Do analysts and investors fully understand the persistence of the items excluded from Street earnings?

Previous research has found that the items that are included in GAAP earnings but excluded from Street earnings to allow the firm to meet or beat analyst earnings forecasts (“MBF exclusions”) are more persistent than the other excluded items. In this study, I find that the difference in the levels of persistence between MBF and non-MBF exclusions declined after the introduction of Regulation G, which requires public companies that disclose non-GAAP earnings to also present GAAP earnings and a reconciliation of the two. Analysts underestimate the persistence of non-MBF exclusions, but the degree of this underestimation is lower in the post-regulation period. In contrast, there is little evidence to indicate that analysts underestimate the persistence of MBF exclusions in either time period. I also find strong (weak) evidence that investors underestimate the persistence of Street exclusions in the pre- (post-) regulation period. These results suggest that Regulation G constrains the practice of excluding recurring expenses from Street earnings to meet or beat analyst forecasts and helps analysts and investors to understand the persistence of Street exclusions.     

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.     

Measuring investors’ assessment of earnings persistence: do investors see through smoothed earnings?

Prior studies document that investors value persistent earnings more than transitory earnings. This argument offers incentives to managers to smooth their reported earnings and make them look more persistent. This study examines whether investors are misled by management’s income-smoothing behavior and whether they can correctly assess the persistence of smoothed earnings. Using a simple theoretical model, this paper shows that investors’ assessment of earnings persistence can be derived from their reactions to reported earnings, which is the ratio of the coefficient on earnings change relative to the coefficient on earnings level in the return–earnings relation. Empirical results show that investors’ assessment of earnings persistence is negatively associated with the level of income smoothing after controlling for time-series persistence of earnings and hence suggest that investors understand that the high persistence of smoothed earnings is not real and they discount the persistence of smoothed earnings when they react to such earnings news.     

Are analysts’ earnings forecasts more accurate when accompanied by cash flow forecasts?

We examine whether analysts’ earnings forecasts are more accurate when they also issue cash flow forecasts. We find that (i) analysts’ earnings forecasts issued together with cash flow forecasts are more accurate than those not accompanied by cash flow forecasts, and (ii) analysts’ earnings forecasts reflect a better understanding of the implications of current earnings for future earnings when they are accompanied by cash flow forecasts. These results are consistent with analysts adopting a more structured and disciplined approach to forecasting earnings when they also issue cash flow forecasts. Finally, we find that more accurate cash flow forecasts decrease the likelihood of analysts being fired, suggesting that cash flow forecast accuracy is relevant to analysts’ career outcomes.     

Does the cessation of quarterly earnings guidance reduce investors’ short-termism?

The practice of providing quarterly earnings guidance has been criticized for encouraging investors to fixate on short-term earnings and encouraging managerial myopia. Using data from the post–Regulation Fair Disclosure period, we examine whether the cessation of quarterly earnings guidance reduces short-termism among investors. We show that, after guidance cessation, investors in firms that stop quarterly guidance are composed of a larger (smaller) proportion of long-term (short-term) institutions, put more (less) weight on long-term (short-term) earnings in firm valuation, become more (less) sensitive to analysts’ long-term (short-term) earning forecast revisions, and are less likely to dismiss chief executive officers for missing quarterly earnings targets by small amounts, relative to investors in firms that continue to issue quarterly earnings guidance. Our study provides new evidence of the benefit of stopping quarterly earnings guidance, that is, the reduction of short-termism among investors.     

