Discussion of “Are earnings forecasts more accurate when accompanied by cash flow forecasts?”

Call et al. (Rev Account Stud 2009, this issue) demonstrate that, relative to analysts who issue earnings but not cash flow forecasts, analysts who issue both forecasts (i) produce relatively more accurate earnings forecasts, (ii) have a better understanding of the persistence of current earnings, and (iii) are less likely to get fired. In my discussion, I highlight some general challenges facing research on analyst cash flow forecasts, demonstrate the diminishing difference in the relative accuracy over time (including its compete elimination by 2004), and examine the sensitivity of some of the evidence in Call et al. (2009) to the age of the forecast and to the presence of extreme bad-news earnings surprises.     

Are analysts' cash flow forecasts useful?

This study provides evidence that the cost of equity capital decreases with the number of analysts who issue both cash flow and earnings forecasts (cash analysts). The evidence also shows that cash analysts reduce information asymmetry and predict long‐term earnings more accurately than analysts who issue only earnings forecasts. Taken together, these findings suggest that cash analysts provide market participants with high‐quality information and, as a result, firms benefit from cash analyst coverage in the form of a reduced cost of equity capital.     

Market implied future earnings and analysts’ forecasts

This study provides evidence on market implied future earnings based on the residual income valuation (RIV) framework and compares these earnings with analyst earnings forecasts for accuracy (absolute forecast error) and bias (signed forecast error). Prior research shows that current stock price reflects future earnings and that analyst forecasts are biased. Thus, how price-based imputed forecasts compare with analyst forecasts is interesting. Using different cost of capital estimates, we use the price-earnings relation and impute firms’ future annual earnings from three residual income (RI) models for up to 5 years. Relative to I/B/E/S analyst forecasts, imputed forecasts from the RI models are less or no more biased when cost of capital is low (equal to a risk-free rate or slightly higher). Analysts slightly outperform these RI models in terms of accuracy for immediate future (1 or 2) years in the forecast horizon but the opposite is true for more distant future years when cost of capital is low. A regression analysis shows that, in explaining future earnings changes, analyst forecasts relative to imputed forecasts do not impound a significant amount of earnings information embedded in current price. In additional tests, we impute future long-term earnings growth rates and find that they are more accurate and less biased than I/B/E/S analyst long-term earnings growth forecasts. Together, the results suggest that the RIV framework can be used to impute a firm’s future earnings that are high in accuracy and low in bias, especially for distant future years.     

To beat or not to beat? The importance of analysts’ cash flow forecasts

We investigate the implications of firms’ benchmark-beating patterns with respect to analysts’ quarterly cash flow forecasts for firms’ current capital market valuation and their future performance. We hypothesize that nonnegative earnings surprises are more likely to be supported by real operating performance and signal higher earnings quality if they are achieved via higher than expected cash flows or lower than expected accruals. We show that firms beating analyst earnings forecasts have larger positive capital market reactions and larger earnings response coefficients if they beat analyst cash flow forecasts or report lower than expected accruals. We also demonstrate that these firms’ superior future performance may provide an economic justification for their more favorable market response. Our findings suggest that firms’ ability to beat analyst cash flow forecasts is informative regarding the quality of their earnings surprises.     

Does short selling reduce analysts’ optimism bias in earnings forecasts?

We examine the relationship between short selling and analyst optimism bias of earnings forecasts of stocks in China. We propose two possible hypotheses: short selling enhances analysts’ information set to lower optimism bias and analysts drum up optimistic earnings forecasts to counter short selling. Our results suggest that short selling and earnings optimism bias are negatively correlated. The findings are robust to a two-stage least square method, a difference in-differences fixed effect model, an alternative measure of optimism bias, incorporated different time windows to calculate short selling, considered bull and bear market conditions, accounting for media coverage, and using abnormal short selling. By leveraging rich data, we conduct additional analyses using stocks with different forecasting horizons and earnings forecasts that were made after the accounting year but prior to the earnings announcement to further support expanding the information set argument. Lastly, we document that short selling information improves the accuracy of earnings forecasts.     

