Market Expectations Of Earnings Research Articles

Would Managers Sacrifice Conservative Financial Reporting to Meet/Beat Market Earnings Expectations?

Prior studies show that engaging in conservative financial reporting (CON) positively affects earnings quality. However, managers also manage earnings to meet/beat market earnings expectations (MBME). This study asks three questions regarding the earnings that MBME. First, it investigates whether managers are willing to sacrifice CON when adopting strategies to MBME. Second, it tests whether managers prefer to use other earnings management (EM) strategies to MBME instead of sacrificing CON. Third, it tests whether information asymmetry between managers and shareholders affects managers’ decisions to sacrifice CON. Results show that managers are more likely to sacrifice CON to MBME but are less likely to do so if they can manage earnings using accrual-based or real EM. Also, managers are more likely to do so when information asymmetry with shareholders is higher. These findings contribute to the literature by examining the circumstances in which managers would sacrifice CON to MBME.

Rationalizing forecast inefficiency

We show analysts’ own earnings forecasts predict error in their own forecasts of earnings at other horizons, which we argue provides a measure of the extent to which analysts inefficiently use information. We construct our measure by exploiting two sources of variation in analysts’ incentives: (i) more recent forecasts have greater salience at the time of the earnings release so accuracy incentives are higher (lower) at shorter (longer) forecast horizons and (ii) analysts have greater incentives for optimism (pessimism) at longer (shorter) horizons. Consistent with these incentives affecting the incorporation of information into forecasts, we document (i) current year forecasts underweight (overweight) information in shorter (longer) horizon forecasts and (ii) the mis-weighting is more pronounced when recent news is negative—when analysts have greater (weaker) incentives to incorporate the news into shorter (longer) horizon forecasts. Finally, returns tests suggest that forecasts adjusted for the inefficiency we document better represent market expectations of earnings.

Market earnings expectation, measurement error in analysts’ consensus forecasts and prediction of stock returns

PurposeIn capital markets research, analysts’ consensus forecasts are widely used as a proxy for unobservable market earnings expectation. However, they measure the market earnings expectation with error that may vary cross-sectionally, as the market does not consistently rely on analysts’ consensus forecasts to form earnings expectation (Walther, 1997). Based on this notion, this paper aims to relate the prediction of future stock returns to the cross-sectional variation of the error in measuring market earnings expectation embedded in analysts’ consensus forecasts.Design/methodology/approachThis study uses empirical analyses based on stock returns and annual analysts’ consensus forecasts.FindingsBased on the analytical work by Abarbanell et al. (1995), this study reports that when the measurement error in annual analysts’ consensus forecasts is the smallest, forward earnings-to-price ratio (constructed with annual analysts’ consensus forecasts) best explains future stock returns, and the forward earnings-to-price ratio-based investment strategy is the most profitable.Originality/valueFindings of this study are useful to capital markets research that relies on the market earnings expectation and to practitioners seeking more profitable investment strategies.

Corporate Culture and Financial Reporting Risk: Looking Through the Glassdoor

We study whether financial reporting risk is associated with job satisfaction, company culture, and opinions of senior leadership. We use novel data on employees’ perspectives obtained from the website Glassdoor, covering 14,282 firm-years in the period 2008-2015. We argue that poorly implemented performance objectives leads to pressure and creates a boiler room effect, negatively impacting the corporate climate of the firm and increasing the propensity to manipulate performance metrics. We find that firms with lower levels of job satisfaction (as measured by employees) and lower levels of “culture and values” are more likely to be subjected to SEC fraud enforcement actions and securities class action lawsuits. Consistent with the boiler room effect, we find that a negative corporate climate is also associated with an increased likelihood of narrowly meeting or beating market earnings expectations. Conversely, we find job satisfaction and positive employee opinions of senior leadership to be associated with lower abnormal accruals. We also find that the association between firms’ culture and financial reporting risk is stronger for firms with weaker board independence. Thus, the work environment, as perceived by employees, appears to play a critical role in financial reporting risk.

Macroeconomic News-Flow, Earnings Expectations and Return Predictability

This paper investigates the usefulness of the real-time macroeconomic news-flow as a leading indicator of firm-level end-of-quarter realized earnings. I find that the macroeconomic news flow strongly anticipates end-of-quarter earnings. However, macroeconomic news is not fully incorporated into market earnings expectations. Subsequently, using earnings announcements pricing tests, I demonstrate that this market failure translates into stock return predictability. These findings have three main implications for capital markets research in accounting. Firstly, they suggest that real-time macroeconomic could be used to update earnings expectations in real-time. Secondly, these findings open the door for developing new quarterly earnings time-series models that could compete with analyst forecasts. Thirdly, the information content of macroeconomic news is economically significant as evident from the magnitude of the risk-adjusted returns around earnings announcements.

