Information Content Of Analysts Research Articles

The information content of analysts’ textual reports and stock returns: Evidence from China

We apply a Long Short-Term Memory (LSTM) deep-learning approach, which can capture the order of words, to extract textual tones from analyst reports written in Chinese. The market reaction is significantly and positively correlated with the textual tone of the analyst reports. Furthermore, we find that the market reaction is stronger to negative tones. Additionally, investors are more responsive to the textual tone from star analysts and the analysts from larger brokerage houses. We also investigate how the margin trading and Shanghai-Hongkong (or Shenzhen-Hongkong) stock connect impact the informativeness of textual opinion.

Analyst Report, Information Transparency and Stock Price Synchronization

This paper uses the relevant data of company characteristics information contained in the analyst research reports of China's A-share listed companies from 2009 to 2015 to study the impact of text content in analyst reports on stock price synchronization. The results of the study found that the more the text content of the analyst research report contains the company's characteristics, the more the company can attract investors' attention and the easier it is to reduce the synchronization of the stock price; The impact of analyst reports on stock price synchronicity is even more pronounced in the context of low transparency of company information. The mechanism by which analysts reduce the synchronization of stock prices is that reports with high content of company characteristic information attract more attention from investors, making the stock price more absorb company characteristic information. From the perspective of information mechanism and corporate governance mechanism, this article explores whether the information conveyed by analyst reports improves or decreases the synchronization of stock prices. This not only enriches the research on the factors influencing the synchronization of stock prices, but also enriches the research on the information content of analysts' reports, which has important theoretical and practical significance for investors, analysts and companies.

Do the Securities Analysts Play the Role of Information Competition or Information Supplement? Empirical Analysis Based on Investor Sentiment

The purpose of this article is to investigate the role of securities analysts in Chinese stock market. Taking the earnings announcements of listed companies, analysts’ earnings forecast and analysts’ recommendations in Chinese stock markets from 2014 to 2018 as the samples, this paper explores the influence mechanism of investor sentiment on the market reaction to announcements, and investigates the influence mechanism of investor sentiment on the role of securities analysts under the framework of behavioral finance theory. On the basis of theoretical analysis, this paper empirically tests the relationship between the information content of analysts’ reports and the information content of the earnings announcements from the perspective of behavioral finance, and discusses the role of securities analysts in the stock market. The results show that during the periods of high investor sentiment, securities analysts do not demonstrate the role of information competition or information supplement. On the other hand, during the periods of low investor sentiment, securities analysts play the role of information competition or information supplement. Furthermore, after excluding the investor sentiment component of the market reaction to announcements, securities analysts do not demonstrate the role of information competition, but play the role of information supplement. The findings of this study offer new insights into the role securities analysts play in Chinese stock market, which is conducive to improving the quality of analysts’ reports, thus enhancing the efficiency of the securities market.

Analysts’ forecasts between last consensus and earning announcement date

Purpose Thomson financial database reports a monthly consensus measure of analysts’ forecasts in the third week of every month, and firms’ earnings announcement dates are usually different from the last consensus calculation date. Thus, there is a gap between the last consensus calculation date and the earnings announcement date of firms. This study aims to address the question: “Do analysts issue forecasts that are slightly higher than the consensus number to increase the accuracy of their forecasts?” Design/methodology/approach This study is based on a sample of 91,172 quarterly earnings forecasts of various firms from 1990 to 2007 made between the last consensus calculation date and quarterly earnings announcement date. Descriptive statistics and statistical tests were used to analyze the data. Findings The findings propose that contrary to expectation, analysts’ forecasts between the last consensus calculation date and earnings announcement date are smaller than the consensus number. Also, the forecasts made between the last consensus and earnings announcement date is not as informative as forecasts made at other times as they could merely reflect the analysts’ herding behavior resulting from their career concerns. Originality/value This study provides a link between the literature that studies firms’ meet or beat analysts’ earnings phenomenon and analysts’ forecast decision-making context. This study also provides useful implications for the literature on the information content of analysts’ forecasts.

The Information Content of Analysts' Book Value Per Share Forecasts

We investigate the information content of analysts’ book value per share (BVPS) forecasts. We test whether analysts’ BVPS forecasts are informative about future realizations of other comprehensive income (OCI) and special items controlling for analysts’ EPS forecasts. Our results suggest that analysts’ BVPS forecasts generally incorporate upcoming realizations of OCI and special items, especially for financial firms. We also find evidence that BVPS forecasts provide expectations of non-EPS income, and that the market responds to BVPS innovations, especially BVPS forecasts misses. Finally, we find evidence that analysts provide more BVPS forecasts for financial firms that 1) have greater absolute levels of accumulated other comprehensive income (AOCI) from securities and derivatives, 2) report higher levels of OCI from securities, and 3) hold more opaque financial assets, and for non-financial firms with high absolute levels of pension-related AOCI.

