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We evaluate the performance of financial analysts versus naïve models in making long-term earnings forecasts. Long-term earnings forecasts are generally defined as third-, fourth-, and fifth-year earnings forecasts. We find that for the fourth and fifth years, analysts' forecasts are no more accurate than naïve random walk (RW) forecasts or naïve RW with economic growth forecasts. Furthermore, naïve model forecasts contain a large amount of incremental information over analysts' long-term forecasts in explaining future actual earnings. Tests based on subsamples show that the performance of analysts' long-term forecasts declines relative to naïve model forecasts for firms with high past earnings growth and low analyst coverage. Furthermore, a model that combines a naïve benchmark (last year's earnings) with the analyst long-term earnings growth forecast does not perform better than analysts' forecasts or naïve model forecasts. Our findings suggest that analysts' long-term earnings forecasts should be used with caution by researchers and practitioners. Also, when analysts' earnings forecasts are unavailable, naïve model earnings forecasts may be sufficient for measuring long-term earnings expectations.

Financial analysts act as crucial conduits of information between firms and stakeholders. However, comparatively little is known about how these information intermediaries evaluate the believability and importance of corporate disclosures. We argue that a firm’s level of managerial discretion, or latitude of executive action, acts as a cue for financial analysts, which helps them interpret and respond to voluntary management earnings forecasts. Our study provides strong, robust evidence that financial analysts find management forecasts significantly less believable in low-discretion than in high-discretion environments, and therefore tend to be much less responsive to these forecasts. We also show that managerial discretion is especially impactful on analysts’ responses in those circumstances where analysts are typically most uncertain about how to interpret management forecasts.

Although prior research documents that analysts sometimes herd their forecasts, very few studies investigate how investors’ judgments are influenced by their perceptions of the likelihood of analyst herding. I conduct an experimental study to investigate the conditions under which investors’ assessments of uncertainty about future earnings are influenced by their perceptions of the likelihood of analyst herding. As expected, and consistent with motivated reasoning, the results show that the temporal order of analyst forecasts influences investors’ estimates of the likelihood of analyst herding and investors’ uncertainty judgments when analyst forecasts are preference-inconsistent but not when analyst forecasts are preference-consistent. This study provides a potential explanation for the mixed findings of prior research in regard to investors’ reactions to the likelihood of analyst herding. In addition, this study extends research on investors’ credulity by providing evidence that motivated reasoning and skepticism may serve as a mechanism that contributes to that credulity.

The aim of this paper is to analyze the impact of corporate governance (focused on some key mechanisms as board size, board independence, managerial ownership, institutional ownership, and chief executive officer duality) on financial analysts’ behavior in US. Results from panel data analysis for 294 US listed firms observed from 2007 to 2014 show that several attributes of the board of directors and audit committee have no effects on the number of analysts who are following the firm and the properties of analysts’ earnings forecasts. Findings also suggest that firms with independent and large boards and blockholders ownership benefit of more analyst following. In addition, it is proven that analysts’ earnings forecasts are optimistic and more accurate for companies where blockholder ownership, either by managers or external entities have larger quoted spreads but of lower quality for the ones which have greater independent board members and institutional investor’s holding.

Financial analysts' forecasts serve as a proxy for market earnings expectations, and research provides mixed evidence of the relation between financial analysts' expertise and forecast accuracy. The judgment and decision-making (J/DM) literature suggests that those with more expertise will not perform better when tasks exhibit either extremely high or extremely low complexity. Expertise is expected to contribute to superior performance for tasks between these two extremes. Using archival data, this research examines the effect of analysts' expertise on forecasting performance by taking into consideration the forecasting task's complexity. Results indicate that expertise is not an explanatory factor for forecast accuracy when the forecasting task's complexity is extremely high or low. However, when task complexity falls between these two extremes, expertise is a significant explanatory variable of forecast accuracy. Both results are consistent with our expectations.

We highlight two mechanisms of limited attention for expert information intermediaries, i.e., analysts, and the effects of such limited attention on the market price discovery process. We approach analysts' limited attention from the perspective of day-to-day arrival of information and processing of tasks. We examine the attention-limiting role of competing tasks (number of earnings announcements and forecasts for portfolio firms) and distracting events (number of earnings announcements for non-portfolio firms) in analysts' forecast accuracy and the effects of such, on the subsequent price discovery process. Our results show that competing tasks worsen analysts' forecast accuracy, and competing task induced limited attention delays the market price adjustment process. On the other hand, distracting events can improve analysts' forecast accuracy and accelerate market price adjustments when such events relate to analysts' portfolio firms through industry memberships.

Krull (2004) finds that US multinational corporations (MNCs) increase amounts designated as permanently reinvested earnings (PRE) to maximize reported after-tax earnings and meet earnings targets. We extend this research by examining the relationship between executive equity compensation and the opportunistic use of PRE by US MNCs, and the market reaction to earnings management using PRE designations. Firms use equity compensation to incentivize executives to strive for maximum shareholder wealth. One unintended consequence is that executives may engage in earnings management activities to increase their equity compensation. In this study, we examine whether the equity incentives of management are associated with an increased use of PRE. We predict and find strong evidence that the changes in PRE are positively associated with the portion of top managers' compensation that is tied to stock performance. In addition, we find this relationship to be strongest for firms that meet or beat forecasts, but only with the use of PRE to inflate income, suggesting that equity compensation incentivizes managers to opportunistically use PRE, especially to meet analyst forecasts.

Further, we provide evidence that investors react negatively to beating analysts' forecasts with the use of PRE, suggesting that investors find this behavior opportunistic and not fully convincing. This chapter makes an important contribution to what we know about the joint effects of tax policy, generally accepted accounting principles, and incentive compensation on the earnings reporting process.

Findings in the literature indicate leading financial analysts attract high levels of market attention and provide more accurate earnings forecasts prior to becoming all-star analysts. Furthermore, these analysts significantly impact the investment decisions of other market participants and thus the market price of assets. Therefore, this study examines the information role of leading financial analysts and identifies two significant conclusions. First, the positive outcomes of these analyst leaders are more informative and attract more followers. Second, informational herding by followers of these analysts is not as naïve as suggested in previous studies, as followers who smartly use information from analyst leaders tend to perform better. We also find that analysts who practice smart learning by studying and selectively employing analyst-leader decisions achieve better career outcomes.

In this study, we investigate whether higher institutional ownership is related to better internal controls and whether better internal control is associated with a higher quality of transparency.

In this paper, we investigate the information content of non-current assets (NCA) among firms listed on the main board of Bursa Malaysia. Specifically, we investigate the information content of tangible and intangible NCA during the economic crisis period of 1997–1998. Our empirical analysis uses time-varying and fixed effects models for the period 1995–1999. We measure information content based on the association of analysts’ earnings forecasts errors (AFE) with both capitalized tangible and intangible NCA. We find evidence of higher information content in tangible NCA compared to intangible NCA during the Asian economic crisis period of 1997–1998. Our evidence is consistent with the assumption that tangible assets are more reliable compared to intangible assets for prediction of expected cash flows during economic crisis periods.