Earnings Forecast Accuracy Research Articles

Government affiliation, analyst behavior and the economic consequences

AbstractA significant number of regional brokerage firms in China are owned by their respective local governments. We use this context to examine how local government affiliation affects brokerage firms’ research activities. Using a sample of analyst reports from 2013 to 2021, we find that analysts working at local government‐affiliated brokerage firms are more likely to cover firms within the local government's jurisdiction than non‐affiliated analysts. Local government‐affiliated analysts enjoy an information advantage, as evidenced by the issuance of more accurate earnings forecasts for local firms, compared to those of non‐affiliated analysts. The effect is stronger for local firms with lower information quality. Additionally, local government‐affiliated analysts show more optimism in stock recommendations, but not in earnings forecasts, for local firms, compared to non‐affiliated analysts. The effect is more pronounced for local firms that receive more local government subsidies, operate in regions with greater local government intervention or during the COVID‐19 pandemic and the National Congress conferences, and require more capital market support. The results of this study advance our understanding of the key determinants of analyst performance and provide new evidence in the debate on the role of government intervention in financial institutions.

The Use and Usefulness of Big Data in Finance: Evidence from Financial Analysts

Alternative data have become a new source of information for investors. This paper examines how this development is reshaping the role of sell-side analysts. Employing textual analysis of analysts’ written reports, we show that analysts themselves have begun to adopt alternative data in their analyses. Furthermore, we find that when analysts report drawing from alternative data they generate more accurate earnings forecasts, and their brokerages subsequently receive higher amounts in trading commissions from investors, suggesting that investors value the adoption of alternative data by analysts. This paper was accepted by Kay Gieseke, finance. Funding: This research is supported by NTU-Singapore under its startup grant program. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.02659 .

Examining the impact of market uncertainty on earnings forecasts: an empirical study from Egypt

PurposeThis paper aims to conduct a comparative analysis of the impact of market uncertainty on the degree of accuracy and bias of analysts' earnings forecasts versus four model-based earnings forecasts.Design/methodology/approachThe study employs panel regression analysis on a sample of Egyptian listed companies from 2005 to 2022 to examine the impact of market uncertainty on the accuracy and bias of each type of earnings forecast.FindingsThe empirical analysis reveals that market uncertainty significantly affects analysts’ earnings forecast accuracy and bias, while model-based earnings forecasts are less affected. Furthermore, the Earnings Persistence and Residual Income model-based earnings were found to be superior in terms of exhibiting the least susceptibility to the impact of market uncertainty on their forecast accuracy and biasness levels, respectively.Practical implicationsThe findings have important implications for stakeholders within the financial realm, including investors, financial analysts, corporate executives and portfolio managers. They emphasize the importance of considering market uncertainty when formulating earnings forecasts, while concurrently highlighting the potential benefits of using alternative forecasting methods.Originality/valueTo our knowledge, the influence of market uncertainty on analysts' earnings forecast accuracy and bias in the MENA region, particularly in the Egyptian market, remains unexplored in existing research. Additionally, this paper contributes to the existing literature by pinpointing the forecasting method, specifically distinguishing between analysts-based and model-based approaches, whose predictive quality is less adversely impacted by market uncertainty in an emerging market.

Do Financial Analysts See through the Cloud of Carbon Emissions?

SYNOPSIS Carbon risk management plays a crucial role in global environmental development, increasing the demand from environmentally conscious investors and stakeholders for carbon disclosure and control. In parallel with the U.S. Securities and Exchange Commission’s (SEC) release of climate rules in 2024 for enhanced carbon disclosure, this study investigates the effect of voluntary carbon disclosure on analyst forecast accuracy. Using a sample of S&P 500 firms from 2009 to 2020, we find that high-quality carbon disclosure and performance is positively associated with earnings forecast accuracy. Superior disclosures reduce firm-level uncertainties and result in more accurate forecasts. The positive effect is strong in firms that voluntarily disclose climate risks because analysts better comprehend the financial implications of firms’ integrated climate-control strategies. This study contributes to environmental, social, and governance (ESG) disclosure practices and offers implications through specific carbon disclosures. Our evidence supports the SEC in validating its move toward enhanced reporting guidelines. Data Availability: The data for this study are collected from subscription-based databases like Compustat-Capital IQ, I/B/E/S, and Bloomberg and manually from various publicly available sources identified. JEL Classifications: C36; G32; M14; M41; M48; Q51.

ESG performance and analyst recommendations: evidence from sustainability analysts in the Chinese market

PurposeIn this study, we examine the influence of a firm’s environmental, social, and governance (ESG) performance on analysts’ stock recommendations and earnings forecast accuracy in the Chinese context.Design/methodology/approachWe take a textual analysis approach to analyst research reports issued between 2010 and 2019, and differentiate between two distinct analyst categories: “sustainability analysts,” which refer to those more inclined to incorporate ESG information into their analyses, and “other analysts.”FindingsOur evidence indicates that sustainability analysts tend to be significantly more likely than others to provide positive stock recommendations and demonstrate enhanced accuracy in forecasting earnings for companies with superior ESG performance. Our additional analyses reveal that this finding is particularly prominent for analysts who graduated from institutions emphasizing the protection of the environment, those recognized as star analysts, those affiliated with ESG-oriented brokerages, and forecasts made by analysts in the later part of the sample period. Our findings further indicate that sustainability analysts exhibit a more pronounced negative response when confronted with a negative ESG event.Originality/valueIn general, the evidence from this study reveals the interplay between ESG factors and analyst behavior, offering valuable implications for both financial analysts and sustainable investment strategies.

Functional Background Diversity of Top Management Team and Managerial Forecasting Capability

ABSTRACT This study examines whether top management team (TMT) functional background diversity affects managerial forecasting capability. We find that TMTs with more diverse functional backgrounds issue more accurate earnings forecasts. Additional tests reveal that the negative association between TMT functional background diversity and management forecast errors becomes weaker when TMTs work together for a long time, when subgroups are more likely to develop within the team, when CEOs are more powerful, and when team size is larger. By contrast, the reduction in management forecast errors is more significant for functionally diverse TMTs when forecasting difficulty is higher. These findings suggest that TMT functional background diversity plays an important role in managerial forecasting capability. Data Availability: Data are available from the sources cited in the text. JEL Classifications: M14; M41.

Environmental, Social, and Governance Committees and Information Technology Outcomes

ABSTRACT With the recent increase in demand for environmental, social, and governance (ESG) reporting, more companies are creating board-level ESG committees to oversee progress in these areas. Companies are also becoming more aware of the important role that information technology (IT) can play in achieving ESG reporting goals. I argue that an improvement in ESG factors goes hand in hand with an improvement in IT. Specifically, I predict that companies with ESG committees will also benefit through an improvement in IT outcomes. Using a sample of companies from 2004 to 2022 I investigate two direct and two indirect IT outcomes. I find that environmentally and socially focused committees are negatively associated with both IT-related material weaknesses in internal controls and cybersecurity breaches. Further, companies with governance committees report fewer breaches and issue more accurate earnings forecasts. Conversely, I find that firms with environmental and social committees take longer to announce earnings. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: G30; M40; O32.

Confucian culture and analysts' earnings forecast accuracy

This article's findings reveal that Confucian culture enhances the precision of analysts' earnings forecasts. Tests for heterogeneity demonstrate that in private enterprises and more marketized samples, Confucian culture's governance impact is more significant. This study offers empirical support for the notion that Confucian culture serves as a vital external oversight mechanism for businesses.

Do analysts play a monitoring role? Evidence from exogenous changes in litigation risk

AbstractThis paper examines whether securities litigation and sell‐side equity analysts play a substitutive versus complementary role as an external governance mechanism. We expect the 1999 ruling on the stricter interpretation of the Private Securities Litigation Reform Act to make it easier for firms headquartered in the Ninth Circuit to defend against securities class actions filed by shareholders, resulting in weaker protection from a litigation channel and stronger demand for analyst activity. Using a difference‐in‐differences research design, we find that analyst coverage increases as litigation risk decreases in the Ninth Circuit firms. Moreover, we find that analyst earnings forecast accuracy increases for firms in the Ninth Circuit following the ruling, consistent with analysts exerting greater efforts to perform their monitoring role. In cross‐sectional tests, we find that the substitution relation between litigation risk and analyst research is more pronounced in firms with a high level of ex‐ante litigation risk. We conduct extensive robustness tests, including another legal event exogenously increasing the risk of litigation, to gain confidence in our interpretations. We contribute to the literature by documenting causal evidence that analysts have greater incentives to provide meaningful equity research as gatekeepers in times of weaker investor protection by securities litigation.

Sustainable development goals disclosure and analyst forecast quality

PurposeThis study aims to investigate the relationship between corporate sustainable development goals (SDGs) disclosure and analyst forecast quality.Design/methodology/approachThe study focuses on a sample of 95 Italian-listed companies preparing the mandatory non-financial declaration (NFD) according to the Global Reporting Initiative (GRI) standards over a five-year period (2017–2021), corresponding to an unbalanced sample of 438 observations. Analyst forecast quality was proxied by earnings forecast accuracy (FA) and earnings forecast dispersion (FD), built on data retrieved from the Refinitiv database. A manual content analysis was performed on NFDs to derive an SDG disclosure score (SDGD) for each sampled company.FindingsThis study provides empirical evidence suggesting that voluntary SDG disclosure matters to the capital market in that it helps enhance the information environment of companies, evidenced by improved analyst forecast quality. In particular, this study highlighted that SDG disclosure positively influences analyst FA while negatively affecting analyst FD.Research limitations/implicationsThis study focuses on the Italian context, which has idiosyncratic characteristics regarding the structure of the financial market, the composition of corporate ownership and experience in non-financial reporting practices.Practical implicationsThis study indicates to corporate managers that following GRI standards may represent the right way to better integrate SDG disclosure in corporate non-financial reports and increase the relevance of such information for investors and other capital market participants.Originality/valueTo the best of the authors’ knowledge, this is the first study that empirically examines the association between SDG disclosure and analyst forecast quality.

Lead Independent Directors and Internal Information Environment

ABSTRACTResearch Question/IssueThis study explores the relationship between the presence of a lead independent director (LID) and firms' internal information environment. LIDs are elected independent members of the board who perform key duties for the independent directors and the board, including reviewing and approving board meeting agendas, chairing non‐executive board meetings, and acting as a liaison between the CEO and other independent directors. We hypothesize that LID presence lowers information barriers between the CEO and the rest of the board members, enabling more rapid information acquisition and integration and enhancing the internal information environment of the firm.Research Findings/InsightsUsing a sample of US publicly listed companies from 2001 to 2019, we document that LID presence on the board is positively associated with proxies of internal information quality that reflect better information acquisition and information integration: accuracy and precision of management earnings forecasts, speed of earnings announcement, and absence of material weaknesses in internal controls. These results are robust to alternative model specifications, including entropy balancing, Heckman two‐step correction for self‐selection bias, firm fixed effects, and placebo tests. Further analyses suggest that LIDs with financial expertise and audit committee memberships are more effective in positively influencing internal information quality. We also show that LID presence is positively associated with several proxies of external information quality.Theoretical/Academic ImplicationsWe build on agency theory to argue that LIDs improve internal information quality by reinforcing the information quality benefits of unified leadership while mitigating potential compromises in information quality arising from entrenchment. Similarly, we use arguments emanating from the novel strategic leadership systems theory to posit that a LID appointment facilitates the tasks of the CEO and the board, enhancing the effectiveness of both groups in their respective roles: the CEO in making operating and investment decisions and the board in strengthening oversight while bringing cohesion in their shared role of strategy visioning and implementation.Practitioner/Policy ImplicationsOur findings suggest that there is scope for shareholders to consider LID appointments as an addition to their firms' corporate governance structures to enhance the internal information environment and decision‐making efficiency. Policymakers can also encourage LID appointments on the board when promoting best practices in corporate governance through regulatory guidelines.

Stock market liberalization and management earnings forecasts: Evidence from a quasi‐experiment in China

AbstractThis study examines the impact of Chinese stock market liberalization on the quality of firms' information disclosures. Although previous studies have explored the economic outcomes of stock market liberalization, little is known about its impact on the quality of management earnings forecasts. We treat China's Stock Connect program as a quasi‐experiment and draw data from Chinese A‐share‐listed companies from 2012 to 2017. Using a staggered difference‐in‐difference model, we find that eligible firms issue more accurate earnings forecasts after implementation of the Connect program compared with ineligible firms. Our mechanism analyses show that the positive effect is more pronounced for firms with initially opaque information environment and higher ex ante agency costs, suggesting that market liberalization facilitates higher‐opaque firms to issue more accurate earnings forecasts to meet the information demand from foreign investors, and facilitates monitoring in firms with weak internal governance, thereby improving earnings forecasts quality.

It is a small world: The effect of analyst-media school ties on analyst performance

We examine the effect of school ties between sell-side analysts and media executives on the improvement in analysts' performance during the release of informative negative news. Our baseline results and mechanism tests show that analysts obtain fragmented private information to improve their earnings forecast accuracy by taking advantage of the school ties with financial media executives. To establish causality, we perform several identification strategies, such as entropy balancing matching, cross-sectional analyses during university anniversary gatherings, and a placebo test. Further, we find that analysts with less herding behaviors benefit more from the school tie effect. Besides, we reveal that connected analysts are more likely to issue reports in a timely manner after the release of informative negative news, and these revisions in earnings forecast elicit significantly positive market reactions. At the same time, we notice that the media are more likely to interview alumni-affiliated analysts, providing potential evidence of an informational interaction between financial analysts and the media.

Can local fintech development improve analysts’ earnings forecast accuracy? Evidence from China

This paper examines the impact of local fintech development on the accuracy of analysts’ earnings forecasts. We employ the method of web text mining to construct the local fintech development index for empirical test. Our findings indicate that local fintech development has a substantial positive impact on analysts’ earnings forecast accuracy by promoting firm digital transformation and alleviating the information asymmetry between firms and outsiders. Additionally, this effect is particularly pronounced for analysts without equity pledge affiliation and those with weaker buy-side pressure. This study shows that local fintech development can enhance the information environment of the capital market.

Information aggregation to form earnings expectations: Evidence from CEO networks and management forecast accuracy

AbstractWe investigate whether a larger CEO employment network provides access to information that improves firms' earnings forecasts and find a significantly positive relation between CEO employment network size and management earnings forecast accuracy. Our results suggest that firms use information obtained from CEO contacts to increase the accuracy of their earnings forecasts. Our conclusion is further supported by evidence of positive associations between CEO employment network size and the likelihood, frequency, and precision of management earnings forecasts. We also find that CEO employment network size is positively related to analysts' reactions to the forecast news and the accuracy of management earnings forecasts relative to analyst forecasts. Overall, our results are consistent with a larger CEO employment network generating external information that increases the accuracy of firms' earnings forecasts.

Forward-Looking Sustainability Information and Financial Analysts

ABSTRACT This paper empirically examines the relationship between forward-looking environmental and social information in sustainability reports (FLSI) and financial analysts’ forecast accuracy. To provide contextual insights, we conduct semistructured interviews with financial analysts. We find that FLSI quantity, measured by FLSI words and scope, and FLSI quality, measured by the precision, horizon, and direction of the environmental or social forecast, are associated with greater earnings forecast accuracy for short-horizon forecasts. Specifically, the precision and direction of FLSI affect analysts’ short- and midhorizon forecasts. Our results hold only for environmental FLSI and FLSI in externally assured sustainability reports. However, the results indicate that the provision of economic information in sustainability reports does not affect analyst forecasts. Collectively, our findings carry far-reaching implications for practitioners and—in particular—regulators around the world by shedding light on the potential costs and benefits of the new European Corporate Sustainability Reporting Directive (CSRD). Data Availability: Data are available from the public sources cited in the text. JEL Classifications: M40; M41.

Institutional ownership and analysts’ earnings forecasts

This paper selects the data of China's A-share market from 2011 to 2022 to explore the impact of institutional shareholding on analysts’ earnings forecasts. The findings indicate the following: institutional shareholding enhances analysts’ earnings forecast accuracy and reduces analysts’ forecast optimism bias; institutions with small geodesic pits will be more helpful for analysts to improve the quality of earnings forecasts; and institutional shareholding improves the quality of analysts’ earnings forecasts by promoting the quality of firms’ information disclosure.

Earnings Forecast Accuracy and Implied Cost of Capital Portfolio Returns

Earnings Forecast Accuracy and Implied Cost of Capital Portfolio Returns

The information externality of paid analysts

ABSTRACT Using a hand-collected dataset of paid analysts and their earnings forecasts, this study examines the role of paid analysts in capital markets. Paid analysts tend to make more accurate earnings forecasts for the industry counterparts of their paying companies, compared with their non-industry counterparts after they are paid for providing forecasting services. The positive effect of appointing a paid analyst on earnings forecast accuracy for non-paying companies in the same industry (relative to those not in the same industry) is stronger when the paying companies have a weaker information environment and for analysts who have less industry-specific knowledge. Together, the findings of this study support the conjecture that having access to the private information of paying companies creates a positive information externality that enhances paid analysts’ earnings forecasting performance for non-paying companies.

Do climate risk disclosures matter to financial analysts?

AbstractThis paper examines whether and when corporate disclosures about a firm's exposure to climate risks matter to financial analysts. More specifically, we investigate the association between climate risk disclosure (CRD) and two properties of financial analysts’ earnings forecasts (accuracy and dispersion). We predict that climate risk financial materiality at the industry level moderates this association. Using a sample of 2184 US nonfinancial firm‐year observations over the period 2010–2016, we show that CRD is associated with higher forecast precision and lower dispersion only when climate risks are perceived by investors as being financially material at the industry level. We also find that while corporate disclosures about transition risks are not associated with financial analyst forecast properties, 10‐K disclosures about climate‐related material physical risks reduce analyst forecast error and dispersion.