A Comparative Analysis of Earnings Forecasts in Europe

This study examines the accuracy and bias of financial analysts' EPS forecasts in nine European countries during 1987 to 1995. There are significant differences between the countries which may be due to the differences in earnings behaviour, accounting practices, and the influence of securities markets. An optimistic bias is endemic in European forecasts, consistent with research from the US. Investors who incorporate earnings forecasts in their stock selection procedures may be able to improve returns by explicitly adjusting their models for observed regularities in earnings forecast errors. However, we have shown that these regularities differ in incidence and magnitude across the countries studied, and further research is needed to effectively model these differences.     

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.     

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。     

Institutional effects on information content of US and French management earnings forecasts: Evidence from market reactions and analyst revisions

The United States and France are both most developed economies in the world. Their socio-economic institutions, however, are very different. These differences are indications of their dichotomous legal regimes: common law in the US versus code law in France. The political influence of these legal regimes, in turn, leads to a dichotomized classification of accounting systems: the British-American Model and the French Continental Model. This study extends these institutional effects into the field of management earnings forecast. We find that earnings forecasts by French firms are less informative than those made by US firms matched-up by industry and firm size. We also compare US and French financial analysts' revisions of their forecasts following the management forecasts. We find that revisions by French analysts are more influenced by management forecasts. Our findings are consistent with prior studies that argue that information asymmetry in code-law countries is largely resolved through private information channels, rendering less information content in management announcements and less demand and incentives for original research by financial analysts.     

Financial Analysts' Forecast Accuracy and Dispersion: High-Tech versus Low-Tech Stocks

This study focuses on systematic differences in security analysts' forecast accuracy and dispersion between high- and low-tech firms. In line with the recent development in theoretical models and empirical findings, it posits that security analysts' unsigned forecast error and forecast dispersion are expected to differ between high-tech and low-tech firms. The results of this study provide evidence of lower unsigned error and dispersion for high-tech firms vis-à-vis low-tech firms. The higher forecast accuracy and forecast convergence for high-tech firms relative to low-tech firms in financial analysts' forecasts of earnings can be attributed to the information effect prevailing over the noise effect. Given the lack of empirical studies that compare analysts' forecast accuracy and dispersion between high-tech and low-tech sectors, the results of this paper provide a fresh basis for assessing how market participants vary in their treatment of New Economy stocks and factors that affect such decisions. In the light of the fact that the 1990s is a period characterized by the start of the Information Revolution through the Internet, the results of this study shed light on the usefulness of examining factors that differentiate between high-tech firms (New Economy stocks) and low-tech firms (Old Economy stocks) in financial analysts' forecasting earnings.     

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.     

Domestic Accounting Standards, International Accounting Standards, and the Predictability of Earnings

We investigate (1) whether the variation in accounting standards across national boundaries relative to International Accounting Standards (IAS) has an impact on the ability of financial analysts to forecast non-U.S. firms' earnings accurately, and (2) whether analyst forecast accuracy changes after firms adopt IAS. IAS are a set of financial reporting policies that typically require increased disclosure and restrict management's choices of measurement methods relative to the accounting standards of our sample firms' countries of domicile. We develop indexes of differences in countries' accounting disclosure and measurement policies relative to IAS, and document that greater differences in accounting standards relative to IAS are significantly and positively associated with the absolute value of analyst earnings forecast errors. Further, we show that analyst forecast accuracy improves after firms adopt IAS. More specifically, after controlling for changes in the market value of equity, changes in analyst following, and changes in the number of news reports, we find that the convergence in firms' accounting policies brought about by adopting IAS is positively associated with the reduction in analyst forecast errors.     

THE USE OF MULTIPLE INSTRUMENTS FOR MEASUREMENT OF EARNINGS FORECAST ERRORS, FIRM SIZE EFFECT AND THE QUALITY OF ANALYSTS'FORECAST ERRORS

This paper develops an instrumental variables framework to form a better proxy for earnings forecast errors. The key aspect of the approach is to extract information from alternative proxies for the same underlying variable, namely a portion of realized earnings signals unexpected by the market. We use signs of various proxies for earnings forecast errors obtained from different time-series forecasting models as multiple instruments. The results show that the instrumental variables approach is effective for reducing measurement errors inherent in various proxies for earnings forecast errors. It produces not only a smaller magnitude but also a narrower dispersion of earnings forecast errors. The paper provides evidence that the instrumental variables approach performs better for small-firm samples than for large-firm samples. Finally, we observe that analysts' forecast errors seasoned with the signs of various time-series forecast errors (as well as the signs of their own forecast errors) outperform those without seasoning. This indicates that analysts' forecast errors can still be improved by employing the instrumental variables technique.     

On the Use of Intra-Industry Information to Improve Earnings Forecasts

We investigate whether earnings forecasts are improved by earlier earnings disclosures by firms in the same industry. We find improvements for time series forecasts, but not for analysts' forecasts. Considering prior earnings announcements reduces correlations between forecast errors and security price reactions to earnings announcements, even when incorporating these announcements improves forecast accuracy. Our explanation for this anomaly, which is supported by additional analysis, is that intra-industry information facilitates predicting transitory, rather than permanent, earnings components. The question of whether information transfers improve earnings forecasts provides the context for the analysis, but the primary contribution is the documentation of intra-industry information transfers in a setting other than capital markets.     

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.     

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.     

Stock option compensation and the likelihood of meeting analysts' quarterly earnings targets

One role of stock options in executive compensation packages is to counterbalance the inherently short-term orientation of base salary and annual bonuses. Managerial compensation plans frequently include stock options in order to better align the interests of managers and outside shareholders and reduce agency problems. However, since option values are sensitive to fluctuations in stock prices, and investors reward firms that meet or exceed earnings expectations, executives of firms with sizable option components in their compensation plans have increased incentives to report earnings that meet or exceed analysts' forecasts. We show that the propensity to meet or exceed analysts' quarterly earnings forecasts is positively related to the use of options in top executives' compensation plans. Further, firms that employ relatively more options in their compensation plans more frequently report earnings surprises that exceed analysts' forecast by small amounts (between 0 and 1 cent per share). These results suggest that the use of stock-based compensation intensifies top executives' focus on financial analysts' short-term earnings forecasts.     

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.     

Financial Analysts' Earnings Forecast Dispersion and Intraday Stock Price Variability Around Quarterly Earnings Announcements

This study investigates the relationship between the dispersion of analysts' earnings forecasts and stock price variability around quarterly earnings announcements. Consistent with theoretical predictions, the empirical analysis shows that stock price variability at the time of earnings announcements is positively related to the degree of analysts' predisclosure earnings forecast dispersion. Additionally, firms with high levels of forecast dispersion exhibit significant increases in price variability for longer periods prior to and following earnings announcements than do firms with low levels of forecast dispersion. These results suggest that there is information about the earnings announcement that becomes available to at least a subset of investors prior to the earnings release and that market participants take different amounts of time to process the information conveyed by the earnings announcement.     

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.     

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.     

Investors' Use of Historical Forecast Bias to Adjust Current Expectations

We explore the extent to which investor response to earnings information differs in the presence of historical bias in earnings forecasts. Overall, the results are consistent with the notion that investors take historical forecast bias into account when interpreting information in earnings announcements and that the market's reaction to forecast errors is larger (less negative) when forecasts are historically more optimistic and suggests that the functional form commonly used in the earnings response literature does not appropriately capture the effect of real unexpected earnings information (i.e., investors' expectation errors as opposed to analysts' forecast errors) on stock returns.     

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' 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.     

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。