What Do Analysts’ Provision Forecasts Tell Us About Expected Credit Loss Recognition?

We examine the incremental predictive ability and information content of analysts’ provision forecasts to explore the potential effects of the FASB’s new current expected credit loss (CECL) accounting method. Controlling for the recognized loan loss provision, consensus analyst provision forecasts are incrementally associated with future non-performing loans (NPLs) and equity markets returns. This incremental association is increasing in banks’ unconstrained ability to estimate future losses as evidenced by their loan fair value disclosures and the extent of the constraints imposed by the incurred loss model measured by the fraction of heterogeneous loans individually reviewed for impairment. For a sample of analysts that also forecast NPLs, the association between the individual analyst’s provision forecast and future NPLs is increasing in the analyst’s comparative NPL forecasting accuracy. Finally, we find that the association between the analyst’s provision forecast and future NPLs is increasing in EPS forecast errors but decreasing in target price forecast errors. Together these results suggest that the reported provisions under the current incurred loss model do not fully incorporate banks’ information about future losses and that the extent to which this occurs depends both on banks’ ability to forecast expected losses and the constraints imposed by the incurred loss model. These results suggest that analysts forecast future losses beyond those reflected in the recognized provision and that the incremental information in these forecasts and potential CECL provision timeliness effect is greater when the constraints imposed by the incurred loss model are greater.

Do Financial Analysts Generate Value-Relevant Interpretive Information from 10-K Filings?

Many papers in the academic and practitioner literature question the value-relevance of sell-side analysts’ interpretation of information in 10-K filings. This paper examines the information content of analysts’ forecast revisions that straddle 10-K filing dates, as compared to the information content of revisions straddling earnings announcement dates. Our evidence suggests that annual earnings forecast accuracy improves more and price discovery takes longer in relation to forecast revisions straddling 10-K filing dates. Our evidence also suggests that analysts underreact to information in 10-K filings to a greater extent than their underreaction to the information released around the time of earnings announcements. These results are consistent with the inference that increased uncertainty created by greater complexity, opacity, and volume of information in 10-K filings causes analysts to react with more restraint than the restraint associated with their reaction to information released around the time of earnings announcements. More generally, our results are consistent with the inference that analysts play an important interpretive role with respect to information in firms’ 10-K filings.

Analyst Rankings and Forecast Informativeness

Does competition for a higher reputational ranking induce analysts to reveal more information? Two analysts make simultaneous forecasts about a company's future value to achieve a higher reputation relative to their peers, and are paid a tournament-style compensation. I show that the effect of reputational rankings on the information content of analysts' forecasts depends on the convexity of their payoffs and the correlation between their private signals. Competition diminishes forecast informativeness under a convex payoff structure when their signals are positively correlated and the market uncertainty is high. Under a convex payoff, analysts expecting a positive signal correlation tend to differentiate from each other by forecasting against their own signals, revealing less information in equilibrium. For a concave payoff, competition improves forecast informativeness. Forecasts by more reputable analysts may not be more informative under a convex payoff structure. These results have important implications for Regulation Fair Disclosure.

<b>Information Content of Analysts' Stock Ratings and Earnings Forecasts in the Presence of Management Earnings Forecasts</b>

This paper evaluates the informativeness of analysts’ ratings and earnings forecast information contained in analyst reports beyond what is publicly provided by management earnings forecasts. Using only analyst reports that have been released practically simultaneously with management forecasts, I find that both analysts’ ratings and earnings forecasts have incremental information content conditional on management forecasts. Further analysis also reveals that analysts’ earnings forecasts are significantly more accurate than concurrently-announced management earnings forecasts. Overall, the findings in this paper present strong evidence that analysts offer informational value to the market beyond information that is provided by company management.

The information content of analysts reports and bankruptcy risk measures

We evaluate the information content of analysts’ reports and bankruptcy risk quantities towards each other, and examine whether differences arise between low- and high-risk firms and between stock recommendations and earnings forecasts. We reveal that past changes in analysts’ reports convey valuable information towards future developments in default risk measures, analysts’ outcome rely upon lagged modifications in corporate creditworthiness, and the predictive power in both directions is more pronounced among high risk enterprises. Furthermore, default likelihoods and analysts’ recommendations and forecasts Granger cause each other, generating a significant feedback system. Moreover, earnings forecasts portray more profound relations to credit risk quantities than stock recommendations.

The Effect of Earnings Projection Revisions on Stock Returns in Brazil

This paper investigates the information content of analysts’ earnings forecast revisions for Brazilian companies, defined as the ability to change stock prices. Using data from I/B/E/S and Economatica covering the period from 1995 through 2002, we find that forecast revisions that follow the consensus (herding behavior) provide small information content. A forecast revision is more informative when it deviates from the consensus, both in the case of good or bad news. Momentum is the main element to explain the behavior of stock returns in light of revised earnings forecasts. The results provide evidence that these revisions are largely based on previous stock performance. The findings are relevant, especially for those that use analysts’ earnings forecasts in their valuation models, as well as portfolio managers and individual investors.

