The use of management forecasts to dampen analysts' expectations by Chinese listed firms

This paper studies the use of management earnings forecasts (MEF) to dampen analysts' expectations, i.e. expectation management, by Chinese listed companies. We reveal several important findings: Firstly, information asymmetry is positively associated with the use of MEF to dampen analysts' expectations. State control has been found to moderate this relationship. Secondly, dampening analysts' expectations using MEF leads to negative stock return reactions and downward analysts' forecast revisions. Thirdly, the effectiveness of “pre-empting bad news through MEF” appears mixed and dependent on the information content of MEF and measures of actual earnings surprises. Finally, firms that disclose MEF are found to engage in more earnings management to meet the forecasts than firms that do not.     

Expected Mispricing: The Joint Influence of Accounting Transparency and Investor Base

We examine how accounting transparency and investor base jointly affect financial analysts' expectations of mispricing (i.e., expectations of stock price deviations from fundamental value). Within a range of transparency, these two factors interactively amplify analysts' expectations of mispricing—analysts expect a larger positive deviation when a firm's disclosures more transparently reveal income‐increasing earnings management and the firm's most important investors are described as transient institutional investors with a shorter‐term horizon (low concentration in holdings, high portfolio turnover, and frequent momentum trading) rather than dedicated institutional investors with a longer‐term horizon (high concentration in holdings, low portfolio turnover, and little momentum trading). Results are consistent with analysts anticipating that transient institutional investors are more likely than dedicated institutional investors to adjust their trading strategies for near‐term factors affecting stock mispricings. Our theory and findings extend the accounting disclosure literature by identifying a boundary condition to the common supposition that disclosure transparency necessarily mitigates expected mispricing, and by providing evidence that analysts' pricing judgments are influenced by their anticipation of different investors' reactions to firm disclosures.     

RATIONAL EXPECTATIONS AND THE DYNAMIC ADJUSTMENT OF SECURITY ANALYSTS' FORECASTS TO NEW INFORMATION

We report the results of unbiasedness tests of security analysts' earnings forecasts. By examining how analysts incorporate new information into their updated earnings forecasts we can analyze directly the effect of new information on analysts' forecast revisions and evaluate whether these revised forecasts converge to rational expectations forecasts. The forecasts made by security analysts participating in the Institutional Brokers Estimate System (IBES) database are analyzed. Using standard statistical tests, we reject the simple form of the rational expectations hypothesis. However, by extending the standard tests used in previous studies, we obtain results that suggest that analysts' earnings forecasts conform to a dynamic form of rationality. The tendency of revised forecasts to converge stochastically toward the rational expectations forecast cautions against the rejection of more complicated forms of rationality.     

The Predictive Role of Analyst Coverage Intensity: Evidence from Cross-Listing in the US

This paper investigates financial analysts' predictive power of future performance and earnings quality, using a sample of firms cross-listed in the US. We find that analyst coverage is positively related to analysts' expectations about firms' future performance and negatively related to analysts' concern over firms' earnings quality. Country-level legal origin and disclosure index are two significant determinants of analyst coverage of cross-listed firms. In addition, the intensity of analyst coverage can predict future abnormal stock price performance. While documenting the substantial informational benefits to cross-listing, our study suggests that these benefits may not be complete since analysts appear to have predictive power and selectively provide coverage for firms with favorable future prospects.     

Earnings Surprises in Analysts' Forecasts,Mandatory Disclosure,and Share Repurchases

This paper examines the impact of forecast errors and the mandatory disclosure of repurchase transactions required by 2003 Securities and Exchange Commission (SEC) regulations on share repurchases. We define forecast errors as the difference between analysts' forecasted earnings and actual earnings. We argue that firms with positive forecast errors imply greater information asymmetry, which may induce them to signal through share repurchases. We show that both the repurchase target and analysts' forecast revision are positively related to forecast errors. Furthermore, these associations are more pronounced in the low disclosure period (1989–2003) where greater information asymmetry between managers and outside investors is found, while increased transparency in the high disclosure period (2004–2006) leads to more significant improvement in long‐term performances for firms with positive forecast errors. The results are consistent with our expectations that the information asymmetry implied in forecast errors, along with a shock change from the introduction of the 2003 SEC regulation, affect both corporate and analysts' behaviour.     

