Are analysts' cash flow forecasts useful?

This study provides evidence that the cost of equity capital decreases with the number of analysts who issue both cash flow and earnings forecasts (cash analysts). The evidence also shows that cash analysts reduce information asymmetry and predict long‐term earnings more accurately than analysts who issue only earnings forecasts. Taken together, these findings suggest that cash analysts provide market participants with high‐quality information and, as a result, firms benefit from cash analyst coverage in the form of a reduced cost of equity capital.     

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.     

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.     

The effect of cash flow forecasts on accrual quality and benchmark beating

When analysts provide forecasts of both earnings and operating cash flow, they also implicitly provide a forecast of total operating accruals. We posit that this increases the transparency and the expected costs of accrual manipulations used to manage earnings. As a consequence, we predict and find that accrual quality improves and firms’ propensity to meet or beat earnings benchmarks declines following the provision of cash flow forecasts. We also predict and find that firms turn to other benchmark-beating mechanisms, such as real activities manipulation and earnings guidance in response to the provision of cash flow forecasts.     

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.     

分析师为什么选择性的发布现金流预测?——基于信息需求理论的实证研究

分析师在对公司发布盈余预测的同时,还对一些公司发布了现金流预测。分析师为什么仅针对某些公司发布现金流预测?其动因何在?本文基于信息需求理论对上述问题进行了研究,研究发现,分析师针对现金流信息需求高的公司发布现金流预测的可能性更大。进一步发现,分析师更可能对非国有控股的公司发布现金流预测。本文首次基于我国独特的制度背景,研究分析师选择性发布现金流预测的动因问题。本文的结论有助于加深对分析师行为的理解,并对投资者决策具有一定的参考价值。     

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.     

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.     

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.     

Slow price reactions to analysts’ recommendation revisions

This study explores the reasons for the slow price reactions to analysts’ recommendation revisions. We predict that analysts’ recommendation revisions contain earnings-related information that is not incorporated in analysts’ earnings forecasts and that the slow price reaction is attributable to a gradual incorporation of this earnings-related information into stock prices. We find that, consistent with our prediction, stocks with recommendation upgrades subsequently experience more upward earnings forecast revisions than stocks with recommendation downgrades, and that the differences in subsequent stock returns between upgraded and downgraded stocks is attributable to differences between subsequent earnings forecast (especially, FY2 earnings forecast) revisions.     

Analysts Earnings Forecasts and the Roles of Earnings and Book Value in Equity Valuation

This study examines the effect of the degree of association between current earnings and expected future earnings on the relative importance of earnings and book value for explaining equity price. Consensus analysts forecasts of one-year-ahead earnings are used to proxy for expected future earnings and are compared to reported current earnings to measure the degree of the association. We find that the value-relevance of current earnings negatively correlates with the extent to which consensus analysts forecasts deviate from current earnings. We also find that the incremental explanatory power of book value for equity price positively correlates with this measure. These results remain robust after controlling for factors known to be affecting the value-relevance of earnings such as negative earnings and the earnings-to-book ratio. Our results also show that this analysts' forecast-based measure of `earnings persistence' dominates historical earnings variance in explaining cross-sectional variations in the value-relevance of earnings and book value.     

Alternative adjustments to analysts' earnings forecasts: relative and complementary performance

This study examines the relative and complementary performance of alternative earnings forecast adjustments using a common set of consensus analysts’ earnings forecasts. We document that a simple adjustment to analysts’ earnings forecasts, based solely on cross-sectional relationships between actual and forecasted earnings in the prior year, performs as well as more complicated adjustment methods, i.e., composite forecasts and persistence adjusted forecasts. A forecast adjustment that is based on prior year earnings and returns, however, provides significant incremental reductions in forecast error and dominates all of the other adjustment methods.     

Do banks care about analysts' forecasts when designing loan contracts?

