Accurate Analysts Research Articles

Synchronicity and Sentiment: Decoding Earnings Quality and Market Returns in EU under Economic Policy Uncertainty

This study investigates the impact of economic policy uncertainty on earnings quality and market returns in the European Union, a topic of growing importance in the wake of fluctuating global economic conditions. Using data from 14 EU countries spanning the period from 2000 to 2022, the findings of this study are significant, revealing a clear correlation between heightened economic policy uncertainty and altered investor behavior, as well as a deterioration in earnings quality. We also found that (a) stock market returns are threatened by the shroud of economic uncertainty, (b) higher market sentiment anticipates a negative return but, on the other hand, lower market sentiment expects an increase in the return, (c) stock market returns are higher in the case of highly accurate analyst forecasts, and (d) stock market returns are higher in the case of a higher level of stock return synchronicity. These insights have profound implications for investors, policymakers, and scholars, offering a deeper understanding of market dynamics under uncertainty and guiding more informed decision-making in turbulent economic times.

A comparison of analysts’ and investors’ information efficiency of corporate social responsibility activities

Purpose This paper aims to examine the extent to which sell-side analysts efficiently incorporate firms’ corporate social responsibility (CSR) activities into their earnings forecasts. In addition, this paper also investigate the CSR information efficiency of analysts vis-à-vis that of investors. Design/methodology/approach This paper measures CSR activities by using CSR strength and CSR concern scores from the Morgan Stanley Capital International Environmental, Social and Governance database. This paper uses analysts’ earnings forecast errors and dispersion as proxies for their information efficiency. To compare the CSR information efficiency of analysts to that of investors, this paper uses the Vt/Pt ratio, which is the equity value estimates inferred from analysts’ earnings forecasts (a proxy for analysts’ CSR information efficiency) to the stock price of the focal company (a proxy for investors’ CSR information efficiency). Findings The regression analysis indicates that analysts’ earnings forecasts are optimistically biased and more dispersed for firms with positive CSR activities. The paper also finds that analysts’ forecasts are more optimistically biased than investors in interpreting CSR activities. Practical implications The lack of standardized protocols in CSR reporting and activities has raised the risk of mispricing by analysts, threatening the stability of sustainable investments. This paper suggests that regulators and standard-setters should establish a uniform framework governing firms’ CSR activities, along with their reporting and measurement, to ensure more consistent and reliable evaluations of CSR practices. Social implications Analysts’ mispricing of CSR activities may distort sustainable investing, as it can overly focus on the positive impacts of stakeholder theory, overlooking agency theory’s warnings about managerial self-interest. Investors need to assess CSR efforts with a dual perspective, acknowledging their societal value but also examining their alignment with shareholder interests. Originality/value To the best of the authors’ knowledge, this research is the first to assess the efficiency of analysts versus investors in processing CSR information amidst growing sustainable investment interests. Furthermore, building on Dhaliwal et al. (2012), which found that voluntary CSR disclosures correlate with more accurate analyst forecasts, this research provides fresh perspectives on the evolving nature of how analysts assimilate CSR information over time.

Does the “Greenwashing” and “Brownwashing” of Corporate Environmental Information Affect the Analyst Forecast Accuracy?

Taking the listed firms of heavy pollution industries in China for 2010–2021 as a sample, this study explored the impact and heterogeneity of corporate environmental disclosure behavior on analyst forecasts’ accuracy. We discovered that corporates measure or disclose environmental information and, the more environmental information is measured or disclosed, the more accurate analysts’ forecasts are; moreover, there is a strong and significant correlation between the environmental information given in the special reports and analysts’ forecast accuracy. This positive correlation is even more significant in cases of “matching words to deeds” and “brownwashing” by corporates. A mechanism analysis revealed that the analysts’ coverage and site visits both have a full or partial mediating effect. Specifically, analysts’ coverage is more likely to be elicited when corporates measure or disclose environmental information; the higher the degree of measurement or disclosure, disclose in the special reports, “matching words to deeds” and “brownwashing”. Analysts conducted site visits when corporates measured or disclosed environmental information, the higher the degree of measurement or disclosure, disclose in the special reports and “brownwashing”. The information above demonstrates that, on the one hand, specialized reports are published to supplement financial disclosures and, on the other hand, that analysts place importance on corporates’ incremental and explicit environmental information; however, “information screening” is insufficient and some “information mining” was carried out when corporate environmental information disclosure was insufficient. This study shed light on analysts’ roles in the improvement of the information environment of China’s capital market as well as the objective appraisal of the impact of corporate environmental information disclosure.

