Do investor expectations affect sell-side analysts’ forecast bias and forecast accuracy?

We examine the association between investor expectations and its components and sell-side analysts’ short-run quarterly earnings forecast bias and forecast accuracy. To measure investor expectations, we use the Index of Consumer Expectations survey and decompose it into the “fundamental” component related to underlying economic factors (FUND) and the “sentiment” component unrelated to underlying economic factors (SENT). We find that analysts are the most optimistic and the least accurate when SENT is higher. Management long-horizon earnings forecasts attenuate the effects of SENT on forecast optimism and forecast accuracy. Analysts are also the most accurate when FUND is higher. Last, the market places more weight on unexpected earnings when SENT is high. These findings suggest that analysts are affected by investor sentiment and the market reacts more strongly to unexpected earnings when analyst forecasts are the least accurate. The last result potentially explains why prior research (for example, Baker and Wurgler, The Journal of Finance 61:1645–1680, 2006) finds an association between investor sentiment and cross-sectional stock returns.     

Determinants of analysts’ revenue forecast accuracy

This study investigates financial analysts’ revenue forecasts and identifies determinants of the forecasts’ accuracy. We find that revenue forecast accuracy is determined by forecast and analyst characteristics similar to those of earnings forecast accuracy—namely, forecast horizon, days elapsed since the last forecast, analysts’ forecasting experience, forecast frequency, forecast portfolio, reputation, earnings forecast issuance, forecast boldness, and analysts’ prior performance in forecasting revenues and earnings. We develop a model that predicts the usefulness of revenue forecasts. Thereby, our study helps to ex ante identify more accurate revenue forecasts. Furthermore, we find that analysts concern themselves with their revenue forecasting performance. Analysts with poor revenue forecasting performance are more likely to stop forecasting revenues than analysts with better performance. Their decision is reasonable because revenue forecast accuracy affects analysts’ career prospects in terms of being promoted or terminated. Our study helps investors and academic researchers to understand determinants of revenue forecasts. This understanding is also beneficial for evaluating earnings forecasts because revenue forecasts reveal whether changes in earnings forecasts are due to anticipated changes in revenues or expenses.     

Internal control material weakness, analysts’ accuracy and bias, and brokerage reputation

The main purpose of this paper is to examine the impact of internal control material weaknesses (ICMW hereafter) on sell side analysts. We find that ICMW reporting firms have less accurate analyst forecasts relative to non-reporting firms when the reported ICMWs belong to the Pervasive type. ICMW reporting firms have more optimistically biased analyst forecasts compared than non-reporting firms. The optimistic bias exists only in the forecasts issued by the analysts affiliated with less-highly-reputable brokerage houses. The differences in accuracy and bias between ICMW and non-ICMW firms disappear when ICMW disclosing firms stop disclosing ICMWs. Collectively, our results suggest that the weaknesses in internal control increases forecasting errors and upward bias for financial analysts. However, a good brokerage reputation can curb the optimistic bias.     

Political patronage and analysts’ forecast precision

We test whether the channel by which the government plays the role of political patron to selected firms influences analysts’ forecast precision in Malaysia. Correcting for analysts’ self-selection bias, we find a negative relation between analysts’ forecast errors and the social dimension of political patronage, as proxied by government-controlled institutional ownership. The reverse is found for the economic dimension of political patronage, as proxied by the percentage shareholding of government-linked corporations. We find no evidence that the personal dimension of political patronage influences analysts’ forecast precision.     

Economic policy uncertainty and analysts’ forecast characteristics

We examine the influence of economic policy uncertainty (EPU) on the characteristics of analysts’ earnings forecasts over a thirty-year period, spanning a wide variety of political and economic conditions. Motivated by both theory and empirical evidence that suggest a decline in the quality of the information environment for firms as EPU increases, we establish that analysts’ forecast errors increase with EPU, as does the degree of forecast dispersion. Increased error and dispersion persist after controlling for several competing sources of economy-wide uncertainty. Cross sectional analysis exploring heterogeneity in forecast quality across both analyst and firm characteristics establishes that forecast error and dispersion increase with EPU across a broad spectrum of firms and levels of analyst expertise. We control for analysts’ experience overall and the years spent covering a particular industry and firm. Five alternative methods for classifying firms as policy sensitive versus policy neutral provide consistent evidence that analyst forecast errors and dispersion increase with EPU, even for firms not deemed to be particularly sensitive to policy.     

