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.     

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.     

When does analyst reputation matter? Evidence from analysts’ reliance on management guidance

We investigate the joint effects of analyst reputation, uncertainty and guidance news valence on analysts’ reliance on management guidance. We find that, compared to less reputable analysts, reputable analysts rely less on guidance when they issue earnings forecasts. This analyst reputation effect is stronger when earnings and information uncertainty are higher or when the guidance contains good news. Further analysis suggests that both reputable and less reputable analysts sacrifice their forecast accuracy when they rely less on guidance; however, reputable analysts are compensated to a greater extent by the increased informativeness of their forecasts. Finally, we find that analysts’ future career advancement is enhanced when their reliance is low.     

The Effect of Issuing Biased Earnings Forecasts on Analysts' Access to Management and Survival

This study offers evidence on the earnings forecast bias analysts use to please firm management and the associated benefits they obtain from issuing such biased forecasts in the years prior to Regulation Fair Disclosure. Analysts who issue initial optimistic earnings forecasts followed by pessimistic earnings forecasts before the earnings announcement produce more accurate earnings forecasts and are less likely to be fired by their employers. The effect of such biased earnings forecasts on forecast accuracy and firing is stronger for analysts who follow firms with heavy insider selling and hard‐to‐predict earnings. The above results hold regardless of whether a brokerage firm has investment banking business or not. These results are consistent with the hypothesis that analysts use biased earnings forecasts to curry favor with firm management in order to obtain better access to management's private information.     

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.     

The Impact of AASB 8 Operating Segments on Analysts’ Earnings Forecasts: Australian Evidence

This paper evaluates the impact of firms’ adoption of AASB 8 segment disclosure rules on analysts’ earnings forecasts. It examines whether providing more disaggregated segment information following the adoption of AASB 8 is associated with an increase in analysts’ ability to forecast earnings. We find that analysts’ earnings forecasts have not improved significantly after adopting AASB 8 in Australia, regardless of whether firms disclosed more disaggregated segment information. Our use of control firms provides assurance that the results are due to AASB 8 and not to some other events concurrent with the adoption of AASB 8. Overall, our results imply that the benefits associated with the management approach as experienced by financial analysts in the United States have not been realised by financial analysts in Australia. This suggests that the successful adoption of an accounting standard in one country should not be the justification for recommending adoption in other countries. Further, our results raise questions about whether the enhanced disclosures required in the new standard are more for the other users of financial statements, such as investors, rather than analysts.     

Market implied future earnings and analysts’ forecasts

This study provides evidence on market implied future earnings based on the residual income valuation (RIV) framework and compares these earnings with analyst earnings forecasts for accuracy (absolute forecast error) and bias (signed forecast error). Prior research shows that current stock price reflects future earnings and that analyst forecasts are biased. Thus, how price-based imputed forecasts compare with analyst forecasts is interesting. Using different cost of capital estimates, we use the price-earnings relation and impute firms’ future annual earnings from three residual income (RI) models for up to 5 years. Relative to I/B/E/S analyst forecasts, imputed forecasts from the RI models are less or no more biased when cost of capital is low (equal to a risk-free rate or slightly higher). Analysts slightly outperform these RI models in terms of accuracy for immediate future (1 or 2) years in the forecast horizon but the opposite is true for more distant future years when cost of capital is low. A regression analysis shows that, in explaining future earnings changes, analyst forecasts relative to imputed forecasts do not impound a significant amount of earnings information embedded in current price. In additional tests, we impute future long-term earnings growth rates and find that they are more accurate and less biased than I/B/E/S analyst long-term earnings growth forecasts. Together, the results suggest that the RIV framework can be used to impute a firm’s future earnings that are high in accuracy and low in bias, especially for distant future years.     

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 Analysts Disclose Cash Flow Forecasts with Earnings Estimates when Earnings Quality is Low?

Cash flows are incrementally useful to earnings in security valuation mainly when earnings quality is low. This suggests that when earnings quality decreases, analysts will be more likely to supplement their earnings forecasts with cash flow estimates. Contrary to this prediction, we find that analysts do not disclose cash flow forecasts when the quality of earnings is low. This is because cash flow forecast accuracy depends on the accuracy of the accrual estimates and the precision of accrual forecasts decreases for firms with low quality earnings. Consequently, as earnings quality decreases, cash flow forecasts become increasingly inaccurate compared to earnings estimates. Cash flow estimates that lack reliability are not useful to investors and, consequently, unlikely to be reported by analysts. This result provides an explanation for why analysts are less likely to report cash flow estimates when earnings quality is low.     

Market timing using strategists’ and analysts’ forecasts of S&P 500 earnings per share

This paper examines the bias in and usefulness of top-down and bottom-up consensus forecasts of earnings per share for the S&P 500 Index provided by market strategists and analysts to I/B/E/S. These forecasts exhibit a significant optimism bias that decreases over the 12 months up to release of actual earnings per share. The bias is significantly more pronounced for the bottom-up forecasts of analysts. Unlike the findings for country timing, we demonstrate that a stock market timer using switching rules based on the consensus forecasts of S&P 500 earnings or the directional switch in the consensus or in the number of switchers cannot generate a free lunch.     

