Market Institutions,Fair Value,and Financial Analyst Forecast Accuracy

This study investigates the valuation usefulness of fair values and related information disclosure in China and examines how regional-level market institutions influence the valuation usefulness of fair value information. Based on a sample of Chinese listed companies during 2007 to 2016, the empirical results show a negative association between overall fair values and analyst forecast accuracy. Further analyses suggest that the negative association is likely driven by biases and/or errors in fair value estimates. Using a difference-in-difference research design, the study also documents that the implementation of ASBE 39 in 2014 has improved the valuation usefulness of fair values. There is evidence that different aspects of market institutions—including the extent of government intervention in the market and the legal environment—influence analysts’ use of fair value information. This study contributes to the literature by providing new and different evidence on the usefulness of fair values to financial analysts outside developed countries. Moreover, by taking advantage of the uneven institutional development across China, the study shows that different aspects of market institutions influence the valuation usefulness of fair value information.     

Analyst Forecast Accuracy and Media Independence

Using a large international sample of 47,307 firm‐years from 52 countries, we investigate the impact of media independence on the forecast quality of financial analysts. We find that analyst forecast errors are positively associated with the extent of a country's state media ownership and its lack of freedom of the press. We also find that financial analysts with more inaccurate forecasts disappear from the institutional broker's estimate system more quickly in countries with more independent media.     

Analyst Following and Forecast Accuracy After Mandated IFRS Adoptions

This study investigates how accounting harmonization affects one particular group of financial statement users—financial analysts. We find that mandatory International Financial Reporting Standards (IFRS) adoption attracts foreign analysts, particularly those from countries that are simultaneously adopting IFRS along with the covered firm's country and those with prior IFRS experience. We also find that mandatory IFRS adoption improves foreign analysts’ forecast accuracy. The change in analyst following increases with the distance between prior local Generally Accepted Accounting Principles (GAAP) and IFRS and with the extent to which IFRS adoption eliminates GAAP differences between the firm's country and the analyst's country. IFRS adoption also attracts more local analysts, particularly those with prior IFRS experience and with an international portfolio prior to mandated IFRS adoption in their home country. Local analysts’ forecast accuracy is not affected by IFRS adoption. Overall, our results suggest that accounting harmonization brings comparability benefits that enhance the usefulness of accounting data.     

ESG Controversies,ESG Disclosure and Analyst Forecast Accuracy

We investigate whether an environmental social governance (ESG) disclosure moderates the relation between ESG controversies and analyst forecast accuracy. The previous literature has shown that ESG controversies increase uncertainty about a firm's future prospects, while ESG disclosure decreases this uncertainty. We therefore take the next step and integrate ESG controversies, ESG disclosure and uncertainty into one model. Our study is based on 8,369 firm-year observations across 51 countries from 2008 to 2017, containing data from RepRisk, Bloomberg and the Institutional Brokers' Estimate System. We find that analyst forecast errors are generally higher for firms with higher exposure to ESG controversies. More importantly, we establish ESG disclosure as a moderator that mitigates the strength of the relation between ESG controversies and analyst forecast errors. Additionally, we identify that the most important pillar for the relation derives from social controversies and disclosure.     

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.     

On the Structure of Analyst Research Portfolios and Forecast Accuracy

This study provides insights into the forces and constraints that shape analyst research coverage along country and sector dimensions and the impact of the structure of an analyst's portfolio on forecast accuracy. We find that analyst specialization by country and sector is sensitive to the extent to which firms  within  a country or sector and firms  across  country-sectors are exposed to common economic forces, the potential for revenue generation, and broker culture. Our tests indicate that existing research on the relation between analyst portfolio structure and forecast accuracy may suffer from an endogeneity bias. We use our analysis of analyst specialization to develop controls for this bias. Once we employ these controls, we find that country diversification is associated with superior forecast accuracy. However, the relation between sector diversification and forecast accuracy is context-specific. Specifically, sector diversification enhances forecast accuracy in an international context, while it detracts from forecast accuracy in a domestic U.S. context.     

