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.     

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 Security Analysts' Earnings Forecasts

This paper investigates the rationality of security analysts' forecasts. The forecasts of analysts participating in Lynch, Jones, and Ryan's Institutional Brokers Estimate System (I/BE/S) data base are evaluated relative to past values of their own forecast errors, past values of forecasted earnings per share, and quarterly percentage changes in publicly available macroeconomic and financial time series. The publicly available series include the consumer price index, unemployment rate, oil prices, stock prices, gross national product, and corporate profits. The authors conduct a generalized orthogonality test and include only information available to analysts at the time the forecasts are made. The empirical results reject analyst forecast rationality, but not without exception.     

A new measure of earnings forecast uncertainty

Relying on the well-established theoretical result that uncertainty has a common and an idiosyncratic component, we propose a new measure of earnings forecast uncertainty as the sum of dispersion among analysts and the variance of mean forecast errors estimated by a GARCH model. The new measure is based on both common and private information available to analysts at the time they make their forecasts. Hence, it alleviates some of the limitations of other commonly used proxies for forecast uncertainty in the literature. Using analysts' earnings forecasts, we find direct evidence of the new measure's superior performance.     

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.     

Do UK Security Analysts Over-react?

Consensus analysts' earnings per share forecasts have become increasingly accessible in recent years and such measures have been widely adopted by academics as proxies for the market's expectations of earnings. Some US studies have suggested that analysts, in revising earnings forecasts, are prone to over-reaction. This study tests for evidence of over-reaction in revisions of the consensus earnings per share forecasts of UK companies reported by the Institutional Brokers Estimate System. For a series of periods, portfolios of companies attracting high and low revisions of earnings forecasts are constructed. We then compare the subsequent earnings forecast of the companies which attracted high revisions in the portfolio formation period with those of the companies which attracted low revisions in the portfolio formation period. We also compare actual changes in annual earnings with forecast changes in annual earnings. Both analyses suggest that UK analysts are prone to under-reaction, a finding which contrasts with the US studies which have identified over-reaction. There is little evidence that the market, in reacting to earnings forecast revisions, fails to recognise this under-reaction.     

Mandatory disclosure of comment letters and analysts' forecasts

Comment letters (CLs) have been adopted as the main supervision mechanism for information disclosure by the two main Chinese stock exchanges since 2013. Both CLs and firms' responses have been publicly disclosed since the end of 2014. Using nonfinancial listed firms from 2013 to 2019 as our sample, we investigate the impact of CLs and their mandatory disclosure on analysts' forecast quality. The results show that, in the pre-disclosure period, there is no significant relation between CLs and analysts' forecast quality. However, in the post-disclosure period, CLs are positively (negatively) correlated with analysts' forecast accuracy (optimism). The quality of analysts' forecasts is much higher when CLs contain more questions. In addition, the impact of CLs is larger for samples with a lower percentage of star analysts or samples with higher earnings volatility. CL recipients tend to disclose more information on their internal and external risks, which can offer additional information to analysts.     

ABNORMAL RETURNS AND ANALYSTS' EARNINGS FORECAST REVISIONS ASSOCIATED WITH THE PUBLICATION OF “STOCK HIGHLIGHTS” BY VALUE LINE INVESTMENT SURVEY

We examine the reaction of stocks and the response of financial analysts' earnings forecasts to securities recommended as “Stock Highlights” by Value Line Investment Survey. Significant abnormal returns appear around the publication of stock highlights. Stock price responses are relatively efficient and permanent. Using earnings expectation data provided by the Institutional Brokers Estimate System, we find analysts raise their forecasts significantly following Value Line recommendations. Near-term forecast revisions are significantly related to stock returns at the time of the recommendations. Thus, an explanation for Value Line's security recommendation success is its ability to generate firm-specific earnings information.     

Value relevance of analyst earnings forecasts in emerging markets

Even though research in accounting and finance has extensively examined the role of financial analysts in developed economies, this issue has not been thoroughly examined in an emerging market setting. In this paper, I examine whether, following a market opening, analyst forecast accuracy and the market's reliance on analyst forecasts increase with time. Accuracy is expected to increase over time as analysts exert more effort and gain valuable forecasting experience. Results indicate that time is positively related to analyst forecast accuracy after controlling for a number of other firm and country characteristics. Second, I posit that time should also be related to the market's propensity to use analyst forecasts to form earnings expectations. As markets open and investors become more sophisticated, the reliance on analyst forecasts should also increase. Results are consistent with this expectation. In particular, I find that in the first sub-period earnings expectations based on random walk exhibit greater relative information content than earnings expectations based on analyst forecasts. This pattern is reversed in the third sub-period where analyst forecast errors better explain returns. Incremental information content tests produce similar results. Future research should further investigate the relation between financial analysts and other important market characteristics in emerging economies.     

The use of management forecasts to dampen analysts' expectations by Chinese listed firms

This paper studies the use of management earnings forecasts (MEF) to dampen analysts' expectations, i.e. expectation management, by Chinese listed companies. We reveal several important findings: Firstly, information asymmetry is positively associated with the use of MEF to dampen analysts' expectations. State control has been found to moderate this relationship. Secondly, dampening analysts' expectations using MEF leads to negative stock return reactions and downward analysts' forecast revisions. Thirdly, the effectiveness of “pre-empting bad news through MEF” appears mixed and dependent on the information content of MEF and measures of actual earnings surprises. Finally, firms that disclose MEF are found to engage in more earnings management to meet the forecasts than firms that do not.     