Cost Behavior, Earnings Expectations and Stock Prices

This study empirically examines whether cost stickiness and cost variability (i) are recognized by investors in forming their earnings expectations, and, (ii) influence the speed of incorporating information on earnings surprises into stock prices. Findings indicate that the market earnings expectations are upward biased for firms with high sticky costs and downward biased for firms with high anti-sticky costs, suggesting a systematic bias induced by partial comprehension of cost stickiness. Consequently, cost stickiness slows down the incorporation of earnings surprises into stock prices, substantially exacerbating the widely documented PEAD anomaly. In contrast, implications of cost variability are recognized by investors to a reasonable extent

Dispersion of Beliefs, Stock Prices and the Earnings Surprise Measures - A Generalized Approach

In this paper we address the issue of modelling the relation between the stock prices and accounting earnings in the presence of potential divergence of opinions regarding the earnings data generating process among the investors. In our model the market's earnings expectation is defined as the weighted average of both the time-series and analysts' forecasts, with the weights being estimated directly from stock returns. No assumptions are made on the functional form of the earnings surprise-stock returns relation, which makes our model flexible enough to incorporate a variety of models discussed in the previous literature. The model is estimated semiparametrically following Hardle et. al [Annals of Statistics, 1993]. Our key findings are as follows. First, we find that investors use both the time-series and analysts' forecasts to predict future earnings. Second, the proportion of investors using the time-series (analysts) forecasts is significantly higher (lower) for the stocks with low market capitalization. Third, we find that accounting for the dispersion of earnings forecasts leads to a substantial increase in the magnitude of the post-earnings announcement drift.

Auditor Independence and the Likelihood of a GAAP Violation

This paper examines whether auditor independence is compromised resulting in poor quality audit when auditors provide substantial non-audit services to their clients. Prior studies have used abnormal discretionary accruals, financial restatements, the likelihood of issuing a qualified opinion, or meeting/beating market earnings expectation as proxies for poor audit quality. The findings of these studies have been mixed and can be attributed, in part, to the inherent noise in the proxies for audit quality. This study examines the question of auditor independence by using the likelihood that a firm will violate GAAP (Beneish, 1999) as a proxy for audit quality. The finding of this study is that Fortune? 500 firms, whose auditors provide substantial non-audit services, tend to have a higher propensity to violate GAAP. These finding have policy implications for regulators considering making changes in the current regulations on outsourcing of non-audit services to independent auditors.

How Do Firms Manage Their Earnings Forecast Strategy? A New Zealand Study

In contrast to the trend of research investigating why firms decide to release earnings forecasts to pre-empt any expected change in earnings, our study investigates how firms manage their earnings forecast strategy once they have decided to release earnings forecasts. Using a sample of 350 NZX-listed firm years with balance date ending from 31 January 1999 to 31 December 2005 for 94 companies across the statutory-backed continuous disclosure regime, we document that firms are more likely to adopt an earnings forecast portfolio approach in the post statutory sanctions period, particularly for the group of firms expecting favourable earnings change. We also document that these good news firms have a higher propensity to gradually update the market with good news earnings forecasts while those with bad news are more likely to immediately correct current market expectations of earnings or prior earnings forecast errors. These findings indicate that firms expecting better earnings performance are more conservative in their earnings forecasting compared to those expecting worse earnings performance. Even though this asymmetrical treatment between good news and bad news might not meet the objective of corporate regulators in promoting a continuously updated market, the fact that good news firms indeed increase their earnings forecast practices in the post sanction period does indicate an improvement in the information flow to the capital market.

A Comparison of Analysts' and Investors' Biases in Interpreting Accruals: A Valuation Approach

Elgers, Lo, and Pfeiffer (2003) argue that analysts' earnings forecasts are less biased than the market's earnings expectation in interpreting accruals. Their argument implies that analysts' earnings forecasts could potentially mitigate the market's mispricing of accruals by guiding investors to reduce their earnings prediction errors arising from the misinterpretation of accruals. Their results call for further investigation, however, owing to two questionable research design choices: (1) estimating the magnitude of the market's bias using the traditional earnings response coefficient (ERC) model, which is vulnerable to the well-known omitted-variable problem; and (2) examining only the bias in short-term (i.e., one-year-ahead) earnings expectations, ignoring possible bias in earnings expectations for longer future periods. To alleviate these concerns, we take an alternative approach in which we compare the bias of the market's equity value estimates (i.e., stock prices) against the bias of equity value estimates based on analysts' earnings forecasts in valuing accruals. By taking this alternative approach, we find that analysts' earnings forecasts are more biased than stock prices in interpreting accruals. Thus, contrary to Elgers, Lo, and Pfeiffer (2003), we conclude that analysts' earnings forecasts do not mitigate the market's mispricing of accruals.

