Air pollution and analyst information production

Recent studies investigate the impact of air pollution on labor productivity. We extend this literature by showing that air pollution negatively affects equity analyst information production. Analysts exposed to air pollution are less likely to issue timely forecasts or improve their forecast accuracy. Investigating the underlying mechanism, we find that analysts exposed to air pollution are less likely to provide bold (especially, negatively bold) forecasts. We also find evidence that market pricing is less sensitive to forecast revisions issued by analysts exposed to air pollution. Our results are robust to controlling for firm/analyst and time fixed effects, as well as additional specifications employing difference-in-differences designs and placebo tests.     

The value relevance of timely information: The case of comparable store sales growth

Investors and analysts have called for more timely disclosure of corporate information. Responding to these demands, some retail firms issue comparable store sales (CSS) on a monthly or a quarterly basis in addition to an annual basis. This study examines whether a timely disclosure of CSS provides value-relevant information to market participants by examining investors' and financial analysts' responses at the time of CSS disclosures (short-horizon) and over the month or the quarter (long-horizon). We find that both monthly and quarterly CSS are associated with contemporaneous market returns and analyst forecast revisions. More importantly, we find that quarterly CSS news becomes less important to investors when firms provide more timely CSS information, indicating that monthly CSS reports may preempt the information content of quarterly CSS. Additional tests show that investors and analysts rely less on CSS if CSS news and earnings (sales) news are inconsistent.     

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.     

Market reactions to the closest peer firm’s analyst revisions

Prior analyst literature focuses on the impact of financial analysts on the firms they cover, and prior information-transfer literature concentrates on the externalities of information provided by management. This paper fills gaps in both streams of literature by examining the focal firm’s market reactions to the closest peer firm’s (identified by product similarity) analyst revisions. We find that the focal firm’s stock price reacts to the closest peer’s analyst revisions made by analysts who are not covering the focal firm. The focal firm’s cumulative abnormal return for a five-day window centered on the revision date is 0.54% higher if the peer firm’s analyst revision magnitude is in the top decile than if it is in the bottom decile. Cross-sectional tests show that the sensitivity of the focal firm’s market reactions to the peer firm’s revisions increases with the revision informativeness and the similarity between the focal firm and the peer firm. In addition, we find that focal firms do not react to peer firms’ revisions in industries with strong competition where the competitive effects cancel out the spillover effects. Finally, we find that the focal firm’s market reactions can predict its own future analyst revisions, suggesting that the reactions are at least partially rational.     

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.     

Causes and Consequences of Disaggregating Earnings Guidance

Whether managers should provide earnings guidance, especially quarterly guidance, has been a hotly debated policy issue. Influential organizations have urged firms to stop providing earnings guidance to reduce earnings fixation and short‐termism in the capital markets. Little attention has been paid to an alternative proposal: instead of ceasing earnings guidance, companies could provide disaggregated earnings guidance. No archival evidence exists regarding the determinants of disaggregated earnings guidance and its effects on the firm and its information environment. We find that once managers provide guidance, the decision to disaggregate this guidance is primarily driven by demand‐and‐supply factors that exhibit little change from year to year rather than by strategic factors. We find more timely analyst forecast revisions (with no compromise of forecast accuracy), a greater magnitude of revisions, and a larger reduction in analyst disagreement for disaggregating firms than for non‐disaggregating firms. These findings suggest that disaggregation enriches a firm's information environment. We also find that disaggregation helps managers align analyst expectations with their own, but firms are punished by investors for providing multiple performance targets but missing them.     

The Effect of the Private Securities Litigation Reform Act on Analyst Forecast Properties: The Impact of Firm Size and Growth Opportunities

Abstract:  We provide evidence that the effect of the Private Securities Litigation Reform Act (the Act) of 1995 on analyst forecast properties is conditional on firm size and growth opportunities. We show that analyst coverage, frequency of forecast revisions, forecast errors and dispersion after the Act decreased for large firms and for firms with low growth opportunities but increased for small firms and for firms with high growth opportunities. These results are consistent with the hypothesis that the Act results in additional high quality disclosures in large firms, which face higher litigation risk and tighter scrutiny from investors but not in smaller firms. Our findings of increases in analyst coverage and revision but deterioration in accuracy and precision of analyst forecasts for firms with high growth opportunities after the Act suggest that in spite of increased corporate disclosures, the information environment for analysts deteriorated in those firms.     

