The Role of Expectations in Explaining the Cross-Section of Stock Returns

We find highly significant results when the cross-section of market-adjusted stock returns is regressed against changes in analyst expectations this year about: (1) this year's earnings, (2) next year's earnings, (3) long-term earnings growth, and (4) noise (measured as the standard deviation of analyst forecasts). Surprisingly, changes in expectations about this year's earnings are not significant in a multiple regression with the other independent variables. Changes in expectations about next year's earnings are highly significant but with an impact that is much smaller than that of changes in expectations about the long-term growth in earnings. Changes in noise are also statistically significant and are negatively related to market-adjusted returns, an indication that the signal to noise ratio, rather than merely the signal, is what drives price adjustments to new information.     

Cashflow risk,systematic earnings revisions,and the cross-section of stock returns

The returns of stocks are partially driven by changes in their expected cashflow. Using revisions in analyst earnings forecasts, we construct an analyst earnings beta that measures the covariance between the cashflow innovations of an asset and those of the market. A higher analyst earnings beta implies greater sensitivity to marketwide revisions in expected cashflow, and therefore higher systematic risk. Our analyst earnings beta captures exposure to macroeconomic fluctuations and has a positive risk premium that provides a partial explanation for the value premium, size premium, and long-term return reversals. From 1984 to 2005, 55.1% of the return variation across book-to-market, size, and long-term return reversal portfolios is captured by their analyst earnings betas.     

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.     

Do management EPS forecasts allow returns to reflect future earnings? Implications for the continuation of management’s quarterly earnings guidance

Using 18,253 firm-year observations from 1998 through 2003, we build on literature suggesting that more informative disclosures allow returns to better reflect future earnings and test whether management earnings per share forecasts and their characteristics influence the future earnings response coefficient (FERC). We find that FERCs are greater for forecasting firms and when forecasts are more frequent or precise. We suggest that more frequent and more precise forecasts assist investors in better predicting future earnings. Importantly, we find that quarterly and short-term forecasts incrementally increase the association between returns and future earnings beyond annual and long-term forecasts; thus, even short-term, quarterly forecasts allow investors to form better expectations about future earnings. This suggests a benefit of quarterly earnings forecasts possibly overlooked in recommendations from the United States Chamber of Commerce, CFA Institute, Business Roundtable Institute for Corporate Ethics, and The Conference Board to eliminate quarterly earnings guidance.     

The Effect of Bank-firm Relationships on Sell-side Research

In this paper, I examine how the lending relationships between banks and their borrowers affect the quality of analysts’ earnings forecasts after financial deregulation in Japan. My findings show that short-term lending relationships improve the quality of analysts’ earnings forecasts and that these earnings forecasts are useful for predicting future returns. In contrast, long-term lending relationships decay the quality of forecast and are not valuable for the prediction of future returns. These empirical results indicate that the informational advantage that commercial banks acquire is short-term and that the costs of lending relationships surpass the informational benefits in the long run.     

Why are recommendations optimistic? Evidence from analysts’ coverage initiations

We examine the long-term stock performance of analyst recommendations and the properties of accompanied earnings forecasts for initiations and non-initiations to evaluate the reporting, selection, and processing explanations for analyst optimism. We find that Strong Buy and, to a lesser degree, Buy initiation recommendations underperform their non-initiation counterparts after controlling for analyst, brokerage, and firm characteristics associated with the initiation decision and expected long-term stock returns. Yet, earnings forecasts accompanying Strong Buy and Buy initiation recommendations are less optimistic and more accurate than those accompanying non-initiation recommendations. Our findings suggest that conflicts of interest (that is, the reporting explanation) are the dominant source for favorable recommendations.     

Common Stock Offerings and Earnings Expectations: A Test of the Release of Unfavorable Information

This paper examines the revisions of analysts' forecasts of future earnings around announcements of common stock offerings. The forecasts of the current year earnings are, on average, decreased when firms announce plans to issue additional common stock. The size of the decrease is significantly related to announcement period abnormal stock returns. In contrast, forecasts of the five-year growth rate of earnings are, on average, unchanged. We interpret these results as being consistent with the claim that equity offering announcements convey unfavorable information regarding the firm's short-term but not its long-term earnings prospects.     

