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.     

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.     

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.     

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.     

MD&A Quality as Measured by the SEC and Analysts' Earnings Forecasts*

This study examines the predictive value of Management Discussion and Analysis (MD&A) information. More specifically, this study tests the association between properties of analysts' earnings forecasts and MD&A quality, where MD&A quality is measured by the Securities Exchange Commission (SEC). We find that high MD&A ratings are associated with less error and less dispersion in analysts' earnings forecasts after controlling for many other expected influences on analysts' forecasts. We also find that estimated regression coefficients are consistent with MD&A information having a substantial effect on earnings forecasts. Finally, we find our results are driven by forward-looking disclosures about capital expenditures and operations, and also by historical disclosures about capital expenditures. These findings are consistent with the suggestion by many constituencies (including the SEC) that the type of information found in high quality MD&A is particularly relevant for predicting earnings.     

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.     

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.     

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.     

Does Tax Planning Affect Analysts' Forecast Accuracy?

We investigate whether firms' tax planning affects the accuracy of analysts' forecasts. Tax planning can exacerbate the complexity of firms' operations through strategic choices to exploit tax laws. Because of its effect on firms' operations, tax planning can influence analysts' efforts to understand and forecast earnings. Specifically, if the additional complexity arising from tax planning makes firm attributes less representative of expected earnings, analysts may issue less accurate forecasts. Using auditor‐provided tax services (APTS) as a measure of tax planning, we find that, as firms spend more on tax planning, the accuracy of analysts' forecasts of both earnings per share and tax expense declines. We also document that firms with higher levels of APTS have greater year‐to‐year volatility in, and lower persistence of, effective tax rates and earnings. Our results suggest that increased firm complexity, due to greater tax planning, makes earnings and tax expense more difficult to forecast and that analysts do not properly adjust for these effects. Thus, when deciding to engage in tax planning, firms appear to make trade‐offs between potential tax savings and negative effects on earnings properties and analysts' forecasts.     

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.     

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.     

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.     

The Effect of Investment Banking Relationships on Financial Analysts' Earnings Forecasts and Investment Recommendations*

Abstract. This study shows that financial analysts of brokerage firms that provide investment banking services to a company (investment banker analysts) are optimistic, relative to other (noninvestment banker) analysts, in their earnings forecasts and investment recommendations. Returns earned by following the investment recommendations of investment banker analysts, however, are not significantly different from those of non-investment banker analysts. Given that information regarding the investment banking relationships of brokerage firms is publicly available, we find evidence that capital market participants rely relatively less on the investment banker analysts in forming their earnings expectations. Although we find a significant capital market reaction around the noninvestment banker analysts' research report dates and not around the investment banker analysts' research report dates, the difference between the two market reactions is not statistically significant. Finally, we find that investment banker analysts' earnings forecasts are, on average, as accurate as those of noninvestment banker analysts. Résumé. Les auteurs mettent en évidence le fait que les analystes financiers des maisons de courtage qui offrent des services de prise ferme aux entreprises (les analystes de courtiers preneurs ferme) sont optimistes dans leurs prévisions de bénéfices et leurs recommandations de placements, par comparaison aux autres analystes (c'est-à-dire aux analystes de courtiers qui ne sont pas preneurs ferme). Les rendements obtenus par les investisseurs qui observent les recommandations de placements des analystes de courtiers preneurs ferme ne sont cependant pas sensiblement différents de ceux qu'obtiennent les investisseurs qui se fient aux analystes des courtiers qui ne sont pas preneurs ferme. Compte tenu du fait que l'information relative aux relations qu'entretiennent les maisons de courtage en matière de prise ferme est du domaine public, les constatations des auteurs confirment que les participants au marché financier s'appuient relativement moins sur le verdict des analystes des courtiers preneurs ferme dans le calcul de leur espérance de gains. Bien que les auteurs observent une réaction marquée du marché financier à proximité des dates de publication des rapports de recherche des analystes des courtiers qui ne sont pas preneurs ferme, ce qui n'est pas le cas à proximité des dates de publication des rapports de recherche des analystes des courtiers preneurs ferme, la différence entre ces deux réactions n'est pas statistiquement significative. Enfin, les auteurs constatent que les prévisions de bénéfices des analystes des courtiers preneurs ferme sont, en moyenne, aussi exactes que celles des analystes des courtiers qui ne sont pas preneurs ferme.     

Do Analysts' Cash Flow Forecasts Encourage Managers to Improve the Firm's Cash Flows? Evidence from Tax Planning

Recent research finds that analysts' cash flow forecasts have meaningful financial reporting ramifications, but, to date, the identified effects are unlikely to yield meaningful cash flow benefits. This study examines whether analysts' cash flow forecasts encourage managers to enhance the firm's cash flow position through tax avoidance activities. We evaluate the change in cash tax avoidance after analysts begin issuing cash flow forecasts relative to a propensity score matched control sample of firms without cash flow forecasts. Consistent with analysts' cash flow forecasts encouraging tax avoidance that enhances the firm's cash flow health, we find a negative association between cash tax payments and analysts' cash flow coverage. Additional analysis suggests this association is driven primarily by strategies to permanently avoid rather than to temporarily defer tax payments and that increased cash tax avoidance activity represents a nontrivial component of the overall increase in reported operating cash flows after the initiation of analysts' cash flow coverage.     

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.     

Mitigating the Influence of Analysts Who Issue Aggressive Stock Price Targets: The Role of Joint Versus Separate Evaluation*

Investors frequently rely on individual analysts' stock price targets. Aggressive price targets often reflect analysts' attempts to strategically influence investors. Therefore, investors' welfare may be compromised if they take aggressive price targets at face value. In this study, we examine conditions under which investors are more likely to infer that analysts who issue aggressive price targets are acting strategically. Investors can evaluate multiple analysts' price targets with or without other related information (e.g., earnings estimates). Investors can also evaluate the information provided by multiple analysts jointly or separately one analyst at a time. Two experiments find that as predicted, when investors evaluate multiple analysts' price targets without earnings estimates, there is no difference in investors' perceptions about whether the aggressive analyst is acting strategically across joint versus separate evaluation. However, also as predicted, when investors evaluate multiple analysts' price targets along with their earnings estimates, investors perceive the aggressive analyst as acting more strategically under joint evaluation than under separate evaluation. Our findings suggest that jointly evaluating multiple analysts' price targets with other related information, such as earnings estimates, can reduce the likelihood that investors would be overly influenced by aggressive analysts.     

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.     

Accounting Policy Disclosures and Analysts' Forecasts

Using an international sample, I investigate whether the extent of firms' disclosure of their accounting policies in the annual report is associated with properties of analysts' earnings forecasts. Controlling for firm‐ and country‐level variables, I find that the level of accounting policy disclosure is significantly negatively related to forecast dispersion and forecast error. In particular, I find that accounting policy disclosures are incrementally useful to analysts over and above all other annual report disclosures. These findings suggest that accounting policy disclosures reduce uncertainty about forecasted earnings. I find univariate but not multivariate support for the hypothesis that accounting policy disclosures are especially helpful to analysts in environments where firms can choose among a larger set of accounting methods.     

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.