Range has it: decoding the information content of forecast ranges

Range forecasts have emerged as the predominant form of management forecasts, but prior research has overlooked the information conveyed by forecast ranges. This study fills this void by examining the information content of the extent to which managers’ forecast ranges overlap with the range of individual analysts’ pre-existing estimates (i.e., overlap). We expect managers to signal their superior private information by issuing low-overlap forecasts. We predict and find that, compared with high-overlap forecasts, low-overlap forecasts are associated with stronger market reactions and higher accuracy of management forecasts relative to analyst estimates. Moreover, when responding to low-overlap management forecasts, analysts with prior estimates out of management forecast ranges are more likely to revise into the management forecast range, less likely to revise toward the consensus, and more likely to improve in revised forecast accuracy. Our findings suggest that investors and analysts view low-overlap management forecasts as signals of superior private information.     

Analyst following,staggered boards,and managerial entrenchment

We use agency theory to explore how analyst coverage is influenced by the managerial entrenchment associated with the staggered board. The evidence suggests that firms with staggered boards attract significantly larger analyst following. We also document that firms with staggered boards experience less information asymmetry. Staggered boards insulate managers from the discipline of the takeover market. Entrenched managers are well-protected by the staggered board and have fewer incentives to conceal information, resulting in less information asymmetry. The more transparent information environment facilitates the analyst’s job. As a consequence, more analysts are attracted to firms with staggered boards. We also document the beneficial role of analyst coverage in improving firm value. Our results confirm the notion that analysts, as information intermediaries, provide oversight over management and thus help alleviate agency conflicts. The positive effect of analyst coverage, however, is severely reduced when the firm has a staggered board in place.     

Inefficiency in Analysts' Earnings Forecasts: Systematic Misreaction or Systematic Optimism?

A rational analysis of analyst behavior predicts that analysts immediately and without bias incorporate information into their forecasts. Several studies document analysts' tendency to systematically underreact to information. Underreaction is inconsistent with rationality. Other studies indicate that analysts systematically overreact to new information or that they are systematically optimistic. This study discriminates between these three hypotheses by examining the interaction between the nature of information and the type of reaction by analysts. The evidence indicates that analysts underreact to negative information, but overreact to positive information. These results are consistent with systematic optimism in response to information.     

Who herds?

This paper develops a test for herding in forecasts by professional financial analysts that is robust to (a) correlated information amongst analysts; (b) common unforecasted industry-wide earnings shocks; (c) information arrival over the forecasting cycle; (d) the possibility that the earnings that analysts forecast differ from what the econometrician observes; and (e) systematic optimism or pessimism among analysts. We find that forecasts are biased, but that analysts do not herd. Instead, analysts “anti-herd”: Analysts systematically issue biased contrarian forecasts that overshoot the publicly-available consensus forecast in the direction of their private information.     

Rationality and Analysts' Forecast Bias

This paper proposes and tests a quadratic-loss utility function for modeling corporate earnings forecasting, where financial analysts trade off bias to improve management access and forecast accuracy. Optimal forecasts with minimum expected error are optimistically biased and exhibit predictable cross-sectional variation related to analyst and company characteristics. Empirical evidence from individual analyst forecasts is consistent with the model's predictions. These results suggest that positive and predictable bias may be a rational property of optimal earnings forecasts. Prior studies using classical notions of unbiasedness may have prematurely dismissed analysts' forecasts as being irrational or inaccurate.     

Disclosure of internal control material weaknesses and optimism in analyst earnings forecasts

This paper investigates how analyst forecast optimism is associated with disclosures of internal control material weaknesses (ICMWs) and their remediation under Section 404 of the Sarbanes–Oxley Act (SOX). Drawing on agency theory, I hypothesize that analysts are likely to issue earnings forecasts that are more optimistic for firms with ICMW disclosures than for those without ICMW disclosures. Using a sample of 20,875 firm-year observations with 10-K (10-Q) reports from 2004 to 2018, I find a positive association between ICMW disclosures and analyst forecast optimism. This positive association is partially driven by investors’ inability to unravel analyst forecast bias and analysts’ intentions to curry favor with management for private information. In addition, analysts are found to issue less optimistic forecasts for firms with ICMW remediation disclosures compared with those without ICMW remediation disclosures. A series of propensity score matching and regression analyses are conducted to test the robustness of my inferences. Overall, the paper suggests that analysts have incentives to take the opportunity of firms disclosing ICMWs to bias their forecasts upward for self-interest. The findings have the potential to assist regulators in guiding analyst behavior and educating investors to unravel positive bias in analyst forecasts.     

分析师意见分歧与银行信贷决策——来自中国上市公司的经验证据

作为金融市场重要信息中介,分析师通过发布专业意见向市场传递私有信息,但不同分析师发布的意见可能存在严重分歧。本文从银行信贷决策角度研究了分析师意见分歧的经济后果,结果表明,严重的分析师意见分歧会降低银行信贷规模,提高信贷成本,并缩短信贷期限;进一步研究发现,分析师意见分歧对银行信贷决策的影响在不同内部控制水平、产品市场竞争和媒体报道程度的企业之间存在显著差异,并且是通过缓解信息不对称这一作用机制实现的。本文结论不仅拓展了理论界和实务界对分析师作用的认识,而且为完善银行信贷决策提供了新思路。     

Group-Affiliated Analysts’ Strategic Forecasts During a Year: Evidence from Korea

In examining the family-controlled business groups in Korea, prior literature shows that group-affiliated analysts’ forecasts are optimistically biased. This article investigates whether the group-affiliated analysts strategically time the level of accuracy and bias in their forecasts for the same group-affiliated firms due to the change in information asymmetry in the market. The results show that the group-affiliated analysts issue more accurate and less optimistic earnings forecasts for the affiliated firms when the level of information asymmetry is low; particularly, in April, which is right after annual earnings announcements.     

