001), to motivate stock trades (Kim and Lustgarten 1998), to benefit stocks held by in-house mutual funds (Irvine et al. 1998), and to obtain or maintain investment banking business (Dugar and Nathan 1995; Hunton and McEwen 1997; Lin and McNichols 1998; Dechow et al. 2000; Bradshaw et al. 2003). Other exp lanations for optimistic forecasts include justifying favorable stock recommendations (Eames et al. 2002), failing to sufficiently adjust for earnings management (Abarbanell and Lehavy 2003), and choosing to report only on stocks that are 2 Empirical applications of the residual income model often use analysts' forecasts as proxies for the market's expectations of future earnings (e.g., Dechow et al. 1999; Frankel and Lee 1998; Lee et al. 1999; Liu and Thomas 2000; Sougiannis and Yaekura 2001; Ali et al. 2003). Bradshaw (2004) suggests that analysts' recommendations viewed favorably (McNichols and O'Brien 1997). ...
Prior research demonstrates that forecast optimism is, in part, an unintentional consequence of analysts' cognitive reactions to the scenarios managers use to communicate future plans. In two experiments, we examine whether counter-explanation (explaining why managers' plans could fail) limits unintentional forecast optimism. We find that, when compared to analysts who do not generate counter-explanations, analysts who complete the relatively easy task of generating few counter-explanations make less optimistic forecasts, but analysts who complete the relatively difficult task of generating many counter-explanations do not. Results suggest boundary conditions for the effective use of counter-explanation to limit scenario-induced forecast optimism.
... Cooper, Day and Lewis (2001) find that lead analysts have a greater impact on stock prices than follower analysts. Sougiannis and Yaekura (2001) conclude that, on average, analysts' earnings forecasts convey information about value beyond that conveyed by current earnings, book values and dividends. Lim (2001) suggests that positive and predictable bias may be a rational property of optimal earnings forecasts. ...
... This has flowon effects for firm valuation. For example, there is evidence that a lack of publicly reported information about intangible assets provides opportunities for insider trading (Aboody and Lev 2000), leads to mis-pricing of intangibles intensive firms (see Lev 2001; Chambers, Jennings, and Thompson 2002), and mis-specification of commonly used valuation models (Kohlbeck and Warfield 2002; Sougiannis and Yaekura 2001). From an internal perspective, existing studies show that the current regulatory framework impacts on the firm's internal data collection and information systems. ...
... Some studies documented that the value relevance of financial reporting is lower for industries where investments in intangible assets are higher (Lev and Zarowin, 1999; Amir and Lev, 1996; Aboody and Lev, 1998). Other studies (Sougiannis and Yaekura, 2001) have found that conservative accounting, referring among others to intangibles, are responsible for biases and inaccuracy in stock prices estimation, and the inclusion of intangible-related topics can improve the performance of valuation model (Zhang, 2000; Kohlbeck and Warfield, 2002). Moreover, financial analysts with idiosyncratic information can take benefit from firms with highly and unreported intangible investments (Barth, Kasznik and McNichols, 2001; Barron, Byard, Kile and Riedl, 2002). ...
This paper elaborates on the fundamental role that a theory of the firm can play in order to develop a clear and consistent proposal on accounting for and reporting on intangibles.Departing from some criticisms addressed against IAS/IFRS and SFAS, the paper analyses how intangibles could be consistently accounted for and reported on within four different theories of the firm, namely the Agency Theory, the Transaction Cost Economics, the Resource-Based View, and the Dynamic-Capabilities View of the firm.The paper focuses on some specific problems related to the definition and identification of intangibles, to their recognition and finally to their valuation and measurement, and offers a critical understanding of the different proposal on accounting for intangibles developed within the five theories of the firm.So doing, the paper helps to better understand some critical issues, such as the different importance of internally generated intangible asset, their fair-value versus cost-based valuation, and the relative importance of balance sheet and income statement.
... They found that the AE model had a 27% lower absolute prediction error than the FCF model and a 57% lower absolute prediction error than the DD model. Sougiannis and Yaekura (2001) also consider three multiperiod accounting based valuation methods: an earnings capitalization model (similar to FCF), residual income (a version of AE) without a terminal value, and residual income with a terminal value 4 . ...
By analyzing actual cash flows in comparison with enterprise values (market capitalization plus debt minus cash) we document that the market dramatically undervalues firms. The findings suggest that the equity market appears to have an extraordinarily high discount rate which negates future earnings in the calculus of firm value. That is, the discount rate is so high that the vast majority of future cash flows are virtually ignored. Our research finds that stock prices do not reflect future corporate earnings. This finding contrasts with the well known statement in finance textbooks that "the value of a firm equals the present discounted value of future cash flows." In fact, we find that enterprise values are substantially less than the present discounted value of future cash flows. A one-dollar increase in future cash flows produces only a 75 cent increase in a firm's enterprise value (only 15 cents per dollar of future cash flows when company size is controlled).Market support for our findings appears ever day in the business press. For example, the following quote from Bloomberg.com of December 8, 2008 speaks precisely to our findings: Cheapest Stocks Since 1995 Show Cash Exceeds Market By Michael Tsang and Alexis Xydias Dec. 8 (Bloomberg) – "Stocks have fallen so far that 2,267 companies around the globe are offering profits to investors for free. That's eight times as many as at the end of the last bear market, when the shares rose 115 percent over the next year. "The Bank of New York Mellon, for example, on that day December 8th had a market capitalization of 35.83 billion, and cash of $75.50 billion. In this case, the market has an infinite discount rate on any and all future cash flows. The implication of our work is clear: companies are worth far more than the market believes. This provides strong support to the idea behind the private equity industry. We realize that of late private equity firms have overpaid for acquisitions and may lose their entire investment during the current phase of deleveraging. Yet, if private equity firms acquire companies at reasonable prices using less debt, they are likely to create substantial value as a consequence of the fact that companies are so undervalued by the market relative to their cash flows. There are no previous research efforts following our methodological design based on actual cash flows. Rather, prior research studies have focused on the relationship between forecasted cash flows (by market analysts) and enterprise value. Our approach focuses on a different question – the relationship between discounted future cash flows and the current market value as posited by financial theory.
