nÃo hà / O objetivo do presente estudo visou investigar possÃveis impactos provenientes da crise financeira de 2008 nas aÃÃes das instituiÃÃes financeiras brasileira. Logo apÃs duas dÃcadas de instabilidade, planos econÃmicos malsucedidos e ciclos de crescimento pouco consistentes, chegou-se finalmente, apesar de alguns problemas, diante de um conjunto concreto de oportunidades para avanÃar significativamente no mercado financeiro. O Brasil assegurou diante do mundo um nÃvel de excepcional desempenho no setor financeiro, com instituiÃÃes financeiras que se projetaram como modelos de excelÃncia nos mais diversos segmentos de atuaÃÃo. Com esta finalidade, foram utilizadas algumas mÃtricas estatÃsticas descritivas agregadas Ãs diversas formas de risco e de performance das distribuiÃÃes de retorno lÃquido nominal diÃrio das aÃÃes das empresas que compÃem setor analisado, com periodicidade semestral de 2005 a 2010. Utilizou-se como benchmark o IBOVESPA. Possivelmente em funÃÃo de alguns fatores como, a forte contraÃÃo do crÃdito, o nÃvel de desconfianÃa dos investidores nos sistemas financeiros e diminuiÃÃo da demanda externa pelos produtos brasileiros, fizeram com que os retornos diÃrios das aÃÃes das empresas individuais, assim como o retorno do Ãndice de mercado IBOVESPA, reagissem à crise com perdas acumuladas expressivas. A direÃÃo da variaÃÃo e o valor das aÃÃes foram previstos pelo arcabouÃo microfundamentado dado pelo Capital Asset Pricing Model (CAPM). No perÃodo pÃs-crise, o setor reagiu e demonstrou uma significativa recuperaÃÃo prevista pelos fundamentos e os retornos das aÃÃes das instituiÃÃes superaram o Ãndice de mercado. Ao mesmo tempo as anÃlises estatÃsticas foram favorÃveis ao setor financeiro, apresentando menor desvio padrÃo e boa performance dos Ãndices de Sharpe, Sortino, Treynor e Calmar. Com a utilizaÃÃo do CAPM, e das regressÃes computacionais estimadas, testando os retornos das aÃÃes das instituiÃÃes financeiras analisadas, o estudo demonstrou que as aÃÃes acompanharam as movimentaÃÃes do mercado, variando positivamente o que deveria e desvalorizando quando os fundamentos sinalizavam que deveriam, mostrando-se de acordo com a teoria de precificaÃÃo de ativos. / The aim of this study was to investigate possible impacts from the 2008 financial crisis in the actions of the Brazilian financial institutions. Soon after two decades of instability, economic plans and unsuccessful cycles of growth inconsistent, it was finally, despite some problems, before a concrete set of opportunities to advance significantly in the financial market. Brazil is assured before the world an exceptional level of performance in the financial sector, with financial institutions that are designed as models of excellence in various segments. For this purpose, we used some descriptive statistics aggregated metrics to the various forms of risk and performance of the distributions of nominal daily net return of the stocks of companies that comprise the sector analyzed, every six months from 2005 to 2010. Was used as the benchmark Bovespa Index. Possibly due to such factors as the sharp contraction of credit, the level of distrust of investors in financial systems and reduced foreign demand for Brazilian products, made daily stock returns of individual companies, as well as the return of the index IBOVESPA market, react to the crisis with significant accumulated losses. The direction of change and shareholder value have been provided by microfundamentado framework given by the Capital Asset Pricing Model (CAPM). In the post-crisis period, the industry reacted and demonstrated a significant recovery predicted by fundamentals and stock returns of institutions exceeded the market index. While statistical analyzes were favorable to the financial sector, with lower standard deviation and good performance of the Sharpe ratios, Sortino, Treynor and Calmar. Using the CAPM, and the computational estimated regressions, testing the stock returns of financial institutions analyzed, the study demonstrated that accompanied the stock market movements, which should vary positively and devaluing the fundamentals signaled when they should, showing in accordance with the theory of asset pricing.

