Accuracy Of Analysts Research Articles

Earnings Uncertainty and Analyst Forecast Herding*

AbstractThis study empirically investigates how a firm's earnings uncertainty affects analysts' herding behaviors in earnings forecasts. Trueman (1994) and Graham (1999) analytically predict that analysts have higher incentives to issue a herding forecast when a firm's earnings uncertainty is low. We test this analytical prediction using a proxy for bold forecasts used by Gleason and Lee (2003) and Clement and Tse (2005). We classify analysts' earnings forecasts as bold when an analyst's revised forecast is larger (or smaller) than both the analyst's own prior forecast and the mean consensus forecast of other analysts immediately prior to the analyst's forecast. Earnings uncertainty is measured by standard deviation of time‐serial earnings forecast errors. A logit regression result shows a positive relation between bold forecasts and earnings uncertainty after controlling for analyst characteristics, which is consistent with the prediction by Trueman (1994) and Graham (1999). We also find that as earnings uncertainty increases, the accuracy of analysts' bold forecasts relative to consensus forecast accuracy also increases. These results imply that analysts are active in producing new relevant information about firms when earnings uncertainty is higher.

International evidence on the relative importance of the determinants of earnings forecast accuracy

We analyze earnings forecasting errors made by financial analysts for 18 developed countries over the 1990–2006 period. We use the Heston–Rouwenhorst approach to unravel country -, industry-, and firm-specific effects as a source of variation in financial analysts’ earnings forecast errors. We first estimate each effect with a dummy variable regression, and then decompose the variance of forecast errors into different effects. We provide evidence that the differences between countries, industrial sectors, and analyst-following offer a weak explanation for differences in forecast errors. Country effects however largely dominate industry and analyst-following effects. By contrast, the type of earnings (profits or losses)—and variations in earnings (increases or decreases) play a significant role in the forecast accuracy of financial analysts.

Which Matters? Accuracy or Boldness? Analysts Earnings Forecast and Institutional Holdings

This paper aims to investigate the effect of financial analysts' earnings forecast on the institutional trading. In specific, we address three issues regarding the effect of financial analysts earnings forecast on the institutional holdings: (1) Do institutional investors pay more attention and more sensitive to analyst earnings forecast with higher forecast accuracy? (2) Do institutional investors prefer analysts with higher accuracy on earnings forecast? (3) Do institutional investors prefer analysts with bold attitude toward earnings forecast? Firstly, our empirical results show that institutional investors do pay attention to the accuracy of financial analysts earnings forecast. That is, firms with higher accuracy of analysts' earnings forecast tend to attract more institutional investors' attention and thus higher institutional holdings. Secondly, our results evidence that institutional investors prefer analysts with higher accuracy in their earnings forecast. That means institutional investors tend to follow more closely those analysts whose earnings forecasts are more accurate. Finally, we find that institutional investors in general are indifferent to the boldness of analysts earnings forecast. However, institutional investors will pay more attention and follow more closely those analysts whose earnings forecasts are not only accurate but also close to the consensus.

Do investors learn about analyst accuracy? A study of the oil futures market

AbstractWe study the impact of analyst forecasts on prices to determine whether investors learn about analyst accuracy. The straight‐forward relationship between supply and price, the economic importance of the market, the predictable timing of forecast error realizations, and the high frequency of the data make the crude oil market an interesting and advantageous setting. We find that prices rise (fall) when analysts forecast a decrease (increase) in supplies. During the 15 minutes following supply announcements, prices rise (fall) when forecasts have been too high (low). Importantly, both relationships are stronger for more accurate analysts, implying that investors learn about analyst accuracy. © 2009 Wiley Peridocals, Inc. Jrl Fut Mark 29:414–429, 2009

Theory on the Association between Audit Quality and the Accuracy and Dispersion of Analysts’ Earnings Forecasts

In this study, we establish a link between audit quality and various characteristics of analysts’ earnings forecasts (i.e., accuracy and dispersion) and present theory which suggests that the audit quality enhances the market’s earnings expectation. Our proposition is that enhancing audit quality improves the quality of accounting numbers, which in turn affects analysts’ forecasting ability. Although prior empirical studies investigated this relation by using various proxies, none of them directly show the relation with theoretical base. In this paper, we model that accounting earnings are in autoregressive process and influenced by earnings shock. The earnings shock is composed of unpredictable random shock and accounting errors. Then we show that high-quality audit can reduce the accounting errors which in turn influence the analysts’ earnings forecasts. The model’s predictions are: (1) forecast accuracy is higher, and (2) forecast dispersion is smaller for

