Earnings Forecast Revisions Research Articles

Does Anchoring Heuristic Affect Analyst Recommendation Revisions?

We investigate whether 52-week high stock prices serves as reference points for analyst recommendation revisions. We find that analysts are more likely to downgrade stocks when the prices approach the 52-week high levels. This anchoring effect is stronger for stock with higher information asymmetry but moderated by analysts’ reputation, work experience, and educational background. We also find that a strategy that takes long positions in stocks approaching 52-week high generates positive returns, and a strategy that shorts stocks with recommendation downgrades is less profitable for the downgrades near 52-week high than for other downgrades. Moreover, the downgraded firms with prices near 52-week high subsequently experience less negative earnings forecast revisions, compared with other downgraded firms. Collectively, our results indicate that downgrades near 52-week high are partially attributable to anchoring heuristic and less informative. Overall, our paper provides new evidence on the determinants of analyst recommendation revisions from a behavioral perspective.

Portfolio Construction and Management in the Barra Aegis System: A Case Study using the USER Data

In this article, we demonstrate the effectiveness of the Barra Aegis system and Barra factor model to construct portfolios representing popular and well-established investment management strategies and attribute the performance of these portfolios to the Barra factors. Stock selection models often use momentum, analysts’ expectations, and fundamental data. We employ composite modeling of expected returns using fundamental, expectations, and momentum-based data for U.S. equities during the December 1979 to December 2009 period. We use Barra factor models for portfolio construction and risk control. We report two results: (1) a composite model incorporating fundamental data, such as earnings, book value, cash flow, and sales, with analysts’ earnings forecast revisions and price momentum variables to identify mispriced securities; and (2) the returns to a risk-controlled portfolio allow us to reject the null hypothesis that results are due to data mining.

Eternal Sunshine: Are U.S. Analysts More Optimistic than Foreign Analysts?

A vast literature has documented an optimistic bias of U.S. analysts. This study compares the optimistic bias of U.S. analysts to that of foreign analysts. Using the implied rate of return in target prices, i.e., the ratio of the target price to the stock price one day before the target price announcement, we show that U.S. analysts are significantly more optimistic than their foreign peers, even after controlling for the same set of firms and the same economic conditions. Furthermore, we find U.S. analysts to be more optimistic for foreign-listed stocks, and not only for U.S.-listed stocks. Similar results are obtained for stock recommendations. In subsequent analysis, we find that investors are potentially aware of this bias, reacting more strongly to earnings forecast revisions of foreign analysts than to those of U.S. analysts.

Do analysts treat winners and losers differently when forecasting earnings?

We investigate whether the well-known positive association between past stock returns and analysts’ earnings forecast revisions differs for stocks that have experienced extreme positive (or negative) price changes. We document an asymmetry in this association depending on whether a stock experienced consecutive rounds of capital gains (winner) or losses (loser): the association is strong for losers, but weak for winners. We also find that earnings forecasts are less accurate for analysts who treat winners and losers differently from moderately-performing stocks. However, the degree of such aberrant reactions to winners and losers and the consequent detrimental effect on the forecasting accuracy are less acute for analysts who have more forecasting experience with winners and losers. Finally, consistent with the efficient market hypothesis (EMH), we find that investors discount earnings forecast revisions by analysts who treat winners and losers differently, particularly after 2003, coinciding with the Global Settlement that aims to improve the integrity of analyst research and investors’ financial literacy.

Share Repurchase Announcements Together with Earnings Forecast Revisions and Long-Term Stock Performance: Evidence from Japan

This article examines whether the presence of large revisions in management EPS forecasts alongside repurchase announcements offers a more appropriate measurement for ex-post actual repurchase implementations than do repurchase programme size and earnings managements before repurchase announcements. I also investigate whether repurchase announcements alongside large revisions in management EPS forecasts are over-performed relative to repurchase announcements with no or slight revisions in management EPS forecasts. The results empirically suggest that repurchase programmes are likely to be implemented if announcements accompany large revisions in management EPS forecasts. This finding implies that EPS forecasts revisions around repurchase programmes announcements convey more information on the ex-post actual implementation of repurchase programmes than do repurchase programmes size and earnings management. The findings also indicate that management reporting behaviour regarding EPS forecast revisions is significantly and positively related to long-term stock performance, suggesting that investors evaluate the reliability of the signal in each repurchase programme based on the presence or absence of EPS forecast revisions. These results are robust concerning measurements of long-term stock performance.

