Leaders and Followers among Security Analysts Prepared by Li Wang Dept. of Statistics at McMaster University Supervised by Dr. Veall and Dr. Kanagaretnam

2 Outline Background and Data Description Performance of Security Analysts Logistic Regression Analysis on Security Analysts Dataset Timeliness Analysts and Stock Price Conclusion and Discussion

3 Background on Security Analysts Analyst Brokerage Firm Institutional clients Individual Investor Institution Investor Wall Street Journal Third Party Buy, sell or hold rank Background……

4 Continue Background ……. Firm A Forecast 2 Forecast 4 Forecast 3 Forecast 5 Forecast 6 Forecast 7 Forecast 9 Forecast 11 Forecast 8 Forecast 10 Analyst 1 Analyst 3 Analyst 2 Analyst 1 Analyst 4 Firm B Forecast 1 Leader Follower

5 Institution Brokers Estimate System (I/B/E/S) Adjustment file Identifier File Exchange Rate Stopped Estimate Report Currency Excluded Estimates S/I/G Codes Broker Translations Detail File Actual File Ticker Data Description and Background……

6 Timeliness Leaders (Cooper, Day and Lewis, 2001) Superior access to information Differential ability to process information Release forecast before competing analysts Herd behavior in finance market Performance of Analysts

7 Leader and Follow Ratio (LFR) ~ N : the number of earning forecasts T oj : lead-time T 1j : follow-time ( Cooper et al, 2001) ; Hypothesis 1: Testing the forecast arrival times for leaders in pre- release periods are greater than those in post-release periods. Under null hypothesis θ 0 = θ 1, ( Lawless, 1982 ) Performance of Analysts

8 A1 A2 A3 A4 A5 B5 B4 B3 B2 B days LFR > 1 The selected analyst is a leader. LFR For Leaders Forecast revision dates surrounding the forecast revision of a lead analyst Performance of Analysts

9 LFR For Followers Forecast revision dates surrounding the forecast revision of a follower analyst A1 A2 A3 A4 A5 B5 B4 B3 B2 B days LFR < 1 The selected analyst is a follower. Performance of Analysts

10 Results of classification Lead AnalystsPercentage Each firm over sample period ( ) 13.68% Each firm in a given year 28.10% At least one firm leader in a given year 31.73% Leaders in subsequent year 10.89%

11 Forecast Accuracy and Bias Percentage Forecast Error (Butler, Lang and Larry) Forecast Bias: Signed Forecast Error Standardize the Ranks to Scores (Hong et al, 2000) Performance of Analysts ( R ijt = 1,…, N it )

12 Hypothesis 2: the earning forecasts of followers are more accurate than those of leaders over the estimation year. Performance of Analysts Relative forecast accuracy of leaders and followers Panel A : Half-year ahead earnings forecast errors and forecast bias: OverallLeader follower T test M-W test forecast accuracy: N Mean Median 7, *** *** Bias: Mean Median

13 Panel B: One- Quarter ahead of earnings forecast errors and forecast bias OverallLeader follower T test M-W test forecast accuracy: N Mean Median 3, % Bias: Mean Median * Performance of Analysts Relative forecast accuracy of leaders and followers

14 Boldness Boldness: Absolute value of the difference between a particular forecast and the mean of outstanding consensus forecast. ■ Standardize to Scores: large deviation with higher scores and small deviation with lower scores. Performance of Analysts Forecast Issuance Timeline Jun. Jul. Aug. Sept. Oct. Nov. Dec. Pre-release period Boldness

15 Hypothesis 3: A higher percentage of forecasts of leaders derivate from the consensus forecast compared to those of follower analysis. Performance of Analysts Table 2-6 Boldness of leaders and followers Absolute Consensus Surprise Overall Leader Follow T-test M-W test N Mean Median *** ***

16 Other Attributes Performance of Analysts Other Attributes of Leaders and Followers OverallLeader follower T test M-W test Brokerage Size Mean Median ** ** Forecast Frequency Mean Median ** -9.55* Stock Coverage Mean Median * * Firm-Specific EXPR Mean Median ** * 4.00 Business EXPR Mean Median * *

17 Variable Specification of Security Analyst Dataset Dependent Variable: Leader=1; Follower=0 Explanatory Variable: Forecast Accuracy (ACCUSCORE) Forecast Bias (BIASSCORE) Forecast Boldness (BDSCORE) Larger Brokerage Firm (LARGEBRKR ) Small Brokerage Firm (SMALLBRKR) Stock Coverage (COVER) Relative Forecast Frequency (RFREQ) Experience (EXPR) Following Analyst (NUMANALYST) Model Fitting……

18 Summary Statistics of Analysts Dataset Model Fitting…… Variables MeanStd. Deviation OverallLeaderFollowerOverallLeaderFollower # of analysts BROKERSIZE LARGEBRKR SMALLBRKR BUSYEAR NUMANAYST ACCUSCORE BIASSCORE RFREQ BDSCORE EXPR LFR COVER