Market Reactions to Warnings of Negative Earnings Surprises: Further Evidence

Abstract: This study examines two plausible explanations for Kasznik and Lev's (1995) counterintuitive finding that warning firms are subject to more negative market returns than no‐warning firms. Namely, are the more negative market reactions to warning firms due to their poorer future earnings performance or due to investor overreaction? I find that, compared with no‐warning firms, warning firms experience more severe one‐year‐ahead earnings declines and these earnings declines can explain the stronger market returns to warning firms. However, my results do not support an investor overreaction explanation. The tests of subsequent abnormal returns of warning firms over various windows do not detect stock return reversals due to correction for overreaction. In addition, the greater revisions in analysts' forecasts for warning firms are found to enhance analyst accuracy rather than increase analyst pessimism. Collectively, my results suggest that the more negative market reactions to warning firms reflect investors' rational anticipation of more severe declines in future earnings for warning firms rather than investor overreaction.

Internal Control Material Weakness, Analysts' Accuracy and Bias, And Brokerage Reputation

Using a sample of firms that disclose internal control material weaknesses under Sections 302 and 404 of the Sarbanes-Oxley Act, we investigate the relations between the accuracy and bias of financial analysts' earnings forecasts and disclosed internal control material weaknesses. We find that forecast accuracy is negatively related to material weaknesses in internal control when disclosed internal control material weaknesses are related to controls over firms' broader control environment (firm-level internal control). We also hypothesize and find that optimistic forecast bias is higher for firms disclosing firm-level internal control material weaknesses, suggesting that, due to the increased complexity related to inefficient internal control at firm-level, analysts intentionally bias their forecasts upward to gain favorable access to firms' internal information. In addition, we find that the optimistic bias only exists in forecasts issued by analysts who are affiliated with less reputable brokerage houses.

Patterns in Analysts' Long-Term Earnings Forecasts

This article examines the accuracy of analysts9 long-term estimates (made before the beginning of the year being forecast) of annual operating earnings during the 1986–2002 period, as provided in the Thomson First Call I/B/E/S database. The article asks whether an investor can use the pattern of a particular analyst9s earnings estimates as a way of discerning analyst accuracy; that is, whether there are biases or signals in those patterns. Examining the change between consecutive earnings estimates, we find larger changes (negative or positive) are associated with lower forecast accuracy. Examining the difference between an analyst9s estimate of earnings and the previous year9s actual earnings in joint tests, we find that estimates predicting larger increases in earnings are decreasingly accurate, but those predicting larger decreases in earnings are increasingly accurate. Examining the number of estimates produced by an analyst as a signal of quality, we find no relationship in univariate tests, although one has been reported previously in the literature; in joint tests, a negative relationship is found between forecast frequency and accuracy. <b>TOPICS:</b>Security analysis and valuation, fundamental equity analysis, quantitative methods, statistical methods

The accuracy of analysts' dividend forecasts around the world

We examine the link between the accuracy of consensus analysts' dividend forecasts, earnings predictability and dividend policies of firms in 39 countries from 1995 to 2004. For firms that display stronger dividend smoothing, as modeled by Lintner [Lintner, J., 1956. Distribution of incomes of corporations among dividends, retained earnings and taxes. American Economic Review 46, 97–113], there is a lower correlation between dividend and earnings forecast errors, with less of the earnings uncertainty being passed into dividend uncertainty. The link between earnings and dividend forecast errors is weaker in common-law, capital market-based countries and in countries with well-developed financial (debt and equity) markets, where firm managers have greater incentives to smooth dividends and to use dividends for signaling.

Managerial Ownership and Information Opacity

This study examines the effect of equity ownership by managers on a firm's information environment vis-a-vis its effect on analyst forecast accuracy and analyst following. We collect a sample of over 26,000 observations on managerial ownership during 1988-2002 and find that managerial ownership is negatively related to both the accuracy of analysts' consensus earnings forecasts and analyst coverage. Interestingly, this negative relation is most pronounced for firms with impending We also find that firms with greater managerial ownership are less likely to issue a management earnings forecast, particularly in anticipation of bad news. Our results are consistent with the view that managerial entrenchment leads to information opacity, reducing forecast accuracy and discouraging analyst coverage. We further document a positive relation between analyst coverage and firm value, particularly for firms with greater managerial ownership and a relatively poor governance structure, suggesting that investors view analyst coverage as an alternative governance mechanism to mitigate managerial entrenchment. However, our evidence of reduced analyst following indicates that this monitoring activity appears to be lacking when it would be most beneficial.

