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.     

我国证券分析师预测代表市场预期的能力提高了吗?来自年报信息市场反应检验的证据

本文以集中发布了分析师行为规范的2005年为转折点,参考对比随机模型和管理层预测,在年报公布后的长窗口内检验分析师的盈利预测代表投资者盈利预期的能力是否有所提高。结果表明,在2005年之后,伴随着分析师预测准确度的提高,其代表市场预期的能力也有所提高,这从投资者认同的角度揭示了我国分析师行业的逐步规范和发展。本文的发现还表明,相对于管理层预测和随机模型的预测而言,分析师预测可能是更合适的市场预期替代变量。     

Rationalizing forecast inefficiency

We show analysts’ own earnings forecasts predict error in their own forecasts of earnings at other horizons, which we argue provides a measure of the extent to which analysts inefficiently use information. We construct our measure by exploiting two sources of variation in analysts’ incentives: (i) more recent forecasts have greater salience at the time of the earnings release so accuracy incentives are higher (lower) at shorter (longer) forecast horizons and (ii) analysts have greater incentives for optimism (pessimism) at longer (shorter) horizons. Consistent with these incentives affecting the incorporation of information into forecasts, we document (i) current year forecasts underweight (overweight) information in shorter (longer) horizon forecasts and (ii) the mis-weighting is more pronounced when recent news is negative—when analysts have greater (weaker) incentives to incorporate the news into shorter (longer) horizon forecasts. Finally, returns tests suggest that forecasts adjusted for the inefficiency we document better represent market expectations of earnings.

     

Learning and incentive: A study on analyst response to pension underfunding

There is a long-standing debate on whether sell-side analysts learn from their experience to improve earnings forecast skills. This study shows that incentive is an important factor for understanding the “learning by doing” effect by analysts. We examine analysts’ response to a complex type of information – corporate pension underfunding. Pension underfunding negatively impacts future earnings and analysts on average underreact to such information in their earnings forecasts. More importantly, when there is a strong incentive for analysts to deliver accurate forecasts, analyst learning effectively reduces their underreaction to pension underfunding information. On the other hand, when such an incentive is absent, the analyst learning effect is not discernible in the data. Further evidence suggests that analyst learning and incentive jointly reduce stock market mispricing associated with corporate pension underfunding.     

When do stock analysts find bond rating changes informative?

Credit rating agencies (CRAs) have considerable privileged access to corporate management and are therefore a potentially important source of information to the equity market. We study how stock analysts incorporate bond ratings in their earnings forecasts. We develop an economic framework to explain why equity analysts might look to CRAs as an information source, especially after Regulation Fair Disclosure. Using this framework, we characterize the association between ratings changes and earnings forecast revisions surrounding these changes. We examine whether the extent to which equity analysts glean information from ratings changes is related to the extent and importance of information conveyed in the ratings change and analysts’ information uncertainty. We find that characteristics we examine are strongly related to stock analysts’ use of information in rating downgrades.     

Serial Correlation in Management Earnings Forecast Errors

We examine whether management earnings forecast errors exhibit serial correlation and how analysts understand the serial correlation property of management forecast errors (MFEs). MFEs should not exhibit serial correlation if managers efficiently process information in prior forecast errors and truthfully convey their earnings expectations through management forecasts. However, for long‐horizon management forecasts of annual earnings, we find significantly positive serial correlation in MFEs, and sample self‐selection does not seem to drive this phenomenon. Further analyses suggest that managers’ unintentional information processing bias contributes to this positive serial correlation. Analysts anticipate the intertemporal persistence of MFEs but underestimate the persistence level when reacting to management forecasts. Our findings have implications for market participants who rely on management forecasts to form earnings expectations, and also shed light on the efficiency of managerial decision making.     