19 Logistic regression model has the form Linear predictor Modeling the conditional probability Logistic Regression Model Logistic Regression Analysis……

20 Logistic Regression Model for Analysts Dataset Logistic Regression Analysis…… Coefficient Correlation  Large broker Small brokercover Num analystrfreqaccubiasboldexpr largebroker (**)-.119(**)-.052(**)-.035(**) (**) smallbroker -.299(**)1-.040(**) (**) (**) cover -.098(**)-.071(**)1.168(**).034(**) (**) numanalyst -.045(**) (**)1-.103(**).028(*).027(*) (**) Rfreq -.023(*) (*)-.095(**) (**) accuscore (*)1.433(**).052(**).010 biasscore (*) bdscore (*) (**)-.033(**)1.034(**) expr -.072(**).032(**).195(**).111(**).038(**) (**)1 Pearson coefficients are above the diagonal line and Spearman coefficients are below the line. ***significant at 1% level, ** significant level at 5% level, * significant level at 10% level.

21 Analysis of Maximum Likelihood Estimation Logistic Regression Analysis…… Parameter EstimateStandard Error Walk ChiSq Pr > ChiSq OR95% Wald Confid limits INTECEPT <.0001 COVER FREQ EXPR BOLDNESS < NUMANALYST ACCU BIAS SMALLBRKR LARGEBRKR Goodness-of-fit: Hosmer and Lemeshow χ2= on 8 d.f., P=0.0483

22 Test the Hypothesis: Timeliness leader will have a higher impact on the stock price than followers. Abnormal Excess Return: security return - value weighted industry index in I/B/E/S. (EVENTUS) Forecast Surprise:  Forecast Revision:  Predecessor-based Surprise:  Consensus-based Surprise: Timeliness and Stock Price……

23 Analyst Timeliness and Contemporaneous Stock price Hypothesis 4: The coefficient of regression of excess return (in short window) on forecast surprise for leader analysts is greater than the coefficient for follower analysts. Where is the cumulative excess return over the two-day released period. Timeliness and Stock Price……

24 2-day Release Period Forecast Surprise Coefficients for Lead and Follower Analysts Timeliness and Stock Price…… Forecast Revision Predecessor- based surprise Consensus- based surprise Coefficient (1) F-value (2) Coefficient (3) F-value (4) Coefficient (5) F-value (6) Intercept < < < Leader* FE ijt < < Follow* FE ijt Adj. R N 7,0257,3506,987

25 Analyst Timeliness and Past Stock price Hypothesis 5: Forecast surprises by leader analysts are not significantly correlated with the stock price performance during the period preceding the forecast revisions ( in long window). However, forecast surprises by follower analysts are positively correlated with excess return during the pre-revision period ( in long window). Timeliness and Stock Price…… Where is the cumulative excess return over the 20 days pre- released period.

26 20-Day Pre-Released Period Forecast Surprise Coefficients for Leader and Follower Timeliness and Stock Price…… Forecast Revision Predecessor- based surprise Consensus- based surprise Coefficient (1) P-value (2) Coefficient (3) F-value (4) Coefficient (5) T-value (6) Intercept < < < Leader* FE ijt Follow* FE ijt Adj. R N 6,9456,7526,894

27 Discussion and Conclusion: There are quality differentials among security analysts in terms of the timeliness of their forecasts. Lead analysts tend to be employed by larger brokerage firm and follow up fewer stocks than follow analysts. Leaders are bolder than followers. Followers release more accurate forecasts than leaders since leaders have to sacrifice the accuracy to be the first movers. Lead analysts identified by timeliness have a greater impact on stock price than follower analysts. Forecast surprises by leader analysts are not significantly correlated with the stock price performance during the period preceding the forecast revisions. However, forecast surprises by follower analysts are positively correlated with excess return during the pre-revision period. Discussion and Conclusion……

28 Reference: Rick A. Cooper, Theodore E. Day, Craig M. Lewis, Following the Leader: a study of individual analysts’ earnings forecasts. Journal of Finance Economics, 61, Brown, Lawrence D., 2001, How import is past analyst forecast accuracy?. Financial Analysts Journal 57,4-49 Brennan, M., and Subrahmanyam, A Investment analysis and Price formation in securities markets. Journal of Financial Economics 38, Gleason, Cristi A., and Charles M. C. Lee, 2003, Analyst forecast revisions and market price discovery. The Accounting Review 78, Leone, A., and Wu, J., What does it take to become a superstar? Evidence from institutional investor rankings of financial analysts. Working paper, University of Rochester. Milkhail, M., R. Willis and B. Walther, Do Security Analysts Improve Their Performance with Experience? Journal Accounting Research 35: Reference…..

29 Thank You!