Analysts’ earnings forecast errors and cost of equity capital estimates

This study investigates the relation between analysts’ forecast errors and cost of equity capital estimates implied from analysts’ earnings forecasts and price. My analysis predicts and removes forecast errors from analysts’ earnings forecasts on an out-of-sample basis and then uses these adjusted analysts’ forecasts to reverse-engineer cost of equity capital estimates. While the correction for predictable analysts’ forecast errors meaningfully lowers each of three firm-level implied COEC estimates employed in this study and commonly used in the literature, I do not find that this correction improves their association with realized returns.     

The superiority and disciplining role of independent analysts

We show that although forecasts of independent analysts are less accurate ex post, they yield forecast errors that are more strongly associated with abnormal stock returns. This suggests that forecasts of independent analysts are superior to those of nonindependent analysts in representing ex ante market expectations. We also show that forecasts of nonindependent analysts become more accurate and less biased, and produce forecast errors more strongly associated with abnormal stock returns when independent analysts are following the same firms than when they are not. This suggests that the presence of independent analysts disciplines the behavior of nonindependent analysts.     

Evaluating the information content of earnings forecasts

This study develops a framework to compare the ability of alternative earnings forecast approaches to capture the market expectation of future earnings. Given prior evidence of analysts’ systematic optimistic bias, we decompose earnings surprises into analysts’ earnings surprises and adjustments based on alternative forecasting models. An equal market response to these two components indicates that the associated earnings forecast is a sufficient estimate of the market expectation of future earnings. To apply our framework, we examine four recent regression-based earnings forecasting models, alongside a simple earnings-based random walk model and analysts’ forecasts. Using the earnings forecasts of the model that satisfies our sufficiency condition, we identify a set of stocks for which the market is unduly pessimistic about future earnings. The investment strategy of buying and holding these stocks generates statistically signi?cant abnormal returns. We offer an explanation as to why this and similar strategies might be successful.     

What Drives Target Price Forecasts and Their Investment Value?

This paper examines the informativeness of analysts’ target price forecasts by relating the investment value of target prices to their primary drivers. Decomposing target price forecasts into near‐term earnings forecasts and price‐to‐earnings ratio forecasts, we show that target price revisions reflect information from both components. In addition, we also find that the relative importance of each component in target price revisions is related to firm characteristics. A portfolio based on target price implied expected returns delivers significant abnormal returns. More importantly, we find that the abnormal returns are associated with both earnings and price‐to‐earnings forecasts, which suggests that the informativeness of target price forecasts comes not only from analysts’ ability to forecast short‐term earnings but also from their ability to assess risk and long‐term growth prospect implied in price‐to‐earnings forecasts.     

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.     

Do sell-side analysts exhibit differential target price forecasting ability?

We examine the overall and individual analyst performance of 12-month-ahead target price forecasts over the 10 years from 2000 through 2009. Implied target price-based returns exceed actual returns by an average of 15 %, and absolute target price forecast errors average 45 %. At the end of the 12-month forecast horizon, only 38 % of target prices are met, but 64 % are met at some time during the forecast horizon. We find statistically significant but economically weak evidence of persistent differential abilities by sell-side analysts to forecast target prices. Target price announcement period return analyses indicate no differential market reactions to analysts’ target price revisions conditional on their recent target price forecast performance. This finding is consistent with the market understanding that analysts have, at best, limited abilities to persistently provide accurate target price forecasts.     

Do investor expectations affect sell-side analysts’ forecast bias and forecast accuracy?

We examine the association between investor expectations and its components and sell-side analysts’ short-run quarterly earnings forecast bias and forecast accuracy. To measure investor expectations, we use the Index of Consumer Expectations survey and decompose it into the “fundamental” component related to underlying economic factors (FUND) and the “sentiment” component unrelated to underlying economic factors (SENT). We find that analysts are the most optimistic and the least accurate when SENT is higher. Management long-horizon earnings forecasts attenuate the effects of SENT on forecast optimism and forecast accuracy. Analysts are also the most accurate when FUND is higher. Last, the market places more weight on unexpected earnings when SENT is high. These findings suggest that analysts are affected by investor sentiment and the market reacts more strongly to unexpected earnings when analyst forecasts are the least accurate. The last result potentially explains why prior research (for example, Baker and Wurgler, The Journal of Finance 61:1645–1680, 2006) finds an association between investor sentiment and cross-sectional stock returns.     

