Active investors are always trying to find new ways of systematically beating the market. Since the advent of social media, this has become one of the latest areas where investors are trying to find untapped information to exploit through a technique called sentiment analysis, which is the act of using automatic text processing to discern the opinions of social media users. The purpose of this study is to investigate the possibility of using the sentiment of tweets directed at specific companies to construct portfolios which generate abnormal returns by investing in companies based on the sentiment. To meet this purpose, we have collected company specific tweets for 40 companies from the Nasdaq 100 list. These 40 companies were selected using a simple random selection. To measure the sentiment tweets were downloaded from 2014 to 2016, giving us three years of data. From these tweets we extracted the sentiment using a sentiment program called SentiStrength. The sentiment score for every company was then calculated to a weekly average which we then used for our portfolio construction. The starting point for this study to try and explain the relationship between sentiment and stock returns was the following theories: The Efficient Market Hypothesis, Investor Attention and the Signaling Theory. Tweets act as signals which direct the attention of the investors to which stocks to purchase and, if our hypothesis is correct, this can be exploited to generate abnormal returns. To evaluate the performance of our portfolios the cumulative non-risk adjusted return for all of portfolios was initially calculated followed by calculations of the risk adjusted return by regressing both the Fama-French Three-Factor model and Carhart’s Four-Factor model with the returns for our different portfolios being the dependent variables. The results we obtained from these tests suggests that it might be possible to obtain abnormal returns by constructing portfolios based on the sentiment of tweets, using a few of the strategies tested in this study as no statistically significant negative results were found and a few significant positive results were found. Our conclusion is that the results seems to contradict the strong form of the Efficient Market Hypothesis on the Nasdaq 100 as the information contained in the sentiment of tweets seems to not be fully integrated within the share price. However, we cannot say this with confidence as the EMH is not a testable hypothesis and any test of the EMH is also a test of the models used to measure the efficiency of the market.

