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.     

ABNORMAL RETURNS AND ANALYSTS' EARNINGS FORECAST REVISIONS ASSOCIATED WITH THE PUBLICATION OF “STOCK HIGHLIGHTS” BY VALUE LINE INVESTMENT SURVEY

We examine the reaction of stocks and the response of financial analysts' earnings forecasts to securities recommended as “Stock Highlights” by Value Line Investment Survey. Significant abnormal returns appear around the publication of stock highlights. Stock price responses are relatively efficient and permanent. Using earnings expectation data provided by the Institutional Brokers Estimate System, we find analysts raise their forecasts significantly following Value Line recommendations. Near-term forecast revisions are significantly related to stock returns at the time of the recommendations. Thus, an explanation for Value Line's security recommendation success is its ability to generate firm-specific earnings information.     

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.     

Revenue surprises and stock returns

This paper examines the relation between revenue surprises and contemporaneous and future stock returns. It also investigates whether analysts update their earnings forecasts in response to revenue surprises in a timely and unbiased fashion. Stock price reaction on the earnings announcement date is significantly related to contemporaneous as well as past revenue surprises. After controlling for earnings surprises, we find significant abnormal returns in the post-announcement period for stocks that have large revenue surprises. Although analysts revise their forecasts of future earnings in response to revenue surprises, they are slow to incorporate fully the information in revenue surprises.     

Investor and (Value Line) Analyst Underreaction to Information about Future Earnings: The Corrective Role of Non-Earnings-Surprise Information

Prior research suggests that financial analysts' earnings forecasts and stock prices underreact to earnings news. This paper provides evidence that analysts and investors correct this underreaction in response to the next earnings announcement and to other (non-earnings-surprise) information available between earnings announcements. Our evidence also suggests that analysts and investors underreact to information reflected in analysts' earnings forecast revisions and that non-earnings-surprise information helps correct this underreaction as well. Controlling for corrective non-earnings-surprise information significantly increases estimates of the degree to which analysts' forecasting behavior can explain drifts in returns following both earnings announcements and analysts' earnings forecast revisions.     

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.

     

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.     

Evidence That Management Earnings Forecasts Do Not Fully Incorporate Information in Prior Forecast Errors

Abstract:  This paper investigates whether managers fully incorporate the implications of their prior earnings forecast errors into their future earnings forecasts and, if not, whether this behavior is related to the post-earnings announcement drift. I find a positive association in consecutive management forecast errors, suggesting that managers underestimate the future implications of past earnings information when forecasting earnings. I also find that managers underestimate the information in their prior forecast errors to a greater extent when they make earnings forecasts with a longer horizon. Finally, I find that, similar to managers, the market also underreacts to earnings information in management forecast errors, which leads to predictable stock returns following earnings announcements.     

Do analysts who understand accounting conservatism exhibit better forecasting performance?

This study investigates the performance of analysts when they match the asymmetric timeliness of their earnings forecast revisions (i.e., asymmetric forecast timeliness) with the asymmetric timeliness of firms’ reported earnings (i.e., asymmetric earnings timeliness). We find that better timeliness‐matching analysts produce more accurate earnings forecasts and elicit stronger market reactions to their forecast revisions. Further, better timeliness‐matching analysts issue less biased earnings forecasts, more profitable stock recommendations and have more favorable career outcomes. Overall, our results indicate that analysts’ ability to incorporate conditional conservatism into their earnings forecasts is an important reflection of analyst expertise and professional success.     

THE ASSOCIATION BETWEEN ANALYSTS’ FORECAST REVISIONS AND EARNINGS COMPONENTS: THE EVIDENCE OF FRS 3

This study examines whether the earnings components as required by FRS 3 help UK analysts to predict firms’ earnings changes by investigating the statistical association between analysts’ forecast revisions and firms’ unexpected earnings components. I find that analysts’ forecast revisions made in different time horizons are consistently associated with unexpected earnings components as required by FRS 3. UK analysts are able to incorporate current-year unexpected earnings components into their current and future earnings forecasts even before firms officially release this information. However, empirical results also show that current-year unexpected earnings components are not fully incorporated into analysts’ forecasts of future earnings. Analysts appear to wait for more information releases regarding firms’ future earnings and delay their revisions of future earnings forecasts. This is consistent with the evidence that the cumulative revisions of current earnings forecasts are generally associated with prior-year unexpected earnings components, and the association appears to be stronger as time progresses. Overall, this study provides evidence suggesting that the earnings components as required by FRS 3 help UK analysts to identify firms’ permanent and transitory earnings changes over different forecast horizons. This study also provides strong evidence supporting the informativeness of earnings components for analysts’ forecasts and the information set perspective of FRS 3 that highlights the importance of earnings components in predicting a reporting entity’s future performance.     