Improvement in clinical trial disclosures and analysts’ forecast accuracy: evidence from the pharmaceutical industry

This paper examines whether financial analysts use the information contained in clinical trial disclosures to improve their forecast accuracy for pharmaceutical companies. Findings indicate that the improved clinical trial disclosures due to a quasi-regulation issued by the International Committee of Medical Journal Editors (ICMJE) significantly reduce analysts’ long-term forecast error. In addition, a propensity-score matching analysis provides additional strong evidence that issuance of the 2005 ICMJE’s regulation is accompanied by an average 45 % decrease in long-term forecast error, and a more than 50 % decrease in long-term forecast dispersion. This study contributes to the accounting literature regarding nonfinancial disclosures by providing the first insights into financial analysts’ use of clinical trial disclosures in their forecasts of future earnings. In addition, because the major event examined in this study is a quasi-regulation issued by the ICMJE, we provide additional insights on the effectiveness of industry-initiated regulations (or quasi-regulations) on nonfinancial disclosure practice.     

The effect of consistency in book-tax differences on analysts’ earnings forecasts: Evidence from forecast accuracy and informativeness

This study examines the relationship between the consistency of book-tax differences and the quality of analysts’ earnings forecasts. We find that the consistency of book-tax differences is associated with more accurate and informative forecasts. This suggests that the information embedded in the consistency of book-tax differences plays an important role in elevating the quality of analysts’ forecasts. Furthermore, the effect of consistency in book-tax differences on analyst forecast quality is greater for firms with noisier information environment. Finally, we find that the relation between consistency in book-tax differences and improvements in forecast accuracy and informativeness is stronger after the implementation of Regulation Fair Disclosure, which increased the role of public information in analysts’ forecasts.     

Why do analysts issue forecast revisions inconsistent with prior stock returns? Determinants and consequences

We examine the informativeness of analyst forecast revisions that are directionally inconsistent with prior stock price movements (sign‐inconsistent revisions). Sign‐inconsistent revisions represent approximately one‐half of the forecast revisions from 1995 through 2010. Our tests indicate that sign‐inconsistent revisions are less informative than are sign‐consistent revisions. Sign‐inconsistent revisions are less likely to be closer to actual earnings realizations and they generate smaller stock price reactions. We also find evidence that sign‐inconsistent revisions are associated with analysts' economic incentives to generate trading volume and their behavioural limitations related to information uncertainty. These results suggest that sign‐inconsistent revisions do not necessarily benefit investors.     

The effects of analysts’ tax expense forecast accuracy on corporate tax avoidance: An international analysis

A spotlight has recently been cast on the role of analysts as monitors of corporate tax planning, but investigations beyond the US are rare. After extension to the international setting, I investigate whether the strength of investor protection impacts the relationship between analysts’ tax expense forecast accuracy and tax avoidance. Using a sample from 24 countries, I find that firms with high analysts’ tax expense forecast accuracy engage in lower levels of tax avoidance than firms with low forecast accuracy; this relationship is greater for firms in countries with weaker investor protection. These findings suggest that the extent of country-level investor protection substitutes for firm-level governance in constraining managerial incentives for tax avoidance.     

Factors associated with price reactions and analysts’ forecast revisions around SEC filings

We investigate the extent to which rapid accessibility of financial reports filed electronically through the Securities and Exchange Commission’s EDGAR system has affected the ability of investors and security analysts to use accounting data in pricing decisions and forecasting. Consistent with prior research, we find evidence confirming that stock price reactions to SEC filings are significant in the EDGAR period but not the pre-EDGAR period. We also find significant revisions in analysts’ one-quarter-ahead earnings forecasts around SEC filings dates in both the pre-EDGAR and EDGAR periods. The price and forecast revision evidence indicates that financial analysts have used SEC filings all along. However, it is the advent of EDGAR that has allowed individual investors to also use 10-K and 10-Q filings. Cross-sectional analyses indicate that in the EDGAR period, trading volume around the preceding earnings announcements may influence individual investors to react to SEC filings. In contrast, variables such as the earnings surprise and the level of total accruals attract the attention of financial analysts. Interestingly, analysts appear to have been less likely in the pre-EDGAR period to bear the cost of searching out each SEC filing to identify those with large total accruals, which are known only after examining the SEC filing itself.     