Investors’ Reactions to Analysts’ Forecast Revisions and Information Uncertainty

This study examines the relationship among analysts’ earnings forecast revisions, information uncertainty, and stock returns and provides new evidence that stock price drift occurs after analysts’ earnings forecast revisions. Using data from the Australian stock market over the period of 1992 to 2009, we find that the stocks with upward earnings revisions experience positive returns, while stocks with downward revisions have negative returns. The effect is more prominent in stocks with high information uncertainty. The results are robust after controlling for market conditions, seasonality, and risks. Our evidence supports the conservatism bias model that investors tend to underweight the public information, such as analysts’ earnings forecast revisions. Importantly, our evidence provides possible explanations about the violation of the efficient market hypothesis. Our results suggest that the conservative bias causes investors not to sufficiently update their beliefs and eventually results in subsequent return continuation as investors’ underreaction to analysts’ earnings forecast revision is stronger with higher information uncertainty.

Slow price reactions to analysts’ recommendation revisions

This study explores the reasons for the slow price reactions to analysts’ recommendation revisions. We predict that analysts’ recommendation revisions contain earnings-related information that is not incorporated in analysts’ earnings forecasts and that the slow price reaction is attributable to a gradual incorporation of this earnings-related information into stock prices. We find that, consistent with our prediction, stocks with recommendation upgrades subsequently experience more upward earnings forecast revisions than stocks with recommendation downgrades, and that the differences in subsequent stock returns between upgraded and downgraded stocks is attributable to differences between subsequent earnings forecast (especially, FY2 earnings forecast) revisions.

Delayed Price Reactions to Analystss Recommendation Revisions

This study explores the reasons for the slow price reactions to analysts’ recommendation revisions. We predict that analysts’ recommendation revisions contain earnings-related information that is not incorporated in analysts’ earnings forecasts and that the slow price reaction is attributable to a gradual incorporation of this earnings-related information into stock prices. We find that, consistent with our prediction, stocks with recommendation upgrades subsequently experience more upward earnings forecast revisions than stocks with recommendation downgrades, and that the differences in subsequent stock returns between upgraded and downgraded stocks is attributable to differences between subsequent earnings forecast (especially, FY2 earnings forecast) revisions.

Do Analysts Read the News?

I examine whether and how corporate news releases inuence equity analysts’ earnings forecasts. Combining large databases of U.S. corporate news releases and individual sell-side analysts’ earnings forecasts during 2000 to 2010, I investigate whether corporate news reports inuence the direction and magnitude of equity analysts’ earnings forecast revision. I nd that equity analysts’ forecast revision is signicantly inuenced by the tone of the news. Analysts’ revision directions and magnitude are both positively related to the tone of the news. Moreover, the relation between news and forecast revision is stronger for negative news and news that contains information regarding rm fundamentals. These results are obtained when earnings announcement periods are removed, highlighting the informational roles of corporate news in shaping analysts’ decisions.

Enhancing the profitability of earnings momentum strategies: the role of price momentum, information diffusion and earnings uncertainty

Recent literature indicates that stock characteristics proxying for behavioral biases reinforce the earnings momentum effect – the price drift following analysts’ earnings forecast revisions. Using data from the German HDAX, we analyze the impact of price momentum, the rate of information diffusion and earnings uncertainty on the returns of earnings momentum strategies. We find that the rate of information diffusion has the strongest and most unambiguous impact, going beyond the effect of simply sorting stocks into more extreme revision portfolios. A bivariate sort on earnings momentum and market capitalization yields gross Carhart alphas of up to 22% per year. Our results are robust to reasonable levels of trading costs. As trading costs increase, however, there is some evidence that longer holding period strategies with lower gross returns become more favorable.

