Mandatory disclosure of comment letters and analysts' forecasts

Comment letters (CLs) have been adopted as the main supervision mechanism for information disclosure by the two main Chinese stock exchanges since 2013. Both CLs and firms' responses have been publicly disclosed since the end of 2014. Using nonfinancial listed firms from 2013 to 2019 as our sample, we investigate the impact of CLs and their mandatory disclosure on analysts' forecast quality. The results show that, in the pre-disclosure period, there is no significant relation between CLs and analysts' forecast quality. However, in the post-disclosure period, CLs are positively (negatively) correlated with analysts' forecast accuracy (optimism). The quality of analysts' forecasts is much higher when CLs contain more questions. In addition, the impact of CLs is larger for samples with a lower percentage of star analysts or samples with higher earnings volatility. CL recipients tend to disclose more information on their internal and external risks, which can offer additional information to analysts.     

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.     

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 association between qualitative management earnings forecasts and discretionary accounting in the Netherlands

This paper examines whether there is an association between discretionary accounting and the accuracy of long-run forecasts of annual earnings disclosed voluntarily by Dutch companies in the directors’ report. In particular, investigations were made of the consistency in the sign and direction of discretionary accounting techniques and qualitative earnings forecasts. Long-run forecasts are defined, for the purposes of this paper, as forecasts made at least seven months before the year-end. Although not mandatory, qualitative forecasts are released by well over 60% of the listed companies in the Netherlands. Empirical results indicate that there is consistency in the sign and direction of qualitative earnings forecasts and discretionary accounting. After adopting discretionary accounting, the forecast errors are reduced if the company can reach the management earnings forecast (target). In the event that reserves are insufficient to accomplish this goal, managers choose their next best option and take an earnings bath in order to maximize reserves available for future use. By partitioning the sample in various sub-sets it is shown that earnings management and forecast errors occur most in the extreme ranges of financial performance. Overall, the study shows that management engages in discretionary accounting to present results in line with the disclosed qualitative earnings forecasts in their directors’ reports. Whilst discretionary accounting may clearly improve the consistency of companies’ earnings forecasts released via the directors’ reports and the actual earnings, managers’ earnings forecasts are sometimes disclosed in anticipation of planned discretionary accounting actions.     

Why Do Managers Explain Their Earnings Forecasts?

Managers often explain their earnings forecasts by linking forecasted performance to their internal actions and the actions of parties external to the firm. These attributions potentially aid investors in the interpretation of management forecasts by confirming known relationships between attributions and profitability or by identifying additional causes that investors should consider when forecasting earnings. We investigate why managers choose to provide attributions with their forecasts and whether the attributions are related to security price reactions to management earnings forecasts. Using a sample of 951 management earnings forecasts issued from 1993 to 1996, we find that attributions are more likely for larger firms, less likely for firms in regulated industries, less likely for forecasts issued over longer horizons, more likely for bad news forecasts, and more likely for forecasts that are maximum type. Furthermore, attributions are associated with greater absolute price reactions to management forecasts, more negative price reactions to management forecasts (forecast news held constant), and a greater price reaction per dollar of unexpected earnings. Our findings hold after control for the aforementioned determinants of attributions and after control for other firm‐ and forecast‐specific variables that are often associated with security prices.     

The effect of management earnings forecast characteristics on cost of equity capital

This study uses a framework presented in Hirst, Koonce, and Venkataraman (2008) to assess how differences in management earnings forecast characteristics influence a firm's cost of equity capital. I find that less specific forecasts, pessimistic forecasts, and forecasts that predict a loss for the period are associated with higher cost of equity capital levels and more timely forecasts and forecasts with more information content are associated with lower cost of equity capital levels. Analysis interacting control variables and forecast antecedents with forecast characteristics indicates that the effects forecast characteristics have on cost of equity capital are either enhanced or moderated depending on firm beta, firm size, firm book-to-market ratios, analyst following, prior forecast bias, and earnings quality. The results highlight the importance of interacting key variables when interpreting the market effect of management earnings forecasts.     

