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.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Muitos estudos buscam tentar prever o retorno potencial sobre portfólios de ações, com intuito de obter melhor rentabilidade sobre o capital aplicado. Diversas modelagens já foram utilizadas, sendo que as mais conhecidas são as que relacionam o risco com o retorno. Nesta linha destacam-se a Teoria de Carteiras proposta por Markowitz, e o CAPM de Sharpe. Através destas teorias entende-se a questão da influência da covariância dos retornos e que para um melhor desempenho de uma carteira, não é suficiente avaliar cada ativo individualmente. Por outro lado, diversas críticas em relação ao CAPM, vêm ensejando estudos complementares na busca de outras variáveis que melhorem os métodos de seleção de ativos. Fama e French (1993) fizeram um estudo com variáveis complementares em relação ao beta do CAPM, utilizando o tamanho e a relação Book to Market, conseguindo resultados melhores que o CAPM tradicional. O presente estudo leva em conta a questão do reinvestimento do lucro gerado e utilizando o modelo de Gordon propõe uma variável de classificação de empresas de crescimento e empresas valor, conceito já utilizado na literatura de finanças.Com base nesta variável montam-se carteiras de ações entre os anos de 2005 e 2012 e observa-se que é possível obter ganhos com a lógica proposta. Ao longo do período seria possível obter com as carteiras selecionadas ganhos de até 107,85% contra os retornos de 55,58% das carteiras com todos os ativos. Organizamos os mesmos ativos pela ótica da relação Book to Market as quais obtiveram retorno total do período de 90,42%. Apesar de notar uma mudança clara de comportamento, onde apenas nos quatro primeiros anos do estudo as carteiras com empresas value são superiores e nos quatro últimos períodos as carteiras de empresas growth são as melhores. Estes resultados são compatíveis com os resultados de Braga e Leal (2000), e Mescolin, Martinelli Braga e da Costa Jr. (1997), verificando um melhor desempenho para as empresas value. / Many studies have tried to predict the potential return on stock portfolios, aiming to get better return on invested capital. Several modeling have been used, and the more popular are those that relate the risk with the return. In this area, stand out the Portfolio Theory proposed by Markowitz and the CAPM proposed by Sharpe. Through these theories can be understood the influence of the covariance of returns, and for a best performance of a portfolio, is not enough to assess each individual asset. On the other hand, many criticism of the CAPM, have generating additional studies in search of other variables to improve the methods of selection of assets. Fama and French (1993) conducted a study with additional variables in relation to the CAPM beta, using the size and the relationship Book to Market, achieving better results than the traditional CAPM. This study considers the issue of the generated profit reinvestment, and using the model of Gordon proposes a classification variable for growth companies and value companies, which are concepts already used in finance literature. Based on this variable are set up stock portfolios between the years 2005 and 2012 and it is observed that it is possible to get earnings with the logic proposed. Over the period could be obtained with the selected portfolios up to 107.85% gains against the returns of 55.58% of the complete portfolio with all assets. We organize the same stocks from the perspective of the relationship Book to Market which had a total return of 90.42% on the whole period. Although observed a clear change of behavior, where only the first four years of the study portfolios with value companies are superior and the last four years portfolios of growth companies are the best. These results are consistent with the results of Braga and Leal (2000), and Mescolin Martinelli Braga and Costa Jr. (1997), watching a better performance for value companies.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Muitos estudos buscam tentar prever o retorno potencial sobre portfólios de ações, com intuito de obter melhor rentabilidade sobre o capital aplicado. Diversas modelagens já foram utilizadas, sendo que as mais conhecidas são as que relacionam o risco com o retorno. Nesta linha destacam-se a Teoria de Carteiras proposta por Markowitz, e o CAPM de Sharpe. Através destas teorias entende-se a questão da influência da covariância dos retornos e que para um melhor desempenho de uma carteira, não é suficiente avaliar cada ativo individualmente. Por outro lado, diversas críticas em relação ao CAPM, vêm ensejando estudos complementares na busca de outras variáveis que melhorem os métodos de seleção de ativos. Fama e French (1993) fizeram um estudo com variáveis complementares em relação ao beta do CAPM, utilizando o tamanho e a relação Book to Market, conseguindo resultados melhores que o CAPM tradicional. O presente estudo leva em conta a questão do reinvestimento do lucro gerado e utilizando o modelo de Gordon propõe uma variável de classificação de empresas de crescimento e empresas valor, conceito já utilizado na literatura de finanças.Com base nesta variável montam-se carteiras de ações entre os anos de 2005 e 2012 e observa-se que é possível obter ganhos com a lógica proposta. Ao longo do período seria possível obter com as carteiras selecionadas ganhos de até 107,85% contra os retornos de 55,58% das carteiras com todos os ativos. Organizamos os mesmos ativos pela ótica da relação Book to Market as quais obtiveram retorno total do período de 90,42%. Apesar de notar uma mudança clara de comportamento, onde apenas nos quatro primeiros anos do estudo as carteiras com empresas value são superiores e nos quatro últimos períodos as carteiras de empresas growth são as melhores. Estes resultados são compatíveis com os resultados de Braga e Leal (2000), e Mescolin, Martinelli Braga e da Costa Jr. (1997), verificando um melhor desempenho para as empresas value. / Many studies have tried to predict the potential return on stock portfolios, aiming to get better return on invested capital. Several modeling have been used, and the more popular are those that relate the risk with the return. In this area, stand out the Portfolio Theory proposed by Markowitz and the CAPM proposed by Sharpe. Through these theories can be understood the influence of the covariance of returns, and for a best performance of a portfolio, is not enough to assess each individual asset. On the other hand, many criticism of the CAPM, have generating additional studies in search of other variables to improve the methods of selection of assets. Fama and French (1993) conducted a study with additional variables in relation to the CAPM beta, using the size and the relationship Book to Market, achieving better results than the traditional CAPM. This study considers the issue of the generated profit reinvestment, and using the model of Gordon proposes a classification variable for growth companies and value companies, which are concepts already used in finance literature. Based on this variable are set up stock portfolios between the years 2005 and 2012 and it is observed that it is possible to get earnings with the logic proposed. Over the period could be obtained with the selected portfolios up to 107.85% gains against the returns of 55.58% of the complete portfolio with all assets. We organize the same stocks from the perspective of the relationship Book to Market which had a total return of 90.42% on the whole period. Although observed a clear change of behavior, where only the first four years of the study portfolios with value companies are superior and the last four years portfolios of growth companies are the best. These results are consistent with the results of Braga and Leal (2000), and Mescolin Martinelli Braga and Costa Jr. (1997), watching a better performance for value companies.