Evaluation of Video Technology for Monitoring of Multispecies Longline Catches

AbstractAt‐sea catch monitoring of the Alaskan longline fishery for Pacific halibut Hippoglossus stenolepis is insufficient. The International Pacific Halibut Commission (IPHC) conducted studies in 2002 and 2004 comparing catch composition data from electronic monitoring (EM) systems to those of at‐sea observers. The EM systems use automated data loggers linked to digital video cameras, a transducer on shipboard hydraulic systems, and a global positioning system receiver. The goal of both studies was to determine whether EM technologies could provide precise and verifiable catch composition data on commercial longline vessels to supplement and complement the data collected by fisheries observers. The EM video analyst's catch data were similar to the observers' data in the 2002 study; however, the video analyst recorded fewer fish for 7 of the 17 species categories investigated. In 2004, the IPHC employed EM technology in another study incorporating recommendations from the 2002 study, including improved camera configurations. The video analyst's data showed increased agreement with the observer data. However, the observers recorded slightly fewer individuals of some species categories, opposite the findings of the 2002 study. This change suggests that incorporating the technology recommendations enhanced the video analyst's accuracy relative to the observer data. Our analysis also highlights the fact that data provided by human observers have their own suite of errors and that the comparisons between EM and observers have no absolute standard of reference. The findings indicate that EM technology can effectively address the lack of catch composition data in the Pacific halibut and other hook‐and‐line fisheries in Alaska.

Predictive gains to segmental disclosure matrices, geographic information and industry sector comparability

The aim of this study is to provide a detailed analysis of the multi-dimensional characteristics of segmental reporting, and their impact on improving investor-insight. We do this by examining the ability of segmental reporting characteristics among FTSE-100 firms to explain variation in the accuracy of analysts’ forecasts of earnings per share. We find that analyst-insight is significantly improved by the provision of data within a business-geographical matrix format, consistent with prior ‘laboratory’ evidence and UK analysts’ stated opinions in surveys. We also find that analyst-insight is improved where firms provide information regarding differences between their geographic markets and origins. In addition, analysts obtain improved insight from business segments that have a high degree of comparability to their respective industry sectors and where geographic segments are reported in a detailed manner.

Is Analyst Earnings Forecast Ability Only Firm-Specific?

The state of the art in the analyst forecasting literature is that earnings forecast ability is firm-specific (Chen, Francis, and Jiang 2005; Chen and Jiang 2006). This view is based on Park and Stice (2000)'s finding of the absence of a spillover effect; i.e., when reacting to analyst forecast revisions of firm j, investors ignore analyst forecast ability with respect to firm k. We provide an economic rationale for the absence of a spillover effect. We demonstrate that firm-specific ability is far more important than the spillover effect for the purpose of distinguishing between superior and inferior analysts in holdout periods, suggesting that investors are rational to pay little heed to this effect. We examine the issue of whether analyst earnings forecast ability is firm specific by introducing a general ability effect, defined as analyst accuracy for all the other firms s/he follows. We show that general ability is far more important than firm-specific ability for the purpose of distinguishing between superior and inferior analysts in holdout periods. We also document that investors are rational with respect to general ability; when reacting to analyst forecast revisions, they pay more attention to general ability than to firm-specific ability. We conclude that analyst earnings forecast ability is not firm-specific and that investors are rational regarding the relative attention they pay to general ability (much), firm-specific ability (some) and the spillover effect (none).

Measure for Measure: The Relation between Forecast Accuracy and Recommendation Profitability of Analysts

ABSTRACTWe examine the contemporaneous relation between earnings forecast accuracy and recommendation profitability to assess the effectiveness with which analysts translate forecasts into profitable recommendations. We find that, after controlling for expertise, more accurate analysts make more profitable recommendations, albeit only for firms with value‐relevant earnings. Next, we show that conflicts of interest from investment banking activities affect the relation between accuracy and profitability. In the case of buy recommendations, more accurate forecasts are associated with more profitable recommendations only for the nonconflicted analysts. For hold recommendations, higher levels of accuracy are associated with higher levels of profitability for conflicted analysts, provided these recommendations are treated as sells. Finally, we find that regulatory reforms aimed at mitigating analyst conflicts of interest appear to have improved the relation between accuracy and profitability. Specifically, the integrity of buy and hold recommendations has improved and the change is more pronounced for analysts expected to be most conflicted.