Cette recherche porte sur la description et la compréhension de l’évolution du sentiment d’efficacité personnelle (SEP) chez des personnes en emploi dans un processus de counseling de carrière ayant pour objectif un bilan de compétences (BC). Il s’agit de décrire et de comprendre les quatre sources d’information du SEP (expériences actives de maitrise, expériences vicariantes, persuasion verbale et états émotionnels et physiologiques) au travers des tâches réalisées selon les phases de rétrospective, de prospective et de réalisation en modes exploration, compréhension et action de la démarche de BC. La mondialisation de l’économie et l’avènement des nouvelles technologies sont considérés comme étant à la base des transformations massives du marché du travail qui ont des effets importants sur l’adaptabilité à la carrière des travailleuses et des travailleurs. Qui plus est, certains d’entre eux deviennent à risque de précarité étant donné les obstacles qui se dressent au regard de l’instabilité et du mouvement constant du marché du travail. L’adaptabilité à la carrière est définie par Savickas (1997) comme étant : « la volonté de faire face aux tâches prévisibles de préparation et de participation dans le rôle de travailleuse ou de travailleur et avec les ajustements imprévisibles provoqués par des changements dans le travail et les conditions de travail » (p. 254). Les recherches démontrent que l’adaptabilité à la carrière est favorisée par un SEP élevé et, qu’un processus de counseling de carrière a des effets sur l’évolution du SEP d’individus dans différents contextes, notamment à la suite d’une démarche de BC. Bien qu’un processus de counseling de carrière ou, plus spécifiquement, une démarche de BC ait un effet sur le SEP, aucune recherche ne s’est attardée à comprendre ce qui, à l’intérieur d’une telle démarche, favorise l’évolution du SEP. Cette thèse est issue d’une recherche source (Michaud, Savard, Paquette et Lamarche, 2010) portant sur l’évaluation des effets d’une démarche de BC auprès de personnes en emploi sur le SEP, l’estime de soi et la qualité de la gestion du maintien en emploi. En se basant sur une approche qualitative, l’analyse secondaire des données est effectuée à partir de l’étude de cas en profondeur afin de décrire et de comprendre l’évolution du SEP chez des personnes en emploi dans une démarche de BC. Trois personnes en emploi ont été retenues en regard des critères d’inclusion. Les données ayant servi à cette analyse sont : 1) les enregistrements des rencontres de la démarche de BC pour chacune des personnes en emploi; 2) les entrevues semi-dirigées avec les personnes en emploi et les personnes conseillères d’orientation; 3) les dossiers évolutifs des personnes en emploi. L’analyse montre que les quatre sources d’information relatives au SEP sont présentes dans les trois cas étudiés, mais ce sont les expériences actives de maitrise et les états émotionnels et physiologiques qui sont le plus évoqués au cours de la démarche BC. L’analyse confirme le modèle du SEP de Bandura (1977) qui stipule que les sources d’information positives favorisent des comportements d’approche, de persistance et de performance alors que les expériences actives de non maitrise ou les états émotionnels et physiologiques négatifs amènent les individus à un comportement d’évitement. La présence de ces sources d’information est favorisée par les tâches d’exploration et de compréhension de l’histoire développementale des compétences des personnes en emploi du modèle de BC de Michaud, Dionne et Beaulieu (2007a). Les tâches d’exploration et de compréhension des mécanismes d’autorégulation et d’autoprotection ainsi que des expériences actives de maitrise et de non maitrise en lien avec des états émotionnels et physiologiques, mèneraient l’individu en emploi vers l’identification de compétences développées au cours de son parcours professionnel. Cela aiderait également à cibler les compétences à développer dans un projet professionnel. La tâche de rédaction du portfolio consolide l’écriture comme étant un ingrédient actif dans la démarche de BC qui permet d’engager la personne en emploi dans un processus de conscience réflexive de soi, de validation de ses compétences et de mobilisation des ressources personnelles et environnementales qui soutiennent l’agir de ses compétences. La réalisation de ces tâches favoriserait le SEP, notamment par la conscience d’expériences actives de maitrise passées et actuelles et, par le développement des compétences à partir de la mise en action d’un projet professionnel. Le SEP évolue ainsi à partir des tâches réalisées dans la démarche de BC. De plus, la démarche favorise la motivation à s’engager dans un projet professionnel en matière de compétences à développer, ce qui permet l’évolution du SEP dans l’atteinte et la réalisation des objectifs par la rédaction du plan d’action ou de développement de compétences. La conclusion permet de montrer la pertinence de l’adaptation du nouveau modèle de bilan et développement de compétences en entreprise (BDCE) de Michaud et al. (2010) qui bonifie la démarche en spécifiant la centralité du développement des compétences dans le processus de changement du BDCE.

L'objectif de ce travail doctoral est de tester et d'expliquer l'influence des bénéfices que les membres perçoivent dans les communautés virtuelles de support initiées par les entreprises sur leurs intentions comportementales à l'égard de ses produits. Une étude ethnographique a d'abord été menée et a complété les enseignements tirés de la revue de littérature. Ensuite, une collecte de données quantitative a été menée sur des communautés virtuelles des éditeurs des logiciels. A l'issue des résultats de la recherche, nous avons principalement démontré que les bénéfices perçus par les membres favorisent leurs intentions de réachat et de recommandation des produits de l'entreprise sous conditions que cette dernière participe activement dans les activités de sa communauté. Par ailleurs, cette influence positive s'opère aussi à travers le sentiment communautaire du membre. / The objective of this doctoral work is to test and to explain the influence of the benefits that are paid to members in virtual communities of support initiated by companies on their behavioral intentions with respect to its products. An ethnographic study was first conducted and completed the lessons learned from the literature review. Then, quantitative data collection was conducted on virtual communities of software publishers. At the end of the search results, we mainly demonstrated that the benefits received by members promote their intentions of reachat and recommendation of the products of the company under conditions that the latter actively participates in the activities of its community. Moreover, this positive influence also operates through the community feeling of the Member.

