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’ Use of Nonfinancial Information Disclosures*

In this study I examine how analysts process nonfinancial information and how this is affected by the patterns of firms’ nonfinancial information disclosures. More specifically, I examine the association between analyst earnings forecast errors and the persistence of nonfinancial disclosures, both across information content and over time. The study focuses on firms in the wireless industry for the period 1997–2007. The results show that analysts tend to underreact to the information contained in customer acquisition cost, average revenue per user, and the number of subscribers. These are the performance measures that have significant predictive ability for future earnings of wireless firms. Distinguishing between firms on the basis of their nonfinancial disclosure patterns reveals that the above findings are driven primarily by firms with irregular disclosures. There is no evidence of analysts’ inefficiency in evaluating the content of nonfinancial metrics provided by persistently disclosing firms. This implies that the lack of systematic disclosures of performance measures restricts financial analysts’ ability to fully analyze the contributions of these metrics for future earnings.     

Are Investors Misled by “Pro Forma” Earnings?*

This paper uses stock market data to investigate the popular claim that investors are misled by the “pro forma” earnings numbers conspicuously featured in the press releases of some U.S. firms. We first document the frequency and magnitude of pro forma earnings in press releases issued during June through August 2000, and describe the 433 firms that engaged in this financial disclosure strategy. Our test period predates public expressions of concern by trade associations and regulators that pro forma earnings may mislead investors and the subsequent issuance of guidelines and rules on the disclosure of pro forma earnings numbers. We use two complementary approaches to determine whether the share prices that investors assign to pro forma firms are systematically higher than the prices assigned to other firms. Our market‐multiples tests for differences in price levels find some evidence suggesting that pro forma firms may be priced higher than firms that do not use the disclosure strategy. This apparent overpricing is not, however, related to the pro forma earnings numbers themselves. Our narrow‐window stock returns tests reveal no evidence of a stock return premium for pro forma firms at the quarterly earnings announcement date. Collectively, the results cast doubt on the notion that investors are, on average, misled by pro forma earnings disclosures despite the widespread concern expressed in the financial press and by regulators.     

International Diversification,SFAS 131 and Post‐Earnings‐Announcement Drift

Using 1990 through 2013 data of U.S. firms with foreign operations, we show that (i) the serial correlation of analyst forecast errors increases in the extent of international diversification, (ii) post‐earnings‐announcement drift (PEAD) based on analyst forecast errors increases in the extent of international diversification, and (iii) the impact of international diversification on the serial correlation of analyst forecast errors and its associated drift is significantly reduced after the implementation of SFAS 131 on segment disclosures. When we replicate our tests using seasonally differenced earnings, we fail to observe similar patterns. Overall, our results suggest that investors’ underreaction to announced earnings is a likely explanation for PEAD. Our findings also indicate that disclosures required under SFAS 131 are useful to analysts in forming efficient earnings expectations, thereby helping capital market participants in the pricing of internationally diversified firms’ earnings.     

To Guide or Not to Guide? Causes and Consequences of Stopping Quarterly Earnings Guidance

In recent years, quarterly earnings guidance has been harshly criticized for inducing “managerial short‐termism” and other ills. Managers are, therefore, urged by influential institutions to cease guidance. We examine empirically the causes of such guidance cessation and find that poor operating performance — decreased earnings, missing analyst forecasts, and lower anticipated profitability — is the major reason firms stop quarterly guidance. After guidance cessation, we do not find an appreciable increase in long‐term investment once managers free themselves from investors’ myopia. Contrary to the claim that firms would provide more alternative, forward‐looking disclosures in lieu of the guidance, we find that such disclosures are curtailed. We also find a deterioration in the information environment of guidance stoppers in the form of increased analyst forecast errors and forecast dispersion and a decrease in analyst coverage. Taken together, our evidence indicates that guidance stoppers are primarily troubled firms and stopping guidance does not benefit either the stoppers or their investors.     

Do Firms Use Tax Reserves to Meet Analysts’ Forecasts? Evidence from the Pre‐ and Post‐FIN 48 Periods

We examine whether firms decrease tax reserves to meet analysts’ quarterly earnings forecasts in the period prior to FIN 48, and whether that behavior changed following FIN 48. We use analysts’ forecasts of pretax and after‐tax income to impute premanaged earnings, or earnings before any tax manipulation. Pre‐FIN 48, we observe that firms reduce their tax reserves (i.e., increase income) when premanaged earnings are below analysts’ forecasts. Specifically, 78 percent of firm‐quarters that would have missed the analyst forecast if not for the tax reserve decrease, meet that target when the decrease is included. Furthermore, we find a significant positive association between the decrease in tax reserves and the deviation of premanaged earnings from analysts’ forecasts. In contrast, post‐FIN 48, we find no evidence that firms use changes in tax reserves to manage earnings to meet analysts’ forecasts. Thus, our results suggest that FIN 48 has, at least initially, curtailed firms’ use of tax reserves to manage earnings.     