The effect of Regulation FD on the properties of management earnings forecasts

We investigate Regulation FD’s (FD) effect on management earnings forecast properties. We posit FD’s prohibition on private manager-analyst communication reduces (increases) optimism (pessimism) in management earnings forecasts. Prior to FD, managers could avoid publicly retracting prior optimistic forecasts by privately communicating with analysts, who could lower investor expectations with a new analyst forecast. After FD, managers with optimistic forecasts must either publicly admit their optimism by issuing a new management forecast or they must negatively surprise investors at the earnings announcement. Further, FD forces managers to use public forecasts instead of private communications to establish beatable expectations. Our evidence suggests FD reduced optimism in management forecasts. This reduction in optimistic bias is not offset by an increase in pessimistic bias. Consistent with this, we further find post-FD improvements in forecast accuracy and informativeness. We find no such changes around several potentially confounding events or for foreign firms surrounding FD. Overall, our evidence suggests FD improved firms’ forecast properties (less bias, greater accuracy, and greater informativeness).     

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.     

Voluntary Causal Disclosures: Tendencies and Capital Market Reaction

In this study, we provide empirical evidence on whether voluntarily disclosed causal attributions made in management earnings forecasts are credible by investigating the conditions under which such attributions are made and the extent to which security price responses are associated with attribution existence. We find that causal attributions are more likely to be made when forecast news is bad (relative to good), and that the type of attribution made is more likely to be external (internal) for bad (good) forecast news. Incorporating the existence and type of attribution into models that explain announcement period three-day cumulative abnormal returns yields significant effects for attribution incidence and type after controlling for unexpected earnings and forecast type (e.g., point, range, etc.). Consistent with the idea that attributions enhance the credibility or precision of management forecasts, attribution disclosure enhances price reactions per dollar of unexpected earnings conveyed in a management forecast.     

Mutual Fund Manager Forecasting Behavior

I examine publicly released annual earnings forecasts issued in conjunction with stock recommendations by mutual fund managers of actively managed open-end mutual funds. I find that mutual fund manager annual earnings forecasts systematically overestimate the earnings number later disclosed at the annual earnings announcement. In further analyses, I attempt to distinguish between two explanations for this forecast bias: an untruthful reporting bias (market manipulation) and a truthful cognitive bias (optimism). These explanations generate different predictions about the timing of changes in fundholdings of forecasted securities between the forecast release and annual earnings announcement dates. I interpret my findings as more consistent with an optimism explanation for mutual fund manager annual forecast bias and less consistent with a market manipulation explanation for this bias. I am, however, unable to eliminate an unobservable selection bias either in the decision of the mutual fund manager to report a forecast publicly or in the media's decision to publish that forecast as an explanation for my finding that mutual fund manager forecasts are biased.     

积极回应内部控制法案与管理层利润预测精度——基于日本数据的实证研究

以日本上市公司为研究对象,在考虑盈余管理行为的基础上分析并检验积极回应内部控制法案的上市公司是否具有较高的管理层利润预测精度。结果表明,那些委托会计师事务所构建和完善其内部控制系统以应对内部控制法案的上市公司具有较高的管理层利润预测精度。因此,有效的内部控制有助于企业实施全面预算管理。     

Analyst revenue forecast reporting and the quality of revenues and expenses

We decompose earnings quality into revenue and expense quality and examine their associations with analyst propensity to supplement their earnings forecasts with revenue forecasts. Analysts report more revenue forecasts to I/B/E/S when expense quality is low to compensate for the low accuracy of their earnings estimates, which has a positive association with expense quality. Expense quality is unassociated with revenue forecast accuracy, thus revenue forecasts become increasingly useful for valuing firms when expense quality is low. Analysts report fewer revenue forecasts when revenue quality is low because both earnings and revenue forecast accuracy decline as revenue quality deteriorates. To control for endogeneity, we use firm‐fixed effects to control for unobserved time‐invariant heterogeneity across firms, instrumental variables regressions and regression in changes.     

