UK Analysts' Earnings Forecasts

This paper reports the results of an empirical study of UK analysts' earnings forecasts for 126 firms for the years 1980 and 1981. Six hypotheses regarding the accuracy of these forecasts are tested, with results which both confirm and conflict with prior UK findings. In addition, evidence is found of a greater than generally attributed sensitivity of test results to the measure of accuracy used.     

Analysts' Incentives and Street Earnings

We examine whether analysts' incentives are associated with street earnings. Because prior research argues that analysts' incentives to promote stocks increase in the extent to which the stock exhibits glamour characteristics, we predict that analysts are more likely to make income-increasing adjustments in determining street earnings for glamour stocks than for value stocks. We find that analysts are more likely to exclude expense items from street earnings for glamour stocks than for value stocks and that excluded expense items help predict future earnings for glamour stocks but not for value stocks. Overall, our results suggest that analysts' self-interest influences street earnings and this self-interest leads to street earnings that are less useful in predicting future earnings for glamour stocks.     

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.     

Rational Expectations and Security Analysts' Earnings Forecasts

This paper investigates the rationality of security analysts' forecasts. The forecasts of analysts participating in Lynch, Jones, and Ryan's Institutional Brokers Estimate System (I/BE/S) data base are evaluated relative to past values of their own forecast errors, past values of forecasted earnings per share, and quarterly percentage changes in publicly available macroeconomic and financial time series. The publicly available series include the consumer price index, unemployment rate, oil prices, stock prices, gross national product, and corporate profits. The authors conduct a generalized orthogonality test and include only information available to analysts at the time the forecasts are made. The empirical results reject analyst forecast rationality, but not without exception.     

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.     

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.     

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。     

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.     

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.     

The Effect of Issuing Biased Earnings Forecasts on Analysts' Access to Management and Survival

This study offers evidence on the earnings forecast bias analysts use to please firm management and the associated benefits they obtain from issuing such biased forecasts in the years prior to Regulation Fair Disclosure. Analysts who issue initial optimistic earnings forecasts followed by pessimistic earnings forecasts before the earnings announcement produce more accurate earnings forecasts and are less likely to be fired by their employers. The effect of such biased earnings forecasts on forecast accuracy and firing is stronger for analysts who follow firms with heavy insider selling and hard‐to‐predict earnings. The above results hold regardless of whether a brokerage firm has investment banking business or not. These results are consistent with the hypothesis that analysts use biased earnings forecasts to curry favor with firm management in order to obtain better access to management's private information.     

Improving the Precision of Analysts' Earnings Forecasts by Adjusting for Predictable Bias

This research demonstrates that publicly-available information can be used to develop estimates of analysts' optimistic bias in earnings forecasts. These bias estimates can be used to produce more accurate forecasts, resulting in significant reductions of both cross-sectional mean forecast error and error variance. When bias estimates are based on past observations of forecast error alone, however, reductions in mean forecast error are smaller, and forecast precision is unimproved. Further tests provide evidence of a significant association between returns and the bias predictable from contemporaneously-available information, suggesting that predictable bias is only partially discounted by market participants. This study has significant implications for researchers and investors. The pricing of predictable bias in analysts' forecasts may add error toinferences which are based on the association between returns and analyst forecast errors, and knowledge of the market's partial discounting of predictable bias may help investors to make more efficient resource allocations.     

Intraday Stock Price Reactions to Interim-Quarter versus Fourth-Quarter Earnings Announcements

This study investigates intraday patterns of quarterly return-earnings relations. We find that fourth quarter announcements exhibit a lower earnings response coefficient but a more rapid adjustment to new equilibrium levels of prices and a higher R2 than interim quarter announcements. While prior short event window studies document that interim quarter earnings have greater explanatory power than fourth quarter earnings or annual earnings, our analysis indicates that the prior results may be driven by the use of two-day event window that is much wider than what it takes for the market to adjust to fourth quarter announcements.     

年报风险信息披露有助于提高分析师预测准确度吗?

