Lead indicator models and UK analysts' earnings forecasts

This study examines the predictive ability of models which adjust random walk forecasts of corporate earnings, to incorporate past changes in economic lead indicators. The results suggest that changes in the broad money supply measure M4 contain predictive ability, beyond equivalent changes in other lead indicators or an individual firm's earnings. When forecasts from the broad-money model are compared with forecasts generated by financial analysts a size effect is evident: the superiority of analysts' forecasts is apparent much earlier for large firms than for small firms. This result is consistent with studies suggesting a size-related differential in the collection and dissemination of information by market participants.     

Company size and the issue of quarterly segment reporting

This study explores the proposition that differences between consolidated (CN) and segmented (SG) income forecasts may depend in part on company size. Simulated mergers of existent autonomous firms provide quarterly time series data and ARIMA models are used to project both quarterly and annual earnings. Small-segment firms tended to yield SG superior predictions for quarterly forecasts, but no such differences were observed for annual forecasts. Large-segment firms tended to yield no CN-SG differences for either quarterly or annual forecasts.     

Refining the Degree of Earnings Surprise: A Comparison of Statistical and Analysts' Forecasts

This paper compares the relative predictive ability of several statistical models with analysts' forecasts. It is one of the first attempts to forecast quarterly earnings using an autoregressive conditional heteroskedasticity (ARCH) model. ARCH and autoregressive integrated moving average models are found to be superior statistical forecasting alternatives. The most accurate forecasts overall are provided by analysts. Analysts have both a contemporaneous and timing advantage over statistical models. When the sample is screened on those firms that have the largest structural change in the earnings process, the forecast accuracy of the best statistical models is similar to analysts' predictions.     

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.     

Analyst rounding of EPS forecasts and stock recommendations

We examine the association between analysts' stock recommendations and their tendency to round annual EPS forecasts to nickel intervals (i.e. placing a zero or five in the penny location of the forecast). We find that prior to Regulation Fair Disclosure (Reg FD), analysts were more likely to provide rounded EPS forecasts in association with unfavorable (underperform and sell) recommendations. However, after Reg FD, we find no significant association between rounded forecasts and unfavorable stock recommendations. Further, other regulations (NASD 2711, NYSE 472, and Global Research Analyst Settlement) have no impact on analyst rounding behavior. The findings in this study suggest that analyst rounding behavior is a particular form of forecasting optimism motivated, at least in part, by management relations incentives. Further, Reg FD appears partially successful at curbing the influence of management relations incentives on analysts' research.     

Trends in statistically based quarterly cash-flow prediction models

This paper provides a succinct review and synthesis of the literature on statistically based quarterly cash-flow prediction models. It reviews extant work on quarterly cash-flow prediction models including: (1) complex, cross-sectionally estimated disaggregated-accrual models attributed to 0170 and 0175 and Bernard and Stober (1989), (2) parsimonious ARIMA models attributed to Hopwood and McKeown (1992), (3) disaggregated-accrual, time-series regression models attributed to Lorek and Willinger (1996), and (4) parsimonious ARIMA models with both adjacent and seasonal characteristics attributed to 0120 and 0130. Due to the unavailability of long-term cash-flow forecasts attributed to analysts, increased importance has been placed upon the development of statistically based cash-flow prediction models given their use in firm valuation. Specific recommendations are also provided to enhance future research efforts in refining extant statistically based quarterly cash-flow prediction models.     

Does revenue-expense matching play a differential role in analysts’ earnings and revenue forecasts?

This paper investigates whether matching has differential implications for the accuracy of analysts' earnings and revenue forecasts. We construct a novel measure of firm-level matching and document that matching improves analysts' earnings forecasts to a greater extent than their revenue forecasts. We also document matching's differential impact on analysts' earnings and sales forecasts by proposing a new count metric capturing a wedge in the accuracy of earnings and revenue forecasts. In additional tests, we report that the differential impact of matching is less (more) pronounced in a situation where the balance sheet (income statement) orientation likely dominates. We also report that matching's differential role is weaker (stronger) when firms have high intangible intensity (analysts have appropriate resources or expertise). In short window tests, matching's role in analysts' forecast revisions is more pronounced for earnings than sales forecasts. Overall, these results show how analysts benefit from better revenue-expense matching.     

