Real earnings management and the properties of analysts' forecasts

Prior literature generally finds analysts are able to identify and process complex financial information. However, research suggests that in certain settings, analysts struggle to fully incorporate into their forecasts all available information. We examine analysts' forecast properties in the face of a specific type of complex financial information: real earnings management (REM). First, we investigate the relation between measures of REM and analysts' forecast properties. We find REM measures are associated with greater forecast error and dispersion in the following year. However, REM measures, by definition, capture abnormal operating results, and thus include both firms engaging in manipulative REM as well as firms experiencing firm-specific economic shocks. Thus, we conduct cross-sectional tests of analysts' forecasts for firms with and without incentives to manipulate earnings. We find that firms with low incentives to engage in earnings management (i.e., firms most likely experiencing firm-specific economic shocks) generate the strongest positive relation between REM measures and the following year's analysts' forecast properties, suggesting analysts more fully incorporate the earnings implications of firms with high incentives (i.e., firms most likely engaging in manipulative REM). Our results are consistent across numerous REM proxies and indicators of earnings management incentives.     

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 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.     

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.     

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.     

Relationship Incentives and the Optimistic/Pessimistic Pattern in Analysts' Forecasts

We examine whether analysts' incentives to maintain good relationships with management contribute to the optimistic/pessimistic within‐period time trend in analysts' forecasts. In our experiments, 81 experienced sell‐side analysts from two brokerage firms predict earnings based on historical information and management guidance. Analysts' forecasts exhibit an optimistic/pessimistic pattern across the two timing conditions (early and late in the quarter), and the effect is significantly stronger when the analysts have a good relationship with management than when their only incentive is to be accurate. Debriefing results indicate that analysts are aware of this pattern of forecasts, and believe that this benefits their future relationships with management and with brokerage clients. The analysts most frequently cite favored conference call participation and information access when describing benefits from maintaining good relationships with management. Our results suggest the following: The optimistic/pessimistic pattern in forecasts is in part a conscious response to relationship incentives, information access is perceived to be a major benefit of management relationships, and recent regulatory changes may have lessened but have not eliminated this conflict of interest source.     

Common Stock Offerings and Earnings Expectations: A Test of the Release of Unfavorable Information

This paper examines the revisions of analysts' forecasts of future earnings around announcements of common stock offerings. The forecasts of the current year earnings are, on average, decreased when firms announce plans to issue additional common stock. The size of the decrease is significantly related to announcement period abnormal stock returns. In contrast, forecasts of the five-year growth rate of earnings are, on average, unchanged. We interpret these results as being consistent with the claim that equity offering announcements convey unfavorable information regarding the firm's short-term but not its long-term earnings prospects.     

Stakeholder relations and stock returns: On errors in investors' expectations and learning

A significant number of institutional investors publicly state the belief that corporate stakeholder relations are associated with firm value in a manner that the financial market fails to understand. We investigate whether stakeholder information predicted risk-adjusted returns due to errors in investors' expectations and ultimately ceased to do so as attention for such information increased. We build a stakeholder-relations index (SI) for a wide range of U.S. firms over the period 1992–2009 and provide evidence that the SI explained errors in investors' expectations about firms' future earnings. The SI was positively associated with long-term risk-adjusted returns, earnings announcement returns, and errors in analysts' earnings forecasts over the period 1992–2004. However, as attention for stakeholder issues became more widespread, subsequently, these relationships diminished considerably. The results are consistent with the idea that increased investor attention for stakeholder issues eventually eliminates mispricing.     

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.     

The impact of meeting or beating analysts' operating cash flow forecasts on a firm's cost of debt

Extant literature provides conflicting results with respect to the usefulness and accuracy of analysts' operating cash flow forecasts. Our study empirically examines the importance and influence of meeting or beating analysts' operating cash flow forecasts on a firm's cost of debt. Results indicate that firms meeting/beating analysts' cash flow forecasts have higher initial bond ratings as well as lower initial bond yields. Additionally, based upon an analysis of rating changes, firms meeting or beating cash flow forecasts have a higher probability of receiving a debt rating upgrade and a lower probability of a ratings downgrade compared to firms missing cash flow forecasts. A direct comparison of the importance of meeting/beating cash flow versus earnings benchmarks indicates that debt market participants appear to incrementally value both types of forecasts, and contrary to selected equity market findings, neither forecast subsumes the other for debt market participants.     

