Analysts' Rationality and Forecast Bias: Evidence from Sales Forecasts

When optimistic forecasts can improve access to management, rational analysts have incentives to issue optimistically-biased forecasts (Lim, 2001). This paper proposes that the extent of this optimistic forecast bias will depend on the forecast's importance to management. If management attaches less importance to a forecasted measure, analysts should decrease their forecast bias because the expected benefits of issuing optimistic forecasts are less. We examine analysts' earnings and sales forecasts, and predict that analysts' optimistic bias will be greater for earnings than for sales. Results are consistent with our predictions and contribute to the evidence that analysts' forecast bias is rational and intentional.     

Analyst Earnings Forecasts for Publicly Traded Insurance Companies

Several trends in the insurance and financial services industry, including demutualizationconsolidation, and deregulation, have attracted increasing attention from investors and financial analysts. This paper investigates the accuracy of the earnings forecasts of financial analysts for insurance companies. Our empirical results indicate that analyst forecasts outperform random walk time-series forecasts. Furthermore, we find that both disagreement over earnings forecasts among analysts and the relative forecasting error in the mean forecasts is smaller for life insurers than for property-casualty insurers, whereas the relative errors for forecasts for multiple-line insurers are in between the two. Forecasting error is a negative function of firm size and the number of analysts who are following a company, and is a positive function of the disagreement among analysts.Analyst forecasts have a timing advantage over the random walk model. Our results also suggest that the fair value reporting requirement (SFAS 115), which has been in effect since 1994, has enhanced the accuracy of analyst forecasts. The SFAS 115 has improved the superiority of analyst forecasts over the random walk forecasts for life insurers, but not for property-casualty insurers, and there is a weak improvement for multiple-line insurers. JEL Classification: G15     

Analysts' Forecasts and the Broker Relationship

Analysts' ability to forecast earnings per share has been the subject of considerable debate. A concern highlighted in previous research is the agency problem which may arise when analysts have a close working relationship with the firms for which they are providing forecasts. This paper provides evidence that this relationship does not improve the accuracy of the earnings forecasts, but stimulates optimistic forecasts. In addition, the paper examines whether firm size is a factor in forecast accuracy or bias.     

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.     

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.     

Analysts' Forecasts Following Forced CEO Changes

This paper examines analysts' earnings forecasts during the period of uncertainty following a change of chief executive officer (CEO). It distinguishes between forced and non‐forced CEO changes, and examines whether analysts utilize their information advantage to reduce the heightened uncertainty of a forced change of CEO. Examining a sample of Australian companies followed by analysts between 1999 and 2009, we find that forecasting accuracy is lower and earnings forecasts are more optimistic for firms experiencing forced CEO turnover compared to firms not undergoing such a change. However, dispersion is not statistically different. The results suggest that forced CEO turnover events provide a challenge to the forecasting environment for analysts. During CEO changes, investors should be aware that forecasts are less accurate and have an optimistic bias.     

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.     

The Quality of Analysts' Earnings Forecasts During the Asian Crisis: Evidence from Singapore

We bring together three disparate strands of literature to develop a comprehensive empirical framework to examine the efficiency of security analysts' earnings forecasts in Singapore. We focus specifically on how the increased uncertainty and the negative market sentiment during the period of the Asian crisis affected the quality of earnings forecasts. While we find no evidence of inefficiencies in the pre-crisis period, our results suggest that after the onset of the crisis, analysts (1) issued forecasts that were systematically upward biased; (2) did not fully incorporate the (negative) earnings-related news; and (3) predicted earnings changes which proved too extreme.     

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.     

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.     

The Implications of Dispersion in Analysts' Earnings Forecasts for Future ROE and Future Returns

Dispersion in analysts' forecasts is empirically evaluated by associating dispersion with a firm's future accounting rate of return-on-equity (ROE) and future returns. Forecast dispersion is significantly and negatively associated with future ROE, consistent with the notion that firm disclosures and analysts' information acquisition efforts increase as firm prospects improve. Forecast dispersion is negatively associated with future returns. This appears due to the implications of dispersion for future ROE, and suggests that the market does not immediately assimilate the information contained in forecast dispersion. Dispersion also conveys information about firm-specific risk not captured by beta and firm size.     

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.     

An Empirical Analysis of the Bias and Rationality of Profit Forecasts Published in New Issue Prospectuses

Our study sets out to assess the accuracy of profit forecasts made by IPOs in Hong Kong. We use a variety of measures and tests to examine the accuracy, bias, rationality, and superiority of earnings estimates. The results show that forecast accuracy compares favourably with the findings from the developed economies of Australia, Britain, Canada, and New Zealand. Forecasts are shown to be superior to the predictions from time series models. IPOs tend to underforecast in the sense that actual profits exceed the forecasts. The rationality tests show mixed results. Cross-sectional analyses of forecast accuracy have poor explanatory power although the Big Six reporting accountants are associated with smaller forecast errors.     