Distinguishing Rational and Behavioral Models of Momentum

One of the many challenges facing financial economists is to distinguish the theories explaining momentum. Brav and Heaton (2002) show that it is very difficult to distinguish the "rational" models of structural uncertainty (SU) from "behavioral" models of conservatism (C). In this paper, I reexamine the SU model and the C model proposed by Brav and Heaton (2002) in explaining short-run momentum. Based on simulated data, I find that they differ from each other in the relation between agent's earnings forecast revision and the lagged earnings change. This relation is significantly negative for the SU model and significantly positive for the C model. Empirical evidence provides support for the SU model.

Analysts’ Momentum Recommendations

AbstractWe document that the likelihood of analyst recommendations following past stock returns decreased abruptly in 2003, coinciding with the Global Settlement and other regulatory changes designed to restrain analysts’ conflicts of interest. We also document that the likelihood of recommendations following past stock returns is abnormally high for recommendations issued after negative stock returns (but not for those issued after positive stock returns), among inexperienced and inaccurate analysts, among large brokerage houses, and for companies with high share turnover. Moreover, the recommendations that are more likely to follow past stock returns are accompanied by earnings forecast revisions that are larger in magnitude and less accurate ex post. Overall, our findings suggest that analysts with conflicts of interest and limited ability are more likely to base their recommendations on past stock returns. Finally, we document that the recommendations that are more likely to follow past stock returns (especially those that were issued before 2003 and those that are issued after negative stock returns) contribute to existing price momentum by generating incrementally stronger short‐term and long‐term stock returns.

Short Interest, Returns, and Fundamentals

We show that short interest predicts future bad news, negative earnings surprises, and downward revisions in analyst earnings forecasts. Moreover, short interest is a better predictor of changes in firm fundamentals for stocks that are harder to short and short sellers appear to have information about these events several months before they become public. Most importantly, the well-known cross-sectional relation between short interest and future stock returns vanishes after controlling for short sellers’ information about future fundamental news. Thus, short sellers contribute in a significant manner to price discovery about firm fundamentals.

What Do Short Sellers Know?

Using a five-year panel of proprietary NYSE short sale order data, we investigate the sources of short sellers’ informational advantage. Heavier shorting is found the week before negative earnings surprises, analyst downgrades, and downward revisions in analyst earnings forecasts. The biggest effects are associated with analyst downgrades. While earnings and analyst event days constitute only 12% of sample days, they account for over 24% of the overall underperformance of heavily shorted stocks. The results are robust to factor timing and indicate that short sellers are well-informed about upcoming earnings news and are able to anticipate analyst recommendation changes. Shorting predictability is still significant after controlling for information in analyst actions, suggesting that short sellers know more than analysts about firm fundamentals. Finally, we find no evidence of price manipulation by short sellers.

Financial restatements by Canadian firms cross-listed and not cross-listed in the U.S.

Canadian financial restatements announced during 1997–2006 lower market quality and signal to market participants that expected future cash flows and their uncertainty are diminished and increased, respectively. Abnormal returns are related to downward revisions in consensus earnings forecasts, and become more negative for U.S. cross-listings, and for revenue recognition and company-initiated restatements. Total residual volatility, its information-based permanent component and the adverse selection spread component increase following such announcements. Relative spreads and a spread-depth market-quality index increase following such announcements and are lower for U.S. cross-listings. Relative spreads (unlike the market-quality index) remain higher post-announcement, and are lower post-Sarbanes-Oxley Act.

Discrepancy between I/B/E/S Actual EPS and Analysts’ Inferred EPS

Users of I/B/E/S data generally act as if I/B/E/S reported actual earnings represent the earnings analysts were forecasting when they issued their earnings estimates. For example, when assessing analyst forecast accuracy, users of I/B/E/S data compare analysts’ forecasts of EPS with I/B/E/S reported actual EPS. I/B/E/S states that it calculates actuals using a “majority rule” indicating that its actuals often do not represent the earnings that all individual analysts were forecasting. We introduce a method for measuring analyst inferred actuals, and we assess how often I/B/E/S actuals do not represent analyst inferred actuals. We find that I/B/E/S reported Q1 actual EPS differs from analyst inferred actual Q1 EPS by at least one penny 39 percent of the time during our sample period, 36.5 percent of the time when only one analyst follows the firm (and hence this consensus forecast is based on the “majority rule”), and 50 percent of the time during the last three years of our sample period. We document two adverse consequences of this phenomenon. First, studies failing to recognize that I/B/E/S EPS actuals often differ from analyst inferred actuals are likely to obtain less accurate analyst earnings forecasts, smaller analyst earnings forecast revisions conditional on earnings surprises, greater analyst forecast dispersion, and smaller market reaction to earnings surprises than do studies adjusting for these differences. Second, studies failing to recognize that I/B/E/S EPS actuals often differ from analyst inferred actuals may make erroneous inferences.