Trading based on forecasts of earnings per share: A test of the efficient market hypothesis

In this paper the semi-strong form of the efficient market hypothesis is tested with a trading rule based on Box-Jenkins forecasts of earnings per share numbers. The quarterly earnings per share series are modeled for a number of firms. The models are updated quarter by quarter and investments are made in the stocks with the largest forecasted growth rates for the next quarter. The risk-adjusted performance of such a strategy is shown to be inconsistant with semi-strong market efficiency.     

Earnings Forecasts and the Information Contained in Spinoff Announcements

This study examines spinoff announcements in conjunction with financial analysts’ forecasts of earnings. The analysis shows that spinoff announcement abnormal returns are significantly related to the firm's information environment as proxieci by financial analysts’ earnings prediction errors. The findings also indicate that analysts significantly increase their short-term earnings forecasts in response to spinoffs, but do not significantly revise their long-term earnings forecasts. However, the earnings revisions are not significantly different across prediction error groups, which confirms that spinoff-related abnormal returns cannot be attributed solely to expected performance gains.     

Diagnostic Expectations and Stock Returns

We revisit La Porta's finding that returns on stocks with the most optimistic analyst long‐term earnings growth forecasts are lower than those on stocks with the most pessimistic forecasts. We document the joint dynamics of fundamentals, expectations, and returns of these portfolios, and explain the facts using a model of belief formation based on the representativeness heuristic. Analysts forecast fundamentals from observed earnings growth, but overreact to news by exaggerating the probability of states that have become more likely. We find support for the model's predictions. A quantitative estimation of the model accounts for the key patterns in the data.     

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.     

The relationship between returns and unexpected earnings: A global analysis by accounting regimes

Numerous studies have documented a long-term association between earnings and returns. Surprisingly, few attempts have been made to internationally examine market reactions to earnings releases over return windows less than 12 months. This paper globally explores the market reaction to unexpected earnings defined by both the change in earnings per share (EPS) and analyst forecast errors (AFE) using a 1-month return window. First, the existence of the earnings-returns relationship is examined using a sample of firms from 32 countries grouped into accounting regimes. Accounting regimes represent groups of countries that exhibit similarities in accounting standards, stock market characteristics, corporate governance mechanisms, and economic conditions. Thus, similar reactions to earnings are expected within regimes. Next, the incremental information content of analyst forecasts, a proxy for investors’ earnings expectations, is examined. Finally, changes in the structure of the earnings-returns relationship over time are investigated. Results support the existence of a relationship between earnings and returns in all accounting regimes. In addition, analyst forecast errors appear to be incorporated into earnings expectations in most developed countries. Finally, evidence suggests that the significance and explanatory power in the earnings-returns relationship has increased in recent years.     

Analyst versus model-based earnings forecasts: implied cost of capital applications

We find that a composite implied cost of capital (ICC) estimate – based on the earnings forecasts generated by cross-sectional models – is highly correlated with future realised returns in both portfolio- and regression-based tests. By contrast, we find very little evidence for an association with future realised returns for an ICC estimate based on analyst earnings forecasts. We also document the time-varying nature of expected returns and risk premia, and provide up-to-date estimates of an implied Australian market risk premium.     

A new approach to predicting analyst forecast errors: Do investors overweight analyst forecasts?

I provide evidence that investors overweight analyst forecasts by demonstrating that prices do not fully reflect predictable components of analyst errors, which conflicts with conclusions in prior research. I highlight estimation bias in traditional approaches and develop a new approach that reduces this bias. I estimate characteristic forecasts that map current firm characteristics into forecasts of future earnings. Contrasting characteristic and analyst forecasts predicts analyst forecast errors and revisions. I find abnormal returns to strategies that sort firms by predicted forecast errors, consistent with investors overweighting analyst forecasts and predictable biases in analyst forecasts influencing the information content of prices.     