... Optimism in annual earnings forecasts is statistically and economically significant (e.g., Darrough and Russell 2002; Duru and Reeb 2002) and increases over the forecast horizon: analysts' two-year-ahead forecasts are relatively more optimistic than their one-year-ahead forecasts (DeBondt and Thaler 1990; Frankel and Lee 1998; Bradshaw et al. 2003). Although optimism in quarterly earnings forecasts decreases as the earnings announcement date approaches (e.g., Brown 1997, 2001; Matsumoto 2002; Richardson et al. 2004), analysts' forecasts of annual earnings often are used to make investment decisions and to estimate firm value. 2 2 For example, empirical applications of the residual income model often use analysts' forecasts as proxies for the market's expectations of future earnings (e.g., Frankel and Lee 1998; Dechow et al. 1999; Lee et al. 1999; Liu and Thomas 2000; Sougiannis and Yaekura 2001; Ali et al. 2003). Bradshaw (2004) suggests that analysts' recommendations reflect a simple heuristic based on forecasts of annual earnings and long-term earnings growth. ...
Prior research demonstrates that forecast optimism is, in part, a consequence of analysts' cognitive reactions to the scenarios managers use to communicate future plans. In two experiments, we examine whether counter-explanation (explaining why managers' plans could fail) reduces scenario-induced optimism. We find that when compared to analysts not asked to generate counter-explanations, analysts who complete the relatively easy task of generating few counter-explanations make less optimistic forecasts, but analysts who complete the relatively difficult task of generating many counter-explanations do not. Results demonstrate the usefulness of a cognitive, theory-based mechanism for reducing forecast optimism and suggest a boundary condition for the use of that mechanism.
... This result is due to a positive association between the level of the firm's (mostly unrecognised) intangible assets and future abnormal earnings. Similarly, Sougiannis and Yaekura (2001) find biases and inaccuracies from long (four year) horizon, earnings based valuation models. Their evidence suggests one cause of these biases is omitted intangible assets from the balance sheet and the concurrent biases in earnings forecast inputs to the valuation model. ...
We examine whether firms that capitalise a higher proportion of their firm’s underlying intangible assets have higher analyst following, lower dispersion of analysts’ earnings forecasts and more accurate earnings forecasts relative to firms that capitalise a lower proportion. Under Australian GAAP, capitalisation of intangible assets has become increasingly ‘routine’ since the late 1980s. It is predicted that this experience leads Australian analysts to expect firms with relatively more certain intangible investments to signal this fact by capitalising intangible assets. Our results are consistent with this. We find capitalisation of intangible assets is associated with higher analyst following and lower absolute earnings forecast error for firms with a stock of underlying intangible assets. Our tests suggest a weaker association between capitalisation and lower earnings forecast dispersion. We conclude that there are benefits for analysts, for management to have the option to capitalise intangible assets. These findings suggest IAS 38 Intangible Assets and AASB 138 Intangible Assets reduce the usefulness of financial statements.
... Moreover, our paper is related to empirical studies investigating the accuracy of valuation models (e.g., Bernard 1995; Kaplan and Ruback 1995; Frankel and Lee 1998; Penman and Sougiannis 1998; Francis et al. 2000; Courteau et al. 2001; Sougiannis and Yaekura 2001). For example, Penman and Sougiannis (1998) are concerned with the important issue of how the three intrinsic value methods perform, if applied to a truncated forecast horizon arising naturally in practice. ...
Standard equity valuation approaches (i.e., DDM, RIM, and DCF model) are derived under the assumption of ideal conditions, such as infinite payoffs and clean surplus accounting. Because these conditions are hardly ever met, we extend the standard approaches, based on the fundamental principle of financial statement articulation. The extended models are then tested empirically by employing two sets of forecasts: (1) analyst forecasts provided by Value Line and (2) forecasts generated by cross-sectional regression models. The main result is that our extended models yield considerably smaller valuation errors. Moreover, by construction, identical value estimates are obtained across the extended models. By reestablishing empirical equivalence under non-ideal conditions, our approach provides a benchmark that enables us to quantify the errors resulting from individual deviations from ideal conditions, and thus, to analyze the robustness of the standard approaches. Finally, by providing a level playing field for the different valuation approaches, our findings have implications for other empirical settings, for example, estimating the implied cost of capital.
... Other researchers present evidence that information asymmetry around intangibles is a potential source of information risk that disadvantages some firms (e.g., younger firms) by generating higher systematic risk (Clarkson and Thompson, 1990). 20 Other evidence suggests the consequences of not identifying and measuring intangible investment may include insider trading (e.g., Aboody and Lev, 2000); mispricing of intangibles-intensive firms (e.g., Chambers et al., 2002); and miss-specification of equity valuation models (e.g., Kohlbeck and Warfield, 2007;Sougiannis and Yaekura, 2001). 20 Easley and O'Hara (2004) suggest that firm-specific information risk is a non-diversifiable risk factor. ...
In search of a unifying measurement feature on which to base a more systematic and potentially comprehensive analysis of intangibles, this paper first analyses the economic and accounting properties of intangibles, and second, empirically evaluates managerial practices for measuring and analyzing expenditure on intangibles. We present evidence from a survey of 614 large Australian firms that suggests gaps in the extent with which firms plan, monitor, record, analyze, and report on intangibles. Third, we evaluate the implications of our analysis and survey for accounting practice. Our evidence suggests GAAP has a role to provide guidance that helps firms identify and classify their expenditure on intangibles, in ways that elucidate the strategic implications of the different types of intangibles for future output. A secondary step for accountants, after identifying and classifying the expenditure on intangibles, is to apply a capitalization test to distinguish expenses from assets. The current asymmetric treatment of expenditure on purchased versus internally generated intangibles is not supportable on economic grounds. However, economists identify weak property rights, as a major cause of uncertainty associated with the outcomes from expenditure on intangibles, suggesting verifiable property rights is a unifying measurement feature on which to base a capitalization test for intangible assets.
