Do analysts who understand accounting conservatism exhibit better forecasting performance?

This study investigates the performance of analysts when they match the asymmetric timeliness of their earnings forecast revisions (i.e., asymmetric forecast timeliness) with the asymmetric timeliness of firms’ reported earnings (i.e., asymmetric earnings timeliness). We find that better timeliness‐matching analysts produce more accurate earnings forecasts and elicit stronger market reactions to their forecast revisions. Further, better timeliness‐matching analysts issue less biased earnings forecasts, more profitable stock recommendations and have more favorable career outcomes. Overall, our results indicate that analysts’ ability to incorporate conditional conservatism into their earnings forecasts is an important reflection of analyst expertise and professional success.     

Determinants of analysts’ revenue forecast accuracy

This study investigates financial analysts’ revenue forecasts and identifies determinants of the forecasts’ accuracy. We find that revenue forecast accuracy is determined by forecast and analyst characteristics similar to those of earnings forecast accuracy—namely, forecast horizon, days elapsed since the last forecast, analysts’ forecasting experience, forecast frequency, forecast portfolio, reputation, earnings forecast issuance, forecast boldness, and analysts’ prior performance in forecasting revenues and earnings. We develop a model that predicts the usefulness of revenue forecasts. Thereby, our study helps to ex ante identify more accurate revenue forecasts. Furthermore, we find that analysts concern themselves with their revenue forecasting performance. Analysts with poor revenue forecasting performance are more likely to stop forecasting revenues than analysts with better performance. Their decision is reasonable because revenue forecast accuracy affects analysts’ career prospects in terms of being promoted or terminated. Our study helps investors and academic researchers to understand determinants of revenue forecasts. This understanding is also beneficial for evaluating earnings forecasts because revenue forecasts reveal whether changes in earnings forecasts are due to anticipated changes in revenues or expenses.     

Political contributions and analyst behavior

We show that the personal traits of analysts, as revealed by their political donations, influence their forecasting behavior and stock prices. Analysts who contribute primarily to the Republican Party adopt a more conservative forecasting style. Their earnings forecast revisions are less likely to deviate from the forecasts of other analysts and are less likely to be bold. Their stock recommendations also contain more modest upgrades and downgrades. Overall, these analysts produce better quality research, which is recognized and rewarded by their employers, institutional investors, and the media. Stock market participants, however, do not fully recognize their superior ability as the market reaction following revisions by these analysts is weaker.     

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.     

Value relevance of analyst earnings forecasts in emerging markets

Even though research in accounting and finance has extensively examined the role of financial analysts in developed economies, this issue has not been thoroughly examined in an emerging market setting. In this paper, I examine whether, following a market opening, analyst forecast accuracy and the market's reliance on analyst forecasts increase with time. Accuracy is expected to increase over time as analysts exert more effort and gain valuable forecasting experience. Results indicate that time is positively related to analyst forecast accuracy after controlling for a number of other firm and country characteristics. Second, I posit that time should also be related to the market's propensity to use analyst forecasts to form earnings expectations. As markets open and investors become more sophisticated, the reliance on analyst forecasts should also increase. Results are consistent with this expectation. In particular, I find that in the first sub-period earnings expectations based on random walk exhibit greater relative information content than earnings expectations based on analyst forecasts. This pattern is reversed in the third sub-period where analyst forecast errors better explain returns. Incremental information content tests produce similar results. Future research should further investigate the relation between financial analysts and other important market characteristics in emerging economies.     

Evaluating the information content of earnings forecasts

This study develops a framework to compare the ability of alternative earnings forecast approaches to capture the market expectation of future earnings. Given prior evidence of analysts’ systematic optimistic bias, we decompose earnings surprises into analysts’ earnings surprises and adjustments based on alternative forecasting models. An equal market response to these two components indicates that the associated earnings forecast is a sufficient estimate of the market expectation of future earnings. To apply our framework, we examine four recent regression-based earnings forecasting models, alongside a simple earnings-based random walk model and analysts’ forecasts. Using the earnings forecasts of the model that satisfies our sufficiency condition, we identify a set of stocks for which the market is unduly pessimistic about future earnings. The investment strategy of buying and holding these stocks generates statistically signi?cant abnormal returns. We offer an explanation as to why this and similar strategies might be successful.     