Analyst Firm Coverage and Forecast Accuracy: The Effect of Regulation Fair Disclosure

In this study, we revisit the relationship between analyst firm coverage and forecast accuracy. In contrast to the proposed negative association in Clement (1999) owing to the portfolio complexity effect, we hypothesize an ‘economy‐of‐scale effect’ that is likely to dominate when analysts rely mostly on public information. In support of the latter effect, we find a positive association between firm coverage and forecast accuracy after the enactment of Regulation Fair Disclosure (Reg FD), which substantially reduces the flow of material private information to analysts. Such a result survives a battery of robustness analyses. We further show that, in the post‐Reg FD period, covering more firms increases an analyst's probability of being selected as a star analyst in the subsequent year. Overall, our findings highlight the importance of the information environment in shaping the economic link between an analyst's firm coverage and forecast accuracy.     

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.     

非财务信息披露与分析师预测——基于深市上市企业社会责任报告的实证检验

以深市上市企业披露的社会责任报告作为非财务信息的替代变量,实证检验了非财务信息披露质量与分析师盈利预测的关系。多元回归分析结果表明,企业社会责任报告披露质量越好,其分析师盈利预测越精确,并且在财务透明度低的企业中,这种正向关系更显著。这说明社会责任报告披露的这类非财务信息对分析师预测不仅具有信息含量,而且能够通过对财务信息的补充作用,缓解财务不透明对分析师预测精度的不利后果。     

证券分析师VS统计模型:证券分析师盈余预测的相对准确性及其决定因素

本文使用2005年35家券商对我国上市公司做出的每股盈余预测数据,考察了证券分析师盈余预测相对于统计模型的相对准确性及其决定因素。我们发现,我国证券分析师做出的盈余预测,同以年度历史数据为基础的统计模型得出的盈余预测相比,预测误差较小,证券分析师盈余预测具有一定的优势;但同某些以季度历史数据为基础的统计模型得出的盈余预测相比,预测误差较大,证券分析师盈余预测不具有优势。我们同时考察了决定证券分析师盈余预测相对准确性的决定因素。我们发现,公司每股盈余的波动性越大,公司上市越晚,跟踪公司的分析师越多,证券分析师的优势就越大。我们的研究对证券分析师以及投资者都有一定的启示作用。     

Analyst Earnings Forecast Revisions and the Pricing of Accruals

We investigate the relation between two market anomalies to provide insights into analysts role as information intermediaries. Prior research finds that accruals and analyst earnings forecast revisions predict future returns. We find that the accrual and forecast revision strategies generate hedge returns of 15.5% and 5.5% when implemented independently. Strikingly, a combined strategy that uses forecast revisions to refine the accrual strategy generates a hedge return of 28.5%. Firms with consistent accrual and forecast revision signals have less persistent accruals and earnings. We also find that accruals can be used to refine the forecast revision strategy—high accruals are associated with overoptimism in analyst forecasts. Our findings indicate that although forecast revisions reflect information about accrual and earnings persistence beyond that reflected in the level of current year accruals, investors do not fully incorporate this information into their valuation assessments.     

The Inefficiency of the Mean Analyst Forecast as a Summary Forecast of Earnings

We show analytically that mean analyst forecasts inefficiently aggregate information by assigning too much weight to analysts' common information relative to their private information when used as a summary forecast measure of forthcoming earnings. A more precise summary forecast of earnings than the current mean forecast is the current mean forecast plus a positive multiple of the change in the mean forecast.     

Predictability in Financial Analyst Forecast Errors: Learning or Irrationality?

In this paper, we propose a rational learning‐based explanation for the predictability in financial analysts' earnings forecast errors documented in prior literature. In particular, we argue that the serial correlation pattern in analysts' quarterly earnings forecast errors is consistent with an environment in which analysts face parameter uncertainty and learn rationally about the parameters over time. Using simulations and real data, we show that the predictability evidence is more consistent with rational learning than with irrationality (fixation on a seasonal random walk model or some other dogmatic belief).     

Analyst Activity and Firm Value: Evidence from the REIT Sector

This paper is the first to examine (1) properties of analyst forecasts and (2) effects of analyst following on firm value for all REITs on CRSP, Compustat and I/B/E/S. Our results suggest that REITs operate in an information environment that has changed over time. We find that for periods when the REIT industry was either in the developmental stage (pre-1992), or after other structural changes in the industry (post-2000), more analysts cover REITs and forecasts are more accurate and less biased. Further, we find that mortgage REITs are more transparent than other REIT structures and exhibit properties of analyst behavior that are different from other types of REITs. Our investigation into the effect of analyst coverage on REIT value suggests that analyst coverage increases REIT value (as measured by Tobin’s q) and that the causality does not run the opposite way.