Long-Term Earnings Forecasts in the Electric Utility Industry: Accuracy and Valuation Implications

This paper integrates research on the accuracy of alternative long-term earnings forecasts, the gain in accuracy achievable from combining various forecasts, and the power of different long-term earnings forecasts to explain stock prices. The tests are performed on 82 electric utility firms because of the relative homogeneity of accounting data in that industry and because of the importance of the findings for the determination of the cost of capital in a regulatory proceeding. The results are consistent with earlier research findings that analyst forecasts of long-term earnings growth are more accurate than forecasts from extrapolative models. Combined forecasts applied to out-of-sample data, however, did not result in markedly improved forecasting accuracy. Finally, valuation tests of alternative forecasting techniques offered strong evidence that investors place the greatest weight on forecasts from Value Line.     

Comparing the Post–Earnings Announcement Drift for Surprises Calculated from Analyst and Time Series Forecasts

Post–earnings announcement drift is the tendency for a stock's cumulative abnormal returns to drift in the direction of an earnings surprise for several weeks following an earnings announcement. We show that the drift is significantly larger when defining the earnings surprise using analysts' forecasts and actual earnings from I/B/E/S than when using a time series model based on Compustat earnings data. Neither Compustat's policy of restating earnings nor the inclusion of “special items” in reported earnings contribute significantly to the disparity in drift magnitudes. Rather, our results suggest that this disparity is attributable to differences between analyst forecasts and those of time‐series models—or at least to factors correlated with these differences. Further, we document that analyst forecasts lead to return patterns around future earnings announcements that differ from those observed when using time‐series models, suggesting that the two types of surprises may capture somewhat different forms of mispricing.     

Value relevance of analyst earnings forecasts in emerging markets

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

Does the Stock Market See a Zero or Small Positive Earnings Surprise as a Red Flag?

This study shows that firms collectively incur a cost for managing earnings and analyst expectations to meet earnings forecasts. We compare the coefficient in the regression of abnormal stock returns on earnings surprise (the earnings response coefficient [ERC]) across ranges of earnings surprises. The ERC for earnings surprises in the range [0, 1¢] is significantly lower than ERCs for earnings surprises in adjacent ranges for firm-quarters in the early and mid 2000s, but not for those in the 1990s. The results are robust to controlling for the sign of estimated discretionary accruals and the trajectory of analyst earnings forecasts. We further find that investors are right to be skeptical about earnings surprises in the range [0, 1¢]. The relation of future earnings surprise with current earnings surprise is more negative for current earnings surprises in that range than for those in any other range. Evidence also suggests analysts react negatively to earnings surprises in that range.     

Alternative adjustments to analysts' earnings forecasts: relative and complementary performance

This study examines the relative and complementary performance of alternative earnings forecast adjustments using a common set of consensus analysts’ earnings forecasts. We document that a simple adjustment to analysts’ earnings forecasts, based solely on cross-sectional relationships between actual and forecasted earnings in the prior year, performs as well as more complicated adjustment methods, i.e., composite forecasts and persistence adjusted forecasts. A forecast adjustment that is based on prior year earnings and returns, however, provides significant incremental reductions in forecast error and dominates all of the other adjustment methods.     

Toward an Implied Cost of Capital

In this study, we propose an alternative technique for estimating the cost of equity capital. Specifically, we use a discounted residual income model to generate a market implied cost-of-capital. We then examine firm characteristics that are systematically related to this estimate of cost-of-capital. We show that a firm's implied cost-of-capital is a function of its industry membership, B/M ratio, forecasted long-term growth rate, and the dispersion in analyst earnings forecasts. Together, these variables explain around 60% of the cross-sectional variation in future (two-year-ahead) implied costs-of-capital. The stability of these long-term relations suggests they can be exploited to estimate future costs-of-capital. We discuss the implications of these findings for capital budgeting, investment decisions, and valuation research.