Conservative Accounting and Linear Information Valuation Models*

Prior research using the residual income valuation model and linear information models has generally found that estimates of firm value are negatively biased. We argue that this could result from the way in which accounting conservatism effects are reflected in such models. We build on the conservative accounting model of Feltham and Ohlson 1995 and the Dechow, Hutton, and Sloan 1999 (DHS) methodology to propose a valuation model that includes a conservatism‐correction term, based on the properties of past realizations of residual income and “other information”. “Other information” is measured using analyst‐forecast‐based predictions of residual income. We use data comparable to the DHS sample to compare the bias and inaccuracy of value estimates from our model and from models similar to those used by DHS and Myers 1999. Valuation biases are substantially less negative for our model, but valuation inaccuracy is not markedly reduced.     

Modeling Goodwill for Banks: A Residual Income Approach with Empirical Tests*

This paper uses the residual income valuation technique outlined in Feltham and Ohlson 1996 to examine the relation between stock valuations and accounting numbers for a prototypical banking firm. Prior work of this nature typically assumes a manufacturing setting. This paper contributes to the prior research by clarifying how the approach can be extended to settings where value is created from financial assets and liabilities. Key elements of our model include allowing banks to generate positive net present value from either lending or borrowing activities, and allowing for accounting policy to affect valuation through the loan loss allowance. We validate our model using archival data analysis, and interpret coefficients in light of our modeling assumptions. These results suggest that banks create value more from deposit‐taking activities than from lending activities. Vuong tests confirm that our model outperforms adaptations of the unbiased accounting model of Ohlson 1995 and adaptations of the base model proposed by Beaver, Eger, Ryan, and Wolfson 1989. However, our model is outperformed by the popular net income‐book value model used in many empirical studies, and we can formally reject one of our key modeling assumptions. These tests of our model suggest future avenues for improving upon the theoretical analysis.     

基丁剩余收益估值模型的市场错误定价研究

基于Ohlson（1995）创立的包含线性信息动态过程的剩余收益估值模型,对1995—2006年部分A股上市公司的内在价值进行测算,据此分析中国证券市场中的错误定价问题。结果发现,剩余收益、净资产账面价值均具有较强的持续性和可预测性。大多数公司年份的股价被高估,表明市场错误定价问题在我国证券市场中常年存在。具体说来,在1997、2000、2001和2007年4月,样本公司股价处于系统性高估状态;相反,多数公司股价在2005和2006年4月被低估。文章的创新之处在于利用可观测的会计信息直接检验线性信息动态过程,避免采用跨期盈余预测值进行估值,一定程度上提高了研究结果的可靠性。     

Earnings,Book Values,and Dividends in Equity Valuation: An Empirical Perspective*

This paper revisits Ohlson 1995 to make a number of points not generally appreciated in the literature. First, the residual income valuation (RIV) model does not serve as a crucial centerpiece in the analysis. Instead, RIV plays the role of condensing and streamlining the analysis, but without any effect on the substantive empirical conclusions. Second, the concept of “other information” in the model can be given concrete empirical content if one presumes that next‐period expected earnings are observable.     

Investors' Misweighting of Firm-Level Information and the Market's Expectations of Earnings

Prior studies use fundamental earnings forecasts to proxy for the market's expectations of earnings because analyst forecasts are biased and are available for only a subset of firms. We find that as a proxy for market expectations, fundamental forecasts contain systematic measurement errors analogous to those in analysts' biased forecasts. Therefore, these forecasts are not representative of investors' beliefs. The systematic measurement errors from using fundamental forecasts to proxy for market expectations occur because investors misweight the information in many firm-level variables when estimating future earnings, but fundamental forecasts are formed using the historically efficient weights on firm-level variables. Thus, we develop an alternative ex ante proxy for the market's expectations of future earnings (“the implied market forecast”) using the historical (and inefficient) weights, as reflected in stock returns, that the market places on firm-level variables. A trading strategy based on the implied market forecast error, which is measured as the difference between the implied market forecast and the fundamental forecast, generates excess returns of approximately 9 percent per year. These returns cannot be explained by investors' reliance on analysts' biased forecasts. Overall, our results reveal that market expectations differ from both fundamental forecasts and analysts' forecasts.     

