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.     

Analysts' Interpretation and Investors' Valuation of Tax Carryforwards*

We examine how financial analysts and equity investors incorporate information on deferred taxes from carryforwards into earnings forecasts and share prices. We focus on carryforwards because, in providing this information each period, management must use their private information about the firm's profitability prospects. Thus, accounting measurement of tax carryforwards is another way of providing a management earnings forecast. In analyzing the role of carryforwards in valuation, we distinguish between two conflicting effects. First, deferred taxes from carryforwards represent future tax savings; hence, they should be valued positively as assets. In contrast, the existence of tax carryforwards may signal a higher likelihood of future losses, which would have a negative effect on expected earnings and share prices. We find that analysts consider earnings of firms with carryforwards to be less persistent because of the increased likelihood of future losses. We also find that analysts tend to be less precise and more optimistic (biased) in forecasting earnings of firms with carryforwards. This higher optimism and lower precision are more pronounced just after firms adopt Statement of Financial Accounting Standards (SPAS) 109 and are almost entirely corrected over time. An analysis of investors' valuation indicates a strong positive relation between deferred taxes from carryforwards and share prices, suggesting that these carryforwards are valued as assets. Also, earnings and book values of equity are valued less in firms that have carryforwards than in firms without carryforwards. Finally, the valuation allowance required under SFAS 109 assists equity investors in valuing a firm's earnings and net assets. The combined findings on analysts' interpretation and investors' valuation suggest that analysts fail to fully capture the implication of carryforwards on future earnings within their forecasting horizon.     

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.     

Are Analysts' Cash Flow Forecasts Naïve Extensions of Their Own Earnings Forecasts?

We examine the sophistication of analysts' cash flow forecasts to better understand what accrual adjustments, if any, analysts make when forecasting cash flows. As a preliminary step, we first demonstrate that prior empirical tests used to evaluate the sophistication of analysts' cash flow forecasts are not diagnostic. We then present three sets of evidence to triangulate our conclusion that analysts' cash flow forecasts incorporate meaningful accrual adjustments. First, we review a stratified random sample of 90 analyst reports and find that the majority of these analysts include explicit adjustments for working capital and other accruals in their cash flow forecasts. Second, using a large sample of analysts' cash flow forecasts from 1993–2008, we find that these forecasts outperform time‐series cash flow forecasts in correctly predicting the sign and magnitude of accruals. Finally, we find a significant market reaction to analysts' cash flow forecast revisions, suggesting that investors find these revisions informative. Collectively, our findings demonstrate that analysts' cash flow forecasts are not simply naïve extensions of their own earnings forecasts, but that they reflect meaningful and useful accrual adjustments. These findings are relevant to researchers who examine analysts' cash flow forecasts in a variety of settings, and to investors and practitioners who employ these forecasts for valuation purposes.     

Analyst Report Readability

Using an extensive database of 356,463 sell‐side equity analysts' reports from 2002 to 2009, this study is one of the first to analyze the readability of analysts' reports. We first examine the determinants of variations in analyst report readability. Using several proxies for ability, we show that reports are more readable when issued by analysts with higher ability. Second, we test the relation between analysts' report readability and stock trading volume reactions. We find that trading volume reactions increase with the readability of analysts' text, consistent with theoretical models that predict that more precise information (and hence more informative signals) results in investors' initiating trades. These results support the view that the readability of analysts' reports is important to analysts and capital market participants.     

Horizon‐Dependent Underreaction in Financial Analysts' Earnings Forecasts*

This paper provides empirical evidence that underreaction in financial analysts' earnings forecasts increases with the forecast horizon, and offers a rational economic explanation for this result. The empirical portion of the paper evaluates analysts' responses to earnings‐surprise and other earnings‐related information. Our empirical evidence suggests that analysts' earnings forecasts underreact to both types of information, and the underreaction increases with the forecast horizon. The paper also develops a theoretical model that explains this horizon‐dependent analyst underreaction as a rational response to an asymmetric loss function. The model assumes that, for a given level of inaccuracy, analysts' reputations suffer more (less) when subsequent information causes a revision in investor expectations in the opposite (same) direction as the analyst's prior earnings‐forecast revision. Given this asymmetric loss function, underreaction increases with the risk of subsequent disconfirming information and with the disproportionate cost associated with revision reversal. Assuming that market frictions prevent prices from immediately unraveling these analyst underreac‐tion tactics, investors buying (selling) stock on the basis of analysts' positive (negative) earnings‐forecast revisions also benefit from analyst underreaction. Therefore, the asymmetric cost of forecast inaccuracy could arise from rational investor incentives consistent with a preference for analyst underreaction. Our incentives‐based explanation for underreaction provides an alternative to psychology‐based explanations and suggests avenues for further research.     

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.     

