Mitigating the Influence of Analysts Who Issue Aggressive Stock Price Targets: The Role of Joint Versus Separate Evaluation*

Investors frequently rely on individual analysts' stock price targets. Aggressive price targets often reflect analysts' attempts to strategically influence investors. Therefore, investors' welfare may be compromised if they take aggressive price targets at face value. In this study, we examine conditions under which investors are more likely to infer that analysts who issue aggressive price targets are acting strategically. Investors can evaluate multiple analysts' price targets with or without other related information (e.g., earnings estimates). Investors can also evaluate the information provided by multiple analysts jointly or separately one analyst at a time. Two experiments find that as predicted, when investors evaluate multiple analysts' price targets without earnings estimates, there is no difference in investors' perceptions about whether the aggressive analyst is acting strategically across joint versus separate evaluation. However, also as predicted, when investors evaluate multiple analysts' price targets along with their earnings estimates, investors perceive the aggressive analyst as acting more strategically under joint evaluation than under separate evaluation. Our findings suggest that jointly evaluating multiple analysts' price targets with other related information, such as earnings estimates, can reduce the likelihood that investors would be overly influenced by aggressive analysts.     

Asymmetric Inventory Management and the Direction of Sales Changes*

We study manufacturing firms' asymmetric inventory investment in response to sales changes. Focusing on the costs of resource adjustment and stockout that likely differ in sales‐increasing and sales‐decreasing periods, we predict and find that inventory investment declines less during periods with sales decreases than it rises during periods with sales increases. We validate this claim by showing that managers' expectations of future demand and desire to avoid inventory stockouts are important determinants of this asymmetry. In addition, we find that asymmetric inventory investment provides useful information for predicting future sales growth, and that both managers' and analysts' sales forecasts are positively associated with the asymmetry. Lastly, we document that forecasts of future sales growth that incorporate asymmetric inventory investment are associated with lower absolute forecast errors than benchmark forecasts. Overall, we highlight the importance of inventory information in understanding managers' resource adjustment and utilization decisions that have implications for forecasting future demand. Our findings on asymmetric inventory management provide new insights to fundamental analysis based on inventory signals.     

An Analysis of Historical and Future-Oriented Information in Accounting-Based Security Valuation Models*

The Ohlson (1995) and Feltham and Ohlson (1995) valuation model provides a rigorous framework for summarizing the information in expected future earnings and book values. However, the model provides little guidance on selecting an empirical proxy for expected future earnings. We examine whether and under what circumstances historical earnings and analyst earnings forecasts offer comparable explanation of security prices. This issue is of particular interest because analyst forecasts are less readily available than historical data. Under appropriate circumstances, historical data may allow wider use of the Feltham-Ohlson valuation model by researchers and investors. A related issue is the incremental explanatory power of historical earnings and realized future earnings (perfect-foresight forecasts) for security prices beyond analyst forecasts. If historical earnings are incrementally informative, that would suggest that analyst forecasts do not fully reflect price-relevant information in past earnings. If future earnings are incrementally informative, that would suggest that security prices reflect investors' implicit earnings forecasts beyond analyst forecasts. We examine these issues using a historical model (based on past earnings), a perfect-foresight model (based on realized future earnings), and a forecast model (based on Value Line earnings forecasts). All three models provide significant explanatory power for security prices, and each set of earnings data provides incremental explanatory power for prices when used with the other sets of earnings data. We estimate the models separately for firms with moderate and extreme earnings-to-price (E/P) ratios, a proxy for earnings permanence. For moderate-E/P firms, the historical model's explanatory power exceeds that of the perfect foresight model, and is indistinguishable from that of the analyst forecast model. In contrast, for extreme-E/P firms, the perfect-foresight model offers greater explanatory power than the historical model, but lower explanatory power than analyst forecasts. Our results suggest that financial analysts' forecasting efforts are best focused on firms whose earnings contain large temporary components (extreme E/P firms). However, in general, both historical data and analyst forecasts are complementary information sources for security valuation.     

An Empirical Examination of the Divergence between Managers’ and Analysts’ Earnings Forecasts

We study circumstances when analysts’ forecasts diverge from managers’ forecasts after management guidance, and the consequences of this divergence for investors and analysts. Our results show that investors’ return response to earnings surprises based on analyst forecasts is significantly weaker when analyst and management forecasts diverge, and that this attenuating effect is stronger when the management forecast is more credible. When the divergent management forecast is more accurate than the analyst consensus forecast, the subsequent‐quarter analyst consensus forecast is significantly more accurate than that of the current quarter, and exhibits less serial correlation. Overall, our findings suggest that, when analyst and management forecasts diverge, investors find the two sources to contain complementary information, and analysts learn to improve their subsequent forecasts.     