Combining Earnings and Book Value in Equity Valuation*

It is common to apply multipliers to both earnings and book value to calculate approximate equity values. However, applying a price-earnings multiplier or a price-to-book multiplier typically produces two valuations and the analyst is left with the question of how to combine them into one valuation. This paper calculates weights that combine the valuations and shows that these weights vary over the difference between earnings and book value, doing so systematically over time. When earnings are small compared to book value, the weights are different from when earnings are large relative to book value, and they vary in a nonlinear way over the difference between the two. The weights also combine forecasts of future earnings, based on earnings and book value separately, into one composite forecast. The paper calculates a second set of weights to ascertain how the two numbers are combined to forecast one-year-ahead earnings and three-years-ahead earnings. The calculated weights are applied out of sample to ascertain their predictive ability against other benchmarks.     

An Analysis of Historical and Future-Oriented Information in Accounting-Based Security Valuation Models*

The Ohlson (1995) and Feltham and Ohlson (1995) valuation model provides a rigorous framework for summarizing the information in expected future earnings and book values. However, the model provides little guidance on selecting an empirical proxy for expected future earnings. We examine whether and under what circumstances historical earnings and analyst earnings forecasts offer comparable explanation of security prices. This issue is of particular interest because analyst forecasts are less readily available than historical data. Under appropriate circumstances, historical data may allow wider use of the Feltham-Ohlson valuation model by researchers and investors. A related issue is the incremental explanatory power of historical earnings and realized future earnings (perfect-foresight forecasts) for security prices beyond analyst forecasts. If historical earnings are incrementally informative, that would suggest that analyst forecasts do not fully reflect price-relevant information in past earnings. If future earnings are incrementally informative, that would suggest that security prices reflect investors' implicit earnings forecasts beyond analyst forecasts. We examine these issues using a historical model (based on past earnings), a perfect-foresight model (based on realized future earnings), and a forecast model (based on Value Line earnings forecasts). All three models provide significant explanatory power for security prices, and each set of earnings data provides incremental explanatory power for prices when used with the other sets of earnings data. We estimate the models separately for firms with moderate and extreme earnings-to-price (E/P) ratios, a proxy for earnings permanence. For moderate-E/P firms, the historical model's explanatory power exceeds that of the perfect foresight model, and is indistinguishable from that of the analyst forecast model. In contrast, for extreme-E/P firms, the perfect-foresight model offers greater explanatory power than the historical model, but lower explanatory power than analyst forecasts. Our results suggest that financial analysts' forecasting efforts are best focused on firms whose earnings contain large temporary components (extreme E/P firms). However, in general, both historical data and analyst forecasts are complementary information sources for security valuation.     

Determinants of Managerial Earnings Guidance Prior to Regulation Fair Disclosure and Bias in Analysts' Earnings Forecasts*

Prior to Regulation Fair Disclosure (“Reg FD”), some management privately guided analyst earnings estimates, often through detailed reviews of analysts' earnings models. In this paper I use proprietary survey data from the National Investor Relations Institute to identify firms that reviewed analysts' earnings models prior to Reg FD and those that did not. Under the maintained assumption that firms conducting reviews guided analysts' earnings forecasts, I document firm characteristics associated with the decision to provide private earnings guidance. Then I document the characteristics of “guided” versus “unguided” analyst earnings forecasts. Findings demonstrate an association between several firm characteristics and guidance practices: managers are more likely to review analyst earnings models when the firm's stock is highly followed by analysts and largely held by institutions, when the firm's market‐to‐book ratio is high, and its earnings are important to valuation but hard to predict because its business is complex. A comparison of guided and unguided quarterly forecasts indicates that guided analyst estimates are more accurate, but also more frequently pessimistic. An examination of analysts' annual earnings forecasts over the fiscal year does not distinguish between guidance and no‐guidance firms; both experience a “walk‐down” in annual estimates. To distinguish between guidance and no‐guidance firms, one must examine quarterly earnings news: unguided analysts walk down their annual estimates when the majority of the quarterly earnings news is negative; guided analysts walk down their annual estimates even though the majority of the quarterly earnings news is positive.     