Evaluating the information in the federal reserve stress tests

We present evidence that the Federal Reserve stress tests produce information about both the stress-tested bank holding companies and the overall state of the banking industry. Our evidence goes beyond a standard event study, which cannot differentiate between small abnormal returns and large, but opposite-signed, abnormal stock returns. We find that stress test disclosures are associated with significantly higher absolute abnormal returns, as well as higher abnormal trading volume. More levered and riskier holding companies seem to be more affected by the stress test information. We find no evidence that stress test disclosures have reduced the production of private information. After disclosure begins, stress tested firms attract equity analysts without changing analysts’ forecast dispersions or their mean forecast error.     

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.     

Mean-variance optimization using forward-looking return estimates

Despite its theoretical appeal, Markowitz mean-variance portfolio optimization is plagued by practical issues. It is especially difficult to obtain reliable estimates of a stock’s expected return. Recent research has therefore focused on minimum volatility portfolio optimization, which implicitly assumes that expected returns for all assets are equal. We argue that investors are better off using the implied cost of capital based on analysts’ earnings forecasts as a forward-looking return estimate. Correcting for predictable analyst forecast errors, we demonstrate that mean-variance optimized portfolios based on these estimates outperform on both an absolute and a risk-adjusted basis the minimum volatility portfolio as well as naive benchmarks, such as the value-weighted and equally-weighted market portfolio. The results continue to hold when extending the sample to international markets, using different methods for estimating the forward-looking return, including transaction costs, and using different optimization constraints.

     

Market reaction to optimistic bias in the recommendations of chaebol-affiliated analysts

Using the setting of chaebol industrial organizations in Korea, which allows for the study of a unique affiliation between a chaebol group and financial analysts, we examine whether investors react to an optimistic bias in affiliated analysts’ recommendations. Our initial market return tests, abnormal trading volume tests and independent analysts’ reaction tests suggest that investors and independent analysts recognize and discount an optimistic bias in chaebol-affiliated ‘buy’ recommendations. However, long-term market returns are more profitable in terms of affiliated analysts’ ‘buy’ recommendations than independent analysts’ recommendations, which suggests that investors excessively discount chaebol-affiliated ‘buy’ recommendations in the short-term.     

Improving the Precision of Analysts' Earnings Forecasts by Adjusting for Predictable Bias

This research demonstrates that publicly-available information can be used to develop estimates of analysts' optimistic bias in earnings forecasts. These bias estimates can be used to produce more accurate forecasts, resulting in significant reductions of both cross-sectional mean forecast error and error variance. When bias estimates are based on past observations of forecast error alone, however, reductions in mean forecast error are smaller, and forecast precision is unimproved. Further tests provide evidence of a significant association between returns and the bias predictable from contemporaneously-available information, suggesting that predictable bias is only partially discounted by market participants. This study has significant implications for researchers and investors. The pricing of predictable bias in analysts' forecasts may add error toinferences which are based on the association between returns and analyst forecast errors, and knowledge of the market's partial discounting of predictable bias may help investors to make more efficient resource allocations.     

Sources of earnings variability and their effect on earnings forecasts

Previous research shows that analysts’ forecasts of earnings do not fully incorporate information contained in reported earnings variability. This study investigates whether the inefficient forecast is because of a failure to incorporate observable information on two components of earnings variability: variability in operating performance and income smoothing. Our results show that analysts’ forecasts fully incorporate information contained in earnings variability for firms with high income smoothing and for firms with low operating variability. A smaller serial correlation of forecast errors is observed for firms with low operating variability, which suggests that analysts recognize the permanence in earnings for such firms.     