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.     

Product market pricing power, industry concentration and analysts’ earnings forecasts

This is the first study to establish a link between product market power and analysts’ earnings forecast accuracy and bias. Relating two different dimensions of market power to earnings forecastability, we document that (a) a firm’s relative pricing power and (b) its industry concentration are strong positive determinants of analysts’ earnings forecast accuracy. We find that forecasting earnings of higher market power firms is less complex due to their ability to withstand cost shocks as well as greater informational-efficiency enjoyed by such firms. Further, forecast optimism increases with weakening product market pricing power and with lower industry concentration. The knowledge derived from this study will hopefully improve the accuracy of equity valuation, and thereby engender better buy-side (stock selections) and sell-side recommendations by analysts. Our analysis also suggests that brokerage firms compensating analysts based on forecast accuracy need to adjust for the differential in the information complexity of different industries.     

Understanding analysts' use of stock returns and other analysts' revisions when forecasting earnings

We investigate analysts' use of stock returns and other analysts' forecast revisions in revising their own forecasts after an earnings announcement. We find that analysts respond more strongly to these signals when the signals are more informative about future earnings changes. Although analysts underreact to these signals on average, we find that analysts who are most sensitive to signal informativeness achieve superior forecast accuracy relative to their peers and have a greater influence on the market. The results suggest that the ability to extract information from the actions of others serves as one source of analyst expertise.     

How do financial analysts interpret industrial firms' corporate refocusing announcements?

This study investigates how analysts perceive the effect of corporate refocusing announcements on UK industrial firms' future earnings by examining current-year and one-year-ahead earnings forecast revisions, current-year target price revisions and earnings forecast errors in the five years surrounding a refocusing announcement year. The results reveal that analysts adjust their earnings forecasts downward in a refocusing announcement year and the following two years, predicting that operating performance in the post-refocusing period is likely to decline relative to their former earnings forecasts. Secondly, there is no evidence that analysts issue biased earnings forecasts after refocusing announcements or that their forecasts appear less accurate. Thirdly, they adjust their earnings forecasts downward in a refocusing announcement year with downward market movement. However, they do not similarly adjust their earnings forecast upward with upward market movement. The magnitude of downward adjustments exceeds that of upward adjustments. They also adjust current-year target price forecasts downward with downward market movement in the year prior to a refocusing announcement.     

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.     

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.     

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.     

Analyst characteristics, timing of forecast revisions, and analyst forecasting ability

We first examine whether analysts with certain characteristics that prior research has identified are related to superior forecasting ability systematically time their forecast revisions later in the fiscal quarter. We then examine whether this superior ability persists after controlling for the timing advantage by using relative forecast error, a measure that largely eliminates the timing advantage of recent forecasts. Using a sample of quarterly earnings forecast revisions over the 20-year period from 1990 to 2009, we find that analysts with more firm-specific and general experience and more accurate prior-period forecasts, analysts employed by larger brokerage firms, and analysts who follow fewer industries and companies tend to revise forecasts later in the quarter. We also find that analyst characteristics that are positively correlated with revision timing are negatively related to relative forecast errors. These results are consistent with analyst characteristics being useful proxies for analyst forecasting ability and analysts with greater ability revising forecasts later in the quarter.     

Do Japanese Analysts Overreact or Underreact to Earnings Announcements?