Earnings Non‐Synchronicity and Voluntary Disclosure

Earnings non‐synchronicity reflects the extent to which firm‐specific factors determine a firm's earnings. Prior research suggests that high earnings non‐synchronicity impedes corporate outsiders' ability to process information. This study examines the impact of earnings non‐synchronicity on managers' decisions to provide earnings forecasts. We propose that high earnings non‐synchronicity motivates managers to issue earnings forecasts to reduce information asymmetry between managers and investors and to preempt costly information acquisition by outsiders. Consistently, we find a positive relation between earnings non‐synchronicity and managers' propensity to issue earnings forecasts, particularly long‐horizon forecasts. This positive relation is weaker when earnings are easier to predict based on the firm's earnings history and is stronger when the firm has higher institutional ownership and greater analyst following. We also find that the market's reaction to management forecasts increases with earnings non‐synchronicity. Overall, the evidence suggests that managers voluntarily provide earnings forecasts to alleviate the adverse consequences of earnings non‐synchronicity. These findings provide a more complete picture about the impact of earnings non‐synchronicity on a firm's information environment, and highlight the effect of the nature of information asymmetry on voluntary disclosures.     

Earnings Forecasts and Price Efficiency after Earnings Realizations: Reduction in Information Asymmetry through Learning from Price*

When information asymmetry is a major market friction, earnings forecasts can lead to higher price efficiency even after the information in forecasts completely dissipates upon earnings realizations. We show this in an experimental market that features information asymmetry (i.e., some traders possess differential private information). Earnings forecasts reduce information asymmetry and lead to prices that reflect a greater amount of private information. Traders can learn more about others' information from prices. This information learned from past prices continues to reduce information asymmetry and improve price efficiency even after earnings realizations. We contribute to the disclosure literature by showing the evidence that the learning‐from‐price effect amplifies the impact of public disclosure on price efficiency.     

To Guide or Not to Guide? Causes and Consequences of Stopping Quarterly Earnings Guidance

In recent years, quarterly earnings guidance has been harshly criticized for inducing “managerial short‐termism” and other ills. Managers are, therefore, urged by influential institutions to cease guidance. We examine empirically the causes of such guidance cessation and find that poor operating performance — decreased earnings, missing analyst forecasts, and lower anticipated profitability — is the major reason firms stop quarterly guidance. After guidance cessation, we do not find an appreciable increase in long‐term investment once managers free themselves from investors’ myopia. Contrary to the claim that firms would provide more alternative, forward‐looking disclosures in lieu of the guidance, we find that such disclosures are curtailed. We also find a deterioration in the information environment of guidance stoppers in the form of increased analyst forecast errors and forecast dispersion and a decrease in analyst coverage. Taken together, our evidence indicates that guidance stoppers are primarily troubled firms and stopping guidance does not benefit either the stoppers or their investors.     

Connections between the Market Pricing of Accruals Quality and Accounting-Based Anomalies*

We examine whether prior findings on the market pricing of accruals quality (AQ) can be attributed to other forms of accounting-based anomalies. Using hedge portfolio analysis and cross-sectional regressions, we find that the return predictive power of AQ overlaps with several other accounting signals. We also find that, similar to other accounting-based anomalies, especially the accruals anomaly, the AQ pricing effect (i) is likely due to mispricing instead of risk pricing, (ii) is attenuated in recent years, and (iii) disappears among firms with cash flow forecasts or long-term growth forecasts. Our findings highlight the importance of controlling for existing return predictive signals when evaluating the market pricing of AQ.     

The Association between the Legal and Financial Reporting Environments and Forecast Performance of Individual Analysts*

We test the ability of analyst characteristics to explain relative forecast accuracy across legal origins (common law versus civil law). Common‐law countries generally have more effective corporate governance mechanisms, including stronger investor protection laws and inputs provided through higher‐quality financial reporting systems. In this type of environment, we predict that analysts with superior ability and resources in common‐law countries will more consistently outperform their peers because appropriate market‐based incentives exist. In civil‐law countries, where the demand for earnings information is reduced because of weaker corporate governance mechanisms and lower‐quality financial reporting, we predict that analysts with superior ability will less consistently provide superior forecasts. Results are consistent with our expectations and suggest an association between legal and financial reporting environments and analysts' forecast behavior.     