The impact of meeting or beating analysts' operating cash flow forecasts on a firm's cost of debt

Extant literature provides conflicting results with respect to the usefulness and accuracy of analysts' operating cash flow forecasts. Our study empirically examines the importance and influence of meeting or beating analysts' operating cash flow forecasts on a firm's cost of debt. Results indicate that firms meeting/beating analysts' cash flow forecasts have higher initial bond ratings as well as lower initial bond yields. Additionally, based upon an analysis of rating changes, firms meeting or beating cash flow forecasts have a higher probability of receiving a debt rating upgrade and a lower probability of a ratings downgrade compared to firms missing cash flow forecasts. A direct comparison of the importance of meeting/beating cash flow versus earnings benchmarks indicates that debt market participants appear to incrementally value both types of forecasts, and contrary to selected equity market findings, neither forecast subsumes the other for debt market participants.     

Earnings management and the allocation of net periodic pension costs to interim periods

We examine the pattern of reported quarterly net periodic pension costs. Quarterly pension costs are one of the largest single expense items for firms with pension plans (around 15% of income before extraordinary items in our sample). Under ASC 270, net pension costs should be recognized as incurred, or as the benefit provided by the expense is realized. We find that over the period of 2004–2010, there is significant variation in the amount of quarterly pension cost firms report. In addition, we find that income-increasing changes in pension costs are significantly associated with meeting or beating analysts' forecasts in a given quarter. We also show that income-decreasing changes to net periodic pension costs that would cause a firm to miss its earnings forecast are extremely rare. Finally, we find evidence that income-increasing and income-decreasing changes in quarterly pension costs are “settled up” in the fourth quarter (e.g., they are reversed).     

The use of management forecasts to dampen analysts' expectations by Chinese listed firms

This paper studies the use of management earnings forecasts (MEF) to dampen analysts' expectations, i.e. expectation management, by Chinese listed companies. We reveal several important findings: Firstly, information asymmetry is positively associated with the use of MEF to dampen analysts' expectations. State control has been found to moderate this relationship. Secondly, dampening analysts' expectations using MEF leads to negative stock return reactions and downward analysts' forecast revisions. Thirdly, the effectiveness of “pre-empting bad news through MEF” appears mixed and dependent on the information content of MEF and measures of actual earnings surprises. Finally, firms that disclose MEF are found to engage in more earnings management to meet the forecasts than firms that do not.     

Valuing Loss Firms: What Can Be Learned From Analysts' Forecasts?

Prior research documents an anomalous negative price–earnings relation when a simple earnings capitalization model is estimated for loss‐making firms. Collins et al. (1999 ) suggest that the model is misspecified due to the omission of book value of equity. However, results from previous studies are confusing. We try to enrich prior literature by focusing on analysts' forecasts. In particular, we assess the role of earnings and book value in valuing loss firms using several measures based on the information provided by analysts. We hypothesize that the role of accounting figures depends on whether the loss firm is supported or not by investors. According to this argument, we construct several measures of investor support based on analysts' forecasts, and then test the value relevance of accounting information depending on the degree of support. Our results confirm the usefulness of the notion of ‘investor support’. For those loss firms that are expected to liquidate, we find that the inclusion of book value of equity in the model removes the negative sign on the earnings coefficient. However, for those loss firms that are expected to reverse current losses, we find that the coefficient on earnings remains negative despite the inclusion of book value.     

Does the mandatory disclosure of audit information affect analysts' information acquisition?

This paper explores the effect of public information on analysts' information acquisition. By introducing the implementation of the Key Audit Matters (KAM) Disclosure Standards for China's firms cross-listed in Hong Kong in 2017, we present evidence that KAM disclosure reduces analysts' firm visits, which is an important channel of information acquisition. The effect is particularly pronounced for firms with audit partner rotation and low institutional ownership. KAM disclosure by industrial leaders has a spillover effect on analyst visits for peer firms. Disclosure also improves the frequency and quality of analysts' forecasts and firms' information environments, indicating that KAMs are informative and audit information is an important determinant of analysts' information acquisition. Our study reveals the real effect of KAM disclosure on analyst decisions, which may be of interest to regulators concerned with the mandatory disclosure of audit information and capital market efficiency.     

Real earnings management and the properties of analysts' forecasts

Prior literature generally finds analysts are able to identify and process complex financial information. However, research suggests that in certain settings, analysts struggle to fully incorporate into their forecasts all available information. We examine analysts' forecast properties in the face of a specific type of complex financial information: real earnings management (REM). First, we investigate the relation between measures of REM and analysts' forecast properties. We find REM measures are associated with greater forecast error and dispersion in the following year. However, REM measures, by definition, capture abnormal operating results, and thus include both firms engaging in manipulative REM as well as firms experiencing firm-specific economic shocks. Thus, we conduct cross-sectional tests of analysts' forecasts for firms with and without incentives to manipulate earnings. We find that firms with low incentives to engage in earnings management (i.e., firms most likely experiencing firm-specific economic shocks) generate the strongest positive relation between REM measures and the following year's analysts' forecast properties, suggesting analysts more fully incorporate the earnings implications of firms with high incentives (i.e., firms most likely engaging in manipulative REM). Our results are consistent across numerous REM proxies and indicators of earnings management incentives.     