An Empirical Analysis of Analysts' Capital Expenditure Forecasts: Evidence from Corporate Investment Efficiency*

We examine whether the information conveyed in a relatively new analyst research output—capital expenditure (capex) forecasts—affects corporate investment efficiency. We find that firms with analyst capex forecasts exhibit higher investment efficiency. This effect is stronger when the forecasts are issued by analysts with higher ability or greater industry knowledge. Moreover, the effect of capex forecasts on investment efficiency varies with the signals they convey about future growth opportunities—positive-growth signals are more effective in reducing underinvestment, while negative-growth signals are more effective in reducing overinvestment. Cross-sectional tests suggest that these effects operate at least in part through both a financing channel and a monitoring channel. Taken together, our results suggest that analysts' capex forecasts convey useful information about firms' growth opportunities to managers and investors, which can facilitate efficient investment.     

Expectations Management and Beatable Targets: How Do Analysts React to Explicit Earnings Guidance?*

This study investigates security analysts' reactions to public management guidance and assesses whether managers successfully guide analysts toward beatable earnings targets. We use a panel data set between 1995 and 2001 to examine the fiscal‐quarter‐specific determinants of management guidance and the timing, extent, and outcomes of analysts' reactions to this guidance. We find that management guidance is more likely when analysts' initial forecasts are optimistic, and, after controlling for the level of this optimism, when analysts' forecast dispersion is low. Analysts quickly react to management guidance and are more likely to issue final meetable or beatable earnings targets when management provides public guidance. Our evidence suggests that public management guidance plays an important role in leading analysts toward achievable earnings targets.     

The Effect of Measurement Subjectivity Classifications on Analysts' Use of Persistence Classifications When Forecasting Earnings Items

Earnings items are typically classified in financial reports based on their persistence and measurement subjectivity. Archival research examines investors' use of persistence and measurement subjectivity classifications for forecasting and valuation. However, this research typically examines only one of these classifications at a time and ignores the potential interactive implications of an earnings item's persistence and measurement subjectivity classifications. We recruited experienced financial analysts to participate in two experiments that examined the effect of measurement subjectivity classifications on analysts' use of persistence classifications when forecasting earnings items. We find that analysts rely less on an earnings item's persistence classification when measurement subjectivity is high relative to when measurement subjectivity is low. We also find that presentation format affects analysts' use of these two classifications. Specifically, we find that the matrix format (i.e., rows display persistence classifications and columns display measurement subjectivity classifications) facilitates analysts' combined use of persistence and measurement subjectivity classifications relative to the sequential format (i.e., the classifications are displayed separately). These findings suggest that archival research could improve its examination of market participants' use of earnings classifications for forecasting and valuation by recognizing that the implications of an earnings item's persistence classification can vary according to the item's measurement subjectivity classification. By also demonstrating how presentation format affects analysts' use of earnings classifications, our study provides further insights into this fundamental issue in accounting research and standard setting.     

Earnings Announcement Disclosures and Changes in Analysts' Information

This study examines how financial disclosures with earnings announcements affect sell‐side analysts' information about future earnings, focusing on disclosures of financial statements and management earnings forecasts. We find that disclosures of balance sheets and segment data are associated with an increase in the degree to which analysts' forecasts of upcoming quarterly earnings are based on private information. Further analyses show that balance sheet disclosures are associated with an increase in the precision of both analysts' common and private information, segment disclosures are associated with an increase in analysts' private information, and management earnings forecast disclosures are associated with an increase in analysts' common information. These results are consistent with analysts processing balance sheet and segment disclosures into new private information regarding near‐term earnings. Additional analysis of conference calls shows that balance sheet, segment, and management earnings forecast disclosures are all associated with more discussion related to these items in the questions‐and‐answers section of conference calls, consistent with analysts playing an information interpretation role with respect to these disclosures.     

Valuation Implications of Unconditional Accounting Conservatism: Evidence from Analysts' Target Prices

We examine whether financial analysts understand the valuation implications of unconditional accounting conservatism when forecasting target prices. While accounting conservatism affects reported earnings, conservatism per se does not have an effect on the present value of future cash flows. We examine whether analysts adjust for the effect of conservatism included in their earnings forecasts when using these forecasts to estimate target prices. We find that signed target price errors (actual minus forecast) have a significant positive association with the degree of conservatism in forward earnings, suggesting that target prices are biased due to accounting conservatism. Cross‐sectional analysis suggests that more sophisticated analysts and superior long‐term forecasters adjust for conservatism to a greater extent than other analysts. In additional analyses, we explore the mechanism through which conservatism leads to bias in target prices. We first show that analysts' earnings forecasts are negatively associated with the degree of conservatism; that is, analysts include the effect of unconditional conservatism in their earnings forecasts. Based on alternative earnings‐based valuation models that analysts may use, our evidence suggests that analysts fail to appropriately adjust their valuation multiple for the effect of conservatism included in their earnings forecasts when using these forecasts to derive target prices. As a consequence, we find that, for extreme changes in conservatism, the bias in analysts' target prices due to conservatism leads to a distortion of market prices. The evidence highlights the concern that analysts may not appreciate the valuation implications of conservative accounting which could inhibit price discovery.     

