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Leaders and Followers among Security Analysts

Graduate Project. Prepared by Li Wang Dept. of Statistics at McMaster University. Leaders and Followers among Security Analysts. Supervised by Dr. Veall and Dr. Kanagaretnam. Outline. Background and Data Description Performance of Security Analysts

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Leaders and Followers among Security Analysts

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  1. Graduate Project Prepared by Li Wang Dept. of Statistics at McMaster University Leaders and Followers among Security Analysts 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…… Background on Security Analysts Individual Investor rank Analyst Institution Investor Third Party rank Wall Street Journal Brokerage Firm Institutional clients Buy, sell or hold

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

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

  6. Performance of Analysts 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

  7. Performance of Analysts Leader and Follow Ratio (LFR) Hypothesis 1: Testing the forecast arrival times for leaders in pre-release periods are greater than those in post-release periods. ~ ( Cooper et al, 2001) ; Under null hypothesis θ0 = θ1, ( Lawless, 1982 ) N :the number of earning forecasts Toj: lead-time T1j: follow-time

  8. Performance of Analysts A1 A2 A3 A4 B5 A5 B4 B3 B2 B1 LFR For Leaders Forecast revision dates surrounding the forecast revision of a lead analyst -12 -10 -8 -7 -5 0 1 3 4 5 7 days LFR > 1 The selected analyst is a leader.

  9. Performance of Analysts B5 B4 A1 B3 A2 B2 A3 B1 A4 A5 LFR For FollowersForecast revision dates surrounding the forecast revision of a follower analyst -5 -4 -3 -2 -1 0 3 5 7 9 11 days LFR < 1 The selected analyst is a follower.

  10. Results of classification

  11. Performance of Analysts 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) ( Rijt = 1,…, Nit)

  12. Performance of Analysts Hypothesis 2: the earning forecasts of followers are more accurate than those of leaders over the estimation year.

  13. Performance of Analysts Relative forecast accuracy of leaders andfollowers

  14. Performance of Analysts Forecast Issuance Timeline Pre-release period Jun. Jul. Aug. Sept. Oct. Nov. Dec. Boldness 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.

  15. Performance of Analysts Hypothesis 3: A higher percentage of forecasts of leaders derivate from the consensus forecast compared to those of follower analysis.

  16. Performance of Analysts Other Attributes

  17. Model Fitting…… 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)

  18. Model Fitting…… Summary Statistics of Analysts Dataset

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

  20. Logistic Regression Analysis…… Logistic Regression Model for Analysts Dataset Coefficient Correlation • 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. Logistic Regression Analysis…… Analysis of Maximum Likelihood Estimation Goodness-of-fit: Hosmer and Lemeshow χ2=14.137 on 8 d.f., P=0.0483

  22. Timeliness and Stock Price…… 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:

  23. Timeliness and Stock Price…… 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.

  24. Timeliness and Stock Price…… 2-day Release Period Forecast Surprise Coefficients for Lead and Follower Analysts

  25. Timeliness and Stock Price…… 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). • Where is the cumulative excess return over the 20 days pre- released period.

  26. Timeliness and Stock Price…… 20-Day Pre-Released Period Forecast Surprise Coefficients for Leader and Follower

  27. Discussion and Conclusion…… 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.

  28. Reference….. Reference: • Rick A. Cooper, Theodore E. Day, Craig M. Lewis, 2000. Following the Leader: a study of individual analysts’ earnings forecasts. Journal of Finance Economics, 61, 383-416. • Brown, Lawrence D., 2001, How import is past analyst forecast accuracy?. Financial Analysts Journal 57,4-49 • Brennan, M., and Subrahmanyam, A. 1995. Investment analysis and Price formation in securities markets. Journal of Financial Economics 38, 361-381. • Gleason, Cristi A., and Charles M. C. Lee, 2003, Analyst forecast revisions and market price discovery. The Accounting Review 78, 227-250. • Leone, A., and Wu, J., 2002. 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, 1997. Do Security Analysts Improve Their Performance with Experience? Journal Accounting Research 35: 131-157.

  29. Thank You!

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