Model-based earnings forecasts vs. financial analysts' earnings forecasts

Existing accounting-based forecasting models of earnings either do not fully consider information that is contained in stock prices or use an ad hoc specification that is not based on rigorous valuation theory. In this paper, we develop an earnings forecasting model built on the theoretical linkages between future earnings and stock prices as well as a number of accounting fundamental variables. We find that our model-based forecasts of earnings are in general less biased and more accurate than both existing model-based forecasts and analysts' consensus forecasts, at both shorter and longer horizons. We also show that the accuracy of both model-based forecasts and financial analysts' forecasts depend on firm-specific characteristics such as firm size and industry membership.     

Information spillovers around seasoned equity offerings

We examine information spillovers in the context of seasoned equity offerings (SEOs). Rival firms react significantly positively (0.26%) to primary SEO announcements, indicative of a competitive effect, but negatively (− 0.35%) to secondary share announcements, which is evidence of a contagion effect. Consistent with the view that primary equity offerings signal favorable industry prospects because firms presumably issue new shares to invest in profitable projects, we find that the rival response is positively related to analysts' EPS growth forecasts. However, when insiders are selling their shares through a secondary offer, this may suggest overvaluation and thus negatively impacts rival firms. Consistent with this view, we find when VCs sell through a secondary offerings, rivals experience a more significant negative reaction. We find rival firms are more likely to follow their peers and conduct a primary SEO if the market reacts favorably to their peer's SEO announcement. Finally, rival firms outperform secondary share issuers of equity, but not primary share issuers. Collectively, the findings support the view that insiders take advantage of windows of opportunity when they sell their own shares, but not when they raise capital for investing purposes.     

Properties of Market Expectations of Accounting Earnings by Financial Analysts: UK versus US

This paper compares patterns and properties of financial analysts' forecasts (FAFs) of earnings between the UK and the US. Using 299 UK and 400 US firms from the same data source—Institutional Brokers Estimate System tapes—the accuracy of forecasts is examined and the sources of errors analysed. The results reveal that FAFs errors in the UK are much smaller than those in the US, and that this disparity persists even after controlling for firm size and industry effects. Further, FAFs of US firms demonstrate consistent overestimation of earnings over the sample period 1988–1990, while UK firms show overestimation in only one of three years. A model developed to test the determinants of forecast error reveals that forecasters of UK firms are influenced in a somewhat different fashion from those of US firms. While dispersion, predisclosure information (market capitalisation or number of analysts), and industry are common determinants of forecast error for both countries, the percentage of forecasts revised is a major determinant only for UK firms.     

Why Do EPS Forecast Error and Dispersion Not Vary with Scale? Implications for Analyst and Managerial Behavior

We document a counter‐intuitive finding regarding analyst forecasts of quarterly earnings per share (EPS): magnitudes of deviations from benchmarks—individual forecasts versus consensus (dispersion) and consensus versus actual (forecast error)—do not vary with scale. Seasonally differenced EPS, or time‐series forecast error, also exhibits substantial lack of variation with scale, but only for firms followed by analysts. This lack of variation with scale is not observed for analyst and time‐series forecasts for (a) EPS for some countries, (b) sales and cash flows for all countries, and (c) stock splits. We propose and investigate different explanations for these puzzling regularities that have important implications for practice and research. We believe the cause is managerial smoothing of EPS designed to reduce across‐firm variation in EPS volatility.     

The effects of operating cash flow disclosure on earnings comparability,analysts' forecasts,and firms’ investment decisions during the Pre-IFRS era

We examine the effects of the availability of operating cash flow (OCF) information disclosed by firms operating in 15 international countries during the pre-IFRS era on: (1) the comparability of these firms' disaggregated earnings to those of U.S. firms for equity valuation purposes, (2) the properties of analysts' earnings forecasts, and (3) the efficiency of firms' investment decisions. We find that the comparability of disaggregated earnings improves after company-disclosed OCF information is available. We also find decreases in analysts' forecast errors and dispersion and a decrease in firms’ tendency to over- or under-invest when they are predisposed to do so.