... On the other hand, it aggravates the impact of small outliers. 9. Research on how a horizon date affects valuation is mainly focused on the significance of post-horizon value relative to the total value of the firm, and how its location affects the valuation error (Bailey and Grey 1968;Ohlson and Zhang 1999;Penman and Sougiannis 1998;Sougiannis and Yaekura 2001). The results indicate that, although the valuation error declines monotonically as the horizon approaches infinity, caution is required since the absence (or presence) of decreasing valuation errors could disappear due to the ambiguity associated with the long-term trend growth expectations implied by the terminal value computation. ...
This paper proposes and tests a variant of the standard discounted cash-flow model for enterprise valuation. The cash-flow (C/F) stream to be discounted is projected as the product of the sales and the free C/F to the enterprise (FCFE)-to-sales ratio and their respective rates of change. The C/F timespan is divided into three intervals. In the first, sales and ratio change according to the company's track record. On the assumption that both industry and firm abnormal earnings disappear at a certain point, marking the beginning of the third interval, the ratio evolves over the second interval to reach the Industry's average and thereafter remains constant. On the same basis, sales grow in the third interval in accordance with the economy's long-term trend, i.e. at the long-term nominal GDP growth rate, and within the second at an average of the latter and the track-record year-on-year growth rate. The proposed variant is tested for the four largest telecommunications companies in continental Europe over a 2.5-year period. The results, together with those of the standard model, are then compared with enterprise market values to test relative performance. Examination of their respective bias (signed valuation errors) and inaccuracy (ditto unsigned) seems to indicate that the proposed variant outperforms the standard model from which it is derived, even for different assumptions about the valuation horizon and for alternative ways to estimate the values of the variables.
... Note 4. The normalized level of FCF is needed for calculation of a firm's terminal value. We conduct sensitivity analyses for the firms' expected growth rate for perpetuity using various growth rates from 0% to 4% (see Sougiannis and Yaekura (2001)). We report here only the results based on 2% growth. ...
This paper is motivated by the recent concern raised by the SEC and other Securities Commissions around the Globe that financial analysts are not impartial. The question addressed is whether expert valuations provide unbiased information to shareholders and other stakeholders, and contribute to full disclosure. We examine the added value of expert valuations and their relationship to insider holdings based on a unique sample of 44 closely held companies listed on the TASE that were appraised by financial experts for transactions outside of the Exchange. These valuations are part of the full disclosure requirements in the case of extraordinary transactions. Each expert valuation is assessed on the basis of pre- and post-valuation data. Our key findings are: (1) expert valuations are 29% higher than market values and significantly affected by insider holdings; (2) there is a systematic upward bias in cash flow and cost of capital figures projected by experts; (3) expert valuations are not impartial; while they are supposed to provide an independent expert opinion, they are in fact biased towards majority shareholders who hired them to value the firm; (4) in the short-run investors respond cautiously to expert valuation; in the long-run, however, the over-valuation appears to be followed by destruction of value that is related to the firm's ownership structure.
... Note 4. The normalized level of FCF is needed for calculation of a firm's terminal value. We conduct sensitivity analyses for the firms' expected growth rate for perpetuity using various growth rates from 0% to 4% (see Sougiannis and Yaekura (2001)). We report here only the results based on 2% growth. ...
International Journal of Business and Management , Vol. 4, No. 3, March 2009, all in one file
Background
Intrinsic Values and DistributionsAutomated Valuation ModelsResearch Design and Empirical ResultsConclusion
Appendix A: Synthesizing the LifeCycle FrameworkAppendix B: Technical Note—Ranges of Bounded RationalityNotesReferences
Models ExaminedData and Initial ParameterizationMeasurement PrinciplesProprietary ModelsConclusion
Appendix: Academic LiteratureNotesReferences
The fall of Enron, WorldCom and other examples of accounting manipulation has awakened everyone associated with the field of accountancy. The importance and attractiveness of accounting numbers is increasing day by day. Equity valuation using accounting numbers play an important role in the area of accounting and finance. Researchers frequently use and compare the performance of different valuation models. Recent academic debate has proven residual income valuation model (RIVM) as the most superior model with lowest valuation errors. Empirical evidence shows that the discounted cash flow valuation model, dividend discount models (DDM), and the multiple base valuations are the most popular models among practitioners. This study investigates that whether the use of more complex accounting flowbased valuation models like the RIVM offer advantages over the use of multiples-based approaches like the P/E, EV/EBITDA and EV/Sale ratios. We find that sophisticated model like RIVM perform better for both high and low intangible firms compared to multiple based valuations. The RIVM predicts stock price better for high intangibles than low intangibles. The findings in this are based on dispersion, accuracy, biasness and explainability of the models to predict the stock prices.
This paper empirically analyses the adequacy of the valuation framework developed by Ohlson [1995] and Feltham and Ohlson [1995]. using specifications with different degrees of complexity. The less sophisticated ones only include the fundamental accounting variables: book value and earnings, while the more complex ones also include additional variables in order to take into account «other information». The sample contains non-financial companies listed in the Madrid Stock Exchange and refers to the period 1991-1999. Our results suggest that Ohlson 11995] advantages the other models, as long as the values obtained in the empirical tests are consistent with its theoretical assumptions and implies lower abnormal earnings prediction errors. When the «other information» variable measured using the analysts' forecasts is included in the models, the results are better than those obtained with models traditionally used in the previous literature. As for those based on Feltham and Ohlson [1995], the conservatism parameter that characterises them produces conflictive results as long as is not able to capture all the effects of accounting conservatism. Copyright © 2001 Asociación Española de Contabilidad y Administración de Empresas.