Detailed management earnings forecasts: do analysts listen?

We provide archival evidence on how a particular type of supplementary information affects the credibility of management earnings forecasts. Managers often provide detailed forecasts of specific income statement line items to shed light on how they plan to achieve their bottom-line earnings targets. We assess the effect of this forecast disaggregation on the credibility of management earnings forecasts. Based on a relatively large hand-collected sample of 900 management earnings forecasts, we find that disaggregation increases analysts’ sensitivity to the news in managers’ earnings guidance, suggesting that analysts find the guidance more credible. More importantly, we identify several factors that influence this relation. First, disaggregation plays a more important role when earnings are otherwise more difficult to forecast. Second, disaggregation is more important after Regulation Fair Disclosure prohibited selective disclosure, especially for firms that were more affected because they had previously provided more private guidance. Finally, in contrast to common assertions in the prior literature, we find that, in more recent years, disaggregation matters more for guidance that conveys bad news. Managers as well as researchers should be interested in evidence suggesting that financial analysts find disaggregation especially helpful in contexts where managers’ credibility is particularly important.     

The effect of non-recurring items on analysts’ earnings forecasts

This article discusses the effects of non-recurring profits and losses on statement users’ decision-making processes from the perspective of securities analysts. We examine the relationship between analysts’ forecast revisions and firms’ non-recurring earnings. We find that 1) non-recurring gains and losses can influence analysts’ earnings forecast revision; 2) compared with non-recurring items resulting from policy changes, analysts are more concerned about those attributed to changes in business scope; 3) if listed companies use non-recurring items to turn losses into gains during earnings management, it will weaken the effects of non-recurring items on analysts’ earnings forecast revision. The results suggest that non-recurring items that result from changes in business scope incorporate information that users need for the future operation of the business. This article verifies the information relevance of non-recurring items and provides evidence for the necessity of non-recurring item disclosure.     

Brokerage trading volume and analysts’ earnings forecasts: a conflict of interest?

Review of Accounting Studies - Using unique new data, we examine whether brokerage trading volume creates a conflict of interest for analysts. We find that earnings forecast optimism is associated...     

A re-examination of analysts’ superiority over time-series forecasts of annual earnings

We re-examine the widely held belief that analysts?? earnings per share (EPS) forecasts are superior to random walk (RW) time-series forecasts. We investigate whether analysts?? annual EPS forecasts are superior, and if so, under what conditions. Simple RW EPS forecasts are more accurate than analysts?? forecasts over longer horizons, for smaller or younger firms, and when analysts forecast negative or large changes in EPS. We also compare the accuracy of a third forecast of longer-term earnings based on a na?ve extrapolation of analysts?? 1-year-ahead forecasts. Surprisingly, this na?ve extrapolation provides the most accurate estimate of long-term (2- and 3-year-ahead) earnings. These findings recharacterize prior generalizations about the superiority of analysts?? forecasts and suggest that they are incomplete, misleading, or both. Moreover, in certain settings, researchers can rely on forecasts other than these explicit forecasts.     

Does revenue-expense matching play a differential role in analysts’ earnings and revenue forecasts?

This paper investigates whether matching has differential implications for the accuracy of analysts' earnings and revenue forecasts. We construct a novel measure of firm-level matching and document that matching improves analysts' earnings forecasts to a greater extent than their revenue forecasts. We also document matching's differential impact on analysts' earnings and sales forecasts by proposing a new count metric capturing a wedge in the accuracy of earnings and revenue forecasts. In additional tests, we report that the differential impact of matching is less (more) pronounced in a situation where the balance sheet (income statement) orientation likely dominates. We also report that matching's differential role is weaker (stronger) when firms have high intangible intensity (analysts have appropriate resources or expertise). In short window tests, matching's role in analysts' forecast revisions is more pronounced for earnings than sales forecasts. Overall, these results show how analysts benefit from better revenue-expense matching.     

