Additional Evidence on Analysts’ Decision to Issue Disaggregated Earnings Forecasts: Strategic Biasing

This study examines why analysts issue disaggregated earnings forecasts to I/B/E/S. Some recent studies suggest that analysts with superior forecasting ability issue disaggregated earnings forecasts to build reputation in the marketplace and stop forecast disaggregation once their reputation has been established. Based on an analysis of I/B/E/S forecast data for U.S. firms from 1998 to 2008, we find that, in a given year, about 20%–34% of analysts disaggregate for some, but not for all the firms that they follow. This evidence of selective disaggregation by analysts suggests that reputation building alone does not fully explain the decision to disaggregate forecasts. We hypothesize that the decision to disaggregate earnings forecasts is at the firm‐level as well and is systematically related to the analysts’ bias in the issued forecasts. Our findings are that (a) analysts’ overall optimistic bias and forecast errors decrease monotonically with the level of forecast disaggregation, and (b) analysts that selectively disaggregate their forecasts for some firms or who do not persistently disaggregate a given firm's forecasts exhibit more positive bias and larger forecast errors. Our findings are consistent with the notion that the analysts who issue biased forecasts, for example, to curry favour with the management, are less likely to provide disaggregated information as part of the forecast.     

Further evidence on analyst and investor misweighting of prior period cash flows and accruals

We empirically investigate three questions: (i) whether analysts and investors mis-estimate the persistence of operating cash flows, (ii) if so, is the cash flow effect distinct from the accrual effect in the sense that one effect holds after controlling for the other, and (iii) if these are distinct effects, which effect is stronger in magnitude? We find that prior period operating cash flows have a significant positive effect on forecast errors and stock returns consistent with analysts and investors underestimating the persistence of operating cash flows. Further, we find that not only is the operating cash flow effect distinct from the accrual (more specifically the working capital accrual) effect but it is also considerably larger in magnitude. To our knowledge, this is the first study that documents the relative magnitude of prior period cash flow and working capital accrual effects on forecast errors and stock returns. Our findings have several implications for future research and practice. First, the consistency of results across the two sets of users (analysts and investors) suggests that analyst-forecast inefficiencies are less likely to be driven by their incentives to promote stocks and more likely to be a manifestation of a broader phenomenon that has not been thoroughly investigated in prior studies. Second, for practitioners, our results suggest that a trading strategy based on prior period working capital accruals and cash flows would earn higher abnormal returns than a trading strategy based on accruals alone.     

Stock index adjustments and analysts’ forecast optimism: A quasi-natural experiment on the CSI 300 Index

As stock index adjustments comprise a basic system of capital market, their potential influence on analysts’ earnings forecasts is worthy of research. Based on a research sample of 23 adjustments to the CSI 300 Index from June 2007 to June 2018 and the backup stocks announced during the same period, this study examines the impact of additions to stock index on analysts’ forecast optimism using a staggered difference-in-differences model. The research results show that after stocks are added to the stock index, analysts’ earnings forecast optimism about these stocks increases significantly. Cross-sectional analysis indicates that this increase is more significant when the market is bullish, institutional ownership is low, the ratio of listed brokerage firms is low, star analyst coverage is low, firms show seasoned equity offering activity, the ratio of analysts from the top five brokerage firms ranked by commission income is high, and the analysts’ brokerage firms are shareholders. However, analyst-level tests find that analysts’ ability helps to reduce the impact of additions to stock index on earnings forecast optimism. Furthermore, additions to stock index significantly increase analyst coverage and forecast divergence. Economic consequences tests find additions to stock index significantly increases stock price synchronization, which is partly mediated by analysts’ earnings forecast optimism. This study enriches the literature on the impact of basic capital market systems and analyst behavior. The findings suggest that investors should rationally evaluate analysts’ earnings forecasts for stocks added to the stock index and obtain further information from various channels to improve asset allocation efficiency.     