This paper employs a multi-equation model approach to consider three statistic problems (heteroskedasticity, endogeneity and persistency), which are sources of bias and inefficiency in the predictive regression models. This paper applied the residual income valuation model (RIM) proposed by Ohlson (1995) to forecast stock prices for Taiwan three sectors. We compare relative forecasting accuracy of vector error correction model (VECM) with the vector autoregressive model (VAR) as well as OLS and RW models used in the prior studies. We conduct out-of-sample forecasting and employ two instruments to assess forecasting performance. Our empirical results suggest that the VECM statistically outperforms other three models in forecasting stock prices. When forecasting horizons extend longer, VECM produces smaller forecasting errors and performs substantially better than VAR, suggesting that the ability of VECM to improve VAR forecast accuracy is stronger with longer horizons. These findings imply that an error correction term (ECT) of the VECM contributes to improving forecast accuracy of stock prices. Our economic significance analyses and robustness tests for different data frequency are in favor of the superiority of VECM estimator.
Using accounting-based valuations, Frankel and Lee (1998) document a positive association between fundamental value-to-price ratio (V/P) and abnormal stock returns in subsequent periods. They attribute the V/P effect to the market’s gradual adjustment of stock prices towards a fundamental value, and this is regarded as counter-evidence for market efficiency (i.e. mispricing). This synopsis aims to examine whether the V/P effect also holds for Chinese companies.
The main purpose of this thesis is to analyze the financial analysts of Brazilian firms. By gathering data from the market and analyzing the current performance of the firms, these professionals prepare earnings forecasts and stock recommendations. Using I/B/E/S database, it is presented a broad empirical research of the earnings forecasts and stock recommendations, as well as their information content for the Brazilian capital market. The empirical studies covered the period from January 1995 to June 2003. This thesis starts with the discussion of some concepts and the modus operandi of the financial analysts of Brazilian firms. After a literature review in the area, the empirical studies begin with the analysis of the earnings forecast errors. Some of their characteristics, such as accuracy, bias and precision are investigated in different contexts. After a critical analysis of the informational content for different types of earnings forecast revisions and actual announced earnings deviated form analysts expectations (earnings surprises), evidences of price effects in response to these facts are documented. The last part of this thesis discusses the role of stock recommendations in the Brazilian market. The percentage distribution of stock recommendations is verified as well as the informational content of stock recommendations. Other studies are carried out to verify the performance of the consensus stock recommendations and the effects of downgrades and upgrades of recommendations for Brazilian companies.
This study provides evidence on market implied future earnings based on the residual income valuation (RIV) framework and compares these earnings with analyst earnings forecasts for accuracy (absolute forecast error) and bias (signed forecast error). Prior research shows that current stock price reflects future earnings and that analyst forecasts are biased. Thus, how price-based imputed forecasts compare with analyst forecasts is interesting. Using different cost of capital estimates, we use the price-earnings relation and impute firms’ future annual earnings from three residual income (RI) models for up to 5 years. Relative to I/B/E/S analyst forecasts, imputed forecasts from the RI models are less or no more biased when cost of capital is low (equal to a risk-free rate or slightly higher). Analysts slightly outperform these RI models in terms of accuracy for immediate future (1 or 2) years in the forecast horizon but the opposite is true for more distant future years when cost of capital is low. A regression analysis shows that, in explaining future earnings changes, analyst forecasts relative to imputed forecasts do not impound a significant amount of earnings information embedded in current price. In additional tests, we impute future long-term earnings growth rates and find that they are more accurate and less biased than I/B/E/S analyst long-term earnings growth forecasts. Together, the results suggest that the RIV framework can be used to impute a firm’s future earnings that are high in accuracy and low in bias, especially for distant future years.
This paper investigates the equivalence of equity valuation between the free cash flow model and the residual income model. Two conditions are found to be jointly sufficient for Residual Income and Free Cash Flow models to produce the same equity valuation: (a) the models’ discount rates jointly satisfy the Modigliani and Miller (Am Econ Rev 48:261–297, 1958) condition which relates discount rates for levered equity, unlevered equity, tax savings and debt, and (b) forecasts of the two models’ variables jointly satisfy the income statement and balance sheet identities. Past discussions fail by ignoring or misusing (a).
Valuation or fundamental analysis is the final stage of prospective analysis after forecasting. It is the process of converting a forecast into value of a firm or a component of a firm and the analysis of information that focuses on valuation. From financial, theoretical perspective shareholder value is the present value of all future payoffs. This definition can be implemented by forecasting and discounting all future payoffs. This works presents a comparative analysis of four equity valuation models: RIVM, DDM and P/E (multiples valuation approach).
We examine the relationship between analyst experience and the accuracy of annual earnings forecasts using a 20-year sample (1983-2002) from the Thomson Financial First Call I/B/E/S database. We test for this relationship using three different measures of forecast accuracy employed by prior researchers, which are regressed against measures of general experience and specific experience, along with five other controls, for four independent 5-year subperiods, as well as for the full 20-year period. We find that general experience levels are positively associated with forecast accuracy (negatively associated with forecast error) in most subperiods for two of the three measures of forecast accuracy. We also find, in contrast with the extant literature, that for two of the three measures of forecast accuracy and for most subperiods, specific experience does not have an association with forecast accuracy beyond that provided by the general experience measure. Our results suggest that the relationship between forecast accuracy and analyst experience (as well as some other commonly examined analyst characteristics) is dependent on the measure of accuracy employed and the time period studied.
Focusing on Spanish �rms, the aim of this paper is to investigate how investors incorporate the value of a
�rm's outstanding employee stock options (ESOs hereafter) into its stock price. Aboody (1996) analyzes the
same issue on US data, however our approach improves the empirical speci�cation by incorporating analysts'
forecasts of future abnormal earnings. We �nd a negative correlation between the ESOs value and a �rm's share
price, revealing that "cost e�ect" dominates "incentive e�ect".
Financial research has cast considerable doubt on the theory that stock returns are normally distributed. Recent turmoil in the financial markets furthers that concern. Our study adds additional empirical evidence to the body of research suggesting that returns are not normal and that traditional risk measures, such as standard deviation, can be deceptive. Specifically, we use a proprietary valuation model to examine the risk and return characteristics of under and overvalued securities in the context of a stable Paretian analysis. We find that determining which securities are over or undervalued not only produces great benefits in terms of return but also reduces risk in that sense that returns from over and undervalued securities tend to be significantly less fat-tailed.