Financial Analysts and the False Consensus Effect

Social psychologists have documented a tendency for people to overestimate their similarity to others. I investigate whether financial analysts' forecast errors are consistent with this bias. I model the bias by assuming analysts overestimate the correlation of the private signals they receive about a firm's future earnings. My model predicts a positive relationship between (i) the likelihood of an analyst's revised forecast being too close to his earlier forecast and (ii) the number of analysts issuing forecasts during the time interval between his two forecasts. I empirically confirm this prediction and consider several alternative explanations.     

Natural disasters and analysts' earnings forecasts

The effects of natural disasters on capital markets have been investigated by limited evidence even though these calamities bring considerable damages or loss of life. To fill this gap, we investigate the impacts of natural disasters, particularly earthquakes, on security analysts' earnings forecasts for affected firms in China. We obtain three key findings. First, analysts' optimism significantly decreases for firms located in neighborhood areas. Second, earthquakes do not significantly affect firm earnings and stock returns, thereby indicating that post-earthquake analyst pessimism is not based on rational judgment. Third, media attention promotes irrational pessimism among analysts, and post-earthquake pessimism is a result of heuristics bias attributable to psychological shocks. However, analysts correct the bias after initial irrational forecasts. Taken together, our findings contribute to the broader psychology and economics literature on the effects of natural disasters on analyst forecasts.     

Analysts' Forecasts: Low-Balling,Market Efficiency,and Insider Trading

The phenomenon of low-balling reported in the financial press involves downward biased projections of earnings by managers or analysts, thereby artificially lowering market expectations and creating a positive earnings surprise when actual earnings are announced. This study reports that the stock market does respond to such surprises relative to analysts' reported forecasts. Further, the proportion of insider buy-transactions in the period prior to the earnings forecast is significantly higher for the sample with high positive earnings surprise than for the control sample with zero forecast errors. The study cannot distinguish whether managers or analysts are the source of the low-balling and therefore makes no statement on the legality of such insider trades.     

Causal language intensity in performance commentary and financial analyst behaviour

We use automated techniques to measure causal reasoning on earnings‐related financial outcomes of a large sample of MD&A sections of US firms and examine the intensity of causal language in that context against extent of analyst following and against properties of analysts’ earnings forecasts. We find a positive and significant association between a firm's causal reasoning intensity and analyst following and analyst earnings forecast accuracy respectively. Correspondingly, analysts’ earnings forecast dispersion is negatively and significantly associated with causal reasoning intensity. These results suggest that causal reasoning intensity provides incremental information about the relationship between financial performance outcomes and its causes, thereby reducing financial analysts’ information processing and interpreting costs and lowering overall analyst information uncertainty. Additionally, we find that decreases in analyst following are followed by more causal reasoning on performance disclosure. We also find that firms with a considerable increase of causal disclosure especially attract new analysts who already cover many firms. Overall, our evidence of the relationship between causal reasoning intensity and properties of analyst behaviour is consistent with the proposition that causal reasoning is a generic narrative disclosure quality characteristic, able to provide incremental information to analysts and guide analysts' behaviour.     

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.     

Rational expectations,analysts' forecasts of earnings and sources of value gains for takeover targets

Value gains to target firm shareholders in takeover bids may be due to potential synergy between bidder and target and/or potential target restructuring based on new information released by the bid. Since these two models have different implications for the anticipated earnings of the target as a stand-alone entity, analysts' earnings forecast revisions (AFR) for the target during the bid may provide evidence for the new information hypothesis. For 326 UK targets of takeover bids during 1987–1993, we estimate analysts' earnings forecast revisions using the Institutional Brokers Estimate System (IBES) and relate them to bid premia paid to target shareholders. Analysts revise their forecasts significantly up on bid announcement. For failed, especially failed hostile, bids, the earnings forecast revision and bid premium are more positively correlated than for successful and friendly bids. This is consistent with the rational expectations behaviour of target shareholders modelled by Grossman and Hart [S.J. Grossman, O.D. Hart, Bell Journal of Economics 11(1) (1980) 42; S.J. Grossman, O.D. Hart, Journal of Finance 36 (1981) 253].     

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.     

The role of financial analysts in stock market efficiency with respect to annual earnings and its cash and accrual components

This study examines biases in stock prices and financial analysts' earnings forecasts. These biases take the form of systematic overweighting or underweighting of the persistence characteristics of cash versus accrual earnings components. Our evidence suggests that stock prices tend to overweight and financial analysts tend to underweight these persistence characteristics. Furthermore, we find that analysts' underweighting attenuates stock price overweighting. However, we find little evidence that the overweighting in stock prices attenuates analyst underweighting. This study brings a new perspective to the literature regarding the disciplining role of financial analysts in capital markets.     

Predictability in Financial Analyst Forecast Errors: Learning or Irrationality?

In this paper, we propose a rational learning‐based explanation for the predictability in financial analysts' earnings forecast errors documented in prior literature. In particular, we argue that the serial correlation pattern in analysts' quarterly earnings forecast errors is consistent with an environment in which analysts face parameter uncertainty and learn rationally about the parameters over time. Using simulations and real data, we show that the predictability evidence is more consistent with rational learning than with irrationality (fixation on a seasonal random walk model or some other dogmatic belief).     

CEO happiness and forecasting

We utilize the IBM Watson Tone Analyzer to measure chief executive officers' (CEOs') levels of joy (happiness) in year-end conference calls, and empirically test how CEOs' happiness affects the properties of their own and analysts' forecasts. We find that joyful CEOs are more likely to issue forecasts, less likely to miss their forecast targets, and exhibit lower optimistic bias in their forecasts. When joyful CEOs issue earnings forecasts, analysts revise their forecasts upwards and produce forecasts that are less dispersed and more accurate. Our results demonstrate that inherent CEO happiness significantly impacts the forecast properties of both managers and analysts, thus supporting upper echelons theory.