Analyst reputation and management earnings forecasts

Prior studies show that analysts with high reputation are influential in the market. This paper examines whether managers consider analyst reputation in shaping their voluntary disclosure strategy. Using Institutional Investor magazine’s All-American (AA) rankings as a proxy for analyst reputation, we find that the coverage of AA analysts is positively associated with the likelihood of quarterly management earnings forecasts (MEFs). We also find that AA analysts’ forecast optimism is more positively associated with the likelihood of MEFs than non-AA analysts’ forecast optimism when the firm is covered by AA analysts. Analyses based on AA analyst coverage changes and AA status changes confirm the relation between analyst reputation and MEFs. We further find that analyst reputation influences other MEF properties, such as forecast news, bias, and revisions, and that our results are robust to alternative measures of analyst reputation. Further analyses show that market reactions at quarterly earnings announcements are more positive (negative) when firms meet/beat (miss) AA analysts’ forecasts than when firms meet/beat (miss) non-AA analysts’ forecasts. Collectively, our findings suggest that managers strategically provide voluntary forecasts by taking into account the reputation of individual analysts following their firms.     

Corporate Innovation Strategy,Analyst Forecasting Activities and the Economic Consequences

We examine the impact of corporate innovation strategy on analyst following and forecasting performance, as well as the associated economic consequences. Using a sample of US firms from 1992?2012, we find that firms pursuing an exploration‐oriented innovation strategy (as opposed to an exploitation‐oriented innovation strategy) are associated with lower analyst coverage, higher forecast error and dispersion. The effect is less pronounced for firms with greater disclosure of innovation activities, and for firms followed by analysts with more firm‐specific experience. We also examine how innovation strategy affects the perceived credibility of analyst forecasts and find that investors appear to be less responsive to forecast revisions issued for exploratory firms. Such firms also incur a higher level of cash holdings, greater internal financing, and lower dividend ratio. The findings of this paper advance our understanding of how a public company's choice of innovation strategy affects its performance in the capital markets as well as the associated economic consequences.     

The effects of firms’ information environment on analysts’ herding behavior

We find financial analysts herd to a greater degree in firms with more opaque information environments as measured by the incidence of short-term institutional investors present. The S-statistic, a measure of forecast bias, and forecast timing and quality metrics are used to measure analyst herding behavior. The results are consistent with the notion that opaque information environments are more conducive to analysts engaging in reputational herding behavior where more capable analysts act first and less capable analysts follow. Additionally, analysts are more likely to issue forecast revisions subsequent to management earnings guidance in less opaque environments. Robustness tests indicate our operational measure of opacity is not subsumed by other measures of the information environment, namely information asymmetry.     

Economic policy uncertainty and analysts’ forecast characteristics

We examine the influence of economic policy uncertainty (EPU) on the characteristics of analysts’ earnings forecasts over a thirty-year period, spanning a wide variety of political and economic conditions. Motivated by both theory and empirical evidence that suggest a decline in the quality of the information environment for firms as EPU increases, we establish that analysts’ forecast errors increase with EPU, as does the degree of forecast dispersion. Increased error and dispersion persist after controlling for several competing sources of economy-wide uncertainty. Cross sectional analysis exploring heterogeneity in forecast quality across both analyst and firm characteristics establishes that forecast error and dispersion increase with EPU across a broad spectrum of firms and levels of analyst expertise. We control for analysts’ experience overall and the years spent covering a particular industry and firm. Five alternative methods for classifying firms as policy sensitive versus policy neutral provide consistent evidence that analyst forecast errors and dispersion increase with EPU, even for firms not deemed to be particularly sensitive to policy.     

The Effects of Disclosure and Analyst Regulations on the Relevance of Analyst Characteristics for Explaining Analyst Forecast Accuracy

We posit and find an effect of disclosure and analyst reporting regulations implemented from 2000 through 2003 (including Regulation Fair Disclosure, the Sarbanes‐Oxley Act and the Global Settlement Act) on the importance of analyst and forecast characteristics for analyst forecast accuracy. Following the enactment of these regulations, more experienced analysts and All‐Star analysts do not maintain their superior forecast accuracy, and analysts employed by large brokerage houses perform worse than other analysts. In addition, we find a decrease in the importance of analyst effort, the number of industries and firms followed, days elapsed since the last forecast, and forecast horizon. While the importance of bold upward forecast revisions does not change, bold downward revisions lose their relevance for forecast accuracy after 2003. Finally, we find an increase in the importance of prior forecast accuracy. We find that the importance of these characteristics varies with the precision of publicly available information. Specifically, the decrease in the importance of most analyst and forecast characteristics and the increase in the importance of prior forecast accuracy are greater when the precision of publicly available information is low. Overall, our results suggest that the positive effects of experience, effort, brokerage house size and All‐Star status on forecast accuracy in the pre‐regulation period were because of the information advantages that these analysts enjoyed (rather than their ability to generate private information). In contrast, our results suggest that prior forecast accuracy is related to analysts’ ability to generate private information.     

Is Sell‐Side Research More Valuable in Bad Times?