Analyst Coverage and the Likelihood of Meeting or Beating Analyst Earnings Forecasts

This paper examines the relation between analyst coverage and whether firms meet or beat analyst earnings forecasts. We distinguish between whether a firm's reported quarterly earnings meet (i.e., equal or exceed by one cent) or beat (i.e., exceed by more than one cent) its consensus analyst earnings forecasts. We find a positive relation between analyst coverage and whether a firm meets or beats analyst forecasts. However, the more pronounced relation is that between analyst coverage and meeting analyst forecasts. Also, when we consider exogenous shocks to analyst coverage due to brokerage mergers or closures and conglomerate spinoffs, we continue to find a robust positive relation only between analyst coverage and meeting analyst forecasts. To shed light on the causal relation involved, we examine and find that greater analyst coverage is associated with a significantly larger market reaction to negative earnings surprises. We also document that firms with greater analyst coverage are more likely to guide analyst earnings forecasts downwards. Taken together, our evidence suggests that greater analyst coverage raises the pressure on managers to meet analyst earnings forecasts.     

Price and Volume Reactions to Public Information Releases: An Experimental Approach Incorporating Traders' Subjective Beliefs*

This paper examines how market prices, volume, and traders' dividend expectations respond to public information releases in laboratory markets for a long-lived financial asset. The objective is to study deviations from the symmetric information risk-neutral rational expectations (RE) benchmark, which predicts no trade in such settings. The results of a series of double-auction and call markets are reported in which traders manage a portfolio of cash and asset shares over 15 rounds of trading. A public signal regarding the value of the liquidating dividend is released every third round, and traders' subjective expectations of the liquidating dividend are elicited each round as cash-motivated forecasts. We find that, despite the public dividend signal, traders' dividend forecasts are heterogeneous. Forecasts and prices both underreact to the public signals, with prices under-reacting more than forecasts. In general, price changes are not closely associated with public signals, and there is greater excess price volatility in double auctions than in call markets. Forty-three percent of trades are inconsistent with the trader's forecasts, and inconsistent trades occur more frequently in the double-auction markets. On average, approximately 10 percent of the outstanding shares are traded in each round, and trading volume is increasing in the mean absolute forecast revision and decreasing in the contemporaneous dispersion in forecasts. These results suggest that differential processing of the public signal and/or speculative trading for short-term gain may help to explain why symmetric information RE predictions are often not supported in empirical and experimental settings. They also suggest that market reactions to public information releases may be influenced by market microstructure.     

Linguistic Information Quality in Customers' Forward‐Looking Disclosures and Suppliers' Investment Decisions

This study examines whether and how linguistic information quality (measured by readability) of customer firms' management earnings forecast reports (MEFRs) affects supplier firms' investment quality (measured by investment efficiency). Our analyses reveal that supplier investment efficiency is positively associated with the average linguistic information quality of customers' prior MEFRs, and the positive association between supplier investment efficiency and customer MEFRs' numerical information quality is stronger in supplier firms with more readable customer MEFRs. Our analyses also reveal that higher linguistic information quality of customer MEFRs improves the monitoring of supplier firms by their outside stakeholders, such as institutional investors and financial analysts, and ameliorates the negative impact of suppliers' customer‐dependence on their investment efficiency. Our results suggest that greater linguistic information quality of a customer firm's forward‐looking disclosures is associated with higher‐quality investments made by its suppliers along the supply chain.     