I/B/E/S Reported Actual EPS and Analysts' Inferred Actual EPS

ABSTRACTUsers of I/B/E/S data generally act as if I/B/E/S reported actual earnings represent the earnings analysts were forecasting when they issued their earnings estimates. For example, when assessing analyst forecast accuracy, users of I/B/E/S data compare analysts' forecasts of EPS with I/B/E/S reported actual EPS. I/B/E/S states that it calculates actuals using a “majority rule,” indicating that its actuals often do not represent the earnings that all individual analysts were forecasting. We introduce a method for measuring analyst inferred actuals, and we assess how often I/B/E/S actuals do not represent analyst inferred actuals. We find that I/B/E/S reported Q1 actual EPS differs from analyst inferred actual Q1 EPS by at least one penny 39 percent of the time during our sample period, 36.5 percent of the time when only one analyst follows the firm (hence, this consensus forecast is based on the “majority rule”), and 50 percent of the time during the last three years of our sample period. We document two adverse consequences of this phenomenon. First, studies failing to recognize that I/B/E/S EPS actuals often differ from analyst inferred actuals are likely to obtain less accurate analyst earnings forecasts, smaller analyst earnings forecast revisions conditional on earnings surprises, greater analyst forecast dispersion, and smaller market reaction to earnings surprises than do studies adjusting for these differences. Second, studies failing to recognize that I/B/E/S EPS actuals often differ from analyst inferred actuals may make erroneous inferences.

Properties Of Management Forecast And Analysts' Responsiveness

This paper examines the degree of analysts responsiveness to voluntary management guidance. Prior studies report that the management guidance is informative and influential (e.g. Baginski et al., 1993). This paper studies various factors that trigger equity market reactions around the management forecast issuance date and find that analysts are more reactive to new information contained in management guidance when the guidance conveys information that affects the stock market. The extent of the analysts reaction to management guidance increases when the analysts find that the guidance is more credible. Credibility of management guidance from the standpoint of analysts means ex-post accuracy of the earnings estimate by the management. The direction and the magnitude of earnings forecast revisions are influenced by the assessment of the credibility of management earnings forecast by financial analysts.

Analysts’ Earnings Forecast, Recommendation,and Target Price Revisions

This study examines the immediate and delayed market responses to revisions in analyst forecasts of earnings, target prices, and recommendations. Consistent with prior literature, revisions in earnings forecasts are positively and significantly associated with short-term market returns around the revisions. However, Feldman, Livnat, and Zhang show that short-term market returns around target price revisions and recommendation changes are even stronger. They also find superior future performance (return drift) for portfolios that use information from all three types of revisions to those using information from only one of the three types of revisions. <b>TOPICS:</b>Exchanges/markets/clearinghouses, technical analysis, in markets

Tobin’s q versus CAPE versus CAPER: Predicting Stock Market Returns Using Fundamentals and Momentum

Stock selection models often use momentum, analysts’ expectations, and fundamental data. We found support for composite modeling using these sources of data for U.S. equities during the 1998–2007 period. We found additional evidence to support the use of Barra and APT multifactor models for portfolio construction and risk control. Three levels of testing of stock selection and portfolio construction models were developed and estimated. We created portfolios for the January 1998–December 2007 period. We report three conclusions: 1) Momentum investing was rewarded by the market in the United States from December 1928–December 2007; 2) Momentum can be combined with reported fundamental data—such as earnings, book value, cash flow, and sales—and analysts’ earnings forecast revisions in a stock selection model to identify mispriced securities; 3) the portfolio returns of the multifactor risk-controlled portfolio returns allow us to reject the data mining corrections test null hypothesis.