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revisions, investors perceive downgrades as a more credible signal.14 We also ind that b-the slope on the earnings forecast revision-is not statistically different across the three recommendation revisions. Since an earnings forecast is a key input to the derivation of the target price along with an assumed inancial ratio (Asquith et al. (2002)), this evidence suggests that when analysts issue a recommendation downgrade, investors view the chosen magnitude of the inancial ratio (i.e., multiple) as more informative.

In our second set of regressions, we repeat the same analysis as above but now condition on the sign of target price revision (columns 5-7). Our goal is to gain further insight into the relation between abnormal returns and target price revisions in these specific settings. We find that the slope coefficient of positive target price revisions (column 5) is signiicantly larger (p-value = 0.001) than that of negative revisions (column 6).15 We also ind that the estimated slope coeicients on the earnings forecast revisions are similar across the three groups, consistent with the results in columns 2 -4.

Third, consider the intercept coeicients that capture the average abnormal return resulting from the recommendation revisions. These estimates provide information on the degree ofconsistency in investor reaction when revisions in recommendations and price targets are reinforcing or countervailing. As expected, abnormal returns associated with recommendation upgrades (downgrades) are economically and statistically the largest when such revisions coincide with positive (negative) target price revisions. For example, when target prices are revised upward (column 5), a1, the intercept that captures the abnormal return due to recommendation upgrades, equals 4.311 and is signiicantly larger than the abnormal return due to recommendation downgrades and reiterations (0.048 and 1.571, respectively). Similarly, among the three recommendation revision indicators associated with negative target price revisions (column 6), the one associated with recommendation downgrades is statistically and economically the largest. Another intriguing inding is that, when partitioned by the sign of the target price change, recommendation reiterations are associated with a

14McNichols and OBrien (1997), for example, report that coefficient estimates on recommendation upgrades are smaller in absolute value than those for recommendation downgrades. The evidence from columns 2 and 3, however, suggests that these estimates are not economically diferent. The reason for this discrepancy is our conditioning on the issuance of a target price. In unreported results, we find that when we do not condition on the presence of a target price, investor reaction to recommendation downgrades is larger in absolute value than to upgrades.

15 The magnitude of the slopes on the target price revision in columns 5 and 6 are both lower than the slope reported in column 1. Whereas in column 1 we specify a linear relation between target price revisions and abnormal returns, the regressions in columns 5 and 6 allow the coeicient estimates on the stock recommendation to vary depending on the sign of the target price revision, thus exploiting the information in target price revisions as well. Indeed, when we estimate a regression similar to the one in column 1, but with the inclusion of a slope indicator variable that assumes the value of 1 for positive target price revisions and 0 for negative ones, the coeicient estimates on positive target price revisions is 3.095 compared to 4.375 on negative target price revisions (the diference is statistically signiicant, with a p-

value = 0.001).

large and signiicant abnormal return. For instance, when issued along with a positive target price revision, reiterated recommendations are informative as the associated intercepts are economically and statistically signiicant (a3 = 1.571, t-statistic = 29). Similar evidence is obtained for reiterations accompanied by negative target price changes.

In additional unreported tests we have also examined the informativeness of target price revisions using event-day abnormal volume. Following Holthausen and Verrecchia (1990), who argued that abnormal volume and abnormal returns are equally relevant means of assessing information content, we have calculated for every irm and event in our sample an abnormal volume measure and then repeated the analysis reported in Table III. Specifically, we regress the absolute value of abnormal volume on target price revisions controlling for recommendation and earnings forecast revisions. Consistent with our earlier results we ind that changes in target prices are positively related to abnormal volume. Indeed, target price revisions lead to the highest abnormal volume when issued with recommendation downgrades. Moreover, abnormal volume is highest when the direction of the target price and recommendation revisions coincide.