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.     

Institutional investor information network,analyst forecasting and stock price crash risk

In this paper, we construct the information network of fund investors based on the theory of social relationship networks and examine its impact of fund information sharing with analysts on stock price crash risk. Our results show that private information sharing among institutional investors reduces crash risk. Further results show that fund information sharing can alleviate analyst optimism bias and improve analyst forecast accuracy, which further reduces stock price crash risk. Moreover, these identified effects are more pronounced in a bull market than a bear market. Our study contributes to the research on private information transmission in fund information networks, and provides a new perspective for recognizing the relationships among institutional investor behavior, analyst forecasting, and stock price crash risk.     

Analyst Pessimism and Forecast Timing

In this study, we show that on average relatively pessimistic analysts tend to reveal their earnings forecasts later than other analysts. Further, we find this forecast timing effect explains a substantial proportion of the well‐known decrease in consensus analyst forecast optimism over the forecast period prior to earnings announcements, which helps explain why analysts’ longer term earnings forecasts are more optimistically biased than their shorter term forecasts. We extend the theory of analyst self‐selection regarding their coverage decisions to argue that analysts with a relatively pessimistic view–compared to other analysts–are more reluctant to issue their earnings forecasts, with the result that they tend to defer revealing their earnings forecasts until later in the forecasting period than other analysts.     

Who Says there is a High Consensus Among Analysts when Market Uncertainty is High? Some New Evidence from the Commercial Real Estate Market

This paper seeks to determine whether analyst consensus is a function of the level of price informativeness, and therefore attempts to gauge the extent to which analyst consensus is high when market uncertainty is high. There is the view that a small or declining volume of trading implies less information and lower quality information, and that a lower level of price informativeness will lead analysts to put more weight on their private information at the time of forecasting. We add to this view the notion that when uncertainty is high there might be a positive option value of waiting. In this case, it appears reasonable to conclude that analysts may actually lack consensus when uncertainty is high. If this hypothesis is correct, then one would expect the level of price informativeness to override the Keynesian incentive “to fail conventionally than to succeed unconventionally” or at least reduce its magnitude in periods of declining trading volume and low price discovery. Tests of this hypothesis produce favorable results.     

The consequences to analyst involvement in the IPO process: Evidence surrounding the JOBS Act

The JOBS Act allows certain analysts to be more involved in the IPO process, but does not relax restrictions on analyst compensation structure. We find that these analysts initiate coverage that is more optimistically biased, less accurate, and generates smaller stock market reactions. Investors purchasing shares following these initiations lose over 3% of their investment by the firm's subsequent earnings release. By contrast, issuers, analysts, and investment banks appear to benefit from this increased bias, as optimism is more positively associated with proxies for firm visibility and investment banking revenues when analysts are involved in the IPO process.     

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.     

High-Technology Intangibles and Analysts' Forecasts

This study examines the association between firms' intangible assets and properties of the information contained in analysts' earnings forecasts. We hypothesize that analysts will supplement firms' financial information by placing greater relative emphasis on their own private (or idiosyncratic) information when deriving their earnings forecasts for firms with significant intangible assets. Our evidence is consistent with this hypothesis. We find that the consensus in analysts' forecasts, measured as the correlation in analysts' forecast errors, is negatively associated with a firm's level of intangible assets. This result is robust to controlling for analyst uncertainty about a firm's future earnings, which we also find to be higher for firms with high levels of internally generated (and expensed) intangibles. Given that analyst uncertainty increases and analyst consensus decreases with the level of a firm's intangible assets, we also expect and find that the degree to which the mean forecast aggregates private information and is more accurate than an individual analyst's forecast increases with a firm's intangible assets. Finally, additional analysis reveals that lower levels of analyst consensus are associated with high-technology manufacturing companies, and that this association is explained by the relatively high R&D expenditures made by these firms. Overall, our results are consistent with financial analysts augmenting the financial reporting systems of firms with higher levels of intangible assets (in terms of contributing to more accurate earnings expectations), particularly R&D-driven high-tech manufacturers.     

Endogenous overconfidence in managerial forecasts

We examine whether attribution bias leads managers who have experienced short-term forecasting success to become overconfident in their ability to forecast future earnings. Importantly, this form of overconfidence is endogenous and dynamic. We also examine the effect of this cognitive bias on the managerial credibility. Consistent with the existence of dynamic overconfidence, managers who have predicted earnings accurately in the previous four quarters are less accurate in their subsequent earnings predictions. These managers also display greater divergence from the analyst consensus and are more precise. Lastly, investors and analysts react less strongly to forecasts issued by overconfident managers.     

信息披露、信息中介与企业过度投资

本文基于中国上市公司的经验数据,对信息披露、信息中介与企业过度投资之间的关系进行了探索,研究结果表明:信息披露水平提高和信息中介的发展,将减轻信息不对称程度,进而提高了企业的投资效率,抑制过度投资行为。本文还发现上述机制之间存在互补关系,信息中介作用的发挥依赖于信息披露机制,而更多的信息中介参与营造了较好的信息传播环境,增强了信息披露机制的抑制效果。     

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.