Cette thèse s'intéresse au rôle des analystes financiers lors de la couverture des introductions en bourse dans un contexte international. Nous traitons de la valeur informationnelle des couvertures des analystes et de leur conséquence sur la performance à long terme des entreprises nouvellement introduites en bourse. Nous examinons si les recommandations des analystes financiers permettent de réduire le comportement irrationnel des investisseurs en situation de forte incertitude. Nous espérons qu'en réduisant les asymétries d'informations, les analystes financiers aident les investisseurs à mieux cibler la valeur de l'IPO. Cette thèse s'articule autour de deux parties : la première est consacrée au positionnement théorique et à nos hypothèses de recherche ; la seconde se focalise sur la vérification empirique d'un échantillon d'IPOs internationales (Etats-Unis, Angleterre, Allemagne et France) sur la période 1991 à 2005. Les résultats révèlent une sous performance des IPOs plus sévères pour les orphelines (sans couverture des analystes) que pour les non orphelines. Il apparaît que la couverture des analystes est importante pour les IPOs mais que le marché n'en perçoit pas toute la valeur. D'autres analyses soulignent que cette meilleure performance des non orphelines provient du nombre élevé de couvertures. Nous établissons que les recommandations des analystes sont significativement reliées à la performance à long terme des IPOs. Ainsi, nous vérifions le rôle crucial des analystes financiers dans la production et l'interprétation des informations. / This thesis explores the role of financial analysts' coverage on IPOs in an international context. We deal with the informational value of research coverage and the consequence on long run performance of newly public firms. We examine whether financial analyst recommendations allow alleviating the irrational investors' behaviour in the context of strong uncertainty. We expect that by reducing the information asymmetry, financial analyst recommendations help investors to define progressively the true value of the IPO. The thesis is organized in two main parts: the first part presents a survey of literature and define research hypothesis. The second part consists in an empirical validation of an international sample of IPOs (US, United Kingdom, Germany and France) over the 1991-2005 period. The results reveal that long run underperformance is much severe for orphans' IPOs (without financial recommendation) than non orphans' IPOs. The evidence suggests that analyst coverage is indeed important to issuing firm but the market do not fully incorporate the perceived value of this coverage. Further analysis reveals that this outperformance by non orphan stems from high coverage. We establish that analyst recommendations are significantly related to long run performance of IPOs. Hence, we corroborate the crucial role of financial analysts in producing and interpreting IPOs' financial releases.

Financial analysts play a key role in collecting, processing and disseminating information for the stock market. Selecting the best analysts among thousands of analysts is an important task for investors that determines future investment profitability. Extensive research has been dedicated to finding the best analysts of the market based on various criteria for different clienteles. The state of the art approach in this process has developed into so-called Star Rankings with lists of top analysts who have previously outperformed their peers. How useful are such star rankings? Do the recommendations of stars have higher investment value than the recommendations of non-stars (i.e., recommendations of Stars “shoot” more precisely before and after selection)? Or do star rankings simply represent the past performance that will regress to the mean in the future (i.e., in reality, Shooting Stars are not stars and quickly disappear from the sky)? The aim of this Ph.D. thesis is to empirically investigate the performance of sell-side analysts’ recommendations by focusing on a group of star analysts. This thesis comprises four papers that address two overarching questions. (1) Do star rankings capture any true skill, and, thus, can investors rely on the rankings? (Papers I and II) (2) How do market conditions impact star analysts? (Papers III and IV) Paper I examines the profitability persistence of the investment recommendations from analysts who are listed in the four different star rankings of Institutional Investor magazine, StarMine’s “Top Earnings Estimators”, “Top Stock Pickers” and The Wall Street Journal and shows the predictive power of each evaluation methodology. By investigating the precision of the signals that the various methodologies use in determining who the stars are, the study distinguishes between the star-selection methodologies that capture short-term stock-picking profitability and the methodologies that emphasize the more persistent skills of star analysts. As a result, this study documents that there are star-selection methods that select analysts based on more enduring analyst skills, and, thus, the performance of these methods’ stars persists even after ranking announcements. The results indicate that the choice of analyst ranking is economically important in making investment decisions. Paper II investigates the structure of the portfolios that are built on the recommendations of sell-side analysts and confirms that the abnormal returns are explained primarily by analysts’ stock-picking ability and only partially by the effect of over-weight in small-cap stocks. The study examines the number of stocks in the portfolios and the weights that are assigned to market-cap size deciles and GICS sectors and performs an attribution analysis that identifies the sources of overall value-added performance. Paper III examines the differences in seasonal patterns in the expected returns on target prices between star and non-star analysts. Although the market returns in the sample period do not possess any of the investigated seasonal effects, the results show that both groups of analysts, stars and non-stars, exhibit seasonal patterns and issue more optimistic target prices during the summer, with non-stars being more optimistic than stars. Interestingly, the results show that analysts are highly optimistic in May, which contradicts the adage “Sell in May and go away” but is consistent with the notion of a trade-generating hypothesis: since analysts face a conflict of interests, they may issue biased recommendations and target prices to generate a trade. A detailed analysis reveals that the optimism cycle is related to the calendar of companies’ earnings announcements rather than the market-specific effects. Paper IV discusses how a shift in economic conditions affects the competitiveness of sell-side analysts. The focus is on the changes that were triggered by the financial crisis of 2007-2009 and a post-crisis “uncertainty” period from 2010-2013. The study follows Bagnoli et al. (2008) in using a change in the turnover of rankings as a measure of a transformation in analysts’ competitive advantages. Paper IV extends their research and documents how different ranking systems capture analysts’ ability to handle changes in the economic environment. The results show that market conditions impact analyst groups differently, depending on the group’s competitive advantages. / <p>QC 20170412</p> / European Doctorate in Industrial Management

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.

