Value relevance of analyst earnings forecasts in emerging markets

Even though research in accounting and finance has extensively examined the role of financial analysts in developed economies, this issue has not been thoroughly examined in an emerging market setting. In this paper, I examine whether, following a market opening, analyst forecast accuracy and the market's reliance on analyst forecasts increase with time. Accuracy is expected to increase over time as analysts exert more effort and gain valuable forecasting experience. Results indicate that time is positively related to analyst forecast accuracy after controlling for a number of other firm and country characteristics. Second, I posit that time should also be related to the market's propensity to use analyst forecasts to form earnings expectations. As markets open and investors become more sophisticated, the reliance on analyst forecasts should also increase. Results are consistent with this expectation. In particular, I find that in the first sub-period earnings expectations based on random walk exhibit greater relative information content than earnings expectations based on analyst forecasts. This pattern is reversed in the third sub-period where analyst forecast errors better explain returns. Incremental information content tests produce similar results. Future research should further investigate the relation between financial analysts and other important market characteristics in emerging economies.     

Analyst reputation and management earnings forecasts

Prior studies show that analysts with high reputation are influential in the market. This paper examines whether managers consider analyst reputation in shaping their voluntary disclosure strategy. Using Institutional Investor magazine’s All-American (AA) rankings as a proxy for analyst reputation, we find that the coverage of AA analysts is positively associated with the likelihood of quarterly management earnings forecasts (MEFs). We also find that AA analysts’ forecast optimism is more positively associated with the likelihood of MEFs than non-AA analysts’ forecast optimism when the firm is covered by AA analysts. Analyses based on AA analyst coverage changes and AA status changes confirm the relation between analyst reputation and MEFs. We further find that analyst reputation influences other MEF properties, such as forecast news, bias, and revisions, and that our results are robust to alternative measures of analyst reputation. Further analyses show that market reactions at quarterly earnings announcements are more positive (negative) when firms meet/beat (miss) AA analysts’ forecasts than when firms meet/beat (miss) non-AA analysts’ forecasts. Collectively, our findings suggest that managers strategically provide voluntary forecasts by taking into account the reputation of individual analysts following their firms.     

Disclosure of internal control material weaknesses and optimism in analyst earnings forecasts

This paper investigates how analyst forecast optimism is associated with disclosures of internal control material weaknesses (ICMWs) and their remediation under Section 404 of the Sarbanes–Oxley Act (SOX). Drawing on agency theory, I hypothesize that analysts are likely to issue earnings forecasts that are more optimistic for firms with ICMW disclosures than for those without ICMW disclosures. Using a sample of 20,875 firm-year observations with 10-K (10-Q) reports from 2004 to 2018, I find a positive association between ICMW disclosures and analyst forecast optimism. This positive association is partially driven by investors’ inability to unravel analyst forecast bias and analysts’ intentions to curry favor with management for private information. In addition, analysts are found to issue less optimistic forecasts for firms with ICMW remediation disclosures compared with those without ICMW remediation disclosures. A series of propensity score matching and regression analyses are conducted to test the robustness of my inferences. Overall, the paper suggests that analysts have incentives to take the opportunity of firms disclosing ICMWs to bias their forecasts upward for self-interest. The findings have the potential to assist regulators in guiding analyst behavior and educating investors to unravel positive bias in analyst forecasts.     

Confirming Management Earnings Forecasts, Earnings Uncertainty, and Stock Returns

In this study we examine the association among confirming management forecasts, stock prices, and analyst expectations. Confirming management forecasts are voluntary disclosures by management that corroborate existing market expectations about future earnings. This study provides evidence that these voluntary disclosures affect stock prices and the dispersion of analyst expectations. Specifically, we find that the market's reaction to confirming forecasts is significantly positive, indicating that benefits accrue to firms that disclose such forecasts. In addition, although we find no significant change in the mean consensus forecasts (a proxy for earnings expectations) around the confirming forecast date, evidence indicates a significant reduction in the mean and median consensus analyst dispersion (a proxy for earnings uncertainty). Finally, we document a positive association between the reduction of dispersion of analysts' forecasts and the magnitude of the stock market response. Overall, the evidence suggests that confirming forecasts reduce uncertainty about future earnings and that investors price this reduction of uncertainty.     

Performance commitments and the properties of analyst earnings forecasts: Evidence from Chinese reverse merger firms

We investigate whether the performance commitments in Chinese reverse merger (RM) transactions affect the properties of analyst earnings forecasts. All RM firms in China are required to make performance commitments for a limited number of years after being publicly listed. As performance commitment is an important piece of public information, it can influence analysts' understanding of firms and their efforts to forecast earnings. Using manually assembled information on RM transactions, we find that, in comparison to the control firms, RM firms exhibit an increase in analyst forecast error and dispersion after the end of performance commitment. This effect is more pronounced in firms with lower levels of information transparency. We also document that the public information contents of analyst forecasts decrease and forecast revisions increase in the post-commitment period, while the private information content of analyst forecasts and the number of their firm visits remain unchanged. Overall, our findings suggest that analysts rely greatly on public information; they have important implications for academics and policymakers in understanding how performance commitments in RM transactions affect the market information environment.     