We investigate whether banks rely on the information content in equity analysts’ annual earnings forecasts when assessing the risk of potential borrowers. While a long literature finds that analysts provide useful information to market participants, it is not clear that banks, which have access to privileged information, would benefit from publicly available analysts’ forecasts. If, however, banks do rely on this information, then more precise private information in earnings forecasts may inform banks. We focus our analysis on the requirement of collateral because it is a direct measure of default risk, whereas other loan terms such as interest spread and debt covenants can also protect against other risks, such as asset misappropriation. The direct link between collateral and default risk allows us to examine whether information from analysts is relevant to banks when designing loan contracts. Consistent with our predictions, we find that higher precision of the private information in analysts’ earnings forecasts is associated with a lower likelihood of requiring collateral, and this effect is larger when a borrower does not have a prior relationship with the lender or their accounting or credit quality is low. We also find that this association disappears after the implementation of Regulation FD, consistent with this regulation reducing analysts’ access to private information.     

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.     

Analyst earnings forecast precision and local advantage: evidence from American depositary receipt firms

Prior research has documented a finding that local analysts provide more accurate earnings forecasts than nonlocal analysts in many settings. However, little is known about local and nonlocal analysts’ relative earnings forecast abilities for ADR stocks. In this study, we find that the local advantage disappears for ADR stocks and that nonlocal analysts in fact outperform local ones in this case. We investigate the source of this ‘local disadvantage’ and find evidence against hypotheses based on accounting standards and exchange rates. We document that the local advantage decreases with increased investor interest in foreign firms, consistent with our nonlocal investors’ interest hypothesis.     

Has the IASB Been Successful in Making Accounting Earnings More Useful for Prediction and Valuation? UK Evidence

When producing International Financial Reporting Standards (IFRS), one of the main goals of the International Accounting Standards Board (IASB) was to create a set of standards which were more useful to investors as a predictive tool. We assess the success of the IASB in achieving this goal by investigating the effects of the introduction of IFRS on the relative information content of reported earnings and forecasted earnings under UK generally accepted accounting practices (GAAP) and IFRS. Results indicate that the value relevance of forecasted earnings is significantly lower under IFRS while the value relevance of reported earnings is significantly larger. These findings suggest that IFRS substitutes price‐relevant information previously provided to the market in the form of analyst forecasts with information encoded by companies in their reported earnings. This implies that the IASB was indeed successful in its stated goal and points towards IFRS forecasts being more accurate and less dispersed than UK GAAP forecasts. This, in turn, implies that analysts are able to provide more informative forecasts under IFRS than under pre‐IFRS regimes and that the aforementioned substitution effect is not a consequence of any decrease in the quality of forecasts under the new regime.     

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.     

Taxable income,future profitability,and stock returns

Prior research suggests that investors behave ‘as if’ taxable income contains information about future performance by providing evidence of a positive association between taxable income and stock returns. We draw on the fundamental analysis literature and provide direct evidence on this assertion by examining whether taxable income predicts future pretax performance. We find that taxable income positively predicts future pretax cash flows, pretax book income, and ‘Street’ pretax earnings, suggesting that taxable income provides incremental information to book income regarding performance. Moreover, we find a positive association between taxable income and analysts’ pretax forecasts, consistent with analysts utilizing the information in taxable income when forming earnings expectations. We do not find an association between taxable income and future analyst forecast errors, implying analysts do not overreact or underreact to taxable income's performance signal. Overall, we find that taxable income provides a signal of fundamental value and corroborate the implications of prior research.     

The sensitivity of the credit default swap market to financial analysts’ forecast revisions

We examine the impact of analysts’ earnings per share (EPS) and cash flow per share (CPS) forecast revisions on the market for credit default swaps. We find that while the issuance of both EPS and CPS forecast revisions are inversely associated with changes in credit default swap (CDS) spreads, cash flow forecast revisions have a larger effect. We demonstrate that the relationship between CPS forecast revisions and CDS spreads tends to be stronger in cases of financial distress. We provide evidence that cash flow forecasts dominate earnings forecasts in some situations and that participants in the CDS market discriminate between analysts' forecast revisions and recommendation changes.