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.     

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.     

Interlock Concentration and Analyst Forecast Accuracy: Value Implications of Interlock

From the perspective of information commonalities among firms with director interlock relationships, this study mainly investigates the outcomes of earnings forecasts by analysts who choose to concentrate on interlocked firms (analysts following both a firm and its interlocked partner firm in their research portfolio). Using interlocked A‐share firms listed in the Chinese Shanghai and Shenzhen Stock Exchanges from 2008 to 2013 as samples, we empirically find that analysts who concentrate on interlocked firms produce more accurate earnings forecasts than analysts who do not. In additional analysis, we also find that analysts with an interlock concentration provide superior earnings forecast quality for other non‐interlocked firms in their research portfolios. Finally, through examining the market reaction to interlocked firms, we find that analysts with an interlock concentration provide new information and improve information efficiency for the capital market.     

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.     

Do Managers Always Know Better? The Relative Accuracy of Management and Analyst Forecasts

We examine the relative accuracy of management and analyst forecasts of annual EPS. We predict and find that analysts’ information advantage resides at the macroeconomic level. They provide more accurate earnings forecasts than management when a firm's fortunes move in concert with macroeconomic factors such as Gross Domestic Product and energy costs. In contrast, we predict and find that management's information advantage resides at the firm level. Their forecasts are more accurate than analysts’ when management's actions, which affect reported earnings, are difficult to anticipate by outsiders, such as when the firm's inventories are abnormally high or the firm has excess capacity or is experiencing a loss. Although analysts are commonly viewed as industry specialists, we fail to find evidence that analysts have an information advantage over managers at the industry level. The two have comparable abilities to forecast earnings for firms with revenues or earnings that are more synchronous with their industries.     

IPO Underpricing, Firm Quality, and Analyst Forecasts

We find that IPO underpricing is positively related to post-IPO growth in sales and EBITDA, but is not significantly related to growth in earnings. Our evidence suggests that accrual reversals or earnings management may cause this inconsistency. We interpret the growth rates of sales and EBITDA as measures of firm quality, and conclude that our evidence supports the notion that IPO firms with greater underpricing are of better quality. Our tests on analysts' earnings forecast errors show that analysts are less positively biased in their earnings forecasts for IPO firms that have greater underpricing.     

What Drives Target Price Forecasts and Their Investment Value?

This paper examines the informativeness of analysts’ target price forecasts by relating the investment value of target prices to their primary drivers. Decomposing target price forecasts into near‐term earnings forecasts and price‐to‐earnings ratio forecasts, we show that target price revisions reflect information from both components. In addition, we also find that the relative importance of each component in target price revisions is related to firm characteristics. A portfolio based on target price implied expected returns delivers significant abnormal returns. More importantly, we find that the abnormal returns are associated with both earnings and price‐to‐earnings forecasts, which suggests that the informativeness of target price forecasts comes not only from analysts’ ability to forecast short‐term earnings but also from their ability to assess risk and long‐term growth prospect implied in price‐to‐earnings forecasts.     

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.     

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.     

The impact of SOX on opportunistic management behavior

An innovative aspect of this study is the use of a relatively new metric to capture opportunistic earnings management behavior. We define opportunistic earnings management as the difference between a firm's US-GAAP earnings and ex post earnings consensus derived from forecasts of financial analysts who follow that firm. Using over 24,500 quarterly reports of over 2,500 publicly-traded companies spanning two three-year periods, and controlling for factors previously linked to having an effect on earnings management and analysts forecast effort, we find statistical evidence supporting the proposition that, in the aggregate, the Sarbanes–Oxley Act (SOX) has served as a constraint on curbing opportunistic earnings management behavior, and thus should be considered as an effective means to improve the quality of financial reporting information.     

Who herds?

This paper develops a test for herding in forecasts by professional financial analysts that is robust to (a) correlated information amongst analysts; (b) common unforecasted industry-wide earnings shocks; (c) information arrival over the forecasting cycle; (d) the possibility that the earnings that analysts forecast differ from what the econometrician observes; and (e) systematic optimism or pessimism among analysts. We find that forecasts are biased, but that analysts do not herd. Instead, analysts “anti-herd”: Analysts systematically issue biased contrarian forecasts that overshoot the publicly-available consensus forecast in the direction of their private information.     

Serial Correlation in Management Earnings Forecast Errors

We examine whether management earnings forecast errors exhibit serial correlation and how analysts understand the serial correlation property of management forecast errors (MFEs). MFEs should not exhibit serial correlation if managers efficiently process information in prior forecast errors and truthfully convey their earnings expectations through management forecasts. However, for long‐horizon management forecasts of annual earnings, we find significantly positive serial correlation in MFEs, and sample self‐selection does not seem to drive this phenomenon. Further analyses suggest that managers’ unintentional information processing bias contributes to this positive serial correlation. Analysts anticipate the intertemporal persistence of MFEs but underestimate the persistence level when reacting to management forecasts. Our findings have implications for market participants who rely on management forecasts to form earnings expectations, and also shed light on the efficiency of managerial decision making.     

