An Examination of the Differential Impact of Regulation FD on Analysts' Forecast Accuracy

Regulation fair disclosure (FD) requires companies to publicly disseminate information, effectively preventing the selective pre‐earnings announcement guidance to analysts common in the past. We investigate the effects of Regulation FD's reducing information disparity across analysts on their forecast accuracy. Proxies for private information, including brokerage size and analyst company‐specific experience, lose their explanatory power for analysts' relative accuracy after Regulation FD. Analyst forecast accuracy declines overall, but analysts that are relatively less accurate (more accurate) before Regulation FD improve (deteriorate) after implementation. Our findings are consistent with selective guidance partially explaining variation in the forecasting accuracy of analysts before Regulation FD.     

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.     

The coverage assignments of financial analysts

Previous studies document that forecast accuracy impacts analyst career outcomes. This paper investigates the influence of forecast accuracy on coverage assignments. I show that brokerage houses reward accurate analysts by assigning them to high-profile firms and penalise analysts exhibiting poor accuracy by assigning them to smaller firms. The coverage of high-profile firms increases the potential for future compensation linked to investment banking and trading commissions. In addition, covering such firms increases analysts' recognition from buy-side investors, which, in turn, increases the likelihood of obtaining broker votes and votes for the Institutional Investor star ranking. Overall, my results indicate that high forecast accuracy leads to increased future compensation.     

Does Regulation FD work? Evidence from analysts' reliance on public disclosure

We examine how Regulation FD changed analysts' reliance on firms' public disclosure. Regulation FD is associated with a stronger analyst response to earnings announcements, management forecasts and conference calls—that is, analysts respond to these events more quickly, more frequently and with larger forecast revisions after FD. Further, following public disclosure, the decline in analyst forecast dispersion and forecast error accelerates after FD. We find no such changes either for foreign ADR firms or around several confounding events. Overall, Regulation FD levels the playing field between the analysts and individual investors, thereby promoting “fair game” property of the market.     

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.     

Analysts’ accrual-related over-optimism: do analyst characteristics play a role?

Bradshaw et al. (J Acc Res 39:45–74, 2001) find that analyst forecast over-optimism is greater for firms with high accruals. This “accrual-related over-optimism” is generally interpreted as evidence that analyst forecasts do not fully incorporate predictable earnings reversals associated with high accruals. We investigate whether analyst experience, access to resources (brokerage size), and portfolio complexity moderate the relation between over-optimistic forecasts and high accruals. We demonstrate the robustness of accrual-related over-optimism to controls for cash flow and prior forecast errors. We find that accrual-related over-optimism is lower for analysts with greater general experience and for analysts following fewer firms but find only limited evidence of lower accrual-related over-optimism for analysts from larger brokerages and for analysts following fewer industries.     

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.     

Analysts' forecasts as earnings expectations

I examine three composite analyst forecast of earnings per share as proxies for expected earnings. The most current forecast weakly dominates the mean and median forecasts in accuracy. This is evidence that forecast dates are more relevant for determining accuracy than individual error. Consistent with previous research, I find analysts more accurate than time-series models. However prior knowledge of forecast errors from a quarterly autoregressive model predicts excess stock returns better than prior knowledge of analysts' errors. This is inconsistent with previous research, and is anomalous given analysts' greater accuracy.     

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.     

Performance commitments and the properties of analyst earnings forecasts: Evidence from Chinese reverse merger firms

We investigate whether the performance commitments in Chinese reverse merger (RM) transactions affect the properties of analyst earnings forecasts. All RM firms in China are required to make performance commitments for a limited number of years after being publicly listed. As performance commitment is an important piece of public information, it can influence analysts' understanding of firms and their efforts to forecast earnings. Using manually assembled information on RM transactions, we find that, in comparison to the control firms, RM firms exhibit an increase in analyst forecast error and dispersion after the end of performance commitment. This effect is more pronounced in firms with lower levels of information transparency. We also document that the public information contents of analyst forecasts decrease and forecast revisions increase in the post-commitment period, while the private information content of analyst forecasts and the number of their firm visits remain unchanged. Overall, our findings suggest that analysts rely greatly on public information; they have important implications for academics and policymakers in understanding how performance commitments in RM transactions affect the market information environment.     

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.     