This paper provides an empirical assessment of the Feltham-Ohlson models, distinguishing between firms with positive and negative abnormal earnings. Abnormal earnings persistence and conservatism parameters differ for these two groups; this implies different earnings prediction models and valuation functions for both profit-making and loss-making firms. The analysis refers to the period 1991-1999 and uses a sample of Spanish firms quoted on the Madrid S.E. The results suggest that our contextual approach is more useful than the non-contextual one to predict future abnormal earnings and explain current prices. Although the Ohlson (1995) model is accurate in forecasting future abnormal earnings and stock prices, the results improve when firms with negative abnormal earnings are valued using a temporary model and firms with positive abnormal earnings using a more permanent one. The Feltham and Ohlson (1995) model generates the lowest forecast errors in the prediction of positive abnormal earnings, but it produces the least accurate results in forecasting prices.
Recently, Penman and Sougiannis (1998) and Francis, Olsson, and Oswald (2000) compared the bias and accuracy of the discounted cash flow model (DCF) and Edwards‐Bell‐Ohlson residual income model (RIM) in explaining the relation between value estimates and observed stock prices. Both studies report that, with non‐price‐based terminal values, RIM outperforms DCF.
Our first research objective is to explore the question whether, over a five‐year valuation horizon, DCF and RIM are empirically equivalent when Penman's (1997) theoretically “ideal” terminal value expressions are employed in each model. Using Value Line terminal stock price forecasts at the horizon to proxy for such values, we find empirical support for the prediction of equivalence between these valuation models. Thus, the apparent superiority of RIM does not hold in a level playing field comparison.
Our second research objective is to demonstrate that, within each class of the DCF and RIM valuation models, the model that employs Value Line forecasted price in the terminal value expression generates the lowest prediction errors, compared with models that employ non‐price‐based terminal values under arbitrary growth assumptions. The results indicate that, for both DCF and RIM, price‐based valuation models outperform the corresponding non‐price‐based models by a wide margin. These results imply that researchers should exercise care in interpreting findings from models using ad hoc terminal value expressions.
We compare the valuation accuracy of the equity value estimates inferred from empirical implementations of the abnormal earnings growth model (Ohlson and Juettner-Nauroth 2005; the OJ estimates) with the residual income model (Ohlson 1995; the RIV estimates). We find that the OJ estimates generally underperform the RIV estimates. Increasing the forecast horizon for the OJ estimates from two to five years significantly improves their valuation accuracy. However, relative to the RIV estimates, the valuation accuracy of the OJ estimates remains lower even using a five-year forecast horizon. Finally, we compare predicted accounting profitability with actual accounting profitability and find that the lower valuation accuracy of the OJ estimates is attributable to the empirical assumptions regarding future earnings growth beyond the forecast horizon.
Using accounting-based (residual income) valuations, this study examines the extent to which abnormal returns after insider share trades are explained by private information versus mispricing of public information. For a sample of insider trades in the Netherlands (1999-2008), I find that managers’ share purchase decisions are associated with positive future abnormal returns as well as equity undervaluation. Even though undervaluation results in predictable price increases, positive abnormal returns following purchases persist after controlling for fundamental valuations. Thus, this study provides evidence on the sources of managers’ personal trading gains and suggests that positive abnormal returns after insider share purchases reflect both private information and managers’ responses to market mispricing of public information.
In this paper we try to find common factors that can explain the stock returns of Tokyo stock exchange firms with multivariate asset-pricing framework. Specifically, we explore the nature of risk contained in the size and the HML factor variables and their information content. For this purpose we utilize Edwards-Bell-Ohlson model to derive accounting based fundamental price and divide this value by the actual market price, whereas we call "value- to-price ratio" as Frankel and Lee did. By comparing the returns of the portfolios ranked by this candidate variable, we find that this value-to-price ratio variable contains new information content that is not yet reflected in the conventional book-to-price ratio, while its explanatory power is slightly inferior to the book-to-price ratio. The portfolio strategy based on the value-to-price ratios can earn abnormal cumulative returns for some subset of the sample portfolios and for a larger fraction of portfolios during a later sub-period of the sampling period. Some of the return differences are significant based on the t-test whose method initially proposed by Daniel and Titman (1997). To test for whether this variable can be a significant explanatory variable in a multivariate asset pricing model, we construct return difference portfolios ranked by the value-to-price ratio, whose method is identical to Fama and French (1993) method in their constructing the HML return difference portfolios. We call this factor variable as "UMO" (underestimating-minus-overestimating) factor variable. We conduct Fama and MacBeth test with this UMO factor as one of the candidate factor variables. Under the null hypothesis of the existence of the risk premium on each possible factor, we find that the risk premium of for UMO factor is significant. However, the degree of the significance is not universal unlike the case for the HML factor. Accordingly, we test for the characteristic hypothesis raised by Daniel and Titman (1997), and we conclude that this factor is rather a characteristic rather than a risk factor and cannot be a good substitute for the book-to-price ratio variable.
The primary objective of this paper is to assess the gain in valuation accuracy when the analyst performs an exhaustive pro-forma about the target firm beyond the four-year forecast horizon under the direct method, compared to the alternative of using heuristic industry multiples to compute continuing values if she is uncertain about the firm's post-horizon prospects. We also examine the determinants of the edge to direct valuation vis-a-vis industry multiplier approaches. Three industry-multiplier approaches are considered, the ETSS, IHP and PE4 models. Given variations in size and growth prospects across firms within an industry, we expect to achieve greater valuation accuracy under the direct method than any of the multiplier models that we explore in the study. Results from the study are consistent with this prediction. In particular, the direct method generates the lowest mean squared errors, tightest inter-percentile ranges and highest regression, when data are either un-scaled or deflated by current book value per share. The direct method loses some of its edge over the other models, however, when current stock price per share is used as a deflator. Results also indicate that the valuation gains to directly forecasting firm-specific continuing values are greatest for small and fast growing target firms from highly heterogeneous industries. We contribute to the academic literature in three ways: first, we present a benchmark model against which the efficacy of various multiplier approaches may be evaluated; second, we identify firm characteristics and industries under which gains to direct forecasts of continuing value is greatest; third, we show the analyst and students of financial statement analysis how to use reverse engineering techniques to extract from comparable firms inferences about industry average growth prospects at the horizon.