A Re-Examination of Financial Analysts' Differential Earnings Forecast Accuracy*

Abstract. This research re-examines whether there are differences in the forecast accuracy of financial analysts through a comparison of their annual earnings per share forecasts. The comparison of analyst forecast accuracy is made on both an ex post (within sample) and an ex ante (out of sample) basis. Early examinations of this issue by Richards (1976), Brown and Rozeff (1980), O'Brien (1987), Coggin and Hunter (1989), O'Brien (1990), and Butler and Lang (1991) were ex post and suggest the absence of analysts who can provide relatively more accurate forecasts over multiple years. Contrary to the results of prior research and consistent with the belief in the popular press, we document that differences do exist in financial analysts' ex post forecast accuracy. We show that the previous studies failed to find differences in forecast accuracy due to inadequate (or no) control for differences in the recency of forecasts issued by the analysts. It has been well documented in the literature that forecast recency is positively related to forecast accuracy (Crichfield, Dyckman, and Lakonishok 1978; O'Brien 1988; Brown 1991). Thus, failure to control for forecast recency may reduce the power of tests, making it difficult to reject the null hypothesis of no differences in forecast accuracy even if they do exist. In our analysis, we control for the differences in recency of analysts' forecasts using two different approaches. First, we use an estimated generalized least squares estimation procedure that captures the recency-induced effects in the residuals of the model. Second, we use a matched-pair design whereby we measure the relative forecast accuracy of an analyst by comparing his/her forecast error to the forecast error of another randomly selected analyst making forecasts for the same firm in the same year on or around the same date. Using both approaches, we find that differential forecast accuracy does exist amongst analysts, especially in samples with minimum forecast horizons of five and 60 trading days. We show that these differences are not attributable to differences in the forecast issuance frequency of the financial analysts. In sum, after controlling for firm, year, forecast recency, and forecast issuance frequency of individual analysts, the analyst effect persists. To validate our findings, we examine whether the differences in the forecast accuracy of financial analysts persist in holdout periods. Analysts were assigned a “superior” (“inferior”) status for a firm-year in the estimation sample using percentile rankings on the distribution of absolute forecast errors for that firm-year. We use estimation samples of one- to four-year duration, and consider two different definitions of analyst forecast superiority. Analysts were classified as firm-specific “superior” if they maintained a “superior” status in every year of the estimation sample. Furthermore, they were classified as industry-specific “superior” if they were deemed firm-specific “superior” with respect to at least two firms and firm-specific “inferior” with respect to no firm in that industry. Using either definition, we find that analysts classified as “superior” in estimation samples generally remain superior in holdout periods. In contrast, we find that analysts identified as “inferior” in estimation samples do not remain inferior in holdout periods. Our results suggest that some analysts' earnings forecasts should be weighted higher than others when formulating composite earnings expectations. This suggestion is predicated on the assumption that capital markets distinguish between analysts who are ex ante superior, and that they utilize this information when formulating stock prices. Our study provides an ex ante framework for identifying those analysts who appear to be superior. When constructing weighted forecasts, a one-year estimation period should be used because we obtain the strongest results of persistence in this case.     

Who Herds? Who Doesn't? Estimates of Analysts’ Herding Propensity in Forecasting Earnings

We develop parametric estimates of the imitation‐driven herding propensity of analysts and their earnings forecasts. By invoking rational expectations, we solve an explicit analyst optimization problem and estimate herding propensity using two measures: First, we estimate analysts’ posterior beliefs using actual earnings plus a realization drawn from a mean‐zero normal distribution. Second, we estimate herding propensity without seeding a random error, and allow for nonorthogonal information signals. In doing so, we avoid using the analyst's prior forecast as the proxy for his posterior beliefs, which is a traditional criticism in the literature. We find that more than 60 percent of analysts herd toward the prevailing consensus, and herding propensity is associated with various economic factors. We also validate our herding propensity measure by confirming its predictive power in explaining the cross‐sectional variation in analysts’ out‐of‐sample herding behavior and forecast accuracy. Finally, we find that forecasts adjusted for analysts’ herding propensity are less biased than the raw forecasts. This adjustment formula can help researchers and investors obtain better proxies for analysts’ unbiased earnings forecasts.     

Horizon‐Dependent Underreaction in Financial Analysts' Earnings Forecasts*

This paper provides empirical evidence that underreaction in financial analysts' earnings forecasts increases with the forecast horizon, and offers a rational economic explanation for this result. The empirical portion of the paper evaluates analysts' responses to earnings‐surprise and other earnings‐related information. Our empirical evidence suggests that analysts' earnings forecasts underreact to both types of information, and the underreaction increases with the forecast horizon. The paper also develops a theoretical model that explains this horizon‐dependent analyst underreaction as a rational response to an asymmetric loss function. The model assumes that, for a given level of inaccuracy, analysts' reputations suffer more (less) when subsequent information causes a revision in investor expectations in the opposite (same) direction as the analyst's prior earnings‐forecast revision. Given this asymmetric loss function, underreaction increases with the risk of subsequent disconfirming information and with the disproportionate cost associated with revision reversal. Assuming that market frictions prevent prices from immediately unraveling these analyst underreac‐tion tactics, investors buying (selling) stock on the basis of analysts' positive (negative) earnings‐forecast revisions also benefit from analyst underreaction. Therefore, the asymmetric cost of forecast inaccuracy could arise from rational investor incentives consistent with a preference for analyst underreaction. Our incentives‐based explanation for underreaction provides an alternative to psychology‐based explanations and suggests avenues for further research.     