Earnings expectations and interactive discussions with corporate insiders

This study aims to empirically clarify the informational role of interactive discussions with corporate insiders by analyzing how participants’ expectations are affected by their participant comments during analyst and investor days. The results indicate that the tone of management presentations and responses to participants’ comments exhibit no impact on analysts’ expectations of company performance. By contrast, analysts’ earnings forecasts react significantly to comments from their peers (especially star analysts). Furthermore, peer comments contain additional information on analysts’ forecast errors. Finally, analysts whose earnings forecasts diverge positively (negatively) from the consensus are influenced by their peers' negative (positive) opinions. The results suggest that interactive meetings contribute in acquiring information and opinions from other participants (especially informed participants) rather than from corporate insiders.     

Oil price uncertainty and stock price informativeness: Evidence from investment-price sensitivity in China

We study the effects of oil price uncertainty (OPU) on stock price informativeness based on investment-price sensitivity. Using Chinese stocks from 2008 to 2021, we find a negative relationship between OPU and the strength of Tobin's q (a standardized measure of prices) for predicting investment opportunities. This finding is likely due to the crowding out of informed investors rather than the financial constraints brought by a higher cost of capital. Investment-price sensitivity also decreases more among firms in less-competition, high sales volatility, and lower analysts' attention. What is more, the reduction in investment-price sensitivity is more concentrated in public utilities, agriculture & livestock, and industry instead of in real estate or commerce industries. These findings indicate that OPU decreases the acquisition of information related to firms, and consequently, price informativeness for future investment decisions.     

Financial Analyst Characteristics and Herding Behavior in Forecasting

This study classifies analysts' earnings forecasts as herding or bold and finds that (1) boldness likelihood increases with the analyst's prior accuracy, brokerage size, and experience and declines with the number of industries the analyst follows, consistent with theory linking boldness with career concerns and ability; (2) bold forecasts are more accurate than herding forecasts; and (3) herding forecast revisions are more strongly associated with analysts' earnings forecast errors (actual earnings—forecast) than are bold forecast revisions. Thus, bold forecasts incorporate analysts' private information more completely and provide more relevant information to investors than herding forecasts.     

Expectations‐Based Management

The authors begin by summarizing the results of their recently published study of the relation between stock returns and changes in several annual performance measures, including not only growth in earnings and EVA, but changes during the year in analysts' expectations about future earnings over three different periods: (1) the current year; (2) the following year; and (3) the three‐year period thereafter. The last of these measures—changes in analysts' expectations about three‐ to five‐year earnings—had by far the greatest explanatory “power” of any of the measures tested. Besides being consistent with the stock market's taking a long‐term, DCF approach to the valuation of companies, the authors' finding that investors seem to care most about earnings three to five years down the road has a number of important implications for financial management: First, a business unit doesn't necessarily create shareholder value if its return on capital exceeds the weighted average cost of capital—nor does an operation that fails to earn its WACC necessarily reduce value. To create value, the business's return must exceed what investors are expecting. Second, without forecasting returns on capital, management should attempt to give investors a clear sense of the firm's internal benchmarks, both for existing businesses and new investment. Third, management incentive plans should be based on stock ownership rather than stock options. Precisely because stock prices reflect expectations, the potential for prices to get ahead of realities gives options‐laden managers a strong temptation to manipulate earnings and manage for the short term.     

Individual analysts,stock return synchronicity and information efficiency

To shed light on whether and how effective are analysts as information intermediaries, we construct the information efficiency indicator and investigate the information performance of China's analysts from the perspective of heterogeneous individual analysts based on stock return synchronicity. Furthermore, we verify the rationality and generalization of information efficiency based on the regression of primary and expanded indicators on stock characteristics and analyst characteristics. Our indicator provides a novel method to accurately measure analysts' information performance from the level of individual analysts rather than from a homogeneous community or heterogeneous group and highlights the analysts' roles as the information intermediaries.     