Valuing Loss Firms: What Can Be Learned From Analysts' Forecasts?

Prior research documents an anomalous negative price–earnings relation when a simple earnings capitalization model is estimated for loss‐making firms. Collins et al. (1999 ) suggest that the model is misspecified due to the omission of book value of equity. However, results from previous studies are confusing. We try to enrich prior literature by focusing on analysts' forecasts. In particular, we assess the role of earnings and book value in valuing loss firms using several measures based on the information provided by analysts. We hypothesize that the role of accounting figures depends on whether the loss firm is supported or not by investors. According to this argument, we construct several measures of investor support based on analysts' forecasts, and then test the value relevance of accounting information depending on the degree of support. Our results confirm the usefulness of the notion of ‘investor support’. For those loss firms that are expected to liquidate, we find that the inclusion of book value of equity in the model removes the negative sign on the earnings coefficient. However, for those loss firms that are expected to reverse current losses, we find that the coefficient on earnings remains negative despite the inclusion of book value.     

Financial Analyst Characteristics and Herding Behavior in Forecasting

This study classifies analysts' earnings forecasts as herding or bold and finds that (1) boldness likelihood increases with the analyst's prior accuracy, brokerage size, and experience and declines with the number of industries the analyst follows, consistent with theory linking boldness with career concerns and ability; (2) bold forecasts are more accurate than herding forecasts; and (3) herding forecast revisions are more strongly associated with analysts' earnings forecast errors (actual earnings—forecast) than are bold forecast revisions. Thus, bold forecasts incorporate analysts' private information more completely and provide more relevant information to investors than herding forecasts.     

Investor Sentiment and Corporate Disclosure

This paper investigates how firms react strategically to investor sentiment via their disclosure policies in an attempt to influence the sentiment‐induced biases in expectations. Proxying for sentiment using the Michigan Consumer Confidence Index, we show that during low‐sentiment periods, managers increase forecasts to “walk up” current estimates of future earnings over long horizons. In contrast, during periods of high sentiment, managers reduce their long‐horizon forecasting activity. Further, while there is an association between sentiment and the biases in analysts' estimates of future earnings, management disclosures vary with sentiment even after controlling for analyst pessimism, indicating that managers attempt to communicate with investors at large, and not just analysts. Our study provides evidence that firms' long‐horizon disclosure choices reflect managers' desire to maintain optimistic earnings valuations.     

Refining the Degree of Earnings Surprise: A Comparison of Statistical and Analysts' Forecasts

This paper compares the relative predictive ability of several statistical models with analysts' forecasts. It is one of the first attempts to forecast quarterly earnings using an autoregressive conditional heteroskedasticity (ARCH) model. ARCH and autoregressive integrated moving average models are found to be superior statistical forecasting alternatives. The most accurate forecasts overall are provided by analysts. Analysts have both a contemporaneous and timing advantage over statistical models. When the sample is screened on those firms that have the largest structural change in the earnings process, the forecast accuracy of the best statistical models is similar to analysts' predictions.     

Model-based earnings forecasts vs. financial analysts' earnings forecasts

Existing accounting-based forecasting models of earnings either do not fully consider information that is contained in stock prices or use an ad hoc specification that is not based on rigorous valuation theory. In this paper, we develop an earnings forecasting model built on the theoretical linkages between future earnings and stock prices as well as a number of accounting fundamental variables. We find that our model-based forecasts of earnings are in general less biased and more accurate than both existing model-based forecasts and analysts' consensus forecasts, at both shorter and longer horizons. We also show that the accuracy of both model-based forecasts and financial analysts' forecasts depend on firm-specific characteristics such as firm size and industry membership.     