Several recent studies have used U.S. analysts' forecasts to test for underreaction or overreaction to information in earnings announcements. These tests have provided mixed results. Evidence in Mendenhall (1991) is that analysts underreact. By contrast. results in De Bondt and Thaler (1990) show overreaction by U.S. financial analysts to earnings announcements. The current study contributes to this topic by examining over/underreaction by Japanese financial analysts. Test results show that Japanese analysts do not overreact to earnings announcements, market to book ratios and sales growth. Instead. there is strong evidence that Japanese analysts underreact to earnings announcements and that their underreaction is more pronounced for firms with mostly permanent earnings. Our results also show that Japanese analysts display larger forecast biases for earnings reported under U.S. GAAP as opposed to Japanese GAAP. Finally, we find that US. analysts discount information in earnings announcements to a larger degree (relying to a greater extent on information in past prices instead) when compared to their Japanese counterparts. Further, in contrast to their Japanese counterparts, these analysts display no optimistic bias. The results above suggest that the impact of each country's unique culture and capital norms will have to be taken into account by policy makers in evaluating the feasibility of harmonization of accounting standards.     

Effects of Preannouncements on Analyst and Stock Price Reactions to Earnings News

This study examines the effects of earnings preannouncements on financial analyst and stock price reactions to earnings news. Prior experimental research documents that when the signs of a preannouncement surprise and subsequent earnings announcement surprise are consistent (i.e., both either positive or negative), analysts make larger magnitude revisions to their future period earnings forecasts in response to the total earnings news conveyed in the preannouncement and earnings announcement than when the surprise signs are inconsistent. This study extends this research by examining a sample of actual preannouncements from 1993–1997 to determine whether the effects documented in laboratory settings manifest at the aggregate market level in stock prices and consensus analyst forecast revisions. Results indicate that after controlling for the sign of earnings news, sign of earnings, and sign of the earnings announcement surprise, stock prices and analyst forecast revisions respond more strongly when a preannouncement and subsequent earnings announcement elicit the same surprise signs than when the surprise signs are inconsistent. Further analysis indicates that the consistency of the signs of a preannouncement surprise and earnings announcement surprise is not associated with future earnings, suggesting that the magnified reaction of investors and analysts to consistent surprise signs is not a rational reaction to associations observed in market settings.     

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.     

Rationalizing forecast inefficiency

We show analysts’ own earnings forecasts predict error in their own forecasts of earnings at other horizons, which we argue provides a measure of the extent to which analysts inefficiently use information. We construct our measure by exploiting two sources of variation in analysts’ incentives: (i) more recent forecasts have greater salience at the time of the earnings release so accuracy incentives are higher (lower) at shorter (longer) forecast horizons and (ii) analysts have greater incentives for optimism (pessimism) at longer (shorter) horizons. Consistent with these incentives affecting the incorporation of information into forecasts, we document (i) current year forecasts underweight (overweight) information in shorter (longer) horizon forecasts and (ii) the mis-weighting is more pronounced when recent news is negative—when analysts have greater (weaker) incentives to incorporate the news into shorter (longer) horizon forecasts. Finally, returns tests suggest that forecasts adjusted for the inefficiency we document better represent market expectations of earnings.

     

Analyst underreaction and the post-forecast revision drift

The post-forecast revision drift (PFRD), the phenomenon of delayed stock price reactions to analyst forecast revisions, is a well-documented market anomaly. Prior research attributes PFRD to underreaction by investors to analyst forecast revisions. This study investigates the role of the analyst forecast revision process itself in the PFRD anomaly. Using a large sample of US firms, we confirm prior findings of a positive serial correlation (momentum) in individual analysts’ revisions to their earnings forecasts and, based on both indirect and direct tests, document a positive association between this momentum and PFRD. Further analyses reveal that both the forecast revision momentum and PFRD vary in similar ways with respect to the nature of the news driving the revisions and the information environment. Collectively, our findings show that underreaction by individual analysts in the forecast revision process is an important contributor to the PFRD phenomenon.     

公平信息披露与分析师预测精度——来自中国上市公司的经验证据

证券分析师是证券市场重要的信息加工者和传播者,他们的信息行为对中小投资者和市场效率有重要影响。本文基于2003~2009年分析师的年度盈利预测数据,运用面板计量模型实证检验了公平信息披露规则的实施对分析师预测精度的影响。研究结果表明:分析师预测精度在规则实施后显著下降了;而且,随着规则实施时间的推移,分析师预测精度进一步下降;另外,分析师对信息披露水平较差的上市公司的预测精度下降幅度更大。