Did the PCAOB's 2009 Office Expansion Improve Audit Quality?*

We investigate whether the PCAOB's decision to expand the number and location of its inspection offices in 2009 improved the reliability of US audits. We use a difference-in-differences empirical design to consider the impacts of the expansion on audit quality and find that audit quality significantly improved following the PCAOB's expansion in markets where new offices opened relative to markets without an office opening. We find that the improvement in audit quality appears to be driven by auditors' reaction to real changes in PCAOB oversight and that triennially inspected auditors appear to be impacted the most by this office expansion. Our findings provide new insights into the PCAOB's operational decision-making and suggest that the regulator's additional investment in audit oversight was effective in improving audit quality.     

Investor Reaction to the Ambiguity and Mix of Positive and Negative Argumentation in Favorable Analyst Reports

This study experimentally tests the hypothesis that investor reaction to favorable investment ratings is influenced by attributes of analysts’ supporting arguments. Specifically, I argue that argument ambiguity and the mix of positive and negative argumentation interact to influence how investors process and, in turn, react to information contained in analysts’ arguments. When positive arguments are unambiguous, I predict and find that investors react to the content of the arguments because they perceive the arguments provide sufficient support for the rating. In this case, investors react more favorably when the report includes strictly positive argumentation (i.e., one‐sided argumentation) than when it includes a mix of positive and negative argumentation (i.e., two‐sided argumentation). In contrast, when positive arguments are ambiguous, two‐sided argumentation acts as a credibility cue and leads to a higher likelihood of investment than one‐sided argumentation. These results provide important insights about the conditions under which investors react to justifications in favorable analyst reports and shed light on how analysts can credibly convey favorable information.     

Determinants of Managerial Earnings Guidance Prior to Regulation Fair Disclosure and Bias in Analysts' Earnings Forecasts*

Prior to Regulation Fair Disclosure (“Reg FD”), some management privately guided analyst earnings estimates, often through detailed reviews of analysts' earnings models. In this paper I use proprietary survey data from the National Investor Relations Institute to identify firms that reviewed analysts' earnings models prior to Reg FD and those that did not. Under the maintained assumption that firms conducting reviews guided analysts' earnings forecasts, I document firm characteristics associated with the decision to provide private earnings guidance. Then I document the characteristics of “guided” versus “unguided” analyst earnings forecasts. Findings demonstrate an association between several firm characteristics and guidance practices: managers are more likely to review analyst earnings models when the firm's stock is highly followed by analysts and largely held by institutions, when the firm's market‐to‐book ratio is high, and its earnings are important to valuation but hard to predict because its business is complex. A comparison of guided and unguided quarterly forecasts indicates that guided analyst estimates are more accurate, but also more frequently pessimistic. An examination of analysts' annual earnings forecasts over the fiscal year does not distinguish between guidance and no‐guidance firms; both experience a “walk‐down” in annual estimates. To distinguish between guidance and no‐guidance firms, one must examine quarterly earnings news: unguided analysts walk down their annual estimates when the majority of the quarterly earnings news is negative; guided analysts walk down their annual estimates even though the majority of the quarterly earnings news is positive.     

Investors' Misweighting of Firm-Level Information and the Market's Expectations of Earnings

Prior studies use fundamental earnings forecasts to proxy for the market's expectations of earnings because analyst forecasts are biased and are available for only a subset of firms. We find that as a proxy for market expectations, fundamental forecasts contain systematic measurement errors analogous to those in analysts' biased forecasts. Therefore, these forecasts are not representative of investors' beliefs. The systematic measurement errors from using fundamental forecasts to proxy for market expectations occur because investors misweight the information in many firm-level variables when estimating future earnings, but fundamental forecasts are formed using the historically efficient weights on firm-level variables. Thus, we develop an alternative ex ante proxy for the market's expectations of future earnings (“the implied market forecast”) using the historical (and inefficient) weights, as reflected in stock returns, that the market places on firm-level variables. A trading strategy based on the implied market forecast error, which is measured as the difference between the implied market forecast and the fundamental forecast, generates excess returns of approximately 9 percent per year. These returns cannot be explained by investors' reliance on analysts' biased forecasts. Overall, our results reveal that market expectations differ from both fundamental forecasts and analysts' forecasts.     

Internal Information Quality and the Sensitivity of Investment to Market Prices and Accounting Profits

We ask whether the quality of internal information matters for investment decisions. We predict that investment is more sensitive to internal profit signals and less sensitive to external price signals when managers have higher‐quality internal information. Consistent with recent theoretical and empirical research, we proxy for internal information quality using observable information properties. We find that the sensitivity of investment to profitability is increasing, while the sensitivity of investment to market‐to‐book is decreasing in internal information quality. Our focus on internal information and decision making offers new and unique insights on the importance of information quality and complements the growing literature on the role of external reporting quality in reducing financing frictions.