Exploring the Impact of Firm Transparency on Green Innovation Legitimacy: Empirical Evidence from Listed Companies in China

Although the existing literature on innovation has little focus on information transparency, we aimed to determine how information transparency affects the legitimacy of green innovation in China. Accounting data, analyst data, and external audit data are used to evaluate a company’s information transparency. This paper examines the impact of corporate transparency on the legitimacy of green innovation in the context of three external information sources to which stakeholders have access, utilizing data from 4017 Chinese companies listed between 2005 and 2020. Our estimation results indicate a significant positive correlation between informational accessibility and green innovation legitimacy. The results demonstrate a stronger relationship between corporate green innovation legitimacy and greater earning quality, more analyst monitoring, more accurate analyst surplus estimations, and international audits by the Big Four. This study seeks to present new empirical findings for Chinese listed companies in order to strengthen the legality of green innovation and validate the significance of corporate information transparency via a robustness test.

Nondisclosure and analyst behavior: Evidence from redaction of proprietary information from public filings

This study explores how redacting proprietary information from public filings is related to analyst following and the properties of analysts' earnings forecasts. Using hand-collected data on firms' confidential treatment orders from the Securities and Exchange Commission's Electronic Data Gathering, Analysis, and Retrieval database, this study identifies firms that withhold information—redacting firms. Such firms are benchmarked to a matched set of firms not withholding information—non-redacting firms. The study predicts and demonstrates that compared to non-redacting firms, redacting firms have (i) a higher analyst following, (ii) more dispersed and less accurate analysts' earnings forecasts, and (iii) less precise public and private information in analysts' earnings forecasts. Further, additional analyses reveal that analysts covering redacting firms trade off accuracy for timeliness when issuing earnings forecasts, and the market reacts higher to the analyst reports of redacting firms. Moreover, for redacting firms, investors place a higher weight on the information derived from analysts than that obtained from the firm. Overall, the findings suggest that redacted disclosures are associated with greater investor demand for analyst outputs and a deterioration in the analysts' information environment. However, they are also associated with greater investor reliance on analyst outputs.

The usefulness of Non-IFRS segment data

A controversial aspect of International Financial Reporting Standard (IFRS) 8 allows firms to define their segment profit (or loss) on a different basis than IFRS measurement and recognition principles, but whether these non-IFRS segment data are useful is in large part unexplored. We fill this gap by investigating the usefulness of non-IFRS segment data from the perspective of financial analysts. Using hand-collected segment data on a sample of European multi-segment firms, we find empirical evidence that non-IFRS segment data lead to less accurate analyst forecasts. Additionally, we find that non-IFRS segment data are associated with higher forecast dispersion, higher uncertainty in analysts’ forecasts, and a lower precision of analysts’ public information set. Collectively, our findings suggest that non-IFRS segment data impair analysts’ information environment, which casts doubt on their usefulness.

The joint effects of macroeconomic uncertainty and cyclicality on management and analyst earnings forecasts

Prior literature examines the effects of both macroeconomic uncertainty and cyclicality (how strongly a firm's earnings is tied to macroeconomic conditions) on management and analyst earnings forecasts. However, these studies consider macroeconomic uncertainty and cyclicality independently and find conflicting results. This study argues that macroeconomic uncertainty and cyclicality are inextricably linked together, and should be studied jointly. Using a sample of earnings forecasts from 2001 to 2015, we find the following: (1) Kim, Pandit, and Wasley (2016)'s finding that heightened macroeconomic uncertainty decreases management's propensity to issue earnings forecasts is largely driven by firms with low cyclicality and (2) Hutton, Lee, and Shu (2012)'s finding that analysts issue more accurate forecasts than management for firms with high cyclicality only holds when macroeconomic uncertainty is high; increases in macroeconomic uncertainty lead to more accurate analyst forecasts relative to management forecasts only for firms with high cyclicality. These findings are useful to both researchers and investors interested in understanding how macroeconomic factors affect earnings forecasts.