Capitalized intangibles and financial analysts

We examine whether firms that capitalize a higher proportion of their underlying intangible assets have higher analyst following, lower dispersion of analysts’ earnings forecasts and more accurate earnings forecasts relative to firms that capitalize a lower proportion. Under Australian generally accepted accounting principles, capitalization of intangible assets has become increasingly ‘routine’ since the late 1980s. It is predicted that this experience leads Australian analysts to expect firms with relatively more certain intangible investments to signal this fact by capitalizing intangible assets. Our results are consistent with this. We find that capitalization of intangible assets is associated with higher analyst following and lower absolute earnings forecast error for firms with a stock of underlying intangible assets. Our tests suggest a weaker association between capitalization and lower earnings forecast dispersion. We conclude that there are benefits for analysts, for management to have the option to capitalize intangible assets. These findings suggest that IAS 38 Intangible Assets and AASB 138 Intangible Assets reduce the usefulness of financial statements.     

Learning and incentive: A study on analyst response to pension underfunding

There is a long-standing debate on whether sell-side analysts learn from their experience to improve earnings forecast skills. This study shows that incentive is an important factor for understanding the “learning by doing” effect by analysts. We examine analysts’ response to a complex type of information – corporate pension underfunding. Pension underfunding negatively impacts future earnings and analysts on average underreact to such information in their earnings forecasts. More importantly, when there is a strong incentive for analysts to deliver accurate forecasts, analyst learning effectively reduces their underreaction to pension underfunding information. On the other hand, when such an incentive is absent, the analyst learning effect is not discernible in the data. Further evidence suggests that analyst learning and incentive jointly reduce stock market mispricing associated with corporate pension underfunding.     

Information misweighting and the cross-section of stock recommendations

This paper provides evidence that analysts whose earnings forecast revisions showed signs of greater exaggeration in the past make recommendation changes that lead to lower abnormal returns than their peers. Interpreting stock recommendations as a forecast of future abnormal returns, I show that this evidence is consistent with the hypothesis that analysts who typically exaggerate or overstate the weight of their private information when issuing forecasts also do so when making recommendations. The paper also shows that past earnings forecasts provide incremental information about analysts' recommending behavior beyond that contained in past recommendations.     

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。     

Analysts' forecasts of Japanese firms' earnings: additional evidence

This article examines analysts' forecasts of Japanese firms' earnings during Japan's economic burst period in the 1990s. Using the evidence of analyst earnings forecasts in the United States as a benchmark, the article documents the following three findings. First, whereas the forecast accuracy of U.S. analysts following U.S. firms improves over time, the forecast accuracy of U.S. and Japanese analysts following Japanese firms does not. Second, whereas decreases in forecast errors of U.S. analysts following U.S. firms are best explained by decreases in forecast bias of the analysts, increases in forecast errors of U.S. and Japanese analysts following Japanese firms are best explained by increases in the frequency of losses experienced by Japanese firms. Third, Japanese analysts forecast earnings less accurately than do U.S. analysts. These findings reflect the difficulty of producing accurate earnings forecasts during economic downturns. They also suggest that Japanese analysts are more bound than their U.S. counterparts by cultural ties that impede forecast accuracy.     

Do investor expectations affect sell-side analysts’ forecast bias and forecast accuracy?

We examine the association between investor expectations and its components and sell-side analysts’ short-run quarterly earnings forecast bias and forecast accuracy. To measure investor expectations, we use the Index of Consumer Expectations survey and decompose it into the “fundamental” component related to underlying economic factors (FUND) and the “sentiment” component unrelated to underlying economic factors (SENT). We find that analysts are the most optimistic and the least accurate when SENT is higher. Management long-horizon earnings forecasts attenuate the effects of SENT on forecast optimism and forecast accuracy. Analysts are also the most accurate when FUND is higher. Last, the market places more weight on unexpected earnings when SENT is high. These findings suggest that analysts are affected by investor sentiment and the market reacts more strongly to unexpected earnings when analyst forecasts are the least accurate. The last result potentially explains why prior research (for example, Baker and Wurgler, The Journal of Finance 61:1645–1680, 2006) finds an association between investor sentiment and cross-sectional stock returns.     

Expectations and the Cross-Section of Stock Returns

Previous research has shown that stocks with low prices relative to book value, cash flow, earnings, or dividends (that is, value stocks) earn high returns. Value stocks may earn high returns because they are more risky. Alternatively, systematic errors in expectations may explain the high returns earned by value stocks. I test for the existence of systematic errors using survey data on forecasts by stock market analysts. I show that investment strategies that seek to exploit errors in analysts' forecasts earn superior returns because expectations about future growth in earnings are too extreme.     