This thesis analyzes the effects of analysts’ recommendations on stock prices and trade volumes of firms listed on OMXS30 during the three-year period 2018-2020. An event study of 313 recommendations issued during the three- year period was conducted in order to calculate the abnormal returns and abnormal volumes during the event window. Our results show only one occasion respectively where buy and sell recommendations induces abnormal returns significantly different from zero. We thereby conclude that analysts’ recommendations, on average, do not impose significant abnormal returns for OMXS30-firms during the event window. A potential investment value can be found in short selling sell recommended stocks, provided that one obtains information prior to public release. However, the nature of short selling may reduce or erase this value. Our results indicates that recommendations in general, do not contain new information and that the market to an extent, acts efficient. Positive abnormal volumes significant on the 5% level are found on three occasions, hence the majority are found to be insignificant. Significant abnormal volumes of 0,071% were found on the first post-event day of a recommendation, implying a small initial volume reaction. In general, however, the results do not show clear indications of a recommendation generating positive abnormal volumes.

傳統探討分析師推薦資訊價值的研究多採用累積超額報酬的方式，近年來研究顯示個別投資人的績效顯著低於機構投資人，因此是否分析師推薦能夠幫助提升個別投資人的福利。本論文的第一個貢獻在檢定是否個別投資人能夠獲取分析師推薦的資訊價值，為區分推薦資訊分別對於個別與機構投資人的價值為何，本研究採用的每種投資人實際的交易利潤作為衡量指標。 研究結果顯示所有投資人都可以透過買入推薦獲取顯著的正報酬，但在賣出推薦上，僅外資與共同基金仍能維持獲取正的報酬。同時發現在推 薦事件期間，專業機構投資人的利潤顯著高於一般散戶的獲利。 進一步，本論文的第二的主題在探討此推薦的資訊價值對於不同投資人的差異，是否肇因於推薦券商所提供的私有資訊，因此進一步將各類投資人分成推薦券商的客戶與非客戶。結果顯示國內機構投資人的利潤在客戶的身上顯著高於非客戶的獲利，顯示推薦券商在對外公佈推薦資訊前的確提供私有資訊給其國內機構客戶，但此現象在賣出推薦並不存在。 第三，本論文進一步分析是否拿到推薦券商所提供私有資訊的客戶也是推薦券商的經紀業務收益的主要貢獻者。在比較推薦券商與非推薦券商在被推薦股票上的相對交易量(金額)中，發現推薦券商的確因為買入推薦股票而增加經紀業務量，但很驚訝的發現貢獻最多交易量的是個別投資人，而非拿到最多好處的機構投資人。 最後，本研究透過迴歸分析探討不同投資人的交易利潤與推薦券商所獲得的經紀業務量的關係。在控制推薦類型、推薦評等與被推薦股票之股票特性後，發現投資人的交易利潤與推薦券商的經紀業務收益成正相關，再次顯示券商推薦與其各項業務收益間的關係。 / Traditionally, information value of analysts’ recommendations has been well-recognized by cumulative abnormal returns. Recent studies show that individuals are underperformed, and therefore, it is a critical issue on if analysts’ recommendations are helpful to individuals’ welfares. The first contribution of this dissertation to the literature is to examine whether individual investors are capable of capturing the information value. To classify the information value of recommendations for individuals and institutions, respectively, I, thus, use a direct measure to calculate the actual trading profits of types of traders. To our best knowledge, this is the first paper that demonstrates the information value for types of investors. Our results indicate that, all investors get positive and significant profits in brokerages’ buy recommendations, no matter what types of investors are measured. As to sell recommendations, only foreign investors and mutual funds have positive returns. We also find that professional institutions earn more profits than retail investors during the recommendation event periods. Further, the second objective of this dissertation is to test whether the information values are caused by private information from brokerages’ houses, we separate the profits of types of investors into customers and non-customers based. The findings are that only domestic institutional customers of recommending brokerages are more beneficial than those of non-recommending brokerages in buy recommendations, which implies that brokerage houses may reveal private information to their own institutional customers before buy recommendations make public. This does not hold for sell recommendations. Third, we are interested in analyzing whether the private information that recommending brokerages provide to their own customers may, indeed, contribute to brokerages’ commission revenues. By comparing the trading volume of recommending brokerages and non-recommending brokerage for the covered stocks, we find that the volumes of covered stocks issued in the recommending brokerages are increased for buy recommendations. Particularly, we find that the main contribution of trading volume is from individuals. Furthermore, we run regressions to study the relationship between trading profits of types of investors and trading volume of recommending brokerages. After controlling recommendation types, consensus rating of recommendations, and stock characteristics, our results indicate that trading profits of all types of investors are positively related to commission revenues of brokerages. This may justify the importance of brokerage recommendations on their business relationships.