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 Association between the Legal and Financial Reporting Environments and Forecast Performance of Individual Analysts*

We test the ability of analyst characteristics to explain relative forecast accuracy across legal origins (common law versus civil law). Common‐law countries generally have more effective corporate governance mechanisms, including stronger investor protection laws and inputs provided through higher‐quality financial reporting systems. In this type of environment, we predict that analysts with superior ability and resources in common‐law countries will more consistently outperform their peers because appropriate market‐based incentives exist. In civil‐law countries, where the demand for earnings information is reduced because of weaker corporate governance mechanisms and lower‐quality financial reporting, we predict that analysts with superior ability will less consistently provide superior forecasts. Results are consistent with our expectations and suggest an association between legal and financial reporting environments and analysts' forecast behavior.     

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.     

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.     

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.     

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.     

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 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 Approach to Adjusting Analysts' Consensus Forecasts for Selection Bias*

Many recent empirical studies have concluded that analysts' earnings forecasts are optimistic on average. In this paper, we attempt to undo the effect of one potential source of optimistic bias in analysts' earnings forecasts. Assuming forecasts come from a truncated normal distribution, we estimate the “true” population mean using maximum likelihood. We find that our estimates of earnings are more accurate and less biased than standard measures of sample mean and median. However, we do not find a closer relationship between excess market returns and forecast errors from our maximum likelihood estimate than from the sample mean. This may suggest that the market does not fully incorporate analysts' incentives in generating expectations about future earnings.     

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.     

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.     

Information Conveyed in Announcements of Analyst Coverage*

This paper examines the security market response to the announcement of sell-side analysts' decisions to initiate coverage of a firm. We examine the market reaction to the initiation announcement and the accompanying investment recommendation, by disaggregating our sample based on existing analyst coverage at the announcement date. We find, on average, a significantly larger, positive stock price reaction to buy recommendations conveyed in announcements of coverage initiation for firms with a small existing analyst following compared to such announcements for firms receiving no prior analyst coverage. Tests show that the relation between the extent of preexisting analyst coverage and market response is nonlinear and concave down in shape. Specifically we find that lightly followed firms, on average, experience larger price reactions to announcements of coverage initiations than either previously uncovered firms or more heavily followed firms. We test for and find that this result holds over a range of definitions of light coverage and is not attributable to the presence of an underwriting relationship existing between the analyst's employer and the firm receiving coverage. We do find that initiations by analysts named to Institutional Investor magazine's “All-American Research Team” produce a significantly larger market reaction than do initiations by non-All-American security analysts. In addition, similar to the market response associated with other types of information events, we observe that proxies for the richness of the initiated firms' preannouncement information environment are associated with event-day average abnormal returns.     

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.     

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.     

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.     

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.     

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.     

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.     

Earnings Management to Avoid Losses and Earnings Decreases: Are Analysts Fooled?*

This paper explores whether analyst forecasts impound the earnings management to avoid losses and small earnings decreases documented in Burgstahler and Dichev 1997, whether analysts are able to identify which specific firms engage in such earnings management, and the implications for significant forecast error anomalies at zero earnings and zero forecast earnings. We use data from Zacks Investment Research 1999 and find that analysts anticipate earnings management to avoid small losses and small earnings decreases. Further, analysts are much more likely to forecast zero earnings than firms are to realize zero earnings, and analysts are unable to consistently identify the specific firms that engage in earnings management to avoid small losses. This latter inability contributes to significant forecast pessimism associated with zero reported earnings and significant forecast optimism associated with zero earnings forecasts.