分析师留学经历与盈利预测质量

基于2005-2015年期间的分析师预测数据,本文研究发现,相对于非留学分析师,具有海外留学经历的分析师的预测准确性更低,通过分组检验发现,上述结果主要存在于分析师的从业初期和分析师与企业高管之间不具有社会关系时。进一步研究发现,分析师留学越早,时间越长,其预测准确性相对越低。另外,当企业公开信息质量较高时,海外留学分析师与非留学分析师在预测准确性上的差异消失。由此可见,在我国关系型社会中,海外留学归国分析师在认知和获取私有信息方面存在相对劣势,其并没有提供更高质量的盈余预测。本文的研究发现丰富了有关分析师预测质量的研究文献,同时也为当前规范和提高企业信息披露质量的制度改革提供了资本市场的经验证据。     

An Empirical Analysis of the Bias and Rationality of Profit Forecasts Published in New Issue Prospectuses

Our study sets out to assess the accuracy of profit forecasts made by IPOs in Hong Kong. We use a variety of measures and tests to examine the accuracy, bias, rationality, and superiority of earnings estimates. The results show that forecast accuracy compares favourably with the findings from the developed economies of Australia, Britain, Canada, and New Zealand. Forecasts are shown to be superior to the predictions from time series models. IPOs tend to underforecast in the sense that actual profits exceed the forecasts. The rationality tests show mixed results. Cross-sectional analyses of forecast accuracy have poor explanatory power although the Big Six reporting accountants are associated with smaller forecast errors.     

Fundamental Information and Monetary Policy: The Implications for Earnings and Earnings Forecasts

Building on the work of Lev and Thiagarajan (1993) and Abarbanell and Bushee (1997 and 1998) this paper tests whether market-based information including dividend yield (Fama and French, 1998), firm size (Reinganum, 1981), and the ratio of book value to market value (Fama and French, 1992) add explanatory power to accounting data for predicting future earnings. The paper also tests whether earnings changes and the predictability of those changes are conditioned on monetary policy. It is found that the ratio of book value to market value is significantly related to earnings changes. Analyst forecast accuracy differs depending on monetary policy regime, but this difference is not due to differing interpretation of fundamental signals on financial statements appearing under differing monetary policy regimes. It is also found that there is a significant relation between monetary policy, earnings changes, and the level of signals concerning earnings changes.     

Management of Earnings and Analysts' Forecasts to Achieve Zero and Small Positive Earnings Surprises

Abstract:  This paper corroborates the finding of prior studies that managers avoid reporting earnings lower than analyst forecasts (i.e., negative earnings surprises) and provides new evidence of actions contributing to this phenomenon. Specifically, we provide empirical evidence of both (1) upward management of reported earnings and (2) downward 'management' of analysts' forecasts to achieve zero and small positive earnings surprises. Further analysis of the components of earnings management suggests that both the operating cash flow and discretionary accruals components of earnings are managed.     

The Value of Crowdsourced Earnings Forecasts

Crowdsourcing—when a task normally performed by employees is outsourced to a large network of people via an open call—is making inroads into the investment research industry. We shed light on this new phenomenon by examining the value of crowdsourced earnings forecasts. Our sample includes 51,012 forecasts provided by Estimize, an open platform that solicits and reports forecasts from over 3,000 contributors. We find that Estimize forecasts are incrementally useful in forecasting earnings and measuring the market's expectations of earnings. Our results are stronger when the number of Estimize contributors is larger, consistent with the benefits of crowdsourcing increasing with the size of the crowd. Finally, Estimize consensus revisions generate significant two‐day size‐adjusted returns. The combined evidence suggests that crowdsourced forecasts are a useful supplementary source of information in capital markets.     

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.     

Japanese Corporate Groupings (Keiretsu) and the Characteristics of Analysts' Forecasts

This study examines differences in the characteristics of analysts' forecasts of earnings for keiretsu and non-keiretsu firms in Japan. Japanese industrial organization is characterized by enterprise groupings, keiretsu, composed of firms in different industries, but interrelated through cross-holdings of ownership. The strong interrelations of the Japanese keiretsu have been shown to increase the monitoring of managerial performance. An alternative view of keiretsu stewardship suggests the exclusionary environment within a keiretsu creates an information monopoly, resulting in greater information asymmetry between inside and outside constituents. These two views provide opposing predictions on how keiretsu groupings potentially affect the characteristics of earnings forecasts made by analysts: increased monitoring will improve the forecast characteristics of earnings, while the opposite is true under an information monopoly.Our results suggest that forecast accuracy (dispersion) is higher (lower) for keiretsu firms than non-keiretsu firms, supporting a monitoring role by keiretsu. The results also show that keiretsu firms' forecast characteristics are related to the strength of the keiretsu relationship, providing further evidence that it is indeed the keiretsu relationship that increases the monitoring of management, which ultimately improves the accuracy and dispersion of analysts' forecast.