The Walk‐down to Beatable Analyst Forecasts: The Role of Equity Issuance and Insider Trading Incentives*

It has been alleged that firms and analysts engage in an "earnings‐guidance game" where analysts first issue optimistic earnings forecasts and then "walk down" their estimates to a level that firms can beat at the official earnings announcement. We examine whether the walk‐down to beatable targets is associated with managerial incentives to sell stock after earnings announcements on the firm's behalf (through new equity issuance) or from their personal accounts (through option exercises and stock sales). Consistent with these hypotheses, we find that the walk‐down to beatable targets is most pronounced when firms or insiders are net sellers of stock after an earnings announcement. These findings provide new insights on the impact of capital‐market incentives on communications between managers and analysts.     

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.     

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.     

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.     

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.     

Financial Statement Complexity and Meeting Analysts’ Expectations

We examine whether firms with greater financial statement complexity are more likely to meet or beat analysts’ earnings expectations. We proxy for financial statement complexity using the firm's industry and year adjusted accounting policy disclosure length. Firms with more complex financial statements are more likely to just beat expectations than just miss expectations. Firms with complex financial statements appear to use expectations management to beat expectations, but do not use earnings management. Corroborating these findings, we find analysts rely more on management guidance for more complex firms. Firms with complex financial statements are also more likely to have analysts exclude items from actual “street earnings,” but tests suggest this strategy is not specifically used by complex firms to beat expectations. The effect we document is specific to analyst forecasts and not to other alternative benchmarks.     

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.     

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.     

Analyst Coverage and the Likelihood of Meeting or Beating Analyst Earnings Forecasts

This paper examines the relation between analyst coverage and whether firms meet or beat analyst earnings forecasts. We distinguish between whether a firm's reported quarterly earnings meet (i.e., equal or exceed by one cent) or beat (i.e., exceed by more than one cent) its consensus analyst earnings forecasts. We find a positive relation between analyst coverage and whether a firm meets or beats analyst forecasts. However, the more pronounced relation is that between analyst coverage and meeting analyst forecasts. Also, when we consider exogenous shocks to analyst coverage due to brokerage mergers or closures and conglomerate spinoffs, we continue to find a robust positive relation only between analyst coverage and meeting analyst forecasts. To shed light on the causal relation involved, we examine and find that greater analyst coverage is associated with a significantly larger market reaction to negative earnings surprises. We also document that firms with greater analyst coverage are more likely to guide analyst earnings forecasts downwards. Taken together, our evidence suggests that greater analyst coverage raises the pressure on managers to meet analyst earnings forecasts.     

Evidence that Prices Do Not Fully Reflect the Implications of Current Earnings for Future Earnings: An Experimental Markets Approach*

Abstract. Analysts have been found to underweight the innovation in the most recent quarterly earnings when forecasting next-quarter earnings, and these expectations have been posited as an explanation for post-earnings-announcement drift. This study uses an experimental asset market to examine whether similar errors in forecasting quarterly earnings are made by student-subjects. We examine two aspects of their behavior: (1) do subjects underestimate the autocorrelation in quarterly earnings when forming earnings expectations? and (2) are asset prices consistent with a subject's underestimation of the autocorrelation in quarterly earnings? We observe subject errors in forecasts that underweight extreme innovations in the most recent quarterly earnings by approximately 40 percent. The prices in the experimental markets also fail to reflect fully the most recent innovation in quarterly earnings. We are able to predict the sign of the incorrect pricing, from the mean initial earnings predictions of the subjects, in 74 percent of the 135 markets. These forecast errors observed in this study are consistent with forecast errors observed for analysts, and this consistency suggests that errors in analysts' forecasts may be at least partially attributable to the use of judgmental heuristics.     

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.     

The Impact of the Bullwhip Effect on Sales and Earnings Prediction Using Order Backlog

Recent work in the supply chain literature suggests that the variance in orders placed with suppliers will be larger than that of sales to buyers. This distortion in demand information increases as it is passed along the supply chain from customers to upstream suppliers and has been referred to as “the bullwhip effect.” In this paper, we argue that the bullwhip effect reduces the ability of order backlog to predict future sales and earnings for upstream suppliers. Results obtained from our empirical analysis support this proposition. We find that the impact of bullwhip on the predictive ability of order backlog is further accentuated in firms with longer operating cycles. Market intermediaries such as financial analysts, on average, are unable to fully account for differences in the predictive ability of order backlog. However, analysts belonging to employers that follow all firms in a vertical supply chain do a better job of understanding the impact of bullwhip on the predictive ability of order backlog. In additional tests, we find that the bullwhip effect also impedes the ability of inventory components to predict future sales and earnings.     

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.     

Exchange‐Sponsored Analyst Coverage

Several major stock exchanges, including the NASDAQ and NYSE Euronext, have recently embarked on schemes to sponsor and promote analyst coverage for firms listed on their exchanges. We evaluate the efficacy of one such scheme pioneered by the Singapore Exchange (SGX). We find that sponsored analysts produce forecasts with similar bias, but lower accuracy than those issued by analysts voluntarily following a firm. In analyses that control for self‐selection into the SGX Scheme, we find that sponsored firms enjoy at best minor improvements in their information environments and stock liquidity. Any benefits accruing from the scheme are insufficient to make sponsored firms fully comparable to those of firms with voluntary analyst following on the measured attributes.