Analyst bias and forecast consistency

AbstractWe contribute to the literature examining inconsistent analyst forecast revisions. While prior research suggests inconsistent analyst forecasts are less accurate, we find this result is sensitive to both the definition and direction of inconsistency. We define consistency relative to each analyst’s own forecast error and find the relation between analyst characteristics and the likelihood of issuing an inconsistent forecast differs depending on the direction of the revision. Specifically, less accurate analysts are more likely to issue an inconsistent positive revision and have higher future accuracy than their consistent counterparts. Our results suggest that analysts derive a benefit (better future accuracy) from issuing upward forecast revisions in the period immediately following an earnings announcement regardless of the resulting forecast pattern.

Corporate social responsibility disclosure and financial information environment

This study aims to explore whether or not social responsibility disclosure contributes to improve the financial information environment, through examining the impact of quantity and quality of corporate social responsibility (CSR) disclosure on the accuracy of analysts' forecasts and audit fees. Content analysis technique has been used to measure quantity and quality of CSR disclosure in annual reports of Saudi registered companies. OLS regression model is used to examine the relationship between the quantity and quality of CSR disclosure in the annual reports and the quality of the analysts' forecasts, and the audit fees. The results indicated that CSR disclosure provides useful information for outsiders, where it is associated with more accurate analysts’ expectations and reduced audit fees. These results suggest that CSR disclosure is associated with high quality financial information environment. This paper provides comprehensive analysis for financial information environment in Saudi companies. The findings of paper provide useful insights concerning the importance of social responsibility disclosure in Saudi business environment.

Do Long-Tenured Boards Provide Stability?

We investigate whether average director tenure affects a firm’s stock return volatility. Exploiting director deaths as exogenous shocks, we show that firms losing long-tenured directors experience 16.75% higher post-event annualized return volatility compared to control firms. Firms with long-tenured boards tend to have smoother investment patterns and are more likely to promote internal candidates as CEOs. We also find that long board tenure is associated with more accurate analyst forecasts and with smaller post-corporate event volatility. Our results suggest that long-tenured boards help reduce risk through more predictable decisions and efficient information sharing.

Artificial Intelligence and High-Skilled Work: Evidence from Analysts

Policymakers fear artificial intelligence (AI) will disrupt labor markets, especially for high-skilled workers. We investigate this concern using novel, task-specific data for security analysts. Exploiting variation in AI's power across stocks, we show analysts with portfolios that are more exposed to AI are more likely to reallocate efforts to soft skills, shift coverage towards low AI stocks, and even leave the profession. Analyst departures disproportionately occur among highly accurate analysts, leaving for non-research jobs. Reallocating efforts toward tasks that rely on social skills improve consensus forecasts. However, increased exposure to AI reduces the novelty in analysts' research which reduces compensation.

The job rating game: Revolving doors and analyst incentives

Investment banks frequently hire analysts from rating agencies. While many argue that this “revolving door” creates captured analysts, it can also create incentives to improve accuracy. To study this issue, I construct an original data set, linking analysts to their career paths and the securitized finance ratings they issue. First, I show that accurate analysts are more frequently hired by underwriting investment banks. Second, I exploit two distinct sources of variation in the likelihood of being hired by a bank. Both indicate that, as this likelihood rises, analyst accuracy improves. The findings suggest policymakers should consider incentive effects alongside capture concerns.

Analyst Promotions within Credit Rating Agencies: Accuracy or Bias?

We estimate Moody’s preference for accurate versus biased ratings using hand-collected data on the internal labor market outcomes of its analysts. We find that accurate analysts are more likely to be promoted and less likely to depart. The opposite is true for analysts who downgrade more frequently, who assign ratings below those predicted by a ratings model, and whose downgrades are associated with large negative market reactions. Downgraded firms are also more likely to be assigned a new analyst. These patterns are consistent with Moody’s balancing its desire for accuracy against its corporate clients’ desire for higher ratings.

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.

The economic effects of IFRS adoption in Korea

This paper examines whether Korea’s mandatory adoption of International Financial Reporting Standards (IFRS) is associated with higher earnings quality. Based on Korean listed companies, we compare earnings quality and market assessment in the pre-IFRS period (2007–2010) with those in the post-IFRS period (2011–2014). We find significant IFRS adoption effects by documenting smaller absolute values in discretionary accruals and real earnings management, higher accrual quality, stronger earnings persistence, and less frequent negative earnings. Thus, we provide evidence of improved earnings quality with Korea’s mandatory IFRS adoption. Additionally, we document an increase in the value relevance of earnings, more accurate analysts’ earnings forecasts, and higher audit fees and hours. These results show that investors and analysts view improvements in the information environment, and auditors’ respond to the complex environment by demanding higher audit fees and making additional efforts after mandatory IFRS adoption.