Made available in DSpace on 2016-03-15T19:32:58Z (GMT). No. of bitstreams: 1 Peterson Nery Laurindo.pdf: 808755 bytes, checksum: 117488f1a33020cd6cedb85678dc027d (MD5) Previous issue date: 2010-02-11 / Fundo Mackenzie de Pesquisa / This research aimed to test empirically the efficiency of the Brazilian stock market represented by the São Paulo Stock Exchange portfolio - São Paulo Stock exchange in a global crisis period, performed the announcements dates of the events that are the ITR's - the quarterly financial statements of the first quarter of 2008 until as the second quarter of 2009, made by event study s methodology representing better the semi-strong efficiency, it verified if had significant alterations in the stock prices, had been measured by the AR abnormal return, caused by the event announcement, where the AR significance was measured by the sign test, and its expected return measured by the CAPM Capital Asset Pricing Model. Therefore, the empirical test lead the conclusion the announcements had caused significant alterations in the stock prices, given the CAR - accumulated average abnormal returns behavior, had reacted as the expected one, then the CAR had reacted in compliance with of the good news classifications where represented 20% of the net profits increase of the company in relation the same period of the previous year, and for the bad news 20% net profits decrease, and for the classification of no news the companies that they had had the net profits nor over and nor below of 20% deviation. Thus the CAR sign test got the statistical of -3,27, out of the critical value of 1,64 to -1,64 of the normal distribution, indicating the Brazilian stock market adjusts the stock prices around the quarterly financial statements in global period of crisis, also indicating the semi-strong form of the efficient market hypothesis. / Esta pesquisa visou testar empiricamente a eficiência do mercado acionário brasileiro representado pela carteira da Bovespa Bolsa de Valores de São Paulo em um período de crise, compreendido entre as datas dos anúncios dos eventos que são os ITR s - as demonstrações financeiras trimestrais do primeiro trimestre de 2008 até o segundo trimestre de 2009, viabilizado pela metodologia do estudo de eventos que melhor representa a eficiência semiforte, e que verificou se houve alterações significantes nos preços das ações, medidos pelo AR retorno anormal, causados pelo anúncio do evento, onde a significância do AR foi medida pelo teste dos sinais e seu retorno esperado medido pelo CAPM modelo de precificação de ativos. Portanto, de acordo com o teste empírico entende-se que os anúncios causaram alterações significantes nos preços das ações, dado o comportamento dos CAR retornos anormais acumulados médios, reagindo conforme o esperado. Desta forma, os CAR reagiram em conformidade com as classificações de notícias boas que representou 20% de aumento do lucro líquido da empresa em relação ao mesmo período do ano anterior, para as notícias ruins 20% de diminuição no lucro líquido, e para a classificação de sem notícias as empresas que tiveram o lucro líquido nem acima e nem abaixo de 20% de variação. Assim, o teste dos sinais do CAR obteve estatística de -3,27, fora do valor crítico de 1,64 a -1,64 da tabela de distribuição normal, indicando que o mercado acionário brasileiro ajusta os preços das ações ao redor das demonstrações financeiras trimestrais mesmo em período de crise, indicando também a forma semiforte da hipótese do mercado eficiente.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-06-28T19:37:30Z No. of bitstreams: 1 christianjonnatanjacobsensotoherrera.pdf: 883027 bytes, checksum: 3ee1cf348a7392e28d4ef150125ad72c (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-08-07T21:48:11Z (GMT) No. of bitstreams: 1 christianjonnatanjacobsensotoherrera.pdf: 883027 bytes, checksum: 3ee1cf348a7392e28d4ef150125ad72c (MD5) / Made available in DSpace on 2017-08-07T21:48:11Z (GMT). No. of bitstreams: 1 christianjonnatanjacobsensotoherrera.pdf: 883027 bytes, checksum: 3ee1cf348a7392e28d4ef150125ad72c (MD5) Previous issue date: 2017-03-01 / Esta dissertação propõe testar empiricamente, através de otimizações in sample, os modelos de downside risk, Sortino, Upside Pontential Ratio, Omega e Kappa, comparado-os com o tradicional CAPM, derivado a partir da fronteira de média e variância, utilizando as ações listadas no Ibovespa e Dow Jones (DJIA) para construção de carteiras de mercado para cada um dos modelos. Estas duas classes de modelos distinguem-se quanto aos pressupostos e à mensuração do risco. Enquanto o CAPM considera apenas os dois primeiros momentos da distribuição de retornos, as outras medidas levam em conta os momentos superiores. Através da distância Hansen-Jagannathan, que mede o erro de mensuração do Stochastic Discount Factor (SDF) gerado pelos modelos, observou-se grande distinção dos modelos nos dois mercados. Enquanto o CAPM performou melhor no Dow Jones, os modelos de downside risk apresentaram melhores resultados para o Ibovespa, sugerindo vantagem na utilização destes modelos em mercados com menor liquidez e maior assimetria. / This dissertation proposes empirically test the downside risk models, Sortino, Upside Pontential Ratio, Omega and Kappa, by comparing them with the traditional CAPM, derived from the mean and variance boundary, using the listed shares in the Ibovespa and Dow Jones (DJIA) for the construction of market portfolios for each of the models. These two classes of models are distinguished in terms of assumptions and risk measurement. While the CAPM considers only the first two moments of the returns distribution, the other measures take into account the higher moments of such distributions. The Hansen-Jagannathan distance, which measures the Stochastic Discount Factor (SDF) measurement error generated by the models, showed a great distinction of the models in the two markets. While the CAPM performed better in the Dow Jones, the downside risk models presented better results for the Ibovespa, suggesting an advantage in the use of such models in markets with lower liquidity and greater asymmetry.