The impact of accruals and lines of business on analysts’ earnings forecast superiority

In this paper, we examine the linkage between analyst advantage (AA) (compared to the seasonal random walk model) in the prediction of quarterly earnings-per-share (EPS) and a broad set of economic determinants. Specifically, we employ a pooled cross-sectional time-series regression model where AA is linked to a set of firm-specific economic determinants that have been employed in extant work (e.g., Brown et al. in J Account Res 22:49?C67, 1987; Kross et al. in Account Rev 65:461?C476, 1990). We refine this set of independent variables by including a new variable (RATIODEV) based upon Sloan (Account Rev 71(3):289?C315, 1996) who documents that differential levels of accruals impact future earnings performance. This variable is particularly salient in explaining AA since analysts may be in a position to identify the permanent component of accruals via fundamental financial analysis. Additionally, we refine the measurement of lines of business??consistent with the reporting requirements of SFAS No. 131 relative to extant work that operationalized proxies for this variable based upon SFAS No. 14. Parameters for these aforementioned variables are significantly positively related to AA, consistent with theory.     

Management earnings forecasts and the quality of analysts’ forecasts: The moderating effect of audit committees

This study investigates whether effective audit committees influence the association between management earnings forecasts and the properties of analysts’ forecasts. We posit that this influence on the part of an audit committee would likely result from increased responsibility for monitoring voluntary disclosure. Using the four attributes that the Blue Ribbon Committee (1999) and prior research suggest as being indicative of audit committee effectiveness, we find that analysts’ forecasts exhibit higher accuracy and lower dispersion with the issuance of management forecasts for those firms employing audit committees that are composed exclusively of independent directors, include an accounting expert, and act with due diligence. We also find that effective audit committees strengthen the association between management and analyst forecast accuracy. Our evidence, therefore, supports the notion that effective corporate governance influences the reliability of voluntary disclosure, and thereby benefits the users of financial information.     

The effect of non-recurring items on analysts’ earnings forecasts

This article discusses the effects of non-recurring profits and losses on statement users’ decision-making processes from the perspective of securities analysts. We examine the relationship between analysts’ forecast revisions and firms’ non-recurring earnings. We find that 1) non-recurring gains and losses can influence analysts’ earnings forecast revision; 2) compared with non-recurring items resulting from policy changes, analysts are more concerned about those attributed to changes in business scope; 3) if listed companies use non-recurring items to turn losses into gains during earnings management, it will weaken the effects of non-recurring items on analysts’ earnings forecast revision. The results suggest that non-recurring items that result from changes in business scope incorporate information that users need for the future operation of the business. This article verifies the information relevance of non-recurring items and provides evidence for the necessity of non-recurring item disclosure.     

Automatic summarization of earnings releases: attributes and effects on investors’ judgments

Review of Accounting Studies - Firms often include summaries with earnings releases. However, manager-generated summaries may be prone to strategic tone and content management, compared to the...     

Brokerage trading volume and analysts’ earnings forecasts: a conflict of interest?

Review of Accounting Studies - Using unique new data, we examine whether brokerage trading volume creates a conflict of interest for analysts. We find that earnings forecast optimism is associated...     

A re-examination of analysts’ superiority over time-series forecasts of annual earnings

We re-examine the widely held belief that analysts?? earnings per share (EPS) forecasts are superior to random walk (RW) time-series forecasts. We investigate whether analysts?? annual EPS forecasts are superior, and if so, under what conditions. Simple RW EPS forecasts are more accurate than analysts?? forecasts over longer horizons, for smaller or younger firms, and when analysts forecast negative or large changes in EPS. We also compare the accuracy of a third forecast of longer-term earnings based on a na?ve extrapolation of analysts?? 1-year-ahead forecasts. Surprisingly, this na?ve extrapolation provides the most accurate estimate of long-term (2- and 3-year-ahead) earnings. These findings recharacterize prior generalizations about the superiority of analysts?? forecasts and suggest that they are incomplete, misleading, or both. Moreover, in certain settings, researchers can rely on forecasts other than these explicit forecasts.     

The impact of CSR performance and CSR disclosure readability on investors’ earnings estimates

We investigate how the valence of corporate social responsibility (CSR) performance and the readability of CSR disclosure impact investors’ earnings estimates. Ninety-seven part-time MBA students participate in an experiment, in which we manipulate the valence of CSR performance (positive versus neutral) and the readability of CSR reports (high versus low), while holding financial information constant. Our findings reveal that investors make more positive earnings estimates when CSR performance is positive. The readability level of CSR reports also influences investors’ decision-making process. Moreover, by using an eye-tracking device, we are able to observe investors’ different reading behaviours upon the different levels of readability.     