The impact of accruals and lines of business on analysts’ earnings forecast superiority

In this paper, we examine the linkage between analyst advantage (AA) (compared to the seasonal random walk model) in the prediction of quarterly earnings-per-share (EPS) and a broad set of economic determinants. Specifically, we employ a pooled cross-sectional time-series regression model where AA is linked to a set of firm-specific economic determinants that have been employed in extant work (e.g., Brown et al. in J Account Res 22:49?C67, 1987; Kross et al. in Account Rev 65:461?C476, 1990). We refine this set of independent variables by including a new variable (RATIODEV) based upon Sloan (Account Rev 71(3):289?C315, 1996) who documents that differential levels of accruals impact future earnings performance. This variable is particularly salient in explaining AA since analysts may be in a position to identify the permanent component of accruals via fundamental financial analysis. Additionally, we refine the measurement of lines of business??consistent with the reporting requirements of SFAS No. 131 relative to extant work that operationalized proxies for this variable based upon SFAS No. 14. Parameters for these aforementioned variables are significantly positively related to AA, consistent with theory.     

Stock index adjustments and analysts’ forecast optimism: A quasi-natural experiment on the CSI 300 Index

As stock index adjustments comprise a basic system of capital market, their potential influence on analysts’ earnings forecasts is worthy of research. Based on a research sample of 23 adjustments to the CSI 300 Index from June 2007 to June 2018 and the backup stocks announced during the same period, this study examines the impact of additions to stock index on analysts’ forecast optimism using a staggered difference-in-differences model. The research results show that after stocks are added to the stock index, analysts’ earnings forecast optimism about these stocks increases significantly. Cross-sectional analysis indicates that this increase is more significant when the market is bullish, institutional ownership is low, the ratio of listed brokerage firms is low, star analyst coverage is low, firms show seasoned equity offering activity, the ratio of analysts from the top five brokerage firms ranked by commission income is high, and the analysts’ brokerage firms are shareholders. However, analyst-level tests find that analysts’ ability helps to reduce the impact of additions to stock index on earnings forecast optimism. Furthermore, additions to stock index significantly increase analyst coverage and forecast divergence. Economic consequences tests find additions to stock index significantly increases stock price synchronization, which is partly mediated by analysts’ earnings forecast optimism. This study enriches the literature on the impact of basic capital market systems and analyst behavior. The findings suggest that investors should rationally evaluate analysts’ earnings forecasts for stocks added to the stock index and obtain further information from various channels to improve asset allocation efficiency.     

Does short selling reduce analysts’ optimism bias in earnings forecasts?

We examine the relationship between short selling and analyst optimism bias of earnings forecasts of stocks in China. We propose two possible hypotheses: short selling enhances analysts’ information set to lower optimism bias and analysts drum up optimistic earnings forecasts to counter short selling. Our results suggest that short selling and earnings optimism bias are negatively correlated. The findings are robust to a two-stage least square method, a difference in-differences fixed effect model, an alternative measure of optimism bias, incorporated different time windows to calculate short selling, considered bull and bear market conditions, accounting for media coverage, and using abnormal short selling. By leveraging rich data, we conduct additional analyses using stocks with different forecasting horizons and earnings forecasts that were made after the accounting year but prior to the earnings announcement to further support expanding the information set argument. Lastly, we document that short selling information improves the accuracy of earnings forecasts.     

Changes in analysts’ stock recommendations following regulatory action against their brokerage

Review of Accounting Studies - Despite the importance of sell-side analysts in the capital markets, we know little about the effectiveness of routine monitoring of the sell-side industry. We...     

Does foreign investor demand for information affect forecast accuracy? Evidence from the Chinese stock markets

Prior international accounting studies have examined mainly the supply side of analyst research. Specific trading rights and financial reporting systems in China provide a unique opportunity to test both demand and supply factors of analyst information. For shares traded only by less-informed foreign investors, the increased information demand may create incentives for analysts to exert greater efforts than for shares traded by local investors. This study provides evidence that analyst effort (proxied by analyst coverage) and expertise (proxied by consensus cross-analyst forecast variability) affect forecast accuracy more significantly for shares traded by foreign investors than for shares traded by local investors. Additionally, I find that the relation between analyst characteristics and relative forecast accuracy is stronger for shares traded by the foreign investors. The findings are consistent with analysts responding to demands for information by less-informed investors.     

