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.     

CEO bonus compensation: the effects of missing analysts’ revenue forecasts

We investigate the incremental contract relevance of analysts’ revenue forecasts while controlling for earnings forecasts and find CEOs receive smaller bonuses when missing analysts’ annual and quarterly revenue expectations. Our results support the link between the value relevance of the revenue performance measure and the contract relevance of that measure. Further, we find revenue forecasts to be more contract relevant for CEOs of firms with high growth expectations, consistent with Rees and Sivaramakrishnan’s Contemp Acc Res 24(1):259–290, (2007) findings that growth firms receive a larger market penalty for missing revenue targets. Overall, our findings provide empirical support for the conjecture that compensation committees rely on information consistent with that conveyed in analysts’ revenue forecasts when contracting with management.     

The Relevance of Analysts' Earnings Forecasts in Japan

Abstract:   This study examines the role of financial analysts in equity valuation in Japan by comparing the relevance of financial analysts' earnings forecasts, over financial statement information, to investors' decisions. We find that the value‐relevance of a set of accounting variables is very modest, but the incremental contribution of analysts' forecasts is very significant. This is in line with the expectation that the skill and expertise of analysts are more valuable in markets with poor financial disclosure, such as Japan. We also find that the importance of the financial statements increases over time while the importance of the analysts' forecasts does not change. We also provide evidence of the effect of Japanese corporate groupings, keiretsu, on the informativeness of accounting signals and earnings forecasts. The results show that the contribution of accounting variables to valuation is lower for keiretsu firms, which supports the exclusionary hypothesis that companies which are a part of keiretsu, disclose less information than do non‐keiretsu companies. The analysts' forecasts are equally important for investors in both types of firms.     

The Value Relevance of Management Forecasts and Their Impact on Analysts' Forecasts: Empirical Evidence From Japan

A major financial disclosure feature in Japan is that stock exchanges require firms to provide next year's earnings forecasts. This study investigates the value relevance of Japanese management earnings forecasts and their impact on analysts' earnings forecasts. First, the value relevance of management forecasts is investigated using a valuation framework provided by Ohlson (2001 ), in which firm value is expressed as a function of book value, current earnings and next year's expected earnings. The analysis yields that of the three accounting variables examined, management forecasts have the highest correlation and incremental explanatory power with stock price.
Next, the impact of management forecasts on analysts' forecasts is examined. The results show that more than 90% of changes in analysts' forecasts are explained by management forecasts alone. Further analysis reveals that the heavy dependence of financial analysts on management forecasts in formulating their own forecasts may partially be attributed to the relatively high accuracy of management forecasts. At the same time, financial analysts also somewhat modify management forecasts when certain financial factors indicate that the credibility of management forecasts is in doubt.
Overall, this study presents empirical evidence that Japanese management forecasts provide useful information for the market and have a significant influence on analysts' forecasts.     

Analysts' Reactions to Earnings Preannouncement Strategies

Preannouncements of earnings tend to overstate negative or understate positive news, which decreases the chance of a negative surprise when actual earnings is announced. We conduct an experiment to investigate how experienced sell-side analysts' earnings forecasts are affected by preannouncements that either understate, accurately state, or overstate the magnitude of positive or negative total earnings news, holding total earnings news constant. We find that firms with negative (positive) total news receive the highest post-earnings announcement forecasts of future earnings when the earlier preannouncement overstates (understates) the magnitude of the news. These forecasts are consistent with the analysts' perceptions about the firms' future prospects, but not their perceptions of management. While analysts expect preannouncements to be lower than actual earnings, they do not adjust their forecasts for these beliefs. These insights into analysts' responses have implications both for managers and analysts.     

衍生工具应用能改善资本市场信息环境吗？——基于分析师预测行为的视角

本文通过文本搜索获得企业衍生工具运用情况,在此基础上研究了企业衍生工具应用对分析师跟踪和预测信息结构的影响,并且进一步区分了明星分析师和非明星分析师预测行为的差异。研究结果表明,企业运用衍生工具会导致分析师跟踪数量显著减少,公共信息精度下降,从而对资本市场信息环境产生负面影响。但是,进一步我们发现分析师跟踪数量的减少和公共信息精度的下降是由非明星分析师所致,明星分析师跟踪数量和公共信息精度没有显著变化,私有信息精度反而增加;而非明星分析师跟踪数量显著减少,公共信息精度明显下降。本文的结论有助于我们进一步理解衍生工具应用对资本市场信息环境的影响,以及分析师在信息传递中的作用机制。     