Management earnings forecasts and the quality of analysts’ forecasts: The moderating effect of audit committees

This study investigates whether effective audit committees influence the association between management earnings forecasts and the properties of analysts’ forecasts. We posit that this influence on the part of an audit committee would likely result from increased responsibility for monitoring voluntary disclosure. Using the four attributes that the Blue Ribbon Committee (1999) and prior research suggest as being indicative of audit committee effectiveness, we find that analysts’ forecasts exhibit higher accuracy and lower dispersion with the issuance of management forecasts for those firms employing audit committees that are composed exclusively of independent directors, include an accounting expert, and act with due diligence. We also find that effective audit committees strengthen the association between management and analyst forecast accuracy. Our evidence, therefore, supports the notion that effective corporate governance influences the reliability of voluntary disclosure, and thereby benefits the users of financial information.     

Relative accuracy of analysts’ earnings forecasts over time: a Markov chain analysis

The main purpose of this paper is to analyze the time patterns of individual analysts’ relative accuracy ranking in earnings forecasts using a Markov chain model. Two levels of stochastic persistence are found in analysts’ relative accuracy over time. Factors underlying analysts’ performance persistence are identified and they include analyst’s length of experience, workload, and the size and growth rate of firms followed by the analyst. The strength and the composition of these factors are found to vary markedly in different industries. The findings support the general notion that analysts are heterogeneous in their accuracy in earnings forecasts and that their superior/inferior performance tends to persist over time. An analysis based on a refined measure of analysts’ forecast accuracy ranking that strips off firm-specific factors further enhances the empirical validity of the findings. These findings provide a concrete basis for researchers to further explore why and how analysts perform differently in the competitive market of investment information services.     

Regulation FD and analysts’ vs. investors’ weightings of the cash components of earnings

This paper investigates whether investors’ bias in processing the information contained in the cash components of annual earnings has been reduced, and whether the difference in bias between financial analysts and investors has decreased subsequent to Regulation Fair Disclosure (hereafter, Reg FD). We compare analysts’ and investors’ weightings of the three cash flow components of earnings, defined by Dechow, Richardson, and Sloan (2008), from 1985 to 2008, using historical weightings as benchmarks. Our results show that, in the post Reg FD period, the magnitude of investors’ (analysts’) mis-weightings has decreased (increased), and the differences between analysts’ and investors’ mis-weightings have become smaller. Overall, these results suggest that financial analysts’ information advantages over investors declined after Reg FD took effect, and that investors consequently are less biased in assessing the persistence of the cash flow components of earnings following the implementation of Reg FD.     

Do earnings reported under IFRS tell us more about future earnings and cash flows?

We contribute to the debate about the relative benefits and costs of International Financial Reporting Standards (IFRS) adoption by examining whether earnings persistence and the association between current accounting earnings and future cash flows differ for firms reporting under IFRS versus firms reporting under United States Generally Accepted Accounting Principles (U.S. GAAP) and firms reporting under non-U.S. domestic accounting standards (DAS). Using samples comprised of 58,832 firm-year observations drawn from 33 countries from 2002 through 2008, we find that positive earnings reported under IFRS are no more or less persistent than earnings reported under U.S. GAAP but losses reported under IFRS are less persistent than losses reported under U.S. GAAP. Moreover, we find that earnings reported under IFRS are no more or less persistent and are no more or less associated with future cash flows than earnings reported under non-U.S. DAS. However, we find that earnings reported under U.S. GAAP are more closely associated with future cash flows than earnings reported under IFRS. This is important if a key role of reported earnings is to help investors form expectations about future cash flows. These results should be of interest to academics and standard-setters as they debate the merits of transitioning to IFRS, and to parties who use reported earnings to form expectations about future earnings and cash flows.     