<div> <div> <p>Benefited from the booming social network, reading posts from other users overinternet is becoming one of commonest ways for people to intake information. Onemay also have noticed that sometimes we tend to focus on users provide well-foundedanalysis, rather than those merely who vent their emotions. This thesis aims atfinding a simple and efficient way to recognize reliable information sources amongcountless internet users by examining the sentiments from their past posts.<br></p><p>To achieve this goal, the research utilized a dataset of tweets about Apples stockprice retrieved from Twitter. Key features we studied include post-date, user name,number of followers of that user, and the sentiment of that tweet. Prior to makingfurther use of the dataset, tweets from users who do not have sufficient posts arefiltered out. To compare user sentiments and the derivative of Apples stock price, weuse Pearson correlation between them for to describe how well each user performs.Then we iteratively increase the weight of reliable users and lower the weight ofuntrustworthy users, the correlation between overall sentiment and the derivative ofstock price will finally converge. The final correlations for individual users are theirperformance scores. Due to the chaos of real world data, manual segmentation viadata visualization is also proposed as a denoise method to improve performance.Besides our method, other metrics can also be considered as user trust index, suchas numbers of followers of each user. Experiments are conducted to prove that ourmethod out performs others. With simple input, this method can be applied on awide range of topics including election, economy, and job market.<br></p> </div> </div>

O projeto descrito neste documento propõe um modelo para análise de viés em notícias, procurando identificar o viés dos meios de comunicação em relação a entidades políticas. Foram analisados três tipos de viés: o viés de seleção, que avalia o quanto uma entidade é referenciada pelo meio de comunicação; o viés de cobertura, que avalia quanto destaque é destinado a entidade e, por fim, o viés de afirmação, que avalia se estão falando mal ou bem da entidade. Para tal, foi construído um corpus de notícias sistematicamente extraídas de 5 produtores de notícias e classificadas manualmente em relação à polaridade e entidade alvo. Técnicas de análise de sentimentos baseadas em aprendizado de máquina foram validadas utilizando o corpus criado. Criou-se uma metodologia para identificação de viés, utilizando o conceito de outliers, a partir de métricas indicadoras. A partir da metodologia proposta, foi analisado o viés em relação aos candidatos ao governo de São Paulo e à presidência a partir do corpus criado, em que se identificou os três tipos de viés em dois produtores de notícias / The project described here proposes a model to study bias on newswire texts, related to political entities. Three types of bias are analysed: selection bias, which refers to the amount of times an entity is referenced by the media outlet; coverage bias, which assesses the amount of coverage given to an entity and, finally, the assertion bias, which analyses whether the news is a positive or negative report of an entity. To accomplish this, a corpus was systematically built by extracting news from 5 different newswires. These texts were manually classified according to their polarity alignment and associated entity. Sentiment Analysis techniques were applied and evaluated using the corpus. Based on the concept of outliers, a methodology for bias detection was created. Bias was analysed using the proposed methodology on the generated corpus for candidates to the government of the state of São Paulo and to presidency, being identified in two newswires for the three above-defined types