Fair value accounting and analyst forecast accuracy

This study examines the effect of fair value accounting on the behavior of analysts using a large, generalizable sample of U.S. firms. By employing a measure of firms' fair value intensity, we provide evidence showing that firms with higher fair value intensity have more accurate analyst earnings forecasts, a significant main effect elusive to Magnan, Menini, and Parbonetti (2015). Furthermore, by using disclosures required by Statement of Financial Accounting Standards (SFAS) No. 157, we find significant positive associations between analyst forecast accuracy and Level 1 and Level 2 fair value measurements, but we do not find such association for Level 3 measurements. We document that these main effects are predominantly concentrated in non-financial industry firms in contrast to financial industry firms. This suggests that qualitative features of fair value measurements, including their business purpose and on-average accounting treatment (e.g., trading assets, available for sale, etc.), could also have an impact on analyst forecasting accuracy beyond mere measurement issues. Our results contribute to the debate over fair value accounting by showing the impact of fair value accounting upon an important participant in the capital markets.

The Informational Content Of Changes In Stock Recommendation: Chaebol Vs. Non-Chaebol Affiliated Analysts

Accurate analysts’ reports alleviate information asymmetry between companies and investors by providing accounting information that is useful in investment decision-making for market participants. Investors evaluate the credibility of stock recommendations based on the accuracy of the earnings forecasts of analysts, applying them in the decision-making process. Studies of stock recommendations have focused on their informational content, systematically analyzing the characteristics of recommendations and, to a lesser degree, decision-making factors. For most analysts, when stock recommendations and forecast changes are simultaneously disclosed, a large bias results if analysts fail to consider the magnitude of the market reaction relative to the earnings forecast and stock recommendations. In most previous studies, the informational content of both individual stock recommendations and changes in stock recommendations was investigated. In this study, we examine differences in the informational content depending on the stock recommendations of the report released immediately previous to the current report for the same recommendation. An upgraded (or downgraded) revision within the same recommendation category is associated with a greater (lower) stock price return. Even the same recommendation in the market may cause different reactions depending on both the recommendation itself and on the direction of change of the recommendation. Affiliated analysts have more access to inside information of the companies they analyze. The stock returns after revisions of Chaebol-affiliated analysts are significantly higher than those of non-Chaebol-affiliated analysts.

Understanding Rankings of Financial Analysts

The prediction of the most accurate analysts is typically modeled in terms of individual analyst characteristics. This approach has the disadvantage that these data are hard to collect and often unreliable. We follow a different approach in which we characterize the general behavior of rankings of analysts based upon state variables rather than individual analyst characteristics or past accuracy. We use a common learning algorithm, naive Bayes, that we adapted to address the problem of ranking the analysts. Our results show that it is possible to model the relation between the selected variables and the rankings. We show that the uncertainty about future stock performance influences the rankings of the analysts while the macroeconomic variables have the most contribution to the changes in rankings.

Corporate Governance and the Informational Efficiency of Prices

We explore the relation between corporate governance and the informational efficiency of prices (IEP). We find that IEP increases with the quality of corporate governance in a large cross‐section of firms. We show that firms with better governance structures file Form 8‐K reports more promptly and have more accurate analysts’ earnings forecasts, suggesting that corporate voluntary disclosures and analyst forecasts are channels through which corporate governance affects IEP. The positive relation between IEP and governance quality cannot be attributed to reverse causality or other confounding factors (e.g., analyst following, stock market liquidity, and institutional ownership). On the whole, our results show that better governance structures lead to higher IEP by improving the speed and extent of corporate information disclosures.

Retraction: Is Analyst Forecast Accuracy Associated With Accounting Information Use?

In 1994, the AICPA?s Special Committee on Financial Reporting recommended that participants in business reporting can improve the reporting process by focusing on user needs and finding cost-effective ways of aligning business reports with those needs. The Committee noted that professional financial analysts are among the most important users of business reporting and that an examination of their accounting information needs would provide useful insight to the profession. Further, the Committee suggested that an investigation of the link between information usage and decision quality could provide a starting point for determining whether currently reported business information is relevant. The current study examines the relation between the forecast accuracy of financial analysts and specific accounting information items used during financial statement analysis. Findings indicate that relatively more accurate analysts tend to emphasize different information items prior to issuing an earnings forecast than do less accurate analysts. Study results also provide evidence of an association between specific accounting information items and decision quality.