Earnings Surprises in Analysts' Forecasts,Mandatory Disclosure,and Share Repurchases

This paper examines the impact of forecast errors and the mandatory disclosure of repurchase transactions required by 2003 Securities and Exchange Commission (SEC) regulations on share repurchases. We define forecast errors as the difference between analysts' forecasted earnings and actual earnings. We argue that firms with positive forecast errors imply greater information asymmetry, which may induce them to signal through share repurchases. We show that both the repurchase target and analysts' forecast revision are positively related to forecast errors. Furthermore, these associations are more pronounced in the low disclosure period (1989–2003) where greater information asymmetry between managers and outside investors is found, while increased transparency in the high disclosure period (2004–2006) leads to more significant improvement in long‐term performances for firms with positive forecast errors. The results are consistent with our expectations that the information asymmetry implied in forecast errors, along with a shock change from the introduction of the 2003 SEC regulation, affect both corporate and analysts' behaviour.     

The brain gain of CFOs in China: The case of analyst forecasts

We study the impact of CFOs with foreign experience on analysts' forecast accuracy in emerging markets. Using a unique data set from China, we find that analysts' forecast accuracy increases when firms hire CFOs with foreign experience, confirming the brain gain effect of CFOs. Our results are robust after addressing potential endogeneity by introducing the propensity score matched (PSM) procedure and Heckman two-stage method. Channel analyses show that CFOs with foreign experience are related to decreased earnings management and a greater probability of hiring high-quality auditors, indicating that the improvement in financial reporting quality and information environment brought by returnee CFOs mainly drive our results. Further cross-section tests reveal that compared to firms with more external pressure, the positive effect of returnee CFOs on analysts' forecast accuracy is more pronounced among firms with fewer analyst coverage and belonging to less competitive industries. Returnee CFOs with foreign work experience exert a more significant impact on analysts' forecast accuracy than those with foreign study experience. Overall, we provide the first evidence on the brain gain of CFOs in terms of analyst forecasts.     

The Predictive Role of Analyst Coverage Intensity: Evidence from Cross-Listing in the US

This paper investigates financial analysts' predictive power of future performance and earnings quality, using a sample of firms cross-listed in the US. We find that analyst coverage is positively related to analysts' expectations about firms' future performance and negatively related to analysts' concern over firms' earnings quality. Country-level legal origin and disclosure index are two significant determinants of analyst coverage of cross-listed firms. In addition, the intensity of analyst coverage can predict future abnormal stock price performance. While documenting the substantial informational benefits to cross-listing, our study suggests that these benefits may not be complete since analysts appear to have predictive power and selectively provide coverage for firms with favorable future prospects.     

Confirming Management Earnings Forecasts, Earnings Uncertainty, and Stock Returns

In this study we examine the association among confirming management forecasts, stock prices, and analyst expectations. Confirming management forecasts are voluntary disclosures by management that corroborate existing market expectations about future earnings. This study provides evidence that these voluntary disclosures affect stock prices and the dispersion of analyst expectations. Specifically, we find that the market's reaction to confirming forecasts is significantly positive, indicating that benefits accrue to firms that disclose such forecasts. In addition, although we find no significant change in the mean consensus forecasts (a proxy for earnings expectations) around the confirming forecast date, evidence indicates a significant reduction in the mean and median consensus analyst dispersion (a proxy for earnings uncertainty). Finally, we document a positive association between the reduction of dispersion of analysts' forecasts and the magnitude of the stock market response. Overall, the evidence suggests that confirming forecasts reduce uncertainty about future earnings and that investors price this reduction of uncertainty.     

Tests of Analysts' Overreaction/Underreaction to Earnings Information as an Explanation for Anomalous Stock Price Behavior

This study examines whether security analysts underreact or overreact to prior earnings information, and whether any such behavior could explain previously documented anomalous stock price movements. We present evidence that analysts' forecasts underreact to recent earnings. This feature of the forecasts is consistent with certain properties of the naive seasonal random walk forecast that Bernard and Thomas (1990) hypothesize underlie the well-known anomalous post-earnings-announcement drift. However, the underreactions in analysts' forecasts are at most only about half as large as necessary to explain the magnitude of the drift. We also document that the “extreme” analysts' forecasts studied by DeBondt and Thaler (1990) cannot be viewed as overreactions to earnings, and are not clearly linked to the stock price overreactions discussed in DeBondt and Thaler ( 1985 , 1987 ) and Chopra, Lakonishok, and Ritter (Forthcoming). We conclude that security analysts' behavior is at best only a partial explanation for stock price underreaction to earnings, and may be unrelated to stock price overreactions.