Management disclosure bias and audit services

This paper considers the level of bias observed in management disclosures of earnings forecasts and historic earnings data in Australian prospectuses. Management forecasts and naïve forecasts derived from managements’ normalised historic data are analysed. A key focus is upon the possible association between such forecast bias and differential audit services performed upon the data. Audit firm size and level of engagement are modelled against bias. The full sample revealed no overestimation bias for any of the forecast models, but underestimation was observed for elements of the management and random walk naïve forecasts. Cross-sectionally, a significant association was observed between forecast bias and audit firm size across all three forecast models. Specifically, the audit firm size variable (Non Big-5/Big-5) was inversely associated with the extent to which forecasted and normalised historic earnings data were upwardly biased. On the other hand, the level of engagement was not a significant discriminator for forecast bias. These outcomes are contrasted against others reported elsewhere in the literature and suggest a risk in generalising across contexts. The findings imply a level of ‘disclosure management’ regarding company IPO forecasts and normalised historic accounting data, with forecast overestimation and error size more extreme when the monitoring expertise and/or reputation of auditors is lower (JEL D80, G14, M41, N27).     

Analyst information production and the timing of annual earnings forecasts

We investigate whether the reputation-herding theory or the tradeoff theory explains variation in the timing of individual analysts’ forecasts. Using forecast accuracy improvements, forecast boldness, and the price impact of forecasts as measures of forecast quality, we find that in the information discovery phase that precedes an earnings announcement, earlier forecasts have higher quality than later forecasts. We also find a similar pattern in the information analysis phase that begins with the earnings announcement date. Our findings suggest that consistent with the herding theory, analysts who are more capable participate early in discovering and analyzing information, and therefore earlier forecasts in the information discovery and analysis phases are of higher quality than later forecasts in that phase.     

Implied cost of capital investment strategies: evidence from international stock markets

Investors can generate excess returns by implementing trading strategies based on publicly available equity analyst forecasts. This paper captures the information provided by analysts by the implied cost of capital (ICC), the internal rate of return that equates a firm’s share price to the present value of analysts’ earnings forecasts. We find that U.S. stocks with a high ICC outperform low ICC stocks on average by 6.0 % per year. This spread is significant when controlling the investment returns for their risk exposure as proxied by standard pricing models. Further analysis across the world’s largest equity markets validates these results.     

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.     

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.     

The impact of SOX on opportunistic management behavior

An innovative aspect of this study is the use of a relatively new metric to capture opportunistic earnings management behavior. We define opportunistic earnings management as the difference between a firm's US-GAAP earnings and ex post earnings consensus derived from forecasts of financial analysts who follow that firm. Using over 24,500 quarterly reports of over 2,500 publicly-traded companies spanning two three-year periods, and controlling for factors previously linked to having an effect on earnings management and analysts forecast effort, we find statistical evidence supporting the proposition that, in the aggregate, the Sarbanes–Oxley Act (SOX) has served as a constraint on curbing opportunistic earnings management behavior, and thus should be considered as an effective means to improve the quality of financial reporting information.     

The role of accounting conservatism in management forecast bias

We investigate whether management earnings forecasts fully incorporate information in historical accounting conservatism. We find that management earnings forecasts are more optimistic for firms with greater accounting conservatism in the previous year. We further examine whether this conservatism-related optimistic bias in management earnings forecasts varies with managers’ difficulty predicting earnings accurately, managers’ opportunistic incentives, and the firms’ litigation risk. We find that the negative association between management forecast errors and conservatism increases, to various extent, with the firms’ operating cycles, earnings volatility, and the width of forecast range but does not change with proxies for opportunistic incentives or litigation risk. These results suggest that forecast difficulty is the primary reason for managers’ failure to incorporate conservatism fully in their earnings forecasts.     

Analyst information precision and small earnings surprises

This study proposes and tests an alternative to the extant earnings management explanation for zero and small positive earnings surprises (i.e., analyst forecast errors). We argue that analysts’ ability to strategically induce slight pessimism in earnings forecasts varies with the precision of their information. Accordingly, we predict that the probability that a firm reports a small positive instead of a small negative earnings surprise is negatively related to earnings forecast uncertainty, and we present evidence consistent with this prediction. Our findings have important implications for the earnings management interpretation of the asymmetry around zero in the frequency distribution of earnings surprises. We demonstrate how empirically controlling for earnings forecast uncertainty can materially change inferences in studies that employ the incidence of zero and small positive earnings surprises to categorize firms as suspected of managing earnings.