Analyst Forecasting Ability and the Stock Price Reaction to Forecast Revisions

We empirically identifysuperior analysts using their past forecasting track record fora specific firm's earnings and demonstrate that subsequent forecastannouncements by these superior analysts have a greater impacton security prices than do the forecasts of other analysts. Wefind that, in our sample, the price effects of this firm-specificforecasting ability do not spill over to other firms followedby the same analyst. We also demonstrate that an analyst's forecastingability with respect to the earnings of a certain firm is relativelymore important in the period immediately preceding an earningsannouncement by that firm.     

“Big Bang” Accounting Reforms in Japan: Financial Analyst Earnings Forecast Accuracy Declines as the Japanese Government Mandates Japanese Corporations to Adopt International Accounting Standards

The mandated adoption of International Accounting Standards (IAS) for Japanese corporations did not result in improved earnings that forecast predictability. These findings contradict the research findings of Ashbaugh and Pincus (2001). Herrmann, Inoue, and Thomas’ (2003) research findings support the need for mandating the adoption of IAS. They found that Japanese managers were “manipulating” reported earnings by managing the sale of fixed assets and marketable securities. Adoption of IAS decreases the availability of this practice and it was and is expected to increase disclosure and transparency. Increased disclosure and transparency are expected to decrease financial analyst forecast errors, which did not decrease for 139 firms examined in this study for the timeframe of 1999–2002. This research finding does not support the idea that adoption of IAS improves financial information used in decision making relative to forecasting earnings. Assuming that increased predictability indicates higher quality reported earnings and enhanced usefulness of financial information, the mandated adoption of IAS did not result in these. Assuming that adoption of IAS in Japan increased the level of transparency and disclosure by Japanese firms, which made it harder for Japanese firms to manage their earnings in order to meet the managerial earnings forecasts that these firms must make. Thus, after the adoption of IAS in Japan, forecast errors for managerial forecasts of earnings increased. This evidence is new to the literature.     

Financial Analysts' Forecast Accuracy and Dispersion: High-Tech versus Low-Tech Stocks

This study focuses on systematic differences in security analysts' forecast accuracy and dispersion between high- and low-tech firms. In line with the recent development in theoretical models and empirical findings, it posits that security analysts' unsigned forecast error and forecast dispersion are expected to differ between high-tech and low-tech firms. The results of this study provide evidence of lower unsigned error and dispersion for high-tech firms vis-à-vis low-tech firms. The higher forecast accuracy and forecast convergence for high-tech firms relative to low-tech firms in financial analysts' forecasts of earnings can be attributed to the information effect prevailing over the noise effect. Given the lack of empirical studies that compare analysts' forecast accuracy and dispersion between high-tech and low-tech sectors, the results of this paper provide a fresh basis for assessing how market participants vary in their treatment of New Economy stocks and factors that affect such decisions. In the light of the fact that the 1990s is a period characterized by the start of the Information Revolution through the Internet, the results of this study shed light on the usefulness of examining factors that differentiate between high-tech firms (New Economy stocks) and low-tech firms (Old Economy stocks) in financial analysts' forecasting earnings.     

Budget Forecast Deviations in Municipal Governments: Determinants and Implications

This paper analyses the determinants of municipalities’ budget forecast quality, showing opportunistic behaviour influenced by the electoral cycle. Incumbents overestimate revenue to spend more and underestimate expenditure in the quest for popularity and electoral support. Our results suggest that the budget forecast procedure should be made transparent and externally audited or monitored.     

Does Meeting Earnings Expectations Matter? Evidence from Analyst Forecast Revisions and Share Prices

This paper investigates whether the market rewards firms meeting current period earnings expectations, and whether any such reward reflects the implications of meeting expectations in the current period for future earnings or reflects a distinct market premium. We document that abnormal annual returns are significantly greater for firms meeting expectations, controlling for the information in the current year's earnings. We then test whether firms meeting expectations experience higher returns simply because their expected future earnings are also higher. We find firms meeting expectations have significantly higher earnings forecasts and realized earnings than firms that do not. We find that controlling for these higher future earnings, firms meeting expectations in one or two years do not receive a greater valuation than their fundamentals would suggest. We find, however, that the market assigns a higher value to firms that meet expectations consistently, controlling for an estimate of the firm's fundamental value.