Discrete Expectational Data and Portfolio Performance

In this article we examine the information content in analysts' recommendations which are made on a five-point buy, hold, or sell scale. Our data set includes data on 10,000 forecasts per month. Unlike most prior studies, our data set does not suffer from selection or survivorship bias. We find information in analysts' changes in recommendations. Approximately 4.5% extra return can be earned by purchasing new buys rather than new sells.     

Does the mandatory disclosure of audit information affect analysts' information acquisition?

This paper explores the effect of public information on analysts' information acquisition. By introducing the implementation of the Key Audit Matters (KAM) Disclosure Standards for China's firms cross-listed in Hong Kong in 2017, we present evidence that KAM disclosure reduces analysts' firm visits, which is an important channel of information acquisition. The effect is particularly pronounced for firms with audit partner rotation and low institutional ownership. KAM disclosure by industrial leaders has a spillover effect on analyst visits for peer firms. Disclosure also improves the frequency and quality of analysts' forecasts and firms' information environments, indicating that KAMs are informative and audit information is an important determinant of analysts' information acquisition. Our study reveals the real effect of KAM disclosure on analyst decisions, which may be of interest to regulators concerned with the mandatory disclosure of audit information and capital market efficiency.     

The impact of institutional analyst forecast divergence on crude oil market: Evidence from the mixed frequency models

As important information intermediaries, analysts play a non-negligible role in the crude oil market. Existing research often focuses on analysts' collection and interpretation of firm-specific information, but neglects the impact of analysts' forecasts on specific markets such as the crude oil market, which is crucial to the safe and stable development of the crude oil market. Therefore, this study uses historical data from January 2011 to December 2020 as a sample to construct analysts' forecast divergence indicators from 15 institutional analysts' forecast data on international crude oil futures prices. It then explores the impact of institutional analysts' forecast divergence on oil price return volatility, crude oil market jumps and crude oil futures trading volume, based on various mixed-frequency models. The results are as follows: First, volatility in oil price returns increases with a growing divergence in analysts' forecasts. Second, analysts' forecasts do not trigger jump in the crude oil market on the first six days after the information is released, but trigger a significant positive jump in the market on the seventh day. Third, the impact of analysts' forecast divergence on trading volume is weak; however, the reverse effect is significant, while the static and dynamic spillover results are consistent.     

Analysts’ estimates of the cost of equity capital

We explore a large sample of analysts' estimates of the cost of equity capital (CoE) to evaluate their usefulness as expected return proxies (ERP). We find that the CoE estimates are significantly related to a firm's beta, size, book-to-market ratio, leverage, and idiosyncratic volatility but not other risk proxies. Even after controlling for the popular return predictors, the CoE estimates incrementally predict future stock returns. This predictive ability is better explained as the CoE estimates containing ERP information rather than reflecting stock mispricing. When evaluated against traditional ERPs, including the implied costs of capital, the CoE estimates are found to be the least noisy. Finally, we document CoE responses around earnings announcements, demonstrating their usefulness to study discount-rate reactions of market participants. We conclude that analysts' CoE estimates are meaningful ERPs that can be fruitfully employed in a variety of asset pricing contexts.     

Stakeholder relations and stock returns: On errors in investors' expectations and learning

A significant number of institutional investors publicly state the belief that corporate stakeholder relations are associated with firm value in a manner that the financial market fails to understand. We investigate whether stakeholder information predicted risk-adjusted returns due to errors in investors' expectations and ultimately ceased to do so as attention for such information increased. We build a stakeholder-relations index (SI) for a wide range of U.S. firms over the period 1992–2009 and provide evidence that the SI explained errors in investors' expectations about firms' future earnings. The SI was positively associated with long-term risk-adjusted returns, earnings announcement returns, and errors in analysts' earnings forecasts over the period 1992–2004. However, as attention for stakeholder issues became more widespread, subsequently, these relationships diminished considerably. The results are consistent with the idea that increased investor attention for stakeholder issues eventually eliminates mispricing.     