Differential Earnings Behavior and the Security Market Assessment of Variation in Seasonal Earnings Patterns

We provide new evidence regarding the anomalous security market behavior that pertains to the predictability of abnormal security returns at future quarterly earnings announcements (Bernard and Thomas [1990]) as well as the security market's ability to form quarterly earnings expectations that are consistent with the market factoring in the serial correlation in the seasonally differenced quarterly earnings series (Ball and Bartov [1996]; Soffer and Lys [1999]). Consistent with extant work, we find that just prior to the quarterly earnings announcement date, the security market's expectation of quarterly earnings is consistent with the market recognizing the serial correlation in seasonally differenced quarterly earnings but underestimating its magnitude. When we treat all firms as exhibiting the same quarterly earnings process, our results reinforce the findings of Soffer and Lys (1999) that security market earnings expectations at the beginning of the quarter are consistent with investors not recognizing the serial correlation in the seasonally differenced quarterly earnings series. By distinguishing between those firms whose quarterly earnings process is inconsistent with a seasonal random walk (SRW) process (i.e., “bad-fit” firms) vis-à-vis those firms whose quarterly earnings process is better described by the SRW process (i.e., “good-fit” firms), we provide additional insights on this relationship throughout the quarter leading up to the quarterly earnings announcement date. Specifically, we find that security market expectations of quarterly earnings are consistent with a market that recognizes the differential time-series properties of quarterly earnings. That is, at the beginning of the quarter, for the “bad-fit” (“good-fit”) firms, we find that the security market acts as if it is aware (unaware) of the correct sign of the serial correlation in the seasonally differenced quarterly earnings series. However, the security market still acts as if it underestimates the magnitude of the serial correlation.

The Predictive Value of Analyst Characteristics

While numerous intuitively appealing characteristics of individual analyst earnings forecast accuracy have been identified, the extant literature has provided no evidence regarding the out-of-sample predictive validity of these characteristics. We examine whether these characteristics possess incremental predictive ability vis-à-vis forecast age, the control variable of these studies. We compare the predictive ability of a consensus forecast based solely on forecast age (Age) with that of a six-factor model consisting of forecast age plus five analyst characteristics suggested by the literature (Model). We use the dual evaluative criteria suggested by Foster (1977) and employed numerous times thereafter to assess predictive ability: (1) the ability to predict the next number in the time series and (2) the ability to approximate the capital market's earnings expectation. We show that Age predicts as well as Model using both predictive ability criteria. Because Model consists of Age plus five other factors, it is cost-beneficial to use Age in lieu of Model for predictive purposes. FASB Statement of Financial Accounting Concepts No. 2 (1980) identifies predictive value as a criterion of information relevance. We show that analyst characteristics have no relevance for the purpose of obtaining better predictions of the next quarterly earnings number vis-à-vis a simpler model based on forecast age. There are many reasons for identifying individual analyst-based characteristics, but predictive ability of the next quarterly number is not one of them.

Do Stock Prices Fully Reflect Information in Dividends about Future Earnings?

We investigate (1) whether investors' earnings expectations include dividend information that is incremental to information in earnings components and (2) whether investors correctly weight the incremental information reflected in dividends. We find that both dividends and dividend changes are related to future earnings after controlling for earnings-component information, and that the market's earnings-expectation model reflects the incremental dividend information. However, we find that stock prices act as if investors overweight the incremental information in dividends and dividend changes in forming earnings expectations. Consequently, we find predictable future stock returns related to dividends and dividend changes after controlling for the relation between future returns and earnings components.

Time-series Properties and Pricing of the Special Items Component of Earnings

We demonstrate that the effect of special items on the time-series of seasonally-differenced quarterly earnings differs from the effect of other components of earnings. Focusing on earnings four quarters subsequent to the special item where the time-series differences are most pronounced, we also demonstrate that market expectations of earnings impounded in prices reflect these time-series differences. Further, our estimates suggest that the proportion of the time-series implications of special items impounded in prices is larger than the proportion for other, non-special items, components of earnings. Nonetheless, market prices do not fully reflect time-series implications of special items ? a significant proportion of the time-series implications of negative special items is not impounded in prices and past values of special items predict subsequent abnormal returns.