RATIONAL EXPECTATIONS AND THE DYNAMIC ADJUSTMENT OF SECURITY ANALYSTS' FORECASTS TO NEW INFORMATION

We report the results of unbiasedness tests of security analysts' earnings forecasts. By examining how analysts incorporate new information into their updated earnings forecasts we can analyze directly the effect of new information on analysts' forecast revisions and evaluate whether these revised forecasts converge to rational expectations forecasts. The forecasts made by security analysts participating in the Institutional Brokers Estimate System (IBES) database are analyzed. Using standard statistical tests, we reject the simple form of the rational expectations hypothesis. However, by extending the standard tests used in previous studies, we obtain results that suggest that analysts' earnings forecasts conform to a dynamic form of rationality. The tendency of revised forecasts to converge stochastically toward the rational expectations forecast cautions against the rejection of more complicated forms of rationality.     

THE ASSOCIATION BETWEEN ANALYSTS’ FORECAST REVISIONS AND EARNINGS COMPONENTS: THE EVIDENCE OF FRS 3

This study examines whether the earnings components as required by FRS 3 help UK analysts to predict firms’ earnings changes by investigating the statistical association between analysts’ forecast revisions and firms’ unexpected earnings components. I find that analysts’ forecast revisions made in different time horizons are consistently associated with unexpected earnings components as required by FRS 3. UK analysts are able to incorporate current-year unexpected earnings components into their current and future earnings forecasts even before firms officially release this information. However, empirical results also show that current-year unexpected earnings components are not fully incorporated into analysts’ forecasts of future earnings. Analysts appear to wait for more information releases regarding firms’ future earnings and delay their revisions of future earnings forecasts. This is consistent with the evidence that the cumulative revisions of current earnings forecasts are generally associated with prior-year unexpected earnings components, and the association appears to be stronger as time progresses. Overall, this study provides evidence suggesting that the earnings components as required by FRS 3 help UK analysts to identify firms’ permanent and transitory earnings changes over different forecast horizons. This study also provides strong evidence supporting the informativeness of earnings components for analysts’ forecasts and the information set perspective of FRS 3 that highlights the importance of earnings components in predicting a reporting entity’s future performance.     

Tests of Market Reaction and Analysts' Forecast Revisions to the Disclosure of Improved Management Earnings Expectations: A Case of Concurrent Bad News Management Earnings Forecasts

This paper tests whether a negative stock market reaction, associated with a management forecast of near term bad earnings, is lessened by a concurrent management forecast of improved longer term earnings expectations. Stock market reactions depend on the creditability of management forecasts of improved earnings expectations. In this analysis, the authors examined market reactions around the time of management forecasts of bad earnings, with and without longer-term management forecasts of improved earnings expectations. The results show that the stock market reaction is significantly less negative when management forecasts of bad earnings are followed by management forecasts of improved long run earnings expectations than when management forecasts of bad earnings are not accompanied by management forecasts of improved earnings expectations. In addition, this paper examines financial analysts' reactions to management bad earnings forecasts and management forecasts of improved earnings expectations. The findings show that analysts react less negatively to management forecasts of improved earnings expectations than to management forecasts of bad earnings. An analysis of a sub-sample of observations shows that analysts consider management forecasts of improved earnings expectations to imply improved expected future performance, thus conveying that analysts give credence to management forecasts of improved earnings expectations. However, results show that the stock market and analysts are unable to distinguish management forecasts of improved earnings expectations that come true from management forecasts of improved earning expectations that do not come true.     

Do Analysts and Auditors Use Information in Accruals?

Existing research indicates that firms with high accruals are more likely to experience future earnings problems, but that investors' expectations, as reflected in stock prices, do not appear to anticipate these problems. In this paper, we directly examine the published opinions of two types of professional investor intermediaries to see if they provide investors with information concerning the future earnings problems experienced by firms with high accruals. First, we examine the earnings forecasts of sell-side analysts. We show that analysts' earnings forecasts do not incorporate the predictable future earnings declines associated with high accruals. Second, we examine the behavior of independent auditors. We find no evidence that auditors signal the future earnings problems associated with high accruals through either their audit opinions or through auditor changes. Overall, our evidence indicates that analysts and auditors do not alert investors to the future earnings problems associated with high accruals, thus corroborating previous findings that investors do not appear to anticipate these problems.     

Do banks care about analysts' forecasts when designing loan contracts?