Real earnings management and the properties of analysts' forecasts

Prior literature generally finds analysts are able to identify and process complex financial information. However, research suggests that in certain settings, analysts struggle to fully incorporate into their forecasts all available information. We examine analysts' forecast properties in the face of a specific type of complex financial information: real earnings management (REM). First, we investigate the relation between measures of REM and analysts' forecast properties. We find REM measures are associated with greater forecast error and dispersion in the following year. However, REM measures, by definition, capture abnormal operating results, and thus include both firms engaging in manipulative REM as well as firms experiencing firm-specific economic shocks. Thus, we conduct cross-sectional tests of analysts' forecasts for firms with and without incentives to manipulate earnings. We find that firms with low incentives to engage in earnings management (i.e., firms most likely experiencing firm-specific economic shocks) generate the strongest positive relation between REM measures and the following year's analysts' forecast properties, suggesting analysts more fully incorporate the earnings implications of firms with high incentives (i.e., firms most likely engaging in manipulative REM). Our results are consistent across numerous REM proxies and indicators of earnings management incentives.     

Rational expectations,analysts' forecasts of earnings and sources of value gains for takeover targets

Value gains to target firm shareholders in takeover bids may be due to potential synergy between bidder and target and/or potential target restructuring based on new information released by the bid. Since these two models have different implications for the anticipated earnings of the target as a stand-alone entity, analysts' earnings forecast revisions (AFR) for the target during the bid may provide evidence for the new information hypothesis. For 326 UK targets of takeover bids during 1987–1993, we estimate analysts' earnings forecast revisions using the Institutional Brokers Estimate System (IBES) and relate them to bid premia paid to target shareholders. Analysts revise their forecasts significantly up on bid announcement. For failed, especially failed hostile, bids, the earnings forecast revision and bid premium are more positively correlated than for successful and friendly bids. This is consistent with the rational expectations behaviour of target shareholders modelled by Grossman and Hart [S.J. Grossman, O.D. Hart, Bell Journal of Economics 11(1) (1980) 42; S.J. Grossman, O.D. Hart, Journal of Finance 36 (1981) 253].     

Do analysts’' forecast properties deter suboptimal labor investment decisions? Evidence from Regulation Fair Disclosure

We examine whether analysts' forecast properties deter inefficient labor investment decisions. Using accuracy and dispersion as analysts' forecast properties, we find that more accurate and less dispersed forecasts are associated with less inefficient corporate labor investments. Utilizing Regulation Fair Disclosure (Reg FD) as an exogenous variation to analysts' forecast activities, we find a causal relationship between analysts' forecast properties and labor investment inefficiency. We also find that more accurate and less dispersed forecasts decrease labor cost stickiness. Our results are consistent with the view that analysts' forecast properties enhance the information environment, which, in turn, improves corporate labor investment decisions.     

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.     

Tests of Analysts' Overreaction/Underreaction to Earnings Information as an Explanation for Anomalous Stock Price Behavior

This study examines whether security analysts underreact or overreact to prior earnings information, and whether any such behavior could explain previously documented anomalous stock price movements. We present evidence that analysts' forecasts underreact to recent earnings. This feature of the forecasts is consistent with certain properties of the naive seasonal random walk forecast that Bernard and Thomas (1990) hypothesize underlie the well-known anomalous post-earnings-announcement drift. However, the underreactions in analysts' forecasts are at most only about half as large as necessary to explain the magnitude of the drift. We also document that the “extreme” analysts' forecasts studied by DeBondt and Thaler (1990) cannot be viewed as overreactions to earnings, and are not clearly linked to the stock price overreactions discussed in DeBondt and Thaler ( 1985 , 1987 ) and Chopra, Lakonishok, and Ritter (Forthcoming). We conclude that security analysts' behavior is at best only a partial explanation for stock price underreaction to earnings, and may be unrelated to stock price overreactions.