Yes / This study uses the quality of coverage decisions as a new metric to evaluate the performance of star and non-star analysts. We find that the coverage decisions of star analysts are better predictors of returns than those of non-star analysts. The return predictability of star analysts’ coverage decisions is stronger for informationally opaque stocks. We further exploit the staggered short selling deregulations, Google’s withdrawal, and the anti-corruption campaign as three quasi-natural experiments that create plausibly exogenous variations in the quality of information environment. These experiments show that the predictive power of star analysts’ coverage decisions strengthens (weakens) following a sharp deterioration (improvement) in firms’ information environment, consistent with the notion that star analysts possess superior ability to identify mispriced stocks. Overall, star analysts make better coverage decisions and play a superior role as information intermediaries, especially in poor information environment.

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Cette thèse de doctorat comporte trois chapitres distincts. Dans le premier chapitre, nous étudions le comportement moutonnier d'investisseurs individuels français. Notre analyse empirique repose sur une base de données de presque 8 millions de transactions réalisées entre 1999 et 2006 par 87 373 investisseurs individuels français. Nous montrons que le comportement moutonnier persiste dans le temps et que la performance passée ainsi que le niveau de sophistication influencent ce comportement. Nous tentons également d'apporter une réponse à une question très peu abordée dans la littérature : adopter un comportement moutonnier est-il profitable pour l'investisseur individuel ? Notre analyse empirique indique que les investisseurs contrariants obtiennent des rendements plus extrêmes (positifs ou négatifs) que les investisseurs moutonniers. Dans le second chapitre, nous montrons que mesurer la précision d'une prévision du prix futur d'une action n'est pas suffisant pour évaluer la qualité de cette prévision car la prévisibilité des prix est susceptible d'évoluer dans le temps et dépend du titre considéré. Nous montrons que la persistance dans les différences individuelles de précision des prévisions d'analystes, mis en avant dans la littérature, ne constitue pas une preuve de différences de compétences entre analystes. Cette persistance est, en réalité, causée par une persistance de la volatilité de la rentabilité des titres. Nous introduisons une mesure de qualité des prévisions qui incorpore à la fois l'erreur de prévision et la prévisibilité du prix. La théorie des options nous fournit les éléments nécessaires à l'estimation de cette prévisibilité. Lorsque celle-ci est prise en compte, il n'y a plus de différences de compétences entre analystes. Dans le troisième chapitre, nous montrons que les analystes expérimentés et inexpérimentés ne couvrent pas le même type d'entreprises. Les analystes expérimentés couvrent des entreprises de type « blue chips » tandis que les analystes inexpérimentés couvrent des entreprises petites, jeunes et en croissance. Ces différences de couvertures impliquent que les analystes inexpérimentés émettent des prévisions de prix sur des entreprises dont les rendements sont plus volatils et donc moins prévisibles. En conséquence, la précision des prévisions n'est pas une bonne mesure pour évaluer si les analystes expérimentés sont meilleurs ou moins compétents que les analystes inexpérimentés. Lorsque ces différences de couvertures sont prises en compte, nous obtenons que les analystes expérimentés émettent néanmoins de meilleures prévisions. Bien que statistiquement significatif, l'impact économique de l'expérience des analystes est faible. / This dissertation is made of three distinct chapters. In the first chapter, we introduce a new measure of herding that allows for tracking dynamics of individual herding. Using a database of nearly 8 million trades executed between 1999 and 2006 by 87,373 individual investors, we show that individual herding is persistent over time and that past performance and the level of sophistication influence this behavior. We are also able to answer a question that was previously unaddressed in the literature: is herding profitable for investors? Our unique dataset reveals that the investors trading against the crowd tend to exhibit more extreme returns and poorer risk-adjusted performance than the herders. In the second chapter, we show that measuring the accuracy of a target price is not sufficient to assess its quality, because the forecast predictability (which depends on the stock return volatility and on the forecast horizon) is likely to vary across stocks and over time. We argue that the evidence of time persistent differences in analysts' target price accuracy, obtained in previous studies, cannot be interpreted as a proof of persistent differential abilities. Our analysis indicates that the persistence in accuracy is driven by persistence in stock return volatility. We introduce a measure of target price quality that considers both the forecast inaccuracy and the forecast predictability. Using elements from option-pricing theory, we provide a simple solution to the issue of estimating target price predictability. Our empirical analysis reveals that, when forecast predictability is taken into account, financial analysts do not exhibit significant persistent differential abilities to forecast future stock prices. In the third chapter, we show that experienced financial analysts tend to cover different firms than inexperienced analysts. Experienced analysts tend to follow blue chips (i.e., large, international, mature firms) while inexperienced analysts focus on small, young, growth-oriented firms. These differences in coverage decisions imply that inexperienced analysts issue target prices on firms for which stock returns are more volatile, and thus less predictable. As a consequence, the accuracy measure of target prices fails to evaluate differences in ability between experienced and inexperienced analysts. When taking into account these differences in coverage decisions, we still find that experienced analysts do a better job at forecasting stock prices. Our results on the influence of analysts' characteristics on target price quality are statistically significant but economically weak.

Clinical practice guidelines (CPGs) are statements that include recommendations intended to optimize patient care that are informed by a systematic review of evidence and an assessment of the benefits and harms of alternative care options. CPGs’ recommendations have traditionally focused on informing clinicians and patients on the best options, i.e., supporting decisions that occur at the clinical encounter level. Considering all their advantages (a systematic and comprehensive review of the evidence, a multidisciplinary team assessing the evidence and balancing benefits and harms, and the additional considerations such as patients’ preferences, implementability and feasibility of interventions and their costs) CPGs have also become powerful tools to inform decisions and activities outside the clinical encounter. This, because the clinical encounter cannot be completely separated from other decisions that indirectly affect that level, such as those related to quality improvement activities and economic decisions in healthcare. Moreover, activities that are not directly related to the clinical encounter can benefit from CPGs, like education and licensing activities and research prioritization processes, or judicial decisions. The role of CPGs in all these activities has been neglected in the literature. In this study, I performed a critical interpretive synthesis of the literature to summarize the different roles CPGs play outside the clinical encounter and to understand how, and under what conditions CPGs are used in these roles. I also conducted an international survey to describe how frequent these roles exist, from the CPGs developers' perspectives. Lastly, I conducted a multiple case study to understand how and under what conditions CPGs play one of the main roles outside the clinical encounter (drug funding decisions), in two different settings (Colombia and Canada/Ontario). Based on the results, I developed a framework to describe and categorize the roles of CPGs outside the clinical encounter and to determine how and under what conditions CPGs are used in these roles. I highlighted the key areas that require additional methodological research and categorize the roles in main, secondary and unanticipated roles. I also described how international developers reported that CPGs play these roles and how these roles are part of their CPGs final aims in the second study. Lastly, in the case study, I revealed that CPGs were instrumentally used to inform one of the main roles, drug funding decisions, in the Colombian case, and they had a minor conceptual use in the case of Canada/Ontario. / Thesis / Doctor of Philosophy (PhD)