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.     

An empirical assessment of the premium associated with meeting or beating both time-series earnings expectations and analysts’ forecasts

Recent research provides evidence of a market premium accruing to firms that meet or beat analysts’ forecasts. We find similar results for our sample of firms. However, we also find a market premium for firms that meet or beat time-series forecasts, and that the highest market premium accrued to firms that meet or beat both analysts’ and time-series forecasts. These findings are supported by assessments of future financial performance over the next two subsequent years. Our findings are consistent with the notion that when time-series benchmark is used in conjunction with analysts’ forecasts, investors obtain a more reliable (i.e., less noisy) signal regarding whether firms have actually met or beaten market expectations.

Dispersion of analysts’ forecasts and the profitability of trading strategies around the preannouncement

Contrary to prior research, the preannouncement of earnings before taxes, either good or bad, partially reduces the forecast error in the French Stock Market. Moreover, this study shows that the abnormal return at the formal announcement is negatively related to the dispersion of analysts’ forecasts after the preannouncement. It is positively related to the actual earnings surprise, especially for bad news. After controlling for the precision of the preannouncement and the actual earnings surprise, investors should buy stocks with negative (positive) abnormal return at the preannouncement of bad (good) news.     

Who is the more overconfident trader? Individual vs. institutional investors

Guided by the Gervais and Odean (2001) overconfident trading hypothesis, we comprehensively investigate the trading behavior of individual vs. institutional investors in Taiwan in an attempt to identify who is the more overconfident trader. Conditional on the various states of the market, on market volatility, and on the risk level of the securities they trade, we find that both individual and institutional investors trade more aggressively following market gains in bull markets, in up-market states, in up-momentum market states, and in low-volatility market states and that only individual investors trade more in riskier securities following market gains. More importantly, we find that individual investors trade more aggressively following market gains in the three conditional states of the market and in high-volatility market states than institutional investors. Also, individual investors trade more in relatively riskier securities following gains than institutional investors. These findings provide evidence that individual investors are more overconfident traders than institutional investors.     

Relative accuracy of analysts’ earnings forecasts over time: a Markov chain analysis

The main purpose of this paper is to analyze the time patterns of individual analysts’ relative accuracy ranking in earnings forecasts using a Markov chain model. Two levels of stochastic persistence are found in analysts’ relative accuracy over time. Factors underlying analysts’ performance persistence are identified and they include analyst’s length of experience, workload, and the size and growth rate of firms followed by the analyst. The strength and the composition of these factors are found to vary markedly in different industries. The findings support the general notion that analysts are heterogeneous in their accuracy in earnings forecasts and that their superior/inferior performance tends to persist over time. An analysis based on a refined measure of analysts’ forecast accuracy ranking that strips off firm-specific factors further enhances the empirical validity of the findings. These findings provide a concrete basis for researchers to further explore why and how analysts perform differently in the competitive market of investment information services.     

To beat or not to beat? The importance of analysts’ cash flow forecasts

We investigate the implications of firms’ benchmark-beating patterns with respect to analysts’ quarterly cash flow forecasts for firms’ current capital market valuation and their future performance. We hypothesize that nonnegative earnings surprises are more likely to be supported by real operating performance and signal higher earnings quality if they are achieved via higher than expected cash flows or lower than expected accruals. We show that firms beating analyst earnings forecasts have larger positive capital market reactions and larger earnings response coefficients if they beat analyst cash flow forecasts or report lower than expected accruals. We also demonstrate that these firms’ superior future performance may provide an economic justification for their more favorable market response. Our findings suggest that firms’ ability to beat analyst cash flow forecasts is informative regarding the quality of their earnings surprises.