Market implied future earnings and analysts’ forecasts

This study provides evidence on market implied future earnings based on the residual income valuation (RIV) framework and compares these earnings with analyst earnings forecasts for accuracy (absolute forecast error) and bias (signed forecast error). Prior research shows that current stock price reflects future earnings and that analyst forecasts are biased. Thus, how price-based imputed forecasts compare with analyst forecasts is interesting. Using different cost of capital estimates, we use the price-earnings relation and impute firms’ future annual earnings from three residual income (RI) models for up to 5 years. Relative to I/B/E/S analyst forecasts, imputed forecasts from the RI models are less or no more biased when cost of capital is low (equal to a risk-free rate or slightly higher). Analysts slightly outperform these RI models in terms of accuracy for immediate future (1 or 2) years in the forecast horizon but the opposite is true for more distant future years when cost of capital is low. A regression analysis shows that, in explaining future earnings changes, analyst forecasts relative to imputed forecasts do not impound a significant amount of earnings information embedded in current price. In additional tests, we impute future long-term earnings growth rates and find that they are more accurate and less biased than I/B/E/S analyst long-term earnings growth forecasts. Together, the results suggest that the RIV framework can be used to impute a firm’s future earnings that are high in accuracy and low in bias, especially for distant future years.     

Analysts’ forecast revisions and firms’ research and development expenses

This study examines whether reported values for firms’ research and development (R&D) affect analysts’ annual earnings forecast revisions following quarterly earnings announcements. Because R&D introduces uncertainty into earnings forecasts, analysts may benefit from additional information searches in an effort to increase forecast accuracy. Also, accounting standards mandate an immediate expensing of R&D, in essence projecting a zero value for the R&D. To the extent that R&D will produce future payoffs, the expense treatment reduces the informativeness of reported earnings for forecasting future earnings. Thus, the marginal benefit of analysts’ efforts to produce more information may increase with the magnitude of the R&D component of earnings announcements and trigger additional forecast revisions. Alternatively, if the cost of information searches exceeds the benefit, analysts’ forecast revisions may decrease. Our results show a positive relation between R&D expenses and analysts’ forecast revision activity. We also find a positive and significant association between the level of R&D expenses and the magnitude of analysts’ forecast revisions following quarterly announcements. These results point to a greater amount of analyst scrutiny when reported earnings are accompanied by high levels of R&D expenses.

Accounting rules? Stock buybacks and stock options: Additional evidence

This paper finds that CEO stock options influence the choice, amount, and timing of funds distributed as a buyback. These results favor a managerial opportunism motive for buybacks over other theories and support two key research expectations – that buybacks impose option-induced agency costs on outside shareholders, and that managers benefit from weak governance and unclear accounting in this choice. CEOs increase their insider selling following a buyback, which also supports a managerial opportunism perspective. Once we control for these agency factors, we find no evidence that buyback activity associates reliably with EPS accretion from the reduction in common shares. We conclude that the popular use of stock buybacks as a form of cash distribution derives significantly from a strong contemporaneous relation between buybacks and CEOs’ use of stock options as additional compensation.     

Does Regulation Fair Disclosure affect analysts’ forecast performance? The case of restructuring firms

The main purpose of this paper is to investigate how the enactment of Regulation Fair Disclosure (Reg. FD) influences analysts?? forecast characteristics for restructuring firms. The Reg. FD requires all firms disseminate material information not only to some institutional investors and certain financial analysts, but to all market participants simultaneously. We expect that the regulatory effect of Reg. FD on financial analysts?? forecast performance would be pronounced because of uncertain earnings signals and information complexity produced by restructuring activities. Particularly, we examine how the enactment of Reg. FD affects the relationship between analysts?? earnings forecast attributes and the occurrence and magnitude of restructuring charges. Our general finding is that analysts?? forecast errors and forecast dispersion have declined in the post-FD period for restructuring firms. However, such an impact cannot be persistent with an increase in the relative magnitude of restructuring charges, the proxy for restructuring complexity. This study provides additional evidence that Reg. FD has limited private information, and attempts to provide all users with the same access to information within the context of firms reporting restructuring charges.