年报风险信息披露既可能提高信息质量而对分析师预测行为产生积极影响,又可能因增加分析师的风险感知而对分析师预测行为产生消极影响。本文通过文本分析法量化年报风险信息披露,进而探讨其对分析师预测准确度的影响。基于公司层面的证据表明:风险信息披露频率越高,分析师预测准确度越高,而且这种积极影响主要体现在非国有企业、盈余质量较高及公司治理较好组。基于分析师层面的证据表明:风险信息披露频率越高,分析师预测准确度越高,这种积极影响主要体现在非明星、行业专长较低、对公司追踪时间较少的分析师中。这说明我国年报风险信息异质性较弱,有助于提高分析师预测准确度,从而支持了风险信息披露的信息观。本文结论有助于丰富信息披露以及分析师预测文献。     

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 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.     

Effects of Preannouncements on Analyst and Stock Price Reactions to Earnings News

This study examines the effects of earnings preannouncements on financial analyst and stock price reactions to earnings news. Prior experimental research documents that when the signs of a preannouncement surprise and subsequent earnings announcement surprise are consistent (i.e., both either positive or negative), analysts make larger magnitude revisions to their future period earnings forecasts in response to the total earnings news conveyed in the preannouncement and earnings announcement than when the surprise signs are inconsistent. This study extends this research by examining a sample of actual preannouncements from 1993–1997 to determine whether the effects documented in laboratory settings manifest at the aggregate market level in stock prices and consensus analyst forecast revisions. Results indicate that after controlling for the sign of earnings news, sign of earnings, and sign of the earnings announcement surprise, stock prices and analyst forecast revisions respond more strongly when a preannouncement and subsequent earnings announcement elicit the same surprise signs than when the surprise signs are inconsistent. Further analysis indicates that the consistency of the signs of a preannouncement surprise and earnings announcement surprise is not associated with future earnings, suggesting that the magnified reaction of investors and analysts to consistent surprise signs is not a rational reaction to associations observed in market settings.     

Effect of Analysts' Optimism on Estimates of the Expected Rate of Return Implied by Earnings Forecasts

Recent literature has used analysts' earnings forecasts, which are known to be optimistic, to estimate implied expected rates of return, yielding upwardly biased estimates. We estimate that the bias, computed as the difference between the estimates of the implied expected rate of return based on analysts' earnings forecasts and estimates based on current earnings realizations, is 2.84%. The importance of this bias is illustrated by the fact that several extant studies estimate an equity premium in the vicinity of 3%, which would be eliminated by the removal of the bias. We illustrate the point that cross‐sample differences in the bias may lead to the erroneous conclusion that cost of capital differs across these samples by showing that analysts' optimism, and hence, bias in the implied estimates of the expected rate of return, differs with firm size and with analysts' recommendation. As an important aside, we show that the bias in a value‐weighted estimate of the implied equity premium is 1.60% and that the unbiased value‐weighted estimate of this premium is 4.43%.     

Investor and Analyst Reactions to Earnings Announcements of Related Firms: An Empirical Analysis

In this article I examine the response of investors and analysts of nonannouncing firms to the earnings report of the first announcers in the industry. The error in the earnings forecast of the first announcer is found to be informative about the errors in the contemporaneous earnings forecasts of subsequent announcers in the industry. However, investors and analysts do not appear to fully incorporate the information from the first announcers' news in their revised earnings expectations for subsequent announcers. This apparent underreaction to the first announcers' news leads to predictable stock returns for subsequent announcers in the days following the first announcement. Results of this study can be seen as further evidence of investor and analyst underreaction to publicly available information.     

Dispersion of Financial Analysts' Earnings Forecasts and the (Option Model) Implied Standard Deviations of Stock Returns

This study examines whether the information implied by simultaneous levels of option and stock prices (specifically, the implied standard deviation of returns) reflects other contemporaneously available information. The independent contemporaneous measure considered is the observed dispersion (across several financial analysts), at a point in time, in the forecasts of earnings per share for a given firm. The results indicate that implied standard deviations clearly reflect the contemporaneous dispersion in analysts' forecasts incrementally, i.e., beyond the information contained in the historical time series of returns.