We investigate whether banks rely on the information content in equity analysts’ annual earnings forecasts when assessing the risk of potential borrowers. While a long literature finds that analysts provide useful information to market participants, it is not clear that banks, which have access to privileged information, would benefit from publicly available analysts’ forecasts. If, however, banks do rely on this information, then more precise private information in earnings forecasts may inform banks. We focus our analysis on the requirement of collateral because it is a direct measure of default risk, whereas other loan terms such as interest spread and debt covenants can also protect against other risks, such as asset misappropriation. The direct link between collateral and default risk allows us to examine whether information from analysts is relevant to banks when designing loan contracts. Consistent with our predictions, we find that higher precision of the private information in analysts’ earnings forecasts is associated with a lower likelihood of requiring collateral, and this effect is larger when a borrower does not have a prior relationship with the lender or their accounting or credit quality is low. We also find that this association disappears after the implementation of Regulation FD, consistent with this regulation reducing analysts’ access to private information.     

Investor protection and analysts’ cash flow forecasts around the world

We find that analysts are more likely to provide cash flow forecasts in countries with weak investor protection. This finding is consistent with our hypothesis that market participants demand (and analysts supply) cash flow information when weak investor protection results in earnings that are less likely to reflect underlying economic performance. Our results suggest that information intermediaries respond to market-based incentives to attenuate the adverse effects of country-level institutional factors on earnings’ usefulness. These findings contribute to the literature by shedding light on the institutional determinants of analysts’ research activities, and on the nature of the financial information they generate.     

CEO bonus compensation: the effects of missing analysts’ revenue forecasts

We investigate the incremental contract relevance of analysts’ revenue forecasts while controlling for earnings forecasts and find CEOs receive smaller bonuses when missing analysts’ annual and quarterly revenue expectations. Our results support the link between the value relevance of the revenue performance measure and the contract relevance of that measure. Further, we find revenue forecasts to be more contract relevant for CEOs of firms with high growth expectations, consistent with Rees and Sivaramakrishnan’s Contemp Acc Res 24(1):259–290, (2007) findings that growth firms receive a larger market penalty for missing revenue targets. Overall, our findings provide empirical support for the conjecture that compensation committees rely on information consistent with that conveyed in analysts’ revenue forecasts when contracting with management.     

Stock Recommendations for Politically Connected Firms

Social network connections of corporations can significantly affect operating performance and firm valuation. Political connections are one form of social networking which often manifests into improved firm profitability as a result of political favors granted by politicians. However, analysts often have greater difficulty forecasting the earnings of politically connected firms than those of non‐connected firms. This is because politicians often grant political favors to firms in an unpredictable manner making it difficult for market participants to time precisely when political benefits will translate into higher firm profitability. I examine how political connections affect analysts’ stock recommendations using a unique dataset of political contributions in the US over the period 1993–2012. I show that analysts’ recommendations are less profitable for firms with high connectedness than for firms with low (or no) connectedness. I also find that analysts are less effective in translating earnings forecasts into profitable recommendations for highly connected firms. Overall, the findings suggest that analysts do not impound all of the information concerning corporate political connections efficiently into their primary research outputs.     

Are analysts’ earnings forecasts more accurate when accompanied by cash flow forecasts?

We examine whether analysts’ earnings forecasts are more accurate when they also issue cash flow forecasts. We find that (i) analysts’ earnings forecasts issued together with cash flow forecasts are more accurate than those not accompanied by cash flow forecasts, and (ii) analysts’ earnings forecasts reflect a better understanding of the implications of current earnings for future earnings when they are accompanied by cash flow forecasts. These results are consistent with analysts adopting a more structured and disciplined approach to forecasting earnings when they also issue cash flow forecasts. Finally, we find that more accurate cash flow forecasts decrease the likelihood of analysts being fired, suggesting that cash flow forecast accuracy is relevant to analysts’ career outcomes.     