Many existing theories attempt to explain initial public offering (IPO) underpricing by suggesting that underwriters purposefully set offer prices below market value. These theories implicitly assume that underwriters have perfect foresight and can, with complete accuracy, place a value on issuing firms. This chapter evaluates this assumption by comparing offer prices set by underwriters to prices from three objective, valuation-based approaches. Relative to these estimates, the offer prices chosen by underwriters result in lower levels of underpricing, suggesting that the prices underwriters select are actually value creating for issuing firms in that they reduce the opportunity cost of issuance. Within these existing theories, there is an implicit assumption that underwriters possess perfect foresight, meaning that they are able, with certainty, to determine the fundamental, or market, value of an issue. It is also commonly believed, and admitted, that underwriters make subjective adjustments to estimated values in order to select a final offer price. If the assumption of perfect foresight is correct, then these adjustments, given the average positive levels of underpricing that exist, suggest that underwriters actually reduce proceeds to issuing firms by purposefully offering issues at below market value.
The traditional categorisation of expenditures evident in many firms’ charts of accounts and financial statements does not identify and measure expenditures on intangible investment separately from tangible investment and operating expenditures. This contrasts with the accounting for tangible investment, which separately accounts for all expenditures as assets unless the future benefits are consumed in a single accounting period. Further, in searching for better ways to account for intangibles, regulators and researchers have focused on the accounting choice problem relating to the existence and recognisability of intangible assets. In this paper, we argue that identifying and separately reporting the expenditures on intangible investment is the logical first step in accounting for intangible investments. Learning about the firm’s categories of value driving (and sometimes potentially value destroying) expenditures has important implications for understanding aspects of the value chain, performance measurement, valuation, corporate governance and the external audit.
Esta tesis contrasta empíricamente los modelos Feltham-Ohlson, diferenciando entre empresas que presentan resultados anormales positivos y negativos. Para ello, se utilizan diferentes parámetros de persistencia del resultado anormal y de conservadurismo contable para las empresas con resultados anormales positivos y negativos. Esta nueva dinámica lineal de la información implica la utilización de diferentes modelos de predicción de resultados y funciones de valoración para las empresas con beneficios anormales y pérdidas anormales. El análisis empírico va de 1992 a 1999, y utiliza una muestra de empresas españolas cotizadas en la Bolsa de Madrid. Los resultados apoyan el enfoque contextual propuesto, pues mejoran las predicciones de resultados anormales y mejora la explicación de los precios observados en el mercado. En particular, los modelos basados en Ohlson (1995) aparecen como los mejores en la predicción del resultado anormal y de los precios de mercado; mejorando los resultados cuando se emplea el análisis contextual, lo que implica valorar las empresas con resultados anormales negativos mediante modelos transitorios, y las empresas con resultados anormales positivos con modelos permanentes. En cuanto al modelo de Feltham y Ohlson (1995), aunque proporciona los menores errores de predicción de los resultados anormales de las empresas con beneficios anormales, proporciona los peores resultados a la hora de predecir los precios. This thesis provides an empirical assessment of the Feltham-Ohlson models differencing between firms with positive and negative abnormal earnings. We use different abnormal earnings persistence parameters and different conservatism parameters for firms with positive and negative abnormal earnings. This new contextual linear information dynamic implies different earnings prediction models and different valuation functions for profit making firms and loss making firms. The empirical analysis is referred to the period 1992-99, and uses a sample of Spanish firms quoted on the Madrid S.E. Our results support that the contextual approach followed in the thesis is useful to predict future abnormal earnings and explain current prices. In particular, the Ohlson (1995) model is a good model to forecast future abnormal earnings and stock prices, and the results improve with contextual approach: this implies to value firms with negative abnormal earnings using a temporary model and firms with positive abnormal earnings using a more permanent one. As for the Feltham and Ohlson (1995) model, although it generates the lowest forecast errors in the prediction of positive abnormal earnings, it produces the worst results in forecasting prices.
This paper examines the effect of income smoothing on information uncertainty, stock returns, and cost of equity. I show that income smoothing through both total accruals and discretionary accruals tends to reduce firms' information uncertainty, as measured by stock return volatility, analyst earnings forecast dispersion, and analyst earnings forecast error. Further, I provide evidence that stocks of income smoothing firms are priced with a premium. Controlling for earnings shocks and other firm characteristics, income smoothing firms have significantly higher abnormal returns around earnings announcement. In addition, I show that income smoothing reduces firms' implied cost of equity or expected returns. The result is more robust over short horizons up to two years. © 2013 World Scientific Publishing co.and Center for Pacific Basin Business, Economics and Finance Research.
Residual income valuation is based on the assumption that the clean surplus relation holds. As pointed out by Ohlson (2000), among others, the standard clean surplus relation is frequently violated. Moreover, standard residual income valuation models rest on the implicit assumption that future stated earnings belong to current shareholders only. This is clearly invalid for companies granting employee options. In order to overcome these deficiencies, this paper establishes an extension of the clean surplus relation and derives simple analytical solutions for the value of outstanding stocks in terms of already known accounting information.
Academic research into firms that have gone public has focused on the study of two anomalies: initial underpricing and long-run underperformance. We analyse Spanish Initial Public Offerings to provide additional evidence on the long-run performance of IPOs and its relationship with initial underpricing. Results reveal the existence of negative long-run abnormal stock returns, in line with the international literature. Long-run performance presents a positive relationship with underpricing and the volume of funds obtained in seasoned offerings, in consonance with the predictions of Allen and Faulhaber (1989), Welch (1989) and Grinblatt and Hwang (1989). Copyright Blackwell Publishers Ltd, 2005.