Analyst forecast,accounting conservatism and the related valuation implications

This study investigates whether financial analysts incorporate accounting conservatism into their earnings forecasts and whether it is more difficult for them to forecast earnings for less conservative firms, and then examines the impact of the findings on the return predictability of the value‐to‐price (V/P) ratio. After controlling for the other factors affecting forecast accuracy, such as earnings predictability and information uncertainty, I find that analysts incorporate accounting conservatism into their earnings forecasts and that forecasting earnings is more difficult for less conservative firms. Consequently, the return predictability of the V/P ratio is stronger for more conservative firms, and previously reported return predictability of the V/P ratio is an average across firms with differing levels of conservatism.     

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.     

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 joint information role of analysts’ cash flow and earnings forecasts

We study whether the relative magnitudes of analysts’ cash flow and earnings forecasts convey information about the persistence and value relevance of reported earnings. We find that reported earnings are likely to be more (less) persistent and value relevant when analysts forecast relatively moderate (extreme) levels of operating cash flows, relative to earnings. We also find that the market’s response to a given earnings surprise is the strongest for moderate levels of cash flow forecasts relative to earnings. The joint information role of analysts’ cash flow and earnings forecasts persists even after controlling for the absolute accruals in the model.     

Analysts' Rationality and Forecast Bias: Evidence from Sales Forecasts

When optimistic forecasts can improve access to management, rational analysts have incentives to issue optimistically-biased forecasts (Lim, 2001). This paper proposes that the extent of this optimistic forecast bias will depend on the forecast's importance to management. If management attaches less importance to a forecasted measure, analysts should decrease their forecast bias because the expected benefits of issuing optimistic forecasts are less. We examine analysts' earnings and sales forecasts, and predict that analysts' optimistic bias will be greater for earnings than for sales. Results are consistent with our predictions and contribute to the evidence that analysts' forecast bias is rational and intentional.     

CEO happiness and forecasting

We utilize the IBM Watson Tone Analyzer to measure chief executive officers' (CEOs') levels of joy (happiness) in year-end conference calls, and empirically test how CEOs' happiness affects the properties of their own and analysts' forecasts. We find that joyful CEOs are more likely to issue forecasts, less likely to miss their forecast targets, and exhibit lower optimistic bias in their forecasts. When joyful CEOs issue earnings forecasts, analysts revise their forecasts upwards and produce forecasts that are less dispersed and more accurate. Our results demonstrate that inherent CEO happiness significantly impacts the forecast properties of both managers and analysts, thus supporting upper echelons theory.     

Are more able managers good future tellers? Learning from Japan

Baik et al. (2011) find that high-ability managers in the U.S. are more likely to issue accurate management earnings forecasts. Focusing on Japan, where management earnings forecasts are effectively mandated, we extend the literature by exploring (1) whether the relationship between managerial ability and forecast accuracy is unique to the U.S. disclosure system, where management forecasts are voluntary, and (2) how high-ability managers increase their forecast accuracy. We find that managerial ability is negatively associated with forecast errors based on initial forecasts, suggesting that high-ability managers are more likely to issue accurate forecasts at the beginning of the fiscal year. We then show that high-ability managers are less likely to revise their initial earnings forecasts and less likely to use earnings management to improve the accuracy of their earnings forecasts. Our findings show that, while high-ability managers are more likely to issue accurate initial management forecasts, low-ability managers are more likely to revise their forecasts and conduct earnings management to reduce their forecast errors.     

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.     

The characteristics of individual analysts’ forecasts in Europe

This study investigates the determinants of financial analysts’ forecasts differential accuracy in 14 different European stock markets. Using the I/B/E/S Detail History Database, I find that European financial analysts forecast accuracy is positively associated with analyst firm specific experience. Forecast accuracy is negatively associated with the number of countries followed by analysts and the age of the forecast. Surprisingly, I find no relationship between forecast accuracy and analysts’ job experience and the size of the bank employing the analyst.     

Analyst revenue forecast reporting and the quality of revenues and expenses

We decompose earnings quality into revenue and expense quality and examine their associations with analyst propensity to supplement their earnings forecasts with revenue forecasts. Analysts report more revenue forecasts to I/B/E/S when expense quality is low to compensate for the low accuracy of their earnings estimates, which has a positive association with expense quality. Expense quality is unassociated with revenue forecast accuracy, thus revenue forecasts become increasingly useful for valuing firms when expense quality is low. Analysts report fewer revenue forecasts when revenue quality is low because both earnings and revenue forecast accuracy decline as revenue quality deteriorates. To control for endogeneity, we use firm‐fixed effects to control for unobserved time‐invariant heterogeneity across firms, instrumental variables regressions and regression in changes.