The Relation between Analysts' Forecasts of Long‐Term Earnings Growth and Stock Price Performance Following Equity Offerings*

In this paper we evaluate the role of sell‐side analysts' long‐term earnings growth forecasts in the pricing of common equity offerings. We find that, in general, sell‐side analysts' long‐term growth forecasts are systematically overly optimistic around equity offerings and that analysts employed by the lead managers of the offerings make the most optimistic growth forecasts. In additional, we find a positive relation between the fees paid to the affiliated analysts' employers and the level of the affiliated analysts' growth forecasts. We also document that the post‐offering underperformance is most pronounced for firms with the highest growth forecasts made by affiliated analysts. Finally, we demonstrate that the post‐offering underperformance disappears once we control for the overoptimism in earnings growth expectations. Thus, the evidence presented in this paper is consistent with the “equity issue puzzle” arising from overly optimistic earnings growth expectations held at the time of the offerings.     

Forecasting Risk in Earnings

Conventional measures of risk in earnings based on historical standard deviation require long time‐series data and are inadequate when the distribution of earnings deviates from normality. We introduce a methodology based on current fundamentals and quantile regression to forecast risk reflected in the shape of the distribution of future earnings. We derive measures of dispersion, asymmetry, and tail risk in future earnings using quantile forecasts as inputs. Our analysis shows that a parsimonious model based on accruals, cash flows, special items, and a loss indicator can predict the shape of the distribution of earnings with reasonable power. We provide evidence that out‐of‐sample quantile‐based risk forecasts explain incrementally analysts' equity and credit risk ratings, future return volatility, corporate bond spreads, and analyst‐based measures of future earnings uncertainty. Our study provides insights into the relations between earnings components and risk in future earnings. It also introduces risk measures that will be useful for participants in both the equity and credit markets.     

Maintaining a Reputation for Consistently Beating Earnings Expectations and the Slippery Slope to Earnings Manipulation

This paper investigates whether maintaining a reputation for consistently beating analysts' earnings expectations can motivate executives to move from “within GAAP” earnings management to “outside of GAAP” earnings manipulation. We analyze firms subject to SEC enforcement actions and find that these firms consistently beat analysts' quarterly earnings forecasts in the three years prior to the manipulation period and continue to do so by smaller “beats” during the manipulation period. We find that manipulating firms beat expectations around 86 percent of the time in the 12 quarters prior to the manipulation period (versus 75 percent for control firms) and that manipulation often ends with a miss in expectations. We document that executives of manipulating firms face strong stock market and CEO pressure to perform. Prior to the manipulation period, these firms have high analyst optimism, growing institutional interest, and high market valuations, along with powerful CEOs. Further, we find that maintaining a reputation for beating expectations is more important than CEO overconfidence and is incremental to CEO equity incentives for explaining manipulation. Our results suggest that pressure to maintain a reputation for beating analysts' expectations can encourage aggressive accounting and, ultimately, earnings manipulation.     

Valuation and Clean Surplus Accounting: Some Implications of the Feltham and Ohlson Model for the Relative Information Content of Earnings and Cash Flows*

Abstract. This paper provides an analysis of the implications of the Feltham and Ohlson (1995) model for the relationship between unexpected security returns and unexpected earnings and cash flows. A simplified version of the Feltham and Ohlson linear information model is utilized to provide an intuitive explanation of the coefficients in the unexpected returns equation and to show that incremental information content for unexpected free cash flow beyond accounting earnings in the model depends on the existence of positive net present value (NPV) investment opportunities. The paper concludes by arguing that the model provides useful insights into factors that may influence the empirical relationship between security returns and accounting data. Résumé. L'auteur expose les résultats d'une analyse des répercussions du modèle de Feltham et Ohlson (1995) sur la relation entre les rendements imprévus des titres, d'une part, et les bénéfices et les flux monétaires imprévus, d'autre part. Il a recours à une version simplifiée du modèle d'information linéaire de Feltham et Ohlson pour expliquer intuitivement les coefficients de l'équation des rendements imprévus et pour montrer que, dans le modèle, le contenu marginal en information supérieur des flux monétaires disponibles imprévus par rapport aux bénéfices comptables dépend des possibilités d'investissement existantes offrant une valeur actualisée nette (VAN) positive. L'auteur conclut en affirmant que le modèle livre des renseignements utiles quant aux facteurs susceptibles d'influencer la relation empirique entre les rendements des titres et les données comptables.     