Because uncertainty is high in bad times, investors find it harder to assess firm prospects and hence should value analyst output more. However, higher uncertainty makes analysts’ tasks harder, so it is unclear whether analyst output is more valuable in bad times. We find that in bad times, analyst revisions have a larger stock‐price impact, earnings forecast errors per unit of uncertainty fall, and analyst reports are more frequent and longer. The increased impact of analysts is also more pronounced for harder‐to‐value firms. These results are consistent with analysts working harder and investors relying more on analysts in bad times.     

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.     

Analyst Coverage and Intangible Assets

This study examines the relation between analysts' incentives to cover firms and the extent of their intangible assets. Because intangible assets typically are unrecognized and estimates of their fair values are not disclosed, absent analyst coverage firms with more intangible assets likely have less informative prices. Accordingly, we expect analysts have greater incentives to cover firms with more intangible assets and, thus, predict they have higher analyst coverage. As predicted, we find that analyst coverage is significantly greater for firms with larger research and development and advertising expenses relative to their industry, and for firms in industries with larger research and development expense. We also predict and find that analyst coverage is increasing in firm size, growth, trading volume, equity issuance, and perceived mispricing, and is decreasing in the size of the firm's analysts' brokerage houses and the effort analysts expend to follow the firm. These findings indicate that analyst coverage depends on private benefits and costs of covering a firm. We also test hypotheses related to analyst effort. We predict and find that analysts expend greater effort to follow firms with more intangible assets, after controlling for other factors associated with analyst effort. Our evidence indicates that intangible assets, most of which are not recognized in firms' financial statements, are associated with greater incentives for analysts to cover such firms, and greater costs of coverage. An open question is whether financial statement recognition of intangible assets could more efficiently provide information about such assets to investors.     

Complicated firms

We exploit a novel setting in which the same piece of information affects two sets of firms: one set of firms requires straightforward processing to update prices, while the other set requires more complicated analyses to incorporate the same piece of information into prices. We document substantial return predictability from the set of easy-to-analyze firms to their more complicated peers. Specifically, a simple portfolio strategy that takes advantage of this straightforward vs. complicated information processing classification yields returns of 118 basis points per month before transaction costs. Consistent with processing complexity driving the return relation, we further show that the more complicated the firm, the more pronounced the return predictability. In addition, we find that sell-side analysts are subject to these same information processing constraints, as their forecast revisions of easy-to-analyze firms predict their future revisions of more complicated firms.     

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.     

Do analysts who understand accounting conservatism exhibit better forecasting performance?

This study investigates the performance of analysts when they match the asymmetric timeliness of their earnings forecast revisions (i.e., asymmetric forecast timeliness) with the asymmetric timeliness of firms’ reported earnings (i.e., asymmetric earnings timeliness). We find that better timeliness‐matching analysts produce more accurate earnings forecasts and elicit stronger market reactions to their forecast revisions. Further, better timeliness‐matching analysts issue less biased earnings forecasts, more profitable stock recommendations and have more favorable career outcomes. Overall, our results indicate that analysts’ ability to incorporate conditional conservatism into their earnings forecasts is an important reflection of analyst expertise and professional success.     

Do changes in the SG&A ratio provide different information about changes in future earnings,analyst forecast revisions,and stock returns under different circumstances?

In fundamental analysis, increases (decreases) in the ratio of selling, general and administrative (SG&A) costs to sales (SG&A ratio) are perceived as negative (positive) signals regarding future firm performance. However, this interpretation focuses on the overall change in the SG&A ratio and ignores the underlying changes in the components of the ratio (sales and SG&A costs). Although prior research examines the changes in the SG&A ratio under some different circumstances, there is no study that examines all the ways that managers adjust costs in reaction to changes in sales. Therefore, I create six subsamples representing all possible combinations of changes in sales, SG&A costs, and the SG&A ratio and test whether changes in the SG&A ratio are informative about future earnings, analyst forecast revisions, and stock returns under these different circumstances. I find that changes in the SG&A ratio in four of my six subsamples provide information about changes in future earnings. I also find that analysts do not impound all of the information contained in the signals into their forecast revisions and in some cases investors appear to understand this fact.     

Analyst underreaction and the post-forecast revision drift

The post-forecast revision drift (PFRD), the phenomenon of delayed stock price reactions to analyst forecast revisions, is a well-documented market anomaly. Prior research attributes PFRD to underreaction by investors to analyst forecast revisions. This study investigates the role of the analyst forecast revision process itself in the PFRD anomaly. Using a large sample of US firms, we confirm prior findings of a positive serial correlation (momentum) in individual analysts’ revisions to their earnings forecasts and, based on both indirect and direct tests, document a positive association between this momentum and PFRD. Further analyses reveal that both the forecast revision momentum and PFRD vary in similar ways with respect to the nature of the news driving the revisions and the information environment. Collectively, our findings show that underreaction by individual analysts in the forecast revision process is an important contributor to the PFRD phenomenon.