Taken together, the evidence presented in Table III supports the hypothesis that target prices are informative, both unconditionally and conditional on stock recommendation and earning forecast revisions. We ind that target price revisions are deemed more informative when they are negative and when associated with recommendation downgrades. We also ind that investor reaction is the strongest when the direction of the target price and recommendation revisions coincide rather than when they difer.16

C. Postevent Abnormal Returns

The preceding analysis is based on the assumption that investors respond quickly and rationally to the information conveyed in the analyst reports. Since some studies (e.g., Stickel (1995), Womack (1996), Barber et al. (2002)) have shown that market reaction to announcements of recommendation changes is incom-

16 We have performed three additional tests. First, we estimate regressions in which we condition on the sign of the earnings forecast revision. We ind that when earnings forecasts are revised downward, the abnormal return associated with target price revisions is larger than when earnings forecasts are either unchanged or revised upward. This is consistent with the analysis in which we conditioned on the type of recommendation changes in columns 2-4. Second, we examine whether the inclusion of prior stock returns afects the results reported above, since high (low) prior returns might proxy for unusual events in the recent past that might prompt analysts to revise their beliefs regarding irm value. We ind strong evidence that target price revisions are correlated with prior returns. We also ind, however, that in a regression such as that reported in column 1 of Panel A in Table III, the inclusion of prior one-, two-, three-, or six-month market-adjusted abnormal returns does not alter any of our conclusions. Third, we examine the efects of the coincidence of target price issuance with earnings announcements. We repeat the abnormal return regressions (conducted in Section II) separately for those events in which earnings announcements occurred within the previous ive days and those events in which no such recent announcement occurred. We found that the slope coeicient on the target price revision is signiicant and is similar in magnitude across the two scenarios.

plete, we conclude this section with an exploration of postevent abnormal returns in which we ask whether investor reaction to target price revisions is unbiased. Accordingly, we extend the postevent window from event-day + 3 through six months after the event and examine the abnormal returns in this period.

We begin by calculating equal-weight size and book-to-market adjusted cumulative abnormal returns (CAR) for each event in our sample. Speciically, we irst obtain the market capitalization and book-to-market ratio for each irm prior to an event. Then, using the Fama and French 25 size and book-to-market sorted portfolios, we ind the portfolio with the matching characteristics. Finally, we calculate the six-month CAR as the cumulative return on the event irm beginning in the irst month after the event, minus the cumulative matching portfolio return over the same time period. To avoid possible cross-correlation problems arising from identical return observations, all but one of the identical return observations within each portfolio are deleted.

Consider irst the average abnormal returns for subsamples ofevents classiied by recommendation upgrades, reiterations, and downgrades.Within upgrade and downgrade recommendation groups we present abnormal return estimates for the highest and lowest tercile portfolios, sorted by the magnitude of the analysts target price revision at the time of the event. For the reiterated recommendation category we report abnormal return estimates for the highest and lowest decile portfolios, since the number of observations in this case is more than an order of magnitude larger than in the other two categories. In this manner it is possible to observe whether target price revisions contain information for future abnormal returns above and beyond that provided in the associated recommendation. We calculate standard errors for our CAR estimates using the sample standard deviation of the abnormal returns. For example, inferences regarding the six-month CAR are based on the cross-sectional standard deviation of the event irms six-month cumulative abnormal returns.

Table IV presents our results. Consider first the sample of target price revisions that were issued along with recommendation upgrades. From the row labeled All target price revisions we learn that, on average, target prices are revised upwards by 10 percent relative to the pre-event stock price. The average abnormal return is 1.03 percent for the irst month after the event (t-statistic = 4.1), and increases to 3.08 percent (t-statistic = 4.7) six months after the event. The next two rows correspond to the abnormal return estimates for the two subsamples that are sorted based on the magnitude of the price-scaled target price revision. For events in the highest target price revision group (in which revisions averaged 37 percent), the average abnormal return through event month +1 is 1.97 percent (t-statistic = 4.2), and it increases to 5.21 percent (t-statistic = 4.2) through event month + 6. When we examine events whose target price revision is in the lowest tercile (in which revisions average - 20 percent), we ind that abnormal returns are in general negative and insigniicant and that by event month + 6, equal - 0.38 percent (t-statistic =- 0.4).

Next, we examine events associated with recommendation reiterations. While there is little trace of an economically meaningful drift for all reiteration events,

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