This study examines the usefulness of an analyst-based valuation model in predicting cross-sectional stock returns. We estimate firms' fundamental values (V) using I/B/E/S consensus forecasts and a residual income model. We find that V is highly correlated with contemporaneous stock price, and that the V/P ratio is a good predictor of long-term cross-sectional returns. This effect is not explained by a firm's market beta, B/P ratio, or total market capitalization. In addition, we find errors in consensus analyst earnings forecasts are predictable, and that the predictive power of V/P can be improved by incorporating these errors.
This paper compares the reliability ofvalue estimates from the discounted dividend model, the discounted free cash flow model and the discounted abnormal earnings model. Using a large sample of Val ...
ABSTRACT Two easily measured variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with market {3, size, leverage, book-to-market equity, and earnings-price ratios. Moreover, when the tests allow for variation in {3 that is unrelated to size, the relation between market {3 and average return is flat, even when {3 is the only explanatory variable. THE ASSET-PRICING MODEL OF Sharpe (1964), Lintner (1965), and Black (1972)
This paper examines cross-sectional differences in the optimistic behavior of financial analysts. Specifically, we investigate whether the predictive accuracy of past information (e.g., time-series of earnings, past returns, etc.) is associated with the magnitude of the bias in analysts' earnings forecasts. We posit that there is higher demand for non-public information for firms whose earnings are difficult to accurately predict than for firms whose earnings can be accurately forecasted using public information. Assuming that optimism facilitates access to management's non-public information, we hypothesize that analysts will issue more optimistic forecasts for low predictability firms than for high predictability firms. Our results support this hypothesis.
Recently, Penman and Sougiannis (1998) and Francis, Olsson and Oswald (1999) compared the bias and accuracy of the dividend discount model (DDM), discounted cash flow model (DCF), and Edwards-Bell-Ohlson residual income model (RIM) in explaining the relation between value estimates and observed stock prices. Both studies report that, with non price-based terminal values, RIM outperforms DCF and DDM. Our primary research objective is to explore whether, over a five-year valuation horizon, DDM, DCF and RIM are empirically equivalent when Penman's (1998) theoretically "ideal" terminal value expressions are employed in each model. Using Value Line terminal stock price forecasts at the horizon to proxy for such values, we find empirical support for the prediction of equivalence between these three price-based valuation models. Our secondary research objective is to demonstrate that, within each class of the DCF and RIM valuation models, the model that employs Value Line forecasted price in the terminal value expression will generate the lowest pricing errors, compared to models that employ non price-based terminal value under an arbitrary growth assumption. Results indicate that, for both DCF and RIM, price-based valuation models outperform the corresponding non price-based models by a wide margin. We also revisit the issue of the apparent superiority of RIM, and find that this result does not hold in a level playing field where an approximation of ideal terminal values is employed. In fact, the price-based RIM model is marginally outperformed by the price-based DCF and DDM models, in terms of pricing errors as well as its ability to explain current market price.
We invert the residual income valuation model (using current stock prices, current book value of equity and short-term forecasts of accounting earnings) to obtain an estimate of the expected rate of return for a portfolio of stocks. Our approach is analogous to the estimation of the internal rate of return on a bond using market values and coupon payments. Estimation of the cost of equity capital by inverting the residual income valuation model requires an estimate of growth in residual income beyond the forecast horizon. The contribution of our method is that we use the stock price and accounting data to simultaneously estimate the unique implied growth rate and the internal rate of return. This growth rate provides an adjustment for the fact that our estimate of the internal rate of return is based on current book value of equity and short-term earnings forecasts. Our analysis of DJIA firms yields estimates of expected growth that are considerably higher than those assumed by earlier studies. Our estimated market premium over the risk-free rate is closer to the historical premium than that obtained by other studies using earnings forecast data. After completing the pro-forma forecasting of earnings (as described in, Penman [2000], for example) and/or after obtaining analysts' forecasts of earnings for a number of firms with comparable operating activities, our method may be used to estimate the market's expectation of the cost of capital and growth for these firms. These estimates for comparable firms may be used to determine the intrinsic value of an unlisted firm, a division of a firm, or a firm that is believed to be relatively over/under-valued.
This paper examines empirical relations between rules of fundamental analysis and actual future earnings changes, analysts' earnings forecast revisions, and contemporaneous stock returns. Our results indicate that many of the fundamental signals are related to future earnings and forecast revisions in the same way they are related to returns, however some significant exceptions are noted. Conditioning the relations on variables reflecting the macroeconomic, firm-specific and industry-specific contexts in which firms operate provides some further refinement to our understanding of the information contained in the fundamental signals. Additional tests suggest analysts' forecast revisions display generalized underreaction to the future earnings information contained in some of the fundamental signals.
The paper demonstrates empirically that GAAP earnings have properties to serve as a substitute for dividends in equity valuation analysis. Dividends reduce subsequent GAAP earnings, and "intrinsic" equity prices calculated by forecasting earnings are thus reduced by current dividends. This is in accordance with the Miller and Modigliani principle -- the displacement property -- which states that the payment of dividends reduces prices, dollar for dollar. Further, the paper demonstrates that if this displacement is accommodated in calculating equity prices from forecasted GAAP earnings, those prices exhibit the dividend irrelevance property, that is, calculated prices are insensitive to future dividends. The accommodation involves adding the displacement value of dividends to earnings forecasts. Forecasted GAAP earnings cannot be substituted for dividends, dollar for dollar, but the two are substitutes in the sense that the replacement value of expected dividends reduces forecasted earnings, dollar for dollar.
The paper develops and analyzes a model of a firm's market value as it relates to contemporaneous and future earnings, book values, and dividends. Two owners' equity accounting constructs provide the underpinnings of the model: the clean surplus relation applies, and dividends reduce current book value but do not affect current earnings. The model satisfies many appealing properties, and it provides a useful benchmark when one conceptualizes how market value relates to accounting data and other information.