证券分析师VS统计模型:证券分析师盈余预测的相对准确性及其决定因素

本文使用2005年35家券商对我国上市公司做出的每股盈余预测数据,考察了证券分析师盈余预测相对于统计模型的相对准确性及其决定因素。我们发现,我国证券分析师做出的盈余预测,同以年度历史数据为基础的统计模型得出的盈余预测相比,预测误差较小,证券分析师盈余预测具有一定的优势;但同某些以季度历史数据为基础的统计模型得出的盈余预测相比,预测误差较大,证券分析师盈余预测不具有优势。我们同时考察了决定证券分析师盈余预测相对准确性的决定因素。我们发现,公司每股盈余的波动性越大,公司上市越晚,跟踪公司的分析师越多,证券分析师的优势就越大。我们的研究对证券分析师以及投资者都有一定的启示作用。     

Beating market expectations and the pricing of firms’ probability of default

This study explores the impact of beating analysts' forecasts on investors' perceptions about firms' default probability. The information contained in analysts’ forecasts, both earnings and revenues, provides additional information to investors in pricing CDSs. While previous research has focused on the impact of beating analysts’ earnings forecasts, this study shows that firms that beat analysts' revenue forecasts also experience, on average, a decrease in the CDS premium around the earnings announcement date. This study also documents that the effect is stronger when firms beat/miss both earnings and revenue forecasts. When firms beat (miss) earnings and miss (beat) revenues, the effect of earnings is the dominant signal. These effects are stronger for firms with high levels of default risk.     

Economic Value Added,Future Accounting Earnings,and Financial Analysts' Earnings Per Share Forecasts

Empirical research to date on the relative effectiveness of Economic Value Added (EVA) and earnings per share (EPS) as measures of firm performance for stock valuation has been mixed. In contrast to prior research, which primarily focuses on the correspondence of these measures with shareholder value and changes therein, we examine their relative effectiveness in predicting future earnings and their role in enhancing the accuracy of analysts' forecasts. Our results indicate that EVA contains information that is incremental to EPS in predicting future earnings. In addition, we find that despite this potential for EVA to add incremental value to analysts' forecasts of future earnings, analysts do not use the information in reported EVA appropriately, but appear rather to overweigh it.     

Investor and (Value Line) Analyst Underreaction to Information about Future Earnings: The Corrective Role of Non-Earnings-Surprise Information

Prior research suggests that financial analysts' earnings forecasts and stock prices underreact to earnings news. This paper provides evidence that analysts and investors correct this underreaction in response to the next earnings announcement and to other (non-earnings-surprise) information available between earnings announcements. Our evidence also suggests that analysts and investors underreact to information reflected in analysts' earnings forecast revisions and that non-earnings-surprise information helps correct this underreaction as well. Controlling for corrective non-earnings-surprise information significantly increases estimates of the degree to which analysts' forecasting behavior can explain drifts in returns following both earnings announcements and analysts' earnings forecast revisions.     

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 and Auditors Use Information in Accruals?

Existing research indicates that firms with high accruals are more likely to experience future earnings problems, but that investors' expectations, as reflected in stock prices, do not appear to anticipate these problems. In this paper, we directly examine the published opinions of two types of professional investor intermediaries to see if they provide investors with information concerning the future earnings problems experienced by firms with high accruals. First, we examine the earnings forecasts of sell-side analysts. We show that analysts' earnings forecasts do not incorporate the predictable future earnings declines associated with high accruals. Second, we examine the behavior of independent auditors. We find no evidence that auditors signal the future earnings problems associated with high accruals through either their audit opinions or through auditor changes. Overall, our evidence indicates that analysts and auditors do not alert investors to the future earnings problems associated with high accruals, thus corroborating previous findings that investors do not appear to anticipate these problems.     

Information misweighting and the cross-section of stock recommendations

This paper provides evidence that analysts whose earnings forecast revisions showed signs of greater exaggeration in the past make recommendation changes that lead to lower abnormal returns than their peers. Interpreting stock recommendations as a forecast of future abnormal returns, I show that this evidence is consistent with the hypothesis that analysts who typically exaggerate or overstate the weight of their private information when issuing forecasts also do so when making recommendations. The paper also shows that past earnings forecasts provide incremental information about analysts' recommending behavior beyond that contained in past recommendations.     

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.     

