This thesis studies different aspects of analyst behavior, as well as the corresponding implications for stock markets. Chapter 1 studies whether firm intangible information affects analyst behavior. I find direct evidence that when analysts make more judgment-intensive decisions, such as issuing stock recommendations, they overweight intangible information, leading to overreaction to intangible information. On the contrary, when analysts make less judgment-intensive decisions, such as earnings per share (EPS) forecasts, there is no such evidence of overreaction. More specifically, analyst recommendations are much more sensitive to intangible information, while EPS forecasts are more sensitive to tangible information. The sensitivity of long-term growth forecasts to intangible and tangi...[ Read more ]

This thesis studies different aspects of analyst behavior, as well as the corresponding implications for stock markets. Chapter 1 studies whether firm intangible information affects analyst behavior. I find direct evidence that when analysts make more judgment-intensive decisions, such as issuing stock recommendations, they overweight intangible information, leading to overreaction to intangible information. On the contrary, when analysts make less judgment-intensive decisions, such as earnings per share (EPS) forecasts, there is no such evidence of overreaction. More specifically, analyst recommendations are much more sensitive to intangible information, while EPS forecasts are more sensitive to tangible information. The sensitivity of long-term growth forecasts to intangible and tangible information fall in between. I also test and find that the overconfidence bias in analyst recommendations contributes to the market overreaction to intangible information. The results appear to be consistent with the overconfidence hypothesis put forth by Daniel and Titman (2006).

Chapter 2 studies the causal effect of analyst competition on analyst forecast dispersion. Using exogenous shocks to analyst competition arising from broker mergers, I find that a decrease in analyst competition causes a significant increase in analyst forecast dispersion. I propose two explanations for this negative causal effect. First, lower competition among analysts impairs the quality of information environment, leading to more noisy earnings forecasts and higher forecast dispersion. Second, lower competition reduces the herding tendency of analysts, and as analysts place less weight on the public information and more weight on the private information, their forecast dispersion becomes higher. Empirical evidence supports the information quality explanation, and is inconsistent with the herding explanation.