The Incremental Informativeness of Stock Prices for Future Accounting Earnings*

This study extends previous research that documents a stock price reaction leading accounting earnings. The primary issue is that prior studies use a naive earnings expectation model (random walk) as the benchmark for the information content of lagged returns and do not adequately address the “incremental” information content of lagged returns. This study identifies and estimates firm-specific models of earnings to control directly for the autocorrelation in earnings. The explanatory power of lagged prices with respect to this earnings residual is investigated using both a multiple regression model of lagged returns and a multiple time-series vector autoregressive model. In-sample estimation of the models provides clear evidence that stock prices impound information about future earnings incremental to the information contained in historical earnings data. Holdout period analysis of the earnings forecasts from these lagged return models finds that both models outperform the naive seasonal random walk expectation, but neither model outperforms the more sophisticated Box-Jenkins forecasts. On an individual firm basis, earnings forecasts supplemented with the lagged return data tend to be less precise than the Box-Jenkins forecasts, but the price-based models demonstrate an ability to rank the earnings forecast errors from the time-series models. The analysis helps to characterize the limitations of lagged returns as a means of predicting future earnings innovations.     

Equity Valuation Employing the Ideal versus Ad Hoc Terminal Value Expressions*

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.     

Regulation and the Valuation Relevance of Book Value and Earnings: Evidence from the United States*

Electric utilities in the United States are subject to a cost-plus normal profits pricing that is designed to align the market value of equity with the balance sheet book value. Perfect alignment implies the equality of the market and book values. Extant empirical evidence suggests that, for these utilities, actual cost/profit recovery does not follow a pure cost-plus pricing, raising the prospect that income statement items contribute to the determination of market value. What is not obvious is the extent to which the noted departure from pure cost-plus pricing results in misalignment of the market and book values, or the relative contribution of income statement items to the valuation of electric utility shares. This study pursues this question, using benchmark results for a sample of manufacturing firms to highlight the degree of market-to-book alignment for regulated and competitive firms. The results show a considerable alignment of the market and book values for utilities. In examining the relevance of book value and income statement items in the determination of market value, it is found that the contribution of earnings level to explaining market value diminishes markedly in the presence of book value for electric utilities, and the contribution of earnings change to explaining returns diminishes markedly in the presence of earnings levels. Earnings level complements book value in explaining market value for manufacturing firms, while earnings change complements earnings level in explaining returns. The results further show that the market and accounting values exhibit pronounced misalignments in returns-earnings models, especially for utilities.     

CEO Overconfidence and Management Forecasting

This paper examines how overconfidence affects the properties of management forecasts. Using both the “over‐optimism” and “miscalibration” dimensions of overconfidence to generate our predictions, we examine three research questions. First, we examine whether overconfidence increases the likelihood of issuing a forecast. Second, we examine whether overconfidence increases the amount of optimism in management forecasts. Third, we examine whether overconfidence increases the precision of the forecast. Using both options‐ and press‐based measures to proxy for individual overconfidence, we find support for all three research questions.     