Investor Sophistication and Market Earnings Expectations

This paper investigates whether sophisticated investors rely more on analyst forecasts than on time-series model forecasts in forming expected earnings. Specifically, I investigate if earnings-announcement-related returns are more closely associated with analyst (SRW) forecasts for firms for which the marginal investor is more (less) likely to be sophisticated. My proxies for investor sophistication are institutional ownership, analyst following, and firm size (Atiase [1985], Hand [1990]). I predict that market participants place more weight on the analyst forecast for firms with high institutional ownership, firms with high analyst following, and large firms. For a sample of 89,246 firm-quarter observations over 1980-1995, I find that the weight placed on the analyst (SRW) forecast is increasing (decreasing) in institutional ownership, analyst following, and firm size. Forecast availability (as captured by publication in The Wall Street Journal) or forecast accuracy cannot account for these findings. Overall, my results suggest that market earnings expectations do not consistently resemble either analyst or SRW forecasts. Rather, the cross-sectional variation in the relative weights placed on these two forecasts is related to proxies for the sophistication of the marginal investor.

Investor Sophistication and Market Earnings Expectations

This paper investigates whether sophisticated investors rely more on analyst forecasts than on time-series model forecasts in forming expected earnings. Although analyst forecasts are generally more accurate than time-series model forecasts (e.g., O'Brien [1988]), analyst forecasts are not clearly superior to time-series model forecasts as a proxy for expected earnings (e.g., Brown et al. [1987b]). Recent research has concluded that earnings expectations reflected in stock prices at least partially reflect a seasonal random walk (SRW) model (Bernard and Thomas [1990] and Abarbanell and Bernard [1992]). In particular, Ball and Bartov [1996] find that market earnings expectations incorporate the sign of the serial correlation in seasonally differenced earnings but underestimate the correlation magnitude (see also Maines and Hand [1996]). These findings suggest that at least some market participants ignore public information in forming expected earnings; I examine whether information usage is correlated with investor sophistication and/or the degree to which investors are informed.

An empirical examination of the dispersion and accuracy of analyst forecasts surrounding option listing

Prior theoretical and empirical research indicates that option trading enhances the availability and timeliness of market information, and that the market's earnings expectation (belief) is influenced by characteristics of the information environment. Motivated by these research findings, we investigate whether option listing is associated with changes in the market's expectations about future earnings. Assuming that the distribution of analysts' earnings forecasts serves as a proxy for the market's earnings expectations and using I/B/E/S consensus analyst forecasts, we examine two properties of analyst forecasts: accuracy and dispersion. The results indicate that consensus analyst forecast accuracy improves after option listing and that the variability of analyst forecasts increases after option listing. The accuracy and dispersion results are somewhat weaker but still present after controlling for firm size and analyst following.

Earnings forecasting research: its implications for capital markets research

Since the early 1980s, earnings forecasting research has become much more closely aligned with capital markets research. Capital markets research requires a proxy for the (unobservable) market earnings expectation and earnings forecasting research has provided such proxy measures. Questions considered in this paper include: (1) if annual earnings follow a random walk or an IMA (1,1) model, does this mean that earnings changes cannot be predicted? (2) Do stock prices act as if quarterly earnings follow a seasonal random walk with drift process? (3) Is the predictive model which is best on the forecast accuracy dimension also best on the market association dimension? (4) How do analysts formulate their earnings expectations? (5) What is the role of earnings forecasting in ‘earnings response coefficient’ and ‘post-earnings announcement drift’ studies? (6) What is the likely role of earnings forecasting research in future capital market studies?

Analysts' utilization of historical earnings information

This study examines whether security analysts (in)efficiently utilize the information contained in past series of annual and quarterly earnings in producing earnings forecasts. To do so, it investigates whether equal-weighted combinations of security analysts' forecasts with forecasts from statistical models based on historical earnings are superior, both in terms of being a better surrogate for the market's expectations of earnings and of accuracy, to forecasts from either one of these two sources. The empirical findings indicate that, although analysts' forecasts are superior to forecasts from statistical models, performance can be improved—both in terms of accuracy and also of being a better surrogate for market earnings expectations—by combining analysts' forecasts with forecasts from statistical models based on past quarterly earnings. Improvements in proxying for market earnings expectations were obtained even when analysts' forecasts made in June of the forecast year were used in the combinations. An implication of these findings is that investors can improve their investment decisions by using an average of the mean analysts' forecasts and the forecast produced by a time-series model of quarterly earnings in their investment decisions.

The Estimation and Determinants of Associations between Returns and Earnings: Evidence from Cross-Industry Comparisons

Associations between accounting earnings and stock returns are modeled and tested by examining relationships between earnings response coefficients and industry structure characteristics. Response coefficients are estimated using a new approach that does not require proxies for market earnings expectations. This approach appears to be well specified relative to a traditional approach and may have wider applicability in other research contexts. A randomization procedure for controlling for returns dependence is also applied. The results suggest that response coefficients differ considerably across industries and that these differences are related to industry entry barriers, product type, growth, financial leverage, and operating leverage.