Stock index adjustments and analysts’ forecast optimism: A quasi-natural experiment on the CSI 300 Index

As stock index adjustments comprise a basic system of capital market, their potential influence on analysts’ earnings forecasts is worthy of research. Based on a research sample of 23 adjustments to the CSI 300 Index from June 2007 to June 2018 and the backup stocks announced during the same period, this study examines the impact of additions to stock index on analysts’ forecast optimism using a staggered difference-in-differences model. The research results show that after stocks are added to the stock index, analysts’ earnings forecast optimism about these stocks increases significantly. Cross-sectional analysis indicates that this increase is more significant when the market is bullish, institutional ownership is low, the ratio of listed brokerage firms is low, star analyst coverage is low, firms show seasoned equity offering activity, the ratio of analysts from the top five brokerage firms ranked by commission income is high, and the analysts’ brokerage firms are shareholders. However, analyst-level tests find that analysts’ ability helps to reduce the impact of additions to stock index on earnings forecast optimism. Furthermore, additions to stock index significantly increase analyst coverage and forecast divergence. Economic consequences tests find additions to stock index significantly increases stock price synchronization, which is partly mediated by analysts’ earnings forecast optimism. This study enriches the literature on the impact of basic capital market systems and analyst behavior. The findings suggest that investors should rationally evaluate analysts’ earnings forecasts for stocks added to the stock index and obtain further information from various channels to improve asset allocation efficiency.     

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.     

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.     

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.     

Analyst characteristics, timing of forecast revisions, and analyst forecasting ability

We first examine whether analysts with certain characteristics that prior research has identified are related to superior forecasting ability systematically time their forecast revisions later in the fiscal quarter. We then examine whether this superior ability persists after controlling for the timing advantage by using relative forecast error, a measure that largely eliminates the timing advantage of recent forecasts. Using a sample of quarterly earnings forecast revisions over the 20-year period from 1990 to 2009, we find that analysts with more firm-specific and general experience and more accurate prior-period forecasts, analysts employed by larger brokerage firms, and analysts who follow fewer industries and companies tend to revise forecasts later in the quarter. We also find that analyst characteristics that are positively correlated with revision timing are negatively related to relative forecast errors. These results are consistent with analyst characteristics being useful proxies for analyst forecasting ability and analysts with greater ability revising forecasts later in the quarter.     

Disclosure Practices, Enforcement of Accounting Standards, and Analysts' Forecast Accuracy: An International Study

Using a sample from 22 countries, I investigate the relations between the accuracy of analysts' earnings forecasts and the level of annual report disclosure, and between forecast accuracy and the degree of enforcement of accounting standards. I document that firm‐level disclosures are positively related to forecast accuracy, suggesting that such disclosures provide useful information to analysts. I construct a comprehensive measure of enforcement and find that strong enforcement is associated with higher forecast accuracy. This finding is consistent with the hypothesis that enforcement encourages managers to follow prescribed accounting rules, which, in turn, reduces analysts' uncertainty about future earnings. I also find evidence consistent with disclosures being more important when analyst following is low and with enforcement being more important when more choice among accounting methods is allowed.     

Product market pricing power, industry concentration and analysts’ earnings forecasts

This is the first study to establish a link between product market power and analysts’ earnings forecast accuracy and bias. Relating two different dimensions of market power to earnings forecastability, we document that (a) a firm’s relative pricing power and (b) its industry concentration are strong positive determinants of analysts’ earnings forecast accuracy. We find that forecasting earnings of higher market power firms is less complex due to their ability to withstand cost shocks as well as greater informational-efficiency enjoyed by such firms. Further, forecast optimism increases with weakening product market pricing power and with lower industry concentration. The knowledge derived from this study will hopefully improve the accuracy of equity valuation, and thereby engender better buy-side (stock selections) and sell-side recommendations by analysts. Our analysis also suggests that brokerage firms compensating analysts based on forecast accuracy need to adjust for the differential in the information complexity of different industries.     

Are All Security Analysts Equal?

We examine the extent to which security analysts are homogeneous in their effect on firm valuation as measured by Tobin's Q. Earlier research documents a significant and positive relation between analyst coverage and firm valuation. We identify three classes of equity analysts and examine their differential effect on firm valuation associated with their coverage and their information production. We find that equity analysts are not homogeneous in their effect on firm valuation. The presence of analysts at national securities firms have the strongest effect on firm valuation followed by analysts at regional securities firms and finally analysts at nonbrokerage, or research, firms. We attribute this result to the differential monitoring and information dissemination function rendered by the analysts. Information produced by analysts, however, does not share the same credibility. Specifically, we find brokerage firms' buy recommendations are discounted by the market and have a weak effect on firm valuation. The results can be supported by arguments that brokerage firm analysts' recommendations are contaminated by their firms' investment banking relations with corporations.     

Peer-level analyst transitions

This study examines the effect of peer-level analyst transitions (i.e., switching between brokerage houses) on associated regular incumbent analysts' forecasting performance. We employ a difference-in-differences research design with analyst fixed effects and compare incumbent analysts of different groups within the same broker and same time periods. We find that incumbents who cover at least one common industry as the transiting analyst (i.e., affected incumbents) issue more accurate and timely forecasts after a transiting analyst arrives than incumbents who cover different industries (i.e., unaffected incumbents). Further, affected incumbents issue less accurate forecasts after a transiting analyst leaves than do unaffected incumbents. We also examine potential mechanisms of knowledge spillover and find some evidence that the effect is more salient when the transiting analyst switches from a larger brokerage house, has greater industry scope, or covers geographically linked firms.