Serial Correlation in Management Earnings Forecast Errors

We examine whether management earnings forecast errors exhibit serial correlation and how analysts understand the serial correlation property of management forecast errors (MFEs). MFEs should not exhibit serial correlation if managers efficiently process information in prior forecast errors and truthfully convey their earnings expectations through management forecasts. However, for long‐horizon management forecasts of annual earnings, we find significantly positive serial correlation in MFEs, and sample self‐selection does not seem to drive this phenomenon. Further analyses suggest that managers’ unintentional information processing bias contributes to this positive serial correlation. Analysts anticipate the intertemporal persistence of MFEs but underestimate the persistence level when reacting to management forecasts. Our findings have implications for market participants who rely on management forecasts to form earnings expectations, and also shed light on the efficiency of managerial decision making.     

Removing predictable analyst forecast errors to improve implied cost of equity estimates

Prior research documents a weak association between the implied cost of equity inferred from analyst forecasts and realized returns. It points to predictable errors in analyst forecasts as a possible cause. We show that removing predictable errors from analyst forecasts leads to a much stronger association between implied cost of equity estimates obtained from adjusted forecasts and realized returns after controlling for cash flow news and discount rate news. An estimate of implied risk premium based on the average of four commonly used methods after making adjustments for predictable errors exhibits strong correlations with future realized returns as well as the lowest measurement error. Overall, our results confirm the validity of implied cost of equity estimates as measures of expected returns. Future research using implied cost of equity should remove predictable errors from implied cost of capital estimates and then average across multiple metrics.     

Private Placement of Common Equity and Earnings Expectations

We examine earnings forecast revisions by analysts subsequent to the announcement of private equity placements. Results show that analysts make significant upward revisions to their forecasts for current-year earnings. Furthermore, these forecast revisions are significantly related to announcement-period abnormal returns, but not to the risk changes accompanying the equity placement. These findings are consistent with the information hypothesis, which suggests that private equity placements convey favorable information about future earnings.     

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.     

Book-to-Market Components, Future Security Returns, and Errors in Expected Future Earnings

This study investigates whether the ability of book-to-market to predict returns derives from systematic errors in the market's expectation of future earnings. We extend Beaver and Ryan (1996, 2000) by decomposing book-to-market into a more persistent (bias) component and a delayed recognition (lag) component. We find that both components are related to analyst expectations of future earnings, but the lag component is the dominant factor across all forecast horizons. Similarly, we find that the lag component explains most of the inverse relation between book-to-market and future returns. Given that lag is constructed by regressing book-to-market ratios on lagged price changes, our results are consistent with the lag component capturing systematic stock price reversals. We find that the components have unique relations with subsequent earnings forecast revisions, and controlling for these relations substantially mitigates the components' ability to predict returns. Our component-level analysis provides insight into how expected future earnings, summarized in book-to-market ratios help to explain this market anomaly.     

Learning and the disappearing association between governance and returns

The correlation between governance indices and abnormal returns documented for 1990–1999 subsequently disappeared. The correlation and its disappearance are both due to market participants' gradually learning to appreciate the difference between good-governance and poor-governance firms. Consistent with learning, the correlation's disappearance was associated with increases in market participants' attention to governance; market participants and security analysts were, until the beginning of the 2000s but not subsequently, more positively surprised by the earning announcements of good-governance firms; and, although governance indices no longer generated abnormal returns during the 2000s, their negative association with firm value and operating performance persisted.     

Asymmetric trading by insiders – comparing abnormal returns and earnings prediction in Spain and Australia

This paper examines whether the ‘external governance’ imposed by comparative financial accounting standards reduces the trading advantage of insiders. We do this by directly comparing insider trading returns and insider’s ability to predict future earnings from accruals in Spain and Australia. Results show higher excess returns and greater prediction of future earnings from conditioned insider trading in Australia that is then utilized by financial analysts to lower forecast errors – particularly in contrarian‐based accruals trading. Possible explanations include: (i) a high asymmetric quality for market‐based accruals, (ii) information transfer from informed insiders to uninformed insiders and financial analysts and (iii) a more timely dissemination of financial information in Spain through different ownership and governance structures.