On Constructing an EPS Measure: An Assessment of the Properties of Dilution*

This paper evaluates the information content of the treasury stock method for computing diluted earnings per share (EPS). We demonstrate that the treasury stock method decreases the annual association between earnings changes and stock returns and explain why this is the case. Further, we show that the treasury stock method leads to a dilutive adjustment that biases the random walk model of annual earnings in a predictable direction. Finally, we demonstrate that using the treasury stock method appears to confuse both analysts and investors: analysts' forecast errors increase with the size of the dilutive adjustment, and the association between unexpected earnings and stock returns at the earnings announcement date weakens as the dilutive adjustment increases.     

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.     

Individual Investors' Attention to Accounting Information: Evidence from Online Financial Communities*

Online financial communities provide a unique opportunity to directly examine individual investors' attention to accounting information on a large scale and in great detail. I analyze accounting-related content in large samples of Yahoo! message board posts and StockTwits and find investors pay attention to a range of accounting information, fixating particularly on earnings, cash, and revenues. Consistent with the expectation that investors react to relevant information events, I find accounting-related discussion elevated around the filings of earnings releases and 8-K reports, but the reaction to periodic reports is confined to small firms. I also find investors expand their acquisition of accounting information and processing efforts in poor information environments. Greater attention to accounting information at earnings releases does not appear to be meaningfully associated with better information processing.     

Who Herds? Who Doesn't? Estimates of Analysts’ Herding Propensity in Forecasting Earnings

We develop parametric estimates of the imitation‐driven herding propensity of analysts and their earnings forecasts. By invoking rational expectations, we solve an explicit analyst optimization problem and estimate herding propensity using two measures: First, we estimate analysts’ posterior beliefs using actual earnings plus a realization drawn from a mean‐zero normal distribution. Second, we estimate herding propensity without seeding a random error, and allow for nonorthogonal information signals. In doing so, we avoid using the analyst's prior forecast as the proxy for his posterior beliefs, which is a traditional criticism in the literature. We find that more than 60 percent of analysts herd toward the prevailing consensus, and herding propensity is associated with various economic factors. We also validate our herding propensity measure by confirming its predictive power in explaining the cross‐sectional variation in analysts’ out‐of‐sample herding behavior and forecast accuracy. Finally, we find that forecasts adjusted for analysts’ herding propensity are less biased than the raw forecasts. This adjustment formula can help researchers and investors obtain better proxies for analysts’ unbiased earnings forecasts.     

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.     

An Empirical Examination of the Divergence between Managers’ and Analysts’ Earnings Forecasts

We study circumstances when analysts’ forecasts diverge from managers’ forecasts after management guidance, and the consequences of this divergence for investors and analysts. Our results show that investors’ return response to earnings surprises based on analyst forecasts is significantly weaker when analyst and management forecasts diverge, and that this attenuating effect is stronger when the management forecast is more credible. When the divergent management forecast is more accurate than the analyst consensus forecast, the subsequent‐quarter analyst consensus forecast is significantly more accurate than that of the current quarter, and exhibits less serial correlation. Overall, our findings suggest that, when analyst and management forecasts diverge, investors find the two sources to contain complementary information, and analysts learn to improve their subsequent forecasts.     

An Experimental Test of the Interaction of the Insurance and Information‐Signaling Hypotheses in Auditing*

Three incentives for hiring auditing services have been proposed in the literature: (1) to signal outsiders about the company's prospects, (2) to provide a potential source of loss recovery for investors (insurance), and (3) to reduce agency costs. The objective of this study is to examine the potential for the first two (signaling and insurance) to interact while controlling for agency costs. We conduct an experiment in which highly experienced financial analysts provide stock price estimates for a company that is under financial stress. We manipulate, between participants, the signal provided by the audit opinion (going‐concern modification, yes/no) and the ability of investors to recover losses from auditors. The key finding is that the effect of the going‐concern opinion on investor value judgements is moderated by the extent to which the auditor provides an insurance function. Specifically, the negative effect of a going‐concern opinion on the analysts' stock price estimates is reduced by the extent that the environment treats the auditor as an insurer.     

The Effect of Investor Status on Investors' Susceptibility to Earnings Fixation

This study investigates whether an individual's status as a current or a prospective investor affects the investor's susceptibility to earnings fixation and proposes a mechanism to reduce earnings fixation. Our experimental results suggest that current investors are more susceptible to earnings fixation than prospective investors, and that current investors can reduce earnings fixation by explicitly forecasting future earnings as part of their evaluation process. We provide theory‐consistent evidence that current investors' prevention focus makes them elevate the importance of summary earnings in their evaluation of a company. However, after forecasting future earnings, current investors view summary earnings as only one of several similarly important evaluation inputs rather than as one substantially more important input (relative to its components). Our study contributes to research on earnings fixation and investor status. We also contribute to practice by documenting the moderating effect of investor status on earnings fixation and by identifying a simple mechanism that current investors can use to reduce their susceptibility to earnings fixation.