Graduation Year


Document Type




Degree Granting Department


Major Professor

Daniel J. Bradley, Ph.D.

Co-Major Professor

Christos Pantzalis, Ph.D.

Committee Member

Delroy M. Hunter, Ph.D.

Committee Member

Jianping Qi, Ph.D.


Analysts’ Recommendations, Contrarian Revision, Market Efficiency, Analysts’ Earnings Forecasts, Post-Earnings Announcement Drift


In the first essay titled "The Information Role of Analysts' Contrarian Revisions," I study a special group of revisions: contrarian revisions, defined as recommendation changes that are inconsistent with sizable stock price movements during the past week. I find that contrarian revisions are relatively more informative than trending revisions. In particular, contrarian revisions are associated with a both statistically and economically larger post-announcement drift. I also find contrarian downgrades are less likely to be issued by all-star analysts and analysts with more experience. After implementation of Regulation RD, the market reaction to contrarian revisions issued by all-stars significantly decreases, indicating private information contained in contrarian recommendations has declined. Overall, our results suggest analyst recommendations are important information sources for market participants.

In the second essay titled "Market Reaction to Earnings When Investors Disagree," I investigate how the divergence of opinions between individual and institutional investors affects stock price movements around public news events, specifically earnings announcements. I use a discrete static market equilibrium model to illustrate that divergence of investors' opinions has a significant impact on stock price movements around earnings announcements. Specifically, the divergence of opinion has a negative relation with the immediate market reaction but a positive relation with the subsequent stock price drift. I also investigate trading volume around earnings announcements to explore how traders respond to changes in the divergence of investors' opinions. Empirical evidence supports the model implications and indicates announcement trading volume decreases inversely to the divergence of opinions.