Informational role of analyst and investor days

This study empirically clarifies whether analyst and investor days (AI days) affect earnings expectations of participants. The analyses reveal that the tone of the question-and-answer (Q&A) session, rather than that of the management presentation, is positively associated with subsequent revisions of analysts' earnings forecasts. This suggests that such an interactive discussion during a Q&A session plays a key role in affecting analysts' expectations. Furthermore, abnormal returns around the AI days are irrelevant to the tone of the Q&A session. This suggests that AI days mainly provide a partially known (supplemental) information rather than offering new information to analysts and investors.     

Lead indicator models and UK analysts' earnings forecasts

This study examines the predictive ability of models which adjust random walk forecasts of corporate earnings, to incorporate past changes in economic lead indicators. The results suggest that changes in the broad money supply measure M4 contain predictive ability, beyond equivalent changes in other lead indicators or an individual firm's earnings. When forecasts from the broad-money model are compared with forecasts generated by financial analysts a size effect is evident: the superiority of analysts' forecasts is apparent much earlier for large firms than for small firms. This result is consistent with studies suggesting a size-related differential in the collection and dissemination of information by market participants.     

Earnings Forecasts and the Information Contained in Spinoff Announcements

This study examines spinoff announcements in conjunction with financial analysts’ forecasts of earnings. The analysis shows that spinoff announcement abnormal returns are significantly related to the firm's information environment as proxieci by financial analysts’ earnings prediction errors. The findings also indicate that analysts significantly increase their short-term earnings forecasts in response to spinoffs, but do not significantly revise their long-term earnings forecasts. However, the earnings revisions are not significantly different across prediction error groups, which confirms that spinoff-related abnormal returns cannot be attributed solely to expected performance gains.     

Chinese Walls in German Banks*

Analysts in a bank’s research department cover firms that have no relationship with the bank as well as companies in which the bank has a strategic interest. Officially, banks must establish Chinese Walls around their research departments to allow the analysts to work independently and to avoid the flow of insider information. We examine analyst behavior under long-term bank-firm relationships using ownership data and analysts’ earnings per share forecasts for German companies from 1994 to 2001. We find evidence that is consistent with analysts reconciling their employers’ interests with their own career concerns. They seem to use their information advantage strategically by releasing favorable and thereby more precise reports when the market underestimates earnings. In order not to jeopardize the bank-client relationship, they suppress negative information when the market is too optimistic. Combining situations where the market over- and underestimates earnings, we can replicate the unconditional positive bias in analyst forecasts found in the previous literature. Despite the bias in affiliated analysts’ forecasts, they nonetheless selectively communicate valuable information to investors. *We gratefully acknowledge the contribution of I/B/E/S International Inc. for providing earnings per share forecast data. This data has been provided as part of a broad academic program to encourage earnings expectations research. We thankfully acknowledge financial support from the Austrian National Bank (OeNB) under the Jubil?umsfonds grant number 8523. We thank Werner Antweiler, Michael Halling, Helmut Elsinger, Evelyn Hayden, Greg Hebb, Cornelia Kullmann, Kai Li, Colin Mayer, Stefan Pichler, Duane Seppi, Alex Stomper, Neal Stoghton, Michael Stutzer, Suresh Sundaresan, Yishay Yafeh, Josef Zechner, Christine Zulehner, an anonymous referee, and seminar participants at UBC, the Northern Finance Association meetings, the Western Finance Association meetings, and the European Finance Association meetings for helpful comments and Eva Smolen for excellent research assistance.     

Asymmetric trading by insiders – comparing abnormal returns and earnings prediction in Spain and Australia

This paper examines whether the ‘external governance’ imposed by comparative financial accounting standards reduces the trading advantage of insiders. We do this by directly comparing insider trading returns and insider’s ability to predict future earnings from accruals in Spain and Australia. Results show higher excess returns and greater prediction of future earnings from conditioned insider trading in Australia that is then utilized by financial analysts to lower forecast errors – particularly in contrarian‐based accruals trading. Possible explanations include: (i) a high asymmetric quality for market‐based accruals, (ii) information transfer from informed insiders to uninformed insiders and financial analysts and (iii) a more timely dissemination of financial information in Spain through different ownership and governance structures.