A Re-Examination of Financial Analysts' Differential Earnings Forecast Accuracy*

Abstract. This research re-examines whether there are differences in the forecast accuracy of financial analysts through a comparison of their annual earnings per share forecasts. The comparison of analyst forecast accuracy is made on both an ex post (within sample) and an ex ante (out of sample) basis. Early examinations of this issue by Richards (1976), Brown and Rozeff (1980), O'Brien (1987), Coggin and Hunter (1989), O'Brien (1990), and Butler and Lang (1991) were ex post and suggest the absence of analysts who can provide relatively more accurate forecasts over multiple years. Contrary to the results of prior research and consistent with the belief in the popular press, we document that differences do exist in financial analysts' ex post forecast accuracy. We show that the previous studies failed to find differences in forecast accuracy due to inadequate (or no) control for differences in the recency of forecasts issued by the analysts. It has been well documented in the literature that forecast recency is positively related to forecast accuracy (Crichfield, Dyckman, and Lakonishok 1978; O'Brien 1988; Brown 1991). Thus, failure to control for forecast recency may reduce the power of tests, making it difficult to reject the null hypothesis of no differences in forecast accuracy even if they do exist. In our analysis, we control for the differences in recency of analysts' forecasts using two different approaches. First, we use an estimated generalized least squares estimation procedure that captures the recency-induced effects in the residuals of the model. Second, we use a matched-pair design whereby we measure the relative forecast accuracy of an analyst by comparing his/her forecast error to the forecast error of another randomly selected analyst making forecasts for the same firm in the same year on or around the same date. Using both approaches, we find that differential forecast accuracy does exist amongst analysts, especially in samples with minimum forecast horizons of five and 60 trading days. We show that these differences are not attributable to differences in the forecast issuance frequency of the financial analysts. In sum, after controlling for firm, year, forecast recency, and forecast issuance frequency of individual analysts, the analyst effect persists. To validate our findings, we examine whether the differences in the forecast accuracy of financial analysts persist in holdout periods. Analysts were assigned a “superior” (“inferior”) status for a firm-year in the estimation sample using percentile rankings on the distribution of absolute forecast errors for that firm-year. We use estimation samples of one- to four-year duration, and consider two different definitions of analyst forecast superiority. Analysts were classified as firm-specific “superior” if they maintained a “superior” status in every year of the estimation sample. Furthermore, they were classified as industry-specific “superior” if they were deemed firm-specific “superior” with respect to at least two firms and firm-specific “inferior” with respect to no firm in that industry. Using either definition, we find that analysts classified as “superior” in estimation samples generally remain superior in holdout periods. In contrast, we find that analysts identified as “inferior” in estimation samples do not remain inferior in holdout periods. Our results suggest that some analysts' earnings forecasts should be weighted higher than others when formulating composite earnings expectations. This suggestion is predicated on the assumption that capital markets distinguish between analysts who are ex ante superior, and that they utilize this information when formulating stock prices. Our study provides an ex ante framework for identifying those analysts who appear to be superior. When constructing weighted forecasts, a one-year estimation period should be used because we obtain the strongest results of persistence in this case.     

Earnings,Book Values,and Dividends in Equity Valuation*

Abstract. 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.     

An Examination of the Statistical Significance and Economic Relevance of Profitability and Earnings Forecasts from Models and Analysts

In this paper, we propose and empirically test a cross‐sectional profitability forecasting model which incorporates two major improvements relative to extant models. First, in terms of model construction, we incorporate mean reversion through the use of a two‐stage partial adjustment model and inclusion of a number of additional relevant determinants of profitability. Second, in terms of model estimation, we employ least absolute deviation (LAD) analysis instead of ordinary least squares because the former approach is able to better accommodate outliers. Results reveal that forecasts from our model are more accurate than three extant models at every forecast horizon considered and more accurate than consensus analyst forecasts at forecast horizons of two through five years. Further analysis reveals that LAD estimation provides the greatest incremental accuracy improvement followed by the inclusion of income subcomponents as predictor variables, and implementation of the two‐stage partial adjustment model. In terms of economic relevance, we find that forecasts from our model are informative about future returns, incremental to forecasts from other models, analysts’ forecasts, and standard risk factors. Overall, our results are important because they document the increased accuracy and economic relevance of a cross‐sectional profitability forecasting model which incorporates improvements to extant models in terms of model construction and estimation.     

Are Earnings Forecasts Informed by Proxy Statement Compensation Disclosures?

We investigate the extent to which market participants use compensation payouts released in the DEF 14A proxy statement (DEF14A) to assess future firm performance by examining sell-side analysts' earnings forecasts. Consistent with prior work, we confirm that CEO compensation unexplained by current observable economic factors is positively associated with future firm performance. We find that both the likelihood that analysts revise their forecasts following release of the DEF14A and the magnitude and direction of analysts' forecast revisions are positively associated with unexplained CEO compensation. These associations are stronger after the SEC required additional compensation-related disclosures in late 2006 but lower if the firm has weak corporate governance or more precise other information. Analysts' reactions are not complete, however. Analysts' forecast errors measured months after the DEF14A release are associated with past unexplained compensation, especially in the pre-2006 period and for analysts who do not revise at the DEF14A release. Taken together, our results suggest that compensation payouts released in the DEF14A contain useful forward-looking information that is recognized by at least some sophisticated market participants and that the increased disclosure regulations assisted market participants in incorporating this information.