O projeto descrito neste documento propõe um modelo para análise de viés em notícias, procurando identificar o viés dos meios de comunicação em relação a entidades políticas. Foram analisados três tipos de viés: o viés de seleção, que avalia o quanto uma entidade é referenciada pelo meio de comunicação; o viés de cobertura, que avalia quanto destaque é destinado a entidade e, por fim, o viés de afirmação, que avalia se estão falando mal ou bem da entidade. Para tal, foi construído um corpus de notícias sistematicamente extraídas de 5 produtores de notícias e classificadas manualmente em relação à polaridade e entidade alvo. Técnicas de análise de sentimentos baseadas em aprendizado de máquina foram validadas utilizando o corpus criado. Criou-se uma metodologia para identificação de viés, utilizando o conceito de outliers, a partir de métricas indicadoras. A partir da metodologia proposta, foi analisado o viés em relação aos candidatos ao governo de São Paulo e à presidência a partir do corpus criado, em que se identificou os três tipos de viés em dois produtores de notícias / The project described here proposes a model to study bias on newswire texts, related to political entities. Three types of bias are analysed: selection bias, which refers to the amount of times an entity is referenced by the media outlet; coverage bias, which assesses the amount of coverage given to an entity and, finally, the assertion bias, which analyses whether the news is a positive or negative report of an entity. To accomplish this, a corpus was systematically built by extracting news from 5 different newswires. These texts were manually classified according to their polarity alignment and associated entity. Sentiment Analysis techniques were applied and evaluated using the corpus. Based on the concept of outliers, a methodology for bias detection was created. Bias was analysed using the proposed methodology on the generated corpus for candidates to the government of the state of São Paulo and to presidency, being identified in two newswires for the three above-defined types

Energy has been at the top of the national and global political agenda along with other

Traditional asset pricing models such as Capital Asset Pricing Model (CAPM) and Discounted Cash Flow (DCF) have been used widely in academics and practice due to their simplicity and popularity. The CAPM is a prescriptive model that describes the relationship between a stock’s required return and risk relative to the movements in the market, while the DCF is a descriptive model that measures the realized rate of return on a stock based on the market price of the stock, which in turn incorporates investor perceptions about the stock and the market. In an ideal, efficient market where investors behave rationally, we should not see much of a difference between stock returns estimated from these two models. However, because investor perceptions affect the DCF estimate of returns, changes in investor confidence without accompanying changes in firm risk can affect the DCF estimate without changing the CAPM estimate. High growth firm returns are more likely to incorporate changes in investor perception because more of their value is generated from realization of future growth opportunities. In this research, I study whether investor sentiment affects the DCF estimate of stock return more than the CAPM estimate, and whether this impact is more pronounced for high growth firms. I find results consistent with this hypothesis. I find that investor sentiment causes a divergence between the CAPM and DCF estimates of stock returns, and this divergence is higher for high growth firms compared to low growth firms. My findings suggest that high growth firm stock prices are more prone to distortions due to hype or investor pessimism.

Anti-immigrant sentiment particularly against Mexicans in the United States has had a dramatic influence on the lives of immigrants and on how they perceive the host society. Today, little research has addressed the extent to which this enmity has affected the mental-well being of immigrants. Based on 30 in-depth interviews in Houston this study investigates the degree to which nativism contributes to depression among Mexican-origin immigrant women. The findings reveal that undocumented status was salient and contributed to symptoms of depression. Additionally, my respondents revealed perceptions of intra-ethnic conflict among Mexican Americans. This thesis further explores how segmented assimilation theory can be expanded to better understand the complexities and nuances that Mexican immigrant women endure taking into consideration immigration status, racial/ethnic identity, and the structural barriers which plays a major role in their integration and mental health well-being.

The objective of this study is to discover the non-linear effect of market sentiment to characteristic factor returns. We run ¡¥Quantile Regression¡¦ to help us extract useful information and design an effective strategy. Based on the quantitative investment method, using the platform of Multi-Factor Model (MFM), we attempt to construct a portfolio and enhance portfolio performance. If the market-sentiment variable increases performance, we could conclude that some characteristic factors in a high sentiment period will perform better or worse in the next period. What is the market or investor sentiment? It is still a problem in the finance field. There is no co-definition or consensus so far. We do our best to collect the indirect data, such as transaction data, price and volume data, and some indicators in other studies, VIX, put/call ratio and so on. Then, we test the proxy variables independently, and obtain some interesting results. The market turnover, the ratio of margin lending on funds/ margin lending on securities, and the growth rate of consumer confidence index have significant effects on some of the characteristic factors. This holds that some market sentiment variables could influence stocks with certain characteristics, and the factor timing approach could improve portfolio performance under examination by information ratio.