Analysts’ Momentum Recommendations

We document that the likelihood of analyst recommendations following past stock returns decreased abruptly in 2003, coinciding with the Global Settlement and other regulatory changes designed to restrain analysts’ conflicts of interest. We also document that the likelihood of recommendations following past stock returns is abnormally high for recommendations issued after negative stock returns (but not for those issued after positive stock returns), among inexperienced and inaccurate analysts, among large brokerage houses, and for companies with high share turnover. Moreover, the recommendations that are more likely to follow past stock returns are accompanied by earnings forecast revisions that are larger in magnitude and less accurate ex post. Overall, our findings suggest that analysts with conflicts of interest and limited ability are more likely to base their recommendations on past stock returns. Finally, we document that the recommendations that are more likely to follow past stock returns (especially those that were issued before 2003 and those that are issued after negative stock returns) contribute to existing price momentum by generating incrementally stronger short‐term and long‐term stock returns.     

Analysts' forecasts as earnings expectations

I examine three composite analyst forecast of earnings per share as proxies for expected earnings. The most current forecast weakly dominates the mean and median forecasts in accuracy. This is evidence that forecast dates are more relevant for determining accuracy than individual error. Consistent with previous research, I find analysts more accurate than time-series models. However prior knowledge of forecast errors from a quarterly autoregressive model predicts excess stock returns better than prior knowledge of analysts' errors. This is inconsistent with previous research, and is anomalous given analysts' greater accuracy.     

On the relation between predictable market returns and predictable analyst forecast errors

We investigate the relation between predictable market returns and predictable analyst forecast errors. Perfect correlation between predictable components of forecast errors and abnormal returns would lend credence to the view that pricing anomalies are not merely an artifact of inadequately controlled risk. Our evidence implies an imperfect correlation. Moreover, we find that while the predictable component of abnormal returns is significantly associated with future forecast errors, trading strategies based directly on the predictable component of forecast errors are not profitable. Further implications of our findings are that predictable components of analysts’ forecast errors are robust with respect to loss functions and analysts’ earnings forecasts may significantly diverge from the market expectations.     

Disclosure of internal control material weaknesses and optimism in analyst earnings forecasts

This paper investigates how analyst forecast optimism is associated with disclosures of internal control material weaknesses (ICMWs) and their remediation under Section 404 of the Sarbanes–Oxley Act (SOX). Drawing on agency theory, I hypothesize that analysts are likely to issue earnings forecasts that are more optimistic for firms with ICMW disclosures than for those without ICMW disclosures. Using a sample of 20,875 firm-year observations with 10-K (10-Q) reports from 2004 to 2018, I find a positive association between ICMW disclosures and analyst forecast optimism. This positive association is partially driven by investors’ inability to unravel analyst forecast bias and analysts’ intentions to curry favor with management for private information. In addition, analysts are found to issue less optimistic forecasts for firms with ICMW remediation disclosures compared with those without ICMW remediation disclosures. A series of propensity score matching and regression analyses are conducted to test the robustness of my inferences. Overall, the paper suggests that analysts have incentives to take the opportunity of firms disclosing ICMWs to bias their forecasts upward for self-interest. The findings have the potential to assist regulators in guiding analyst behavior and educating investors to unravel positive bias in analyst forecasts.     

How efficient is the market for Australian firms’ earnings information?

We construct a measure of the speed with which forecasts issued by sell-side analysts accurately forecast future annual earnings. Following Marshall, we label this measure earnings information flow timeliness (EIFT). This measure avoids the aggregation problem inherent in price-based measures of information efficiency. We document large variation in EIFT across firm-years, and show that EIFT is positively associated with the extent of analyst following, consistent with increased analyst coverage improving the speed with which earnings-related information is recognised. We also find that EIFT is higher for firm-years classified as ‘bad news’ (i.e., where analysts’ forecasts at the start of the financial period exceed the reported outcome). However, when we separately consider instances where analysts appear to forecast non-GAAP (or ‘street’) earnings rather than GAAP earnings, we find that the greater timeliness of bad news is concentrated among observations where analysts forecast non-GAAP earnings, where unusual items are typically excluded. We conclude that the market for accounting information is more efficient for negative operating outcomes than for negative outcomes reflecting unusual items.     