The Information Content of Analysts' Notes and Analysts' Propensity to Compliment Other Disclosures

This paper studies analysts' notes, which are written disclosures distributed to large institutional investors as part of the brokerage firms' daily sales process. Analysts' notes are issued three times more frequently than recommendations and forecast revisions, and represent the bulk of analyst disclosures. The tests in this paper represent the first systematic study of notes. I find that the capital markets react to notes consistent with the idea that notes provide an economically significant amount of new information to investors. I also show that notes are less (but continue to be) informative after implementation of Regulation FD. My analysis of the timing of different types of analysts' disclosures - recommendations, forecasts and notes - shows that they tend to occur at the same time. These two results suggest that notes are a valid proxy for analyst disclosures. Last, a content analysis of randomly-selected notes enables me to identify analysts' sources of information and create a direct measure of analysts' information acquisition and interpretation activities. I find that analysts primarily add value from an investors perspective by interpreting information.

Effect of Reg FD on Information in Analysts’ Rating Changes

A rich literature examines the effects of analysts’ recommendations on stock prices, and literature is developing on the effect of Regulation Fair Disclosure on the information associated with corporate earnings forecasts and announcements. This study examines the effect of Reg FD on the information content of analysts’ rating changes. Based on recommendations associated with a random sample of S&P 500 Index stocks, the major finding is that investors have been responding to analysts’ recommendations in the same way since Reg FD as they did before implementation of Reg FD. In addition, the results suggest that Reg FD does not require that practitioners change the way they view the analyst recommendation process.

Information Content of Analysts' Forecasts in the Bond Market

Motivated by the paucity of studies examining analysts' forecasts in the bond market, this study addresses the question whether analysts' forecasts are informative to debt rating agencies and bondholders. Specifically, I investigate whether analysts' forecasts provide any incremental explanatory power to cost of borrowing. I construct simultaneous equations by using debt ratings and bond yield premium to measure the cost of borrowing. I apply three-stage-least-squares (3SLS) procedure incorporating firms' industry-adjusted earning forecasts, cash flow forecasts and growth forecasts into the model. Additionally, I examine whether the information content of these forecasts to bond investors vary in different contexts. The results show that analysts' forecasts capture information used by rating agencies to assign debt ratings, while overall bond investors rely heavily on credit ratings and analysts' forecasts do not provide significantly incremental explanatory power in explaining bond yield premium. However, when perceived default risk is high, or when bond investors perceive a high level of private information collection by analysts in the context of high information asymmetry or highly unpredictable earnings, analysts' forecasts become informative to bond investors as well. I also find that analysts' forecasts capture less information used by bond investors after regulation Fair Disclosure (FD) took effect and debt investors rely more heavily on debt ratings in the post-FD period.

The Relative Accuracy of Analysts’ Published Forecasts Versus Whisper Forecasts Surrounding the Adoption of Regulation FD

Abstract This paper examines the accuracy and information content of analysts’ published forecasts relative to whisper forecasts before and after the effective date of Regulation Fair Disclosure (Reg FD). We find that whisper forecasts are generally more accurate than analysts’ consensus forecasts in our pre-Reg FD period (consistent with prior literature), but less accurate during the post-Reg FD period. We also find in the post-Reg FD period that analysts’ forecast errors earn significantly larger abnormal returns compared to whisper forecast errors. These results suggest that Reg FD has had its desired effect of mitigating private communications from management to market participants.

The Timing and Value of Forecast and Recommendation Revisions: Do Analysts Receive Early Peek at Good News?

This paper evaluates the information content of analysts' one-quarter ahead earnings forecast revisions and recommendation revisions at various points in time relative to earnings announcement dates. We conduct three sets of tests to evaluate the information content of revisions. Across all tests, we find that the revisions are least informative in the week after earnings announcements and that the information content of revisions generally increases over event time. We find a sharp increase in the information content of upward forecast revisions and recommendations upgrades, but we do not find a similar increase for downward revisions and recommendation downgrades.

The Information Content of Analysts' Forecasts of REIT Earnings

In this study, we attempt to add some clarification to the ongoing debate of REITs. While REITs have some characteristics similar to those of common stocks, they behave fundamentally different from stocks in general. Using a matched sample comparison, we find that REITs have lower return variability and lower correlation to the market, but higher institutional participation than other firms. In tests of forecast unbiasedness, we observe significant levels of bias and inefficiency for both REITs and common stocks when we use traditional rational expectations models. Lastly, we examine the market reaction to earnings forecast revisions. All forecast revisions, for both REITs and stocks, have significant price reactions around the revision. These returns are magnified when the sample is divided into sub-categories based on the sign of the revision or whether the analyst simultaneously changed his investment recommendation. Furthermore, while forecast errors do have some explanatory power for returns around the revision date, the level is greater for stocks than for REITs.