The impact of regulation fair disclosure on earnings management and analyst forecast bias

Regulation Fair Disclosure (FD) has changed the information transfer process in the US securities market. We examine the impact that regulation FD has had on earnings management and analyst forecast bias. First, we examine the accuracy of financial analysts' earnings forecasts in the post-FD period. We find that analysts have become less accurate in forecasting earnings in the post-FD period and tend to overestimate earnings more relative to the pre-FD period. Second, we examine the level of earnings management after the passage of regulation FD and we find that the level of earnings management did not change after the implementation of regulation FD

The Impact of the Cadbury Committee Recommendations on Analysts' Earnings Forecasts: UK Evidence

This paper examines the relationship between the board structure of UK firms and the accuracy of individual analysts’ earnings forecasts with respect to information asymmetry and agency theory. We hypothesize that managers of firms complying with the recommendations of The Code of Best Practice may have “less to hide” and, subsequently, provide more information to outsiders (including analysts), thus facilitating more accurate analysts’ forecasts. We find that analysts are more optimistic, but less accurate, for firms with a greater proportion of nonexecutive directors. This indicates that non-executive directors are inefficient at addressing the agency disclosure problem (at least in terms of the accuracy of analysts’ earnings forecasts).

Does the financial analysts' usage of non-financial information influence the analysts' forecast accuracy? Some evidence from the Belgian sell-side financial analyst

This paper examines whether the use of non-financial information by sell-side financial analysts influences the accuracy of analysts’ forecasts. The research findings, based on a survey of Belgian financial analysts, suggest that financial analysts who use more forward-looking information and more internal-structure information offer more accurate forecasts. Furthermore, the listed Belgian firms examined in this study have improved their non-financial information reporting over time. However, neither the frequency nor the quantity of non-financial information mentioned by financial analysts in their reports appears to have increased over time.

Analysts' Awareness of Systematic Bias in Management Earnings Forecasts: Empirical Evidence from Japan

The effectively mandatory provision of management earnings forecasts (MEF) is an unique feature of Japan's financial disclosure system. The first objective of this study is to identify the determinants of systematic bias in MEF using a sample of nearly 25,000 one-year-ahead earnings forecasts announced by Japanese firms at the beginning of a fiscal year over the period 1979-1999. The examination of ex post management forecast errors shows that financial distress, firm growth, firm size, and prior forecast errors are all associated with bias in MEF. The second objective of this study is to investigate whether analysts are aware of these factors that are related to systematic bias in MEF. The examination of analysts' forecasts issued subsequent to the announcement of management forecasts reveals that analysts take these factors into consideration when they issue their own earnings forecasts. These findings indicate that analysts are well aware of the determinants of systematic bias in MEF and make correct adjustments that lead to the higher accuracy of analysts' forecasts than management forecasts.

Does corporate governance transparency affect the accuracy of analyst forecasts?

AbstractUsing country‐level proxies for corporate governance transparency, this paper investigates how differences in transparency across 21 countries affect the average forecast accuracy of analysts for the country's firms. The association between financial transparency and analyst forecast accuracy has been well documented in previous published literature; however, the association between governance transparency and analyst forecast accuracy remains unexplored. Using the two distinct country‐level factors isolated by Bushman et al. (2004), governance transparency and financial transparency, we investigate whether corporate governance information impacts on the accuracy of earnings forecasts over and above financial information. We document that governance transparency is positively associated with analyst forecast accuracy after controlling for financial transparency and other variables. Furthermore, our results suggest that governance‐related disclosure plays a bigger role in improving the information environment when financial disclosures are less transparent. Our empirical evidence also suggests that the significance of governance transparency on analyst forecast accuracy is higher when legal enforcement is weak.

Do Investors Learn About Analyst Accuracy?

We study the impact of analyst forecasts on prices to determine whether investors learn about analyst accuracy. Our test market is the crude oil futures market. Prices rise when analysts forecast a decrease (increase) in crude supplies. In the 15 minutes following supply realizations, prices rise (fall) when forecasts have been too high (low). In both the initial price action relative to forecasts and in the subsequent reaction relative to realized forecast errors, the price response is stronger for more accurate analysts. These price reactions imply that investors learn about analyst accuracy and trade accordingly.