Understanding analysts' use of stock returns and other analysts' revisions when forecasting earnings

We investigate analysts' use of stock returns and other analysts' forecast revisions in revising their own forecasts after an earnings announcement. We find that analysts respond more strongly to these signals when the signals are more informative about future earnings changes. Although analysts underreact to these signals on average, we find that analysts who are most sensitive to signal informativeness achieve superior forecast accuracy relative to their peers and have a greater influence on the market. The results suggest that the ability to extract information from the actions of others serves as one source of analyst expertise.     

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.     

On the relation between predictable market returns and predictable analyst forecast errors

We investigate the relation between predictable market returns and predictable analyst forecast errors. Perfect correlation between predictable components of forecast errors and abnormal returns would lend credence to the view that pricing anomalies are not merely an artifact of inadequately controlled risk. Our evidence implies an imperfect correlation. Moreover, we find that while the predictable component of abnormal returns is significantly associated with future forecast errors, trading strategies based directly on the predictable component of forecast errors are not profitable. Further implications of our findings are that predictable components of analysts’ forecast errors are robust with respect to loss functions and analysts’ earnings forecasts may significantly diverge from the market expectations.     

Underwriting Relationships and Analyst Independence in Europe

This paper examines the accuracy of security analysts’ earnings forecasts and stock recommendations for firms in 13 European countries. We document at least three key findings. First, we find strong evidence that lead and co‐lead underwriter analysts’ earnings estimates and stock recommendations are significantly more optimistic than those provided by unaffiliated analysts. Second, we find that lead and co‐lead underwriter analysts’ earnings forecast and stock recommendations are significantly more optimistic for underwriter stocks than for those they provide for other stocks. Third, we also find evidence that these biases found within earnings forecasts and stock recommendations are not driven by one particular country. In short, these findings suggest that affiliated analysts are more optimistic perhaps to maintain investment banking relations.     

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.     

Analysts’ pre-tax income forecasts and the tax expense anomaly

This paper examines whether analysts’ pre-tax income forecasts mitigate the tax expense anomaly documented by Thomas and Zhang (J Account Res 49:791–821, 2011). They find that seasonal changes in quarterly income tax expense are positively related to future returns after controlling for the earnings surprise and conclude that investors underreact to value-relevant information in tax expense. When analysts issue both earnings and pre-tax income forecasts, they implicitly provide a forecast of income tax expense. We posit that this implicit forecast helps investors recognize the persistence of current tax expense surprise for future earnings. Accordingly, we expect that mispricing of tax expense will be less severe for firms with earnings and pre-tax income forecasts. As expected, we find that the presence of pre-tax income forecasts significantly weakens the positive relation between tax expense surprise and future returns, consistent with analysts’ implicit forecasts of tax expense mitigating the tax expense anomaly.     

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.     

Analysts’ earnings forecasts: coexistence and dynamics of overconfidence and strategic incentives

This paper formulates a two-stage model to capture the decision process of financial analysts when issuing earnings forecasts. Our model extends the model of Chen and Jiang [(2005). Analysts’ weighting of private and public information. Review of Financial Studies, 19 (1), 319–355], by allowing for a distortion of forecasts independent of whether an analyst has private information. Using quarterly earnings forecasts, we provide empirical evidence on the coexistence of overconfidence and strategic incentives. Financial analysts overweight their private information and at the same time strategically inflate their forecast.     

Underwriting relationships,analysts' earnings forecasts and investment recommendations

We examine the effect of underwriting relationships on analysts' earnings forecasts and recommendations. Lead and co-underwriter analysts' growth forecasts and recommendations are significantly more favorable than those made by unaffiliated analysts, although their earnings forecasts are not generally greater. Investors respond similarly to lead underwriter and unaffiliated `Strong buy' and `Buy' recommendations, but three-day returns to lead underwriter `Hold' recommendations are significantly more negative than those to unaffiliated `Hold' recommendations. The findings suggest investors expect lead analysts are more likely to recommend `Hold' when `Sell' is warranted. The post-announcement returns following affiliated and unaffiliated analysts' recommendations are not significantly different.     

Learning and incentive: A study on analyst response to pension underfunding

There is a long-standing debate on whether sell-side analysts learn from their experience to improve earnings forecast skills. This study shows that incentive is an important factor for understanding the “learning by doing” effect by analysts. We examine analysts’ response to a complex type of information – corporate pension underfunding. Pension underfunding negatively impacts future earnings and analysts on average underreact to such information in their earnings forecasts. More importantly, when there is a strong incentive for analysts to deliver accurate forecasts, analyst learning effectively reduces their underreaction to pension underfunding information. On the other hand, when such an incentive is absent, the analyst learning effect is not discernible in the data. Further evidence suggests that analyst learning and incentive jointly reduce stock market mispricing associated with corporate pension underfunding.