An International Analysis of Historical and Forecast Earnings in Accounting-Based Valuation Models

Abstract:  In this paper we examine whether the valuation properties of historical accounting amounts, namely earnings and equity book value, differ from those of forecasted earnings for firms in 17 developed countries classified into six accounting regimes. We compare the performance of a historical model and a residual-income forecast model for explaining security prices. The historical model uses the book value of equities and actual historical earnings and the forecast model uses the book value of equities and analysts' forecasts of earnings in the residual income for estimating the intrinsic value of the firm. The results suggest that book values, historical earnings or forecasted earnings are value relevant in most regimes and countries examined. The forecast model offers significantly greater explanatory power for security prices than the historical model in the Anglo-Saxon and North American countries, Japan, Germany, and three Nordic countries. The explanatory power of the historical model is similar to that of the forecast model in the Latin countries, two Nordic countries, and Switzerland. We find that the forecast model performs similarly to the historical model where financial analysts' forecasts are noisy and analysts are less active. Further results indicate that the forecasted earnings are more value-relevant than the historical earnings in countries with stronger investor protection laws, less conservative GAAP, greater income conservatism, and more transparent accounting systems.     

A Simultaneous Equations Analysis of Analysts' Forecast Bias, Analyst Following, and Institutional Ownership

In this paper we use a simultaneous equations model to examine the relationship between analysts' forecasts, analyst following, and institutions' investment decisions. Estimates of our three equation model using US data indicate that higher institutional demand leads to greater optimism among analysts and lower analyst following. At the same time, institutional demand increases with increasing optimism in analysts' forecasts but decreases with analyst following. We also investigate firm characteristics as determinants of analysts' and institutions' decisions. Empirical estimates of the effects of these characteristics indicate that agency‐driven behavioral considerations are significant.     

Biases in multi-year management financial forecasts: Evidence from private venture-backed U.S. companies

This paper studies the properties and determinants of managers’ multi-year financial forecasts. Using one- to five-year-ahead forecasts reported by private venture-backed firms, we ask whether, by how much, and why biases in managers’ forecasts of revenues, expenses and profits depend on the forecasting horizon and the verifiability of assets. We find that profitability forecasts contain a strategic component, in that [1] one-year-ahead revenue (expense) forecasts are slightly and asymmetrically pessimistic (optimistic), while five-year-ahead forecasts are hugely and asymmetrically optimistic (pessimistic); and [2] biases in revenue and expense forecasts are larger, the harder to verify or more intangible-intensive are firms’ assets.     

Accrual usage to manage earnings toward financial analysts' forecasts

This study examines whether management uses discretionary accounting accruals to move earnings upward toward analysts' earnings forecasts when it appears that earnings before discretionary accruals will fall short of the forecast. An earnings shortfall relative to analysts' forecasts could lead management to fear lower compensation and an increase in the likelihood of job termination. The article finds that firms whose earnings before discretionary accruals are below analysts' forecasts use income-increasing discretionary accruals and do so to a greater extent than do firms whose earnings before discretionary accruals are above analysts' forecasts.     

High-Technology Intangibles and Analysts' Forecasts

This study examines the association between firms' intangible assets and properties of the information contained in analysts' earnings forecasts. We hypothesize that analysts will supplement firms' financial information by placing greater relative emphasis on their own private (or idiosyncratic) information when deriving their earnings forecasts for firms with significant intangible assets. Our evidence is consistent with this hypothesis. We find that the consensus in analysts' forecasts, measured as the correlation in analysts' forecast errors, is negatively associated with a firm's level of intangible assets. This result is robust to controlling for analyst uncertainty about a firm's future earnings, which we also find to be higher for firms with high levels of internally generated (and expensed) intangibles. Given that analyst uncertainty increases and analyst consensus decreases with the level of a firm's intangible assets, we also expect and find that the degree to which the mean forecast aggregates private information and is more accurate than an individual analyst's forecast increases with a firm's intangible assets. Finally, additional analysis reveals that lower levels of analyst consensus are associated with high-technology manufacturing companies, and that this association is explained by the relatively high R&D expenditures made by these firms. Overall, our results are consistent with financial analysts augmenting the financial reporting systems of firms with higher levels of intangible assets (in terms of contributing to more accurate earnings expectations), particularly R&D-driven high-tech manufacturers.     

Intangible Assets, Information Complexity, and Analysts' Earnings Forecasts

Abstract:   We examine the relation between analysts' earnings forecasts and firms' intangible assets, including technology‐based intangibles, brand names, and recognized intangibles. We predict that high information complexity of intangible assets increases the difficulty for analysts to assimilate information and increases analysts' forecast error of intangibles‐intensive firms. We find a positive association between analysts' forecast error and the firm's intangible intensity that deviates from the industry norm. We also find that analysts' forecast errors are greater for firms with diverse and innovative technologies. In contrast, analysts' forecast errors are smaller for biotech/pharmaceutical and medical equipment firms that are subject to intangibles‐related regulation.