Analyst characteristics, timing of forecast revisions, and analyst forecasting ability

We first examine whether analysts with certain characteristics that prior research has identified are related to superior forecasting ability systematically time their forecast revisions later in the fiscal quarter. We then examine whether this superior ability persists after controlling for the timing advantage by using relative forecast error, a measure that largely eliminates the timing advantage of recent forecasts. Using a sample of quarterly earnings forecast revisions over the 20-year period from 1990 to 2009, we find that analysts with more firm-specific and general experience and more accurate prior-period forecasts, analysts employed by larger brokerage firms, and analysts who follow fewer industries and companies tend to revise forecasts later in the quarter. We also find that analyst characteristics that are positively correlated with revision timing are negatively related to relative forecast errors. These results are consistent with analyst characteristics being useful proxies for analyst forecasting ability and analysts with greater ability revising forecasts later in the quarter.     

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.     

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.     

Experience, information asymmetry, and rational forecast bias

This study examines whether it is ever rational for analysts to post biased estimates and how information asymmetry and analyst experience factor into the decision. Using a construct where analysts wish to minimize their forecasting error, we model forecasted earnings when analysts combine private information with consensus estimates to determine the optimal forecast bias, i.e., the deviation from the consensus. We show that the analyst??s rational bias increases with information asymmetry, but is concavely related with experience. Novice analysts post estimates similar to the consensus but as they become more experienced and develop private information channels, their estimates become biased and deviated from the consensus. Highly seasoned analysts, who have superior analytical skills and valuable relationships, need not post biased forecasts.     

The association between quarter length,forecast errors,and firms’ voluntary disclosures

Approximately 60 percent of adjacent fiscal quarters contain a different number of calendar days. In preliminary analyses, we find the change in quarter length is significantly associated with the changes in sales and earnings and that analysts condition on the prior quarter's results when making their forecasts. These results indicate that it is important for analysts to adjust for changes in quarter length when making forecasts. However, we find the quarterly change in days is positively associated with analysts’ sales and earnings forecasts errors, where forecast error equals the actual earnings minus the forecasted earnings. These results indicate that analysts systematically underestimate (overestimate) performance when quarter length increases (decreases). We find evidence indicating investors make similar errors as returns around earnings announcements are positively associated with the change in quarter length, but only when changes in firm performance is more sensitive to changes in quarter length. Corroborating these findings, managers are more (less) likely to discuss quarter length during conference calls when quarter length decreases (increases). These results are consistent with managers’ strategic disclosure incentives. In summary, our evidence suggests analysts and investors fail to fully take account of the quasi-mechanical effect that quarter length has on firm performance and managers strategically alter their voluntary disclosures to take advantage of these failures.     

Additional Evidence on Analysts’ Decision to Issue Disaggregated Earnings Forecasts: Strategic Biasing

This study examines why analysts issue disaggregated earnings forecasts to I/B/E/S. Some recent studies suggest that analysts with superior forecasting ability issue disaggregated earnings forecasts to build reputation in the marketplace and stop forecast disaggregation once their reputation has been established. Based on an analysis of I/B/E/S forecast data for U.S. firms from 1998 to 2008, we find that, in a given year, about 20%–34% of analysts disaggregate for some, but not for all the firms that they follow. This evidence of selective disaggregation by analysts suggests that reputation building alone does not fully explain the decision to disaggregate forecasts. We hypothesize that the decision to disaggregate earnings forecasts is at the firm‐level as well and is systematically related to the analysts’ bias in the issued forecasts. Our findings are that (a) analysts’ overall optimistic bias and forecast errors decrease monotonically with the level of forecast disaggregation, and (b) analysts that selectively disaggregate their forecasts for some firms or who do not persistently disaggregate a given firm's forecasts exhibit more positive bias and larger forecast errors. Our findings are consistent with the notion that the analysts who issue biased forecasts, for example, to curry favour with the management, are less likely to provide disaggregated information as part of the forecast.     

Learn from peers? The impact of peer firms' analyst earnings forecasts on a focal firm's corporate investment efficiency

We explore whether a firm can learn from information on peers produced by analysts. Based on a sample of Chinese firms, we document that analyst earnings forecast accuracy (dispersion or optimism) of peer firms is positively (negatively) associated with the focal firm's investment efficiency. The effect is more salient when the focal firm operates in a competitive industry, when analysts are predicting positive earnings, when peers produce low-quality annual reports, or when the focal firm has high information asymmetry. Overall, our findings provide new insights on learning from peer information produced by a third party and show that analyst earnings forecasts have spillover effects in the product market.     

Which types of analyst firms are more optimistic?