Résumé. L'auteur élabore et analyse un modèle dans lequel il conceptualise la relation entre la valeur marchande d'une entreprise et ses bénéfices, ses valeurs comptables et ses dividendes actuels et futurs. Deux postulats de la comptabilisation des capitaux propres servent de charpente au modèle: a) la relation du résultat global s'applique et b) les dividendes réduisent la valeur comptable actuelle sans influer, cependant, sur les bénéfices actuels. Le modèle présente de nombreuses propriétés intéressantes et il peut, fort utilement, servir de repère dans la conceptualisation de la relation entre la valeur marchande et les données comptables et autres renseignements.
Standard formulas for valuing the equity of going concerns require forecasting payoffs to infinity but practical analysis requires that payoffs be forecasted over finite horizons. This truncation inevitably involves often-troublesome terminal value calculations. This paper contrasts dividend discount techniques, discounted cash flow analysis, and techniques based on accrual earnings when each is applied with finite-horizon forecasts. Valuations based on average ex post payoffs over various horizons, with and without terminal value calculations, are compared with ex ante market prices to discover the error introduced by each technique in truncating the horizon. Valuation errors are lower using accrual earnings techniques rather than cash flow and dividend discounting techniques. The accounting features that make a given technique less than ideal for finite horizon analysis are also detailed. Conditions where a given technique requires particularly long forecasting horizons are identified and the performance of the alternative techniques under those conditions is examined.
This paper lays out alternative equity valuation models that involve forecasting for finite periods and shows how they are related to each other. It contrasts dividend discounting models, discounted cash flow models, and residual income models based on accrual accounting. It shows that some models that are apparently different yield the same valuation. It gives the general form of the terminal value calculation in these models and shows how this calculation serves to correct errors in the model. It also shows that all models can be interpreted as providing a particular specification of the terminal value for the dividend discount model. In so doing it shows how one calculates the terminal value for the dividend discount formula. The calculation involves weighting forecasted stocks and flows of value with weights determined by a parameter that can be discovered from pro forma analysis.
When shares are traded infrequently, beta estimates are often severely biased. This paper reviews the problems introduced by infrequent trading, and presents a method for measuring beta when share price data suffer from this problem. The method is used with monthly returns for a one-in-three random sample of all U.K. Stock Exchange shares from 1955 to 1974. Most of the bias in conventional beta estimates is eliminated when the proposed estimators are used in their place.
This paper analyzes how a horizon date affects valuation. We focus on valuation errors that arise because of the horizon, and we assess the magnitudes of such errors. A model due to Ohlson (1995) specifies the information environment. Forecasting of future financial outcomes depends on two kinds of information: current accounting data - earnings, book value, and dividend - and "other", idiosyncratic, information.
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. Copyright The American Finance Association 1999.
This paper presents a stock-flow consistent macroeconomic model in which financial fragility in firm and household sectors evolves endogenously through the interaction between real and financial sectors. Changes in firms' and households' financial practices produce long waves. The Hopf bifurcation theorem is applied to clarify the conditions for the existence of limit cycles, and simulations illustrate stable limit cycles. The long waves are characterized by periodic economic crises following long expansions. Short cycles, generated by the interaction between effective demand and labor market dynamics, fluctuate around the long waves.
We show that immigrant managers are substantially more likely to hire immigrants than are native managers. The finding holds when comparing establishments in the same 5-digit industry and location, when comparing different establishments within the same firm, when analyzing establishments that change management over time, and when accounting for within-establishment trends in recruitment patterns. The effects are largest for small and owner-managed establishments in the for-profit sector. Separations are more frequent when workers and managers have dissimilar origin, but only before workers become protected by EPL. We also find that native managers are unbiased in their recruitments of former co-workers, suggesting that information deficiencies are important. We find no effects on entry wages. Our findings suggest that a low frequency of immigrant managers may contribute to the observed disadvantages of immigrant workers.
The primary aim of the paper is to place current methodological discussions in macroeconometric modeling contrasting the ‘theory first’ versus the ‘data first’ perspectives in the context of a broader methodological framework with a view to constructively appraise them. In particular, the paper focuses on Colander’s argument in his paper “Economists, Incentives, Judgement, and the European CVAR Approach to Macroeconometrics” contrasting two different perspectives in Europe and the US that are currently dominating empirical macroeconometric modeling and delves deeper into their methodological/philosophical underpinnings. It is argued that the key to establishing a constructive dialogue between them is provided by a better understanding of the role of data in modern statistical inference, and how that relates to the centuries old issue of the realisticness of economic theories.
For many years, scholars and investment professionals have argued that value strategies outperform the market. These value strategies call for buying stocks that have low prices relative to earnings, dividends, book assets, or other measures of fundamental value. While there is some agreement that value strategies produce higher returns, the interpretation of why they do so is more controversial. This article provides evidence that value strategies yield higher returns because these strategies exploit the suboptimal behavior of the typical investor and not because these strategies are fundamentally riskier. Copyright 1994 by American Finance Association.
Two easily measured variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with market "beta", size, leverage, book-to-market equity, and earnings-price ratios. Moreover, when the tests allow for variation in "beta" that is unrelated to size, t he relation between market "beta" and average return is flat, even when "beta" is the only explanatory variable. Copyright 1992 by American Finance Association.
CFROI Valuation: A total System Approach to Valuing the Firm
- Madden
- J Bartley
Madden, Bartley, J. CFROI Valuation: A total System Approach to Valuing the Firm. Holt Value Associates: Chicago, IL (1998)
The Equivalence of Dividend, Cash Flows and Residual Earnings Approaches to Equity Valuation Employing Ideal Terminal Value Expressions
- S Claude
- J Kao
- G Richardson
Claude, S., Kao, J. and Richardson, G. "The Equivalence of Dividend, Cash Flows and Residual Earnings Approaches to
Equity Valuation Employing Ideal Terminal Value Expressions." Working Paper, University of Waterloo
(2000).
Stock Returns and Accounting Earnings
- J Liu