The thesis investigates relationship between daily stock return volatility of Dow Jones Industrial Average stocks and data obtained on Twitter, the social media network. The Twitter data set contains a number of tweets, categorized according to their polarity, i.e. positive, negative and neutral sentiment of tweets. We construct two classes of models, GARCH and ARFIMA, where for either of them we research basic model setting and setting with additional Twitter variables. Our goal is to compare, which of them predicts the one day ahead volatility most precisely. Besides, we provide commentary regarding the effects of Twitter volume variables on future stock volatility. The analysis has revealed that the best performing model, given the length and structure of our data set, is the ARFIMA model augmented on Twitter volume residuals. In the context of the thesis, Twitter volume residuals represent unexpected activity on the social media network and are obtained as residuals from Twitter volume autoregression. Plain ARFIMA model was the second best and plain volume augmented ARFIMA was in third place. This means that all three ARFIMA models outperformed all three GARCH models in our research. Regarding the Twitter estimation parameters, we found that higher the activity the higher tomorrow's stock...

This paper examines the capital - asset pricing model (CAPM) which has been extended with a factor for geo-political risk. I use monthly stock return data for all stocks listed on a major US exchange from January 1990 to December 2016 and utilize a Fama-Macbeth Regression with Newey-West standard errors to test the geo-political augmented Sharpe-Lintner CAPM. The paper first determines if increased sensitivity to geopolitical risk lead s to lower average returns and second assesses if geo-political risk as an explanatory variable is a significant enough to expose a failure of the CAPM to capture expected returns fully through beta. The results of our regressions do not confirm the hypothesis that firms with high sensitivities to geo-political risk have expressly different returns in the long run. Furthermore, our Fama-Macbeth regression does not find expressly significant average slopes for geo-political risk as a variable.

Cognitive Limitations and Behavioral Biases In The Asset Pricing Context MAER Thesis Asbtract Giorgi Chavchanidze I incorporate behavioral and bounded rationality elements into a single asset-pricing frame- work by setting up a two-period consumption-based portfolio selection problem in which a representative agent has biased priors, does not observe the current state and thus has in- complete information about future state probabilities. He forms posterior beliefs using signals that he selects according to the rational inattention discrete choice framework of Matějka and McKay (2015), where the precision of the beliefs depend intuitively on the priors and the cost of information λ. In the case of log-utility, the optimal portfolio is a convex combination of the N portfolios the investor would have selected in each of the N states if they were fully observable, where the weights reflect the subjective posterior likelihood of time-zero states. The posterior beliefs are induced by parsimonious reweighing of priors, where the weights depend on λ, discount factor β and the relative entropies of the future state distributions induced by different time-zero states. Using a two-state example, I demonstrate how the cost of information and biases can be jointly analyzed in this framework and discuss implied...

Volatility-managed portfolios offer mixed returns in an international setting based on ex-ante information. The results of this paper further strengthen the theory that the variability of excess returns from volatility-management are more dependent on underlying investor strategy rather than differences of global markets. We find that momentum strategies, as measured by the winners-minus-losers, are universally (except Japan) benefitted from volatility-management with an excess return between 6.96% and 14.28% annually across different regions/cross-sections garnered by the managed portfolio controlled against the Fama and French (2015) five-factor model. Value and profitability factors show mixed results with the beneficial performance in about half of the examined regions respectively. We prove that these relationships are robust through periods of market-wide crashes (Dotcom-bubble and financial crises of 2007/2008), tighter leverage constraints (≤1, ≤1.5) show however that the excess returns are dampened, concluding that access to leverage is a fundamental aspect of employing volatility-management to most portfolios. The results of this research paper expand previous literature of volatility-management by broadening the strategy to global markets.

The point of this thesis is to compare classic asset pricing models using historic UK data. It looks at three of the most commonly used asset pricing models in Finance and tests the suitability of each for the UK market. The models considered are the Capital Asset Pricing Model (1964, 65 and 66) (CAPM), the Fama-French 3-Factor Model (1993) (FF3F) and the Carhart 4-Factor Model (1997) (C4F). The models are analysed using a 34 year sample period (1980-2014). The sample data follows the structure explained in Gregory et al (2013) and is compiled of stocks from the London Stock Exchange (LSE). The stocks are grouped into portfolios arranged by market capitalisation, book-to-market ratio, past 2-12 month stock return and past 12 month standard deviation of stock return. Statistical analysis is performed and the suitability of the models is tested using the methods of Black, Jensen \& Scholes (1972), Fama \& MacBeth (1973) and Gibbons, Ross \& Shanken (1989). The results compare descriptive and test statistics across the range of risk factors and test portfolios for the each testing method on all three models. They show that although the UK market has some noticeable factor anomalies, none of the models clearly explains the 1980-2014 stock returns. However, of the three models, C4F shows the highest explanatory power in predicting stock returns.

This research assessed market efficiency, volatility behaviour, asset pricing, and oil price risk exposure of the oil and gas companies quoted on the London Stock Exchange with the aim of providing fresh evidence on the pricing dynamics in this sector. In market efficiency analysis, efficient market hypothesis (EMH) and random walk hypothesis were tested using a mix of statistical tools such as Autocorrelation Function, Ljung-Box Q-Statistics, Runs Test, Variance Ratio Test, and BDS test for independence. To confirm the results from these parametric and non-parametric tools, technical trading and filter rules, and moving average based rules were also employed to assess the possibility of making abnormal profit from the stocks under study. In seasonality analysis, stock returns were tested for the day-of-the-week and month-of-the-year effects. Volatility processes, estimation, and forecasting were undