Accuracy Of Analysts Research Articles

Non-financial information farsightedness and capital market information efficiency

Non-financial information disclosed by firms is an important channel for investors and analysts to understand the operating conditions of firms and a major source of information other than financial data. This study examines the impact of disclosure of forward-looking non-financial information content by listed companies on the information efficiency of the capital market. Using data from A-share listed companies in China’s Shanghai and Shenzhen markets from 2007 to 2022, it is found that forward-looking non-financial information content has a positive impact on improving capital market information efficiency, while analysts’ attention plays a moderating role. The mechanism study finds that non-financial information disclosure with forward-looking content affects the accuracy of analysts’ earnings forecasts, the type of audit opinion, and the degree of financialisation of firms, which in turn have different impacts on the information efficiency of the capital market. The heterogeneity test finds that disclosure of non-financial information with forward-looking content will more significantly improve the information efficiency of the capital market if the listed company receives a high level of media attention, as well as listed companies with higher quality of internal control. This study explores the forward-looking characteristics of non-financial information in depth, enriches the study of information efficiency in the capital market, and provides theoretical suggestions for the content and direction of corporate non-financial information disclosure.

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.

Common institutional ownership and analyst earnings forecasts

This research investigates the impact of shared institutional ownership on the accuracy of analysts' predictions. Drawing from theoretical frameworks, we have formulated and empirically tested our research hypotheses. The results indicate a negative correlation between shared institutional ownership and the precision of analysts' forecasts. Additionally, peer pressure has been found to mediate this relationship. Furthermore, ownership type has been identified as an intermediary factor, with state-owned enterprises exhibiting a more significant negative effect.

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.

Enterprise digital transformation's impact on stock liquidity: A corporate governance perspective.

The innovation in technology and economic growth, which are brought about by digital transformation in enterprises, will inevitably impact their performance in the capital market. Using a sample of Chinese A-share listed companies from 2012 to 2021, this study extensively examines the impact, mechanism, and economic consequences of enterprises digital transformation on stock liquidity. The research reveals that enterprises digital transformation can significantly improve stock liquidity. From the perspective of corporate governance, a further analysis indicates that the digital transformation of enterprises can improve stock liquidity by three mechanisms: easing financing constraints, improving the quality of internal control, and enhancing information disclosure. The results of the heterogeneity analysis indicate that the digital transformation of enterprises, combined with a high level of financial technology, developed financial markets, and policy guidance, has a significantly more significant effect on improving stock liquidity. The analysis of economic consequences reveals that the digital transformation of enterprises can lower the risk of a stock price crash and enhance the accuracy of analysts' forecasts, primarily by improving stock liquidity. This study offers empirical evidence from a micro-mechanism perspective that elucidates the spillover effect of enterprise digital transformation on the capital market. It provides insight into the impact of enterprise digital transformation on stock liquidity and offers theoretical guidance to promote the adoption of enterprise digital transformation across different countries and enhance stock liquidity in the capital market.

Seeing is believing: are investors’ corporate online visits as informative as site visits?

ABSTRACT This paper examines the post-visit earnings forecast inaccuracy of online visits (visits via videoconferencing) relative to site visits (visits to production or operation sites) with data from China between 2020 and 2021. We use the number of confirmed COVID-19 infections in the city where analysts’ offices are located as an instrument for the choices between online visits and site visits. Our results show that online visits fail to maintain the accuracy of analysts’ EPS forecasts. Moreover, the diminished financial reporting quality of firms amplifies the forecasting disadvantages associated with online visits. Finally, the lack of site observation rather than one-on-one communication is the primary reason for the underperformance of online visits.

The Impact of IFRS Adoption on the Accuracy of Analysts' Forecasts in the Saudi Stock Exchange

The Impact of IFRS Adoption on the Accuracy of Analysts' Forecasts in the Saudi Stock Exchange

Influência da agressividade tributária na previsão dos analistas financeiros

ABSTRACT Purpose: This paper aims to verify whether the management of taxable income through aggressive tax practices negatively impacts the accuracy of market analysts’ forecasts. Originality/value: The central contribution of this study is to relate tax aggressiveness with more significant errors in analysts’ forecasts. Thus, the relevance of this paper is in showing that this practice can lead to a greater perception of companies’ risks and more significant informational asymmetry, in addition to influencing stock prices and resulting in lower analyst accuracy. Design/methodology/approach: This research paper was developed from regression models with panel data with random effects, also using estimators based on instrumental variables with the application of Jensen’s test to verify the validity of the generalized method of moments (GMM) estimation. The data were treated with the winsorization technique at the 1% level. Findings: A sample of companies listed on the B3 between 2010 and 2017 (with a total of 2,805 valid observations) showed that companies with higher tax aggressiveness are subject to a higher analyst forecast error. Thus, it is inferred that, for more aggressive companies, the degree of analyst predictability decreases. With this drop in the quality of analysts’ forecasts, the users of their forecasts and reports are more vulnerable to informational asymmetry.

Assessing physical fit examinations of stabbed and torn textiles through a large dataset of casework-like items and interlaboratory studies.

Several organizations have outlined the need for standardized methods for conducting physical fit comparisons. This study answers this call by developing and evaluating a systematic and transparent approach for examining, documenting, and interpreting textile physical fits, using qualitative feature descriptors and a quantitative metric (Edge Similarity Score, ESS) for the physical fit examination of textile materials. Here, the results from 1027 textile physical fit comparisons are reported. This includes the evaluation of inter and intraanalyst variation when using this method for hand-torn and stabbed fabrics. ESS higher than 80% and ESS lower than 20%, respectively, support fit and nonfit conclusions. The results show that analyst accuracy ranges from 88% to 100% when using this criterion. The estimated false-positive rate for this dataset (2% false positives, 10 of 477 true nonfit pairs) demonstrates the importance of assessing the quality of a physical fit during an examination and reveals that potential errors are low, but possible in textile physical fit examinations. The risk of error must be accounted for in the interpretation and verification processes. Further analysis shows that factors such as the separation method, construction, and design of the samples do not substantially influence the ESS values. Additionally, the proposed method is independently evaluated by 15 practitioners in an interlaboratory exercise that demonstrates satisfactory reproducibility between participants. The standardized terminology and documentation criteria are the first steps toward validating approaches to streamline the peer review process, minimize bias and subjectivity, and convey the probative value of the evidence.

The Role of Digital Accounting in Improving the Quality of Financial Reporting Information and Its Impact on the Accuracy of Financial Analysts’ Predictions: A Field Study

The main objective of the research is to study the role of digital accounting in improving the quality of financial reporting information and its impact on the accuracy of financial analysts’ forecasts in the Egyptian business environment. This ultimately leads to enhancing the relevance, reliability, consistency, comparability, and understandability of the accounting information contained in financial reports, which positively affects the accuracy of financial analysts’ predictions. Consequently, it stimulates investment activities in the Egyptian stock market, increases trading volume, and contributes to the achievement of Egypt’s Vision 2030. The research was based on a field study, and data was collected through survey questionnaires. The research sample consisted of (85) individuals, including internal auditors and accountants working in companies listed on the Egyptian Stock Exchange. The study also provided several recommendations, the most important of which is the necessity of adopting digital accounting in companies as one of the requirements of the digital age and the digital economy, so that they can meet the requirements for digital transformation and the establishment of a digital Egypt. Companies should also focus on providing the necessary technologies to implement digital accounting. Keywords: Digital Accounting, Quality of Financial Reporting Information, Accuracy of Financial Analysts’ Forecasts

CEO Narcissism and Properties of Analysts’ Forecasts

SYNOPSIS Using a sample of S&P 500 companies, this study constructs a measure of CEO narcissism and examines whether and how it impacts the accuracy and dispersion of analysts’ forecasts. Empirical evidence suggests that firms with narcissistic CEOs have higher accuracy and lower dispersion of such forecasts. In investigating the mechanism through which CEO narcissism impacts these properties, we find that firms with narcissistic CEOs are more likely to issue management earnings guidance, albeit less accurate, which results in significant differences in accuracy and dispersion of analysts’ forecasts. This study concludes that through more management voluntary disclosure, CEO narcissism has a positive impact on the accuracy and a negative impact on the dispersion of financial analysts’ forecasts. Although several studies have explored the effect of CEO narcissism on corporate financial reporting, this is the first study to expand such inquiry into the sector of financial analysts. JEL Classifications: G17; M12; M41.

The Impact of Corporate Political Connections on Analyst Forecast Quality

Abstract The purpose of this study is to investigate whether the companies have significant impact of political connections on analyst forecasts quality. Refer to the literature on relevant analyst information in the past, especially distinguish the information obtained by analysts into public information and private information, and check whether it will affect the quality of analysts’ forecast information. Our empirical results show that there is a significant negative correlation between companies with political ties and the accuracy of analysts' public information. It indicates that when companies have political connections, companies are only willing to disclose information to specific stakeholders, resulting in information asymmetry. Meanwhile, the accuracy of public information obtained by analysts is relatively low, while the accuracy of private information is relatively high for the companies with political connections. JEL classification numbers: G30, M41. Keywords: Political Connections, Analyst Forecast Quality.

Analyst workload and information production: Evidence from IPO assignments

AbstractI examine how changes in analysts' workloads affect their information production. Examining determinants of analysts' information production is important because analyst research affects stock prices and capital allocation decisions. Using periods when analysts work on IPOs to proxy for shocks to their workloads, I predict and find that the accuracy, quantity, and timeliness of analysts' forecasts for non‐IPO firms decline when they are working on IPOs, and they herd closer to the consensus. The reductions in research quality are larger for less experienced analysts, larger IPOs, and less important portfolio firms. Last, I predict and find that information asymmetry increases for non‐IPO firms covered by analysts who are working on IPOs, consistent with analysts' reduction in research quality during IPO assignments negatively affecting the information environment of non‐IPO firms. In sum, I provide the first evidence that analysts' work on IPO deals imposes negative externalities on both the quality of research they produce for the non‐IPO firms they cover and the information environments of these firms, highlighting at least one reason why analyst workload is important to firms and investors.

Analysis of the relationship between temporal and behavioral aspects of the analyst's forecasting accuracy

The study analyzed the relationship between optimism, anchoring, overconfidence, representativeness, realism, commonality and time, with the accuracy in the profit forecast of analysts. Publicly traded Brazilian companies were considered in 2019, and correlation tests, mean differences and multiple regression analyses were applied. The results indicated that accuracy is negatively influenced by optimism and positively by anchoring and commonality. In addition, the uncertainty present in the distance between the forecast issued and the disclosure of earnings per share also negatively influences the accuracy of analysts. Additionally, it was found that fair value, profitability, issuing ADRs and self-regulated sector, are aspects related to greater accuracy. Thus, the research contributes to the literature by linking behavioral and temporal aspects to financial ones, as well as by signaling the importance of analysts' forecasting models to consider behavioral aspects in their information technologies.

Public attention and analyst visits: Evidence from China

This paper investigates the impact of public attention on analyst visits. To establish causality, we use Hurun Rich List as an exogenous shock to identify the impact of public attention. Using a difference-in-difference approach, we find that public attention significantly enhances the number of analyst visits. This effect is more pronounced among firms with complex information environments and higher future uncertainty. Our findings indicate that public attention affects analyst visits through influencing investor demand for analyst services. Further analysis reveals that analyst visits improve the accuracy of analysts' forecasts. We also find that the rich listing events indirectly leads to policy changes or the introduction of new policies. Overall, our findings highlight the importance of public attention to the firms' information environment.

Targeted poverty alleviation disclosure and analyst forecast accuracy: Evidence from a quasi-natural experiment

Using the Targeted Poverty Alleviation (TPA) disclosure policy in China as a quasi-natural experiment, this paper analyzes the impact of firm TPA disclosure on analyst forecast accuracy based on a staggered difference-in-differences model. The results show a significant increase in the accuracy of analysts’ forecasts after firms’ disclosure of TPA information, and this effect is more pronounced for firms with greater information processing cost and firms with fewer covering analysts. Our study provides empirical evidence for regulators concerned with the information environment of capital market.

Managerial Strategic Earnings Disclosure via Social Media: Evidence from 18 Million Corporate Tweets

Using a broad sample of earnings announcement tweets (EATs) constructed from 18 million corporate tweets, we document that there exists a substitute relationship between EATs and management earnings forecasts (MEFs). EATs reduce the use and improve the accuracy of MEFs and analysts’ forecast for contemporaneous and subsequent quarters. Such improvement is more pronounced in the presence of negative earnings news. Furthermore, firms with EATs are associated with higher profitability, better information environment, and lower liquidity. Using textual analysis, we show that firms with positive tone of EATs are more likely to have positive earnings surprise. Overall, our findings provide novel evidence on the significant association between corporate Twitter activities and managers’ strategic disclosure as well as firms’ information environment and future performance.

Accuracy of EPS Forecasts of Security Analysts: Taking PROYA as an Example

With the development of security analyst industry, its importance is becoming more prominent. However, the development of security analysts in China is relatively late, and there is still a gap between their forecasting accuracy and that of developed countries in the capital market which have accumulated much experience. Therefore, the accuracy of domestic analysts' forecasting is worth considering. At the same time, in China, cosmetics industry has become one of the few consumer industries to accelerate growth in recent years, and has become the focus of more and more investors. This paper examines the accuracy of PROYA's forecasts by calculating the accuracy of 72 analysts from 28 securities firms' forecasts from 2018 to 2021. The results suggest that investors can gain more accurate information through the latest reports of long-following analyst.

투자자 관심이 재무분석가의 이익예측에 미치는 영향

[Purpose] This study examines whether there is an association between investor attention and analyst’s forecast.
 [Methodology] This study was conducted by using Google searching volume index of Korea listed firms over the period from 2011 to 2017.
 [Findings] The main findings as follow. First we find that the higher investor attention, the more significantly accuracy of analyst’s earnings forecast. Generally, analysts tend to respond in response to investors’ information needs, a higher investor attention in a particular entity also increases the information demand, which can be interpreted that analysts have incentives to provide more accurate earnings forecast to investors to maintain their reputation and compensation. Second, the higher investor attention, the less variance the analyst’s forecast error. This can be interred that as investor attention increases, analysts are tend to modify to the capital market’s consensus.
 [Implications] Nowadays, despite of a growing number of study on the effect of investor attention in various fields, it is largely unexplored in accounting literature. This study extends to the literature by relating investor attention to analyst behavior such as earnings forecast.

The Effect of Brokerage Firm Size on Analysts’ Earnings Forecast Accuracy: Evidence from the Culture Media Industry

The factors influencing analysts’ earnings forecast accuracy are a popular research topic today. Some researchers have found that brokerage firm size affects analysts’ earnings forecast accuracy. However, there is a research gap in the effect of brokerage firm size on analysts’ earnings forecast accuracy in a particular industry. As a result, this study investigates the link between brokerage company size and analysts’ earnings prediction accuracy by collecting and comparing analysts’ earnings forecast data from major brokerage companies and analysts’ earnings forecast data from small and medium-sized brokerage firms. It is found that the accuracy of analysts’ earnings forecasts for the culture media industry is positively correlated with the size of brokerage firms. This indicates that analysts at large brokerage firms have a higher accuracy of earnings forecasts for the culture media industry.