PhD Thesis Defense Presentation: Ken Duan

Ken Duan, a doctoral student at McGill University in the Accounting area will be presenting his thesis defense entitled:

Two Essays on Analyst Expertise

Friday, April 17, 2026, at 12:00 p.m.
(The defense will be conducted online, via Zoom)

Student Committee Co-chairs: Prof. Hongping Tan

Please note that the Defence will be conducted on Zoom. Only the student and their committee members may participate in the defence.​​​​

Abstract

Financial analysts serve as important information intermediaries in capital markets, helping investors process and interpret complex information. While prior research has extensively studied analysts’ numerical forecasts, much less is known about the qualitative content of their written reports and whether domain-specific information in these reports creates value. This thesis examines whether and how financial analysts engage in domain-specific information collection and processing in their equity analysis and whether such activities create value for investors and underlying firms. Across two studies, I provide evidence that the qualitative content of analyst reports, spanning competitive dynamics and tax matters, reflects analysts’ expertise that improves their own forecast accuracy and informs capital market participants.

In the first study, I investigate the role of competition analysis in financial analyst reports and its value to investors. Using textual analysis on a large sample of analyst reports for U.S. firms, I find that analysts’ earnings forecast revisions accompanied by more competition-related discussion are more accurate. This effect is stronger when the discussion comes from analysts with greater industry expertise and when firms face more intense competition. Further analyses show that both investors and managers find these discussions informative: revisions with detailed competition analysis elicit stronger market reactions, and firms covered by more competition-focused analysts exhibit higher investment efficiency. Overall, the results indicate that competition discussions enhance analysts’ forecast accuracy and provide valuable insights to capital markets.

In the second study, I examine whether analysts’ tax-specific expertise, as reflected in the qualitative discussion of tax matters in their written reports, improves forecast accuracy and conveys value-relevant information to investors. Prior work shows that when analysts issue pre-tax income forecasts, their earnings forecasts are more accurate, they are better able to detect earnings management through tax expense, and their coverage helps monitor tax aggressiveness (Baik et al., 2016; Mauler, 2019; Chen et al., 2018). These findings suggest that tax-specific expertise has observable benefits, and I predict that the qualitative tax discussion in analyst reports should similarly improve forecast quality and inform investors. Consistent with this prediction, I find that analysts who discuss more tax matters in their research reports produce more accurate effective tax rates and earnings forecasts, and that this effect is incremental to whether analysts issue explicit pre-tax income forecasts. Further analysis shows that the benefit is particularly pronounced when analysts discuss transitory tax items. I also find that negative tax discussion is associated with significantly negative short-window market reactions, while positive tax discussion has no significant effect. Taken together, the findings suggest that analysts’ tax expertise is both helpful for forecast accuracy and informative for investors, contributing to our understanding of how domain-specific knowledge shapes the value of analyst research.