Ownership structure and forecast accuracy in Spain

This article examines how analysts respond to specific ownership structure characteristics by studying the accuracy of their forecasts after the release of the first Spanish corporate governance code and before IFRS were adopted. Specifically, we analyse the influence of ownership concentration, bank ownership and insider ownership on analyst forecast errors. Overall the results show a positive and significant influence of bank ownership on analyst forecast accuracy, which suggests that bank ownership leads to closer monitoring of management and a reduction in analyst forecast errors. However, the presence of large shareholders and insiders in the ownership structure of the firm does not significantly affect the accuracy of financial analysts. This research provides investors with a more refined sense of how analyst forecasts might be affected through the composition of the ownership structure in a context of high concentration of ownership, relevant presence of banks in firms as creditors and shareholders, and local GAAP.     

Tests of Market Reaction and Analysts' Forecast Revisions to the Disclosure of Improved Management Earnings Expectations: A Case of Concurrent Bad News Management Earnings Forecasts

This paper tests whether a negative stock market reaction, associated with a management forecast of near term bad earnings, is lessened by a concurrent management forecast of improved longer term earnings expectations. Stock market reactions depend on the creditability of management forecasts of improved earnings expectations. In this analysis, the authors examined market reactions around the time of management forecasts of bad earnings, with and without longer-term management forecasts of improved earnings expectations. The results show that the stock market reaction is significantly less negative when management forecasts of bad earnings are followed by management forecasts of improved long run earnings expectations than when management forecasts of bad earnings are not accompanied by management forecasts of improved earnings expectations. In addition, this paper examines financial analysts' reactions to management bad earnings forecasts and management forecasts of improved earnings expectations. The findings show that analysts react less negatively to management forecasts of improved earnings expectations than to management forecasts of bad earnings. An analysis of a sub-sample of observations shows that analysts consider management forecasts of improved earnings expectations to imply improved expected future performance, thus conveying that analysts give credence to management forecasts of improved earnings expectations. However, results show that the stock market and analysts are unable to distinguish management forecasts of improved earnings expectations that come true from management forecasts of improved earning expectations that do not come true.     

Analyst reputation and management earnings forecasts

Prior studies show that analysts with high reputation are influential in the market. This paper examines whether managers consider analyst reputation in shaping their voluntary disclosure strategy. Using Institutional Investor magazine’s All-American (AA) rankings as a proxy for analyst reputation, we find that the coverage of AA analysts is positively associated with the likelihood of quarterly management earnings forecasts (MEFs). We also find that AA analysts’ forecast optimism is more positively associated with the likelihood of MEFs than non-AA analysts’ forecast optimism when the firm is covered by AA analysts. Analyses based on AA analyst coverage changes and AA status changes confirm the relation between analyst reputation and MEFs. We further find that analyst reputation influences other MEF properties, such as forecast news, bias, and revisions, and that our results are robust to alternative measures of analyst reputation. Further analyses show that market reactions at quarterly earnings announcements are more positive (negative) when firms meet/beat (miss) AA analysts’ forecasts than when firms meet/beat (miss) non-AA analysts’ forecasts. Collectively, our findings suggest that managers strategically provide voluntary forecasts by taking into account the reputation of individual analysts following their firms.     

Reputation and Performance Among Security Analysts

Members of the Institutional Investor All-American Research Team supply more accurate earnings forecasts than other analysts when forecasts are matched by the corporation followed and by the date of brokerage house issuance. This contemporaneous advantage is complemented by a timing advantage; All-Americans supply forecasts more often than other analysts. Stocks returns immediately following large upward forecast revisions suggest that All-Americans impact prices more than other analysts. However, there is virtually no difference in returns following large downward revisions. Nevertheless, the collective results suggest a positive relation between reputation and performance, and, assuming that All-Americans are better paid, pay and performance.     

Underwriting Relationships and Analyst Independence in Europe

This paper examines the accuracy of security analysts’ earnings forecasts and stock recommendations for firms in 13 European countries. We document at least three key findings. First, we find strong evidence that lead and co‐lead underwriter analysts’ earnings estimates and stock recommendations are significantly more optimistic than those provided by unaffiliated analysts. Second, we find that lead and co‐lead underwriter analysts’ earnings forecast and stock recommendations are significantly more optimistic for underwriter stocks than for those they provide for other stocks. Third, we also find evidence that these biases found within earnings forecasts and stock recommendations are not driven by one particular country. In short, these findings suggest that affiliated analysts are more optimistic perhaps to maintain investment banking relations.