Analysts' Forecasts: Low-Balling,Market Efficiency,and Insider Trading

The phenomenon of low-balling reported in the financial press involves downward biased projections of earnings by managers or analysts, thereby artificially lowering market expectations and creating a positive earnings surprise when actual earnings are announced. This study reports that the stock market does respond to such surprises relative to analysts' reported forecasts. Further, the proportion of insider buy-transactions in the period prior to the earnings forecast is significantly higher for the sample with high positive earnings surprise than for the control sample with zero forecast errors. The study cannot distinguish whether managers or analysts are the source of the low-balling and therefore makes no statement on the legality of such insider trades.     

Regulation Fair Disclosure and analysts’ reliance on earnings announcements

Regulation Fair Disclosure prohibits corporations from selectively disclosing material information to groups of favored analysts and institutional investors. If information previously provided is excluded by the new regulation from analysts’ information set, it is plausible that the relative importance of the other information, such as earnings announcements, which remains could increase (Arya et al., 2005). The purpose of this study is to investigate whether analysts become more reliant on firm earnings announcements in revising their forecasts after implementation of the regulation. Our empirical results show that, after the regulation, more analysts issue forecasts immediately after earnings announcements. In addition, analysts’ earnings forecasts tend to converge more after observing earnings announcements in the post-regulation period. These results, in conjunction with the finding of higher overall level of forecast errors and dispersion, indicate that earnings announcements become more important information sources in the post regulation period. These findings suggest that analysts are more reliant on earnings announcements and there is an increase in analyst herding as a result of Regulation Fair Disclosure.     

The changing relationship between earnings expectations and earnings for value and growth stocks during Reg FD

Regulation Fair Disclosure (Reg FD) altered the voluntary disclosure practices of firms with publicly traded securities, thereby affecting relationships between value and growth stock expectations and actual earnings. The results show that earnings forecasts for both stock groups are biased but that bias is less after the introduction of Reg FD. In fact, the difference in pre/post FD forecast bias is larger for growth stocks, suggesting that before Reg FD, analysts did not just misinterpret news but consciously tried to maintain relationships with growth firm managers. However, Reg FD limited these relationships severing the monetary advantage that might be gained from manipulating forecasts.     

Rationality and Analysts' Forecast Bias

This paper proposes and tests a quadratic-loss utility function for modeling corporate earnings forecasting, where financial analysts trade off bias to improve management access and forecast accuracy. Optimal forecasts with minimum expected error are optimistically biased and exhibit predictable cross-sectional variation related to analyst and company characteristics. Empirical evidence from individual analyst forecasts is consistent with the model's predictions. These results suggest that positive and predictable bias may be a rational property of optimal earnings forecasts. Prior studies using classical notions of unbiasedness may have prematurely dismissed analysts' forecasts as being irrational or inaccurate.     

Management Forecast Consistency

We posit that management forecasts, which are predictable transformations of realized earnings without random errors, are more informative than unbiased forecasts, which manifest small but unpredictable errors, even if biased forecasts are less accurate. Consistent with this intuition, we find that managers who make consistent forecasting errors have a greater ability to influence investor reactions and analyst revisions, even after controlling for the effect of accuracy. This effect is more economically significant and statistically robust than that of forecast accuracy. More sophisticated investors and experienced analysts are found to have a better understanding of the benefits of consistent management forecasts.     

Forecasts in IPO Prospectuses: The Effect of Corporate Governance on Earnings Management

Prior research suggests that managers may use earnings management to meet voluntary earnings forecasts. We document the extent of earnings management undertaken within Canadian Initial Public Offerings (IPOs) and study the extent to which companies with better corporate governance systems are less likely to use earnings management to achieve their earnings forecasts. In addition, we test other factors that differentiate forecasting from non‐forecasting firms, and assess the impact of forecasting and corporate governance on future cash flow prediction. We find that firms with better corporate governance are less likely to include a voluntary earnings forecast in their IPO prospectus. In addition, we find that while IPO firms use accruals management to meet forecasts; the informativeness of the discretionary accruals depends on whether or not the firm would have missed its forecast without the use of discretionary accruals.     

The effect of Regulation FD on the properties of management earnings forecasts

We investigate Regulation FD’s (FD) effect on management earnings forecast properties. We posit FD’s prohibition on private manager-analyst communication reduces (increases) optimism (pessimism) in management earnings forecasts. Prior to FD, managers could avoid publicly retracting prior optimistic forecasts by privately communicating with analysts, who could lower investor expectations with a new analyst forecast. After FD, managers with optimistic forecasts must either publicly admit their optimism by issuing a new management forecast or they must negatively surprise investors at the earnings announcement. Further, FD forces managers to use public forecasts instead of private communications to establish beatable expectations. Our evidence suggests FD reduced optimism in management forecasts. This reduction in optimistic bias is not offset by an increase in pessimistic bias. Consistent with this, we further find post-FD improvements in forecast accuracy and informativeness. We find no such changes around several potentially confounding events or for foreign firms surrounding FD. Overall, our evidence suggests FD improved firms’ forecast properties (less bias, greater accuracy, and greater informativeness).