Research optimism among securities analysts has been attributed to incentives provided by underwriting activities. We examine how analysts’ forecast and recommendation optimism varies with the business activities used to fund research. We find that analysts at firms that funded research through underwriting and trading activities actually made less optimistic forecasts and recommendations than those at brokerage houses, who performed no underwriting. Optimism was particularly low for bulge underwriter firm analysts, implying that firm reputation reduces research optimism. There is also evidence that analysts at retail brokerage firms are more optimistic than those serving only institutional investors. We conclude that analyst optimism is at least partially driven by trading incentives.     

Do local analysts know more? A cross-country study of the performance of local analysts and foreign analysts

This paper examines whether analysts resident in a country make more precise earnings forecasts for firms in that country than non-resident analysts. Using a sample of 32 countries, we find an economically and statistically significant local analyst advantage even after controlling for firm and analyst characteristics. The local advantage is high in countries where earnings are smoothed more, less information is disclosed by firms, and firm idiosyncratic information explains a smaller fraction of stock returns. It is negatively related to whether a firm has foreign assets and to market participation by foreign investors and by institutions, and positively related to holdings by insiders. The extent to which U.S. investors underweight a country's stocks is positively related to that country's local analyst advantage.     

Do Managers Always Know Better? The Relative Accuracy of Management and Analyst Forecasts

We examine the relative accuracy of management and analyst forecasts of annual EPS. We predict and find that analysts’ information advantage resides at the macroeconomic level. They provide more accurate earnings forecasts than management when a firm's fortunes move in concert with macroeconomic factors such as Gross Domestic Product and energy costs. In contrast, we predict and find that management's information advantage resides at the firm level. Their forecasts are more accurate than analysts’ when management's actions, which affect reported earnings, are difficult to anticipate by outsiders, such as when the firm's inventories are abnormally high or the firm has excess capacity or is experiencing a loss. Although analysts are commonly viewed as industry specialists, we fail to find evidence that analysts have an information advantage over managers at the industry level. The two have comparable abilities to forecast earnings for firms with revenues or earnings that are more synchronous with their industries.     

The supply of analysts and earnings forecasts

Using a unique set of hand-collected data, this study examines whether a larger supply of prospective analysts leads to existing financial analysts' higher earnings forecast accuracy. We analyze the effect of the analyst supply proxied by the number of universities and the number of finance and economics universities located in the same city as the headquarters of brokerage firms. Our findings suggest that brokerage firms located closer to a larger supply of potential analyst candidates are associated with higher analyst forecast accuracy, as observed by a lower forecast error. We further find that the degree of employed analysts' effort acts as a mediator between the supply of prospective analysts and the accuracy of their earnings forecasts.     

Analyst Forecast Accuracy and Media Independence

Using a large international sample of 47,307 firm‐years from 52 countries, we investigate the impact of media independence on the forecast quality of financial analysts. We find that analyst forecast errors are positively associated with the extent of a country's state media ownership and its lack of freedom of the press. We also find that financial analysts with more inaccurate forecasts disappear from the institutional broker's estimate system more quickly in countries with more independent media.     

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.     

Social comparison of cost behaviour and financial analysts

We investigate whether social comparison of a firm’s reported selling, general and administrative (SG&A) expenses affects financial analysts’ information uncertainty (and their behaviour). Based on a sample of US firms, we examine whether similarity of a firm’s SG&A to an industry-specific peer-based benchmark (or social benchmark) is associated with analyst forecast dispersion, forecast error and coverage. For external observers, the SG&A relative to sales (SG&A ratio) is a key diagnostic of a firm’s cost behaviour, but interpretational ambiguity of the SG&A signal is likely to incentivise search for information-relevant external cues to set expectations about and assess a firm’s SG&A ratio. Higher similarity to the social benchmark is expected to attenuate information asymmetry between analysts and firms regarding firms’ ability to effectively control overheads, decreasing analyst information uncertainty about cost behaviour and performance. In line with a varying weights model for social comparison, we observe a negative association between SG&A similarity and both forecast dispersion and error of one-year-ahead earnings for firms with a prior SG&A ratio exceeding the social benchmark. Our findings also show a negative relationship between SG&A similarity and analyst coverage, especially for firms with a prior SG&A ratio exceeding the social benchmark.     

IFRS adoption and analysts’ earnings forecasts: Australian evidence

We study 145 large listed Australian firms to explore the impact of international financial reporting standards (IFRS) adoption on the properties of analysts’ forecasts and the role of firm disclosure about IFRS impact. We find that analyst forecast accuracy improves, and there is no significant change in dispersion in the adoption year, suggesting that analysts coped effectively with transition to IFRS. However, we do not observe the expected relationship between firms’ IFRS impact disclosures in their financial statements issued at the end of the transition year with forecast error and dispersion in the adoption year. The results question the timeliness and usefulness of financial statement disclosure, even in a setting where disclosure was mandated by accounting standards (AASB 1047 and AASB 1) and firms had strong incentives to provide information to analysts.