Market timing using strategists’ and analysts’ forecasts of S&P 500 earnings per share

This paper examines the bias in and usefulness of top-down and bottom-up consensus forecasts of earnings per share for the S&P 500 Index provided by market strategists and analysts to I/B/E/S. These forecasts exhibit a significant optimism bias that decreases over the 12 months up to release of actual earnings per share. The bias is significantly more pronounced for the bottom-up forecasts of analysts. Unlike the findings for country timing, we demonstrate that a stock market timer using switching rules based on the consensus forecasts of S&P 500 earnings or the directional switch in the consensus or in the number of switchers cannot generate a free lunch.     

Are all management earnings forecasts created equal? Expectations management versus communication

Recent studies associate management earnings forecasts (MEFs) with expectations management. These studies, however, neither provide evidence on the extent and scope of expectations management through MEFs nor consider alternative incentives for issuing MEFs. Consequently, existing evidence does not help regulators assess whether MEFs effectively facilitate communication with investors. We investigate to what extent managers exploit their earnings forecasts as a tool of expectations management or as a communication device. By examining relations among MEFs, analysts?? forecasts, and actual earnings, we classify MEFs into three incentive categories: (1) expectations management, (2) communication, and (3) other incentives. We find that a significant proportion (approximately 45%) of MEFs is issued to convey accurate earnings information to the market (that is, communication incentive). We also find that the fraction of MEFs for the expectations-management incentive increases post-Regulation Fair Disclosure. The evidence from examination of the various managerial motives for each incentive category supports our classification. Additional analysis using alternative classifications based on bad/good news and pessimistic/optimistic forecasts reveals that our proposed classification of MEFs works better in defining expectations management than these other classifications. This implies that more caution is warranted in defining expectations management when investigating the association between managerial motives and incentives for issuing MEFs.     

The effects of operating cash flow disclosure on earnings comparability,analysts' forecasts,and firms’ investment decisions during the Pre-IFRS era

We examine the effects of the availability of operating cash flow (OCF) information disclosed by firms operating in 15 international countries during the pre-IFRS era on: (1) the comparability of these firms' disaggregated earnings to those of U.S. firms for equity valuation purposes, (2) the properties of analysts' earnings forecasts, and (3) the efficiency of firms' investment decisions. We find that the comparability of disaggregated earnings improves after company-disclosed OCF information is available. We also find decreases in analysts' forecast errors and dispersion and a decrease in firms’ tendency to over- or under-invest when they are predisposed to do so.     

The characteristics of individual analysts’ forecasts in Europe

This study investigates the determinants of financial analysts’ forecasts differential accuracy in 14 different European stock markets. Using the I/B/E/S Detail History Database, I find that European financial analysts forecast accuracy is positively associated with analyst firm specific experience. Forecast accuracy is negatively associated with the number of countries followed by analysts and the age of the forecast. Surprisingly, I find no relationship between forecast accuracy and analysts’ job experience and the size of the bank employing the analyst.     

Does the midpoint of range earnings forecasts represent managers’ expectations?

The accounting literature has used the midpoint of range forecasts in various research settings, assuming that the midpoint is the best proxy for managers’ earnings expectations revealed in range forecasts. We argue that given managers’ asymmetric loss functions regarding earnings surprises, managers are unlikely to place their true earnings expectations at the midpoint of range forecasts. We predict that managers’ true expectations are close to the upper bound of range forecasts. We find evidence consistent with these predictions in 1996–2010, especially in the recent decade. Despite their role as sophisticated information intermediaries, analysts barely unravel the pessimistic bias that managers embed in range forecasts. Furthermore, we find that the upper bound rather than the midpoint better represents investors’ interpretation of managers’ expectations in recent times. Our study cautions researchers to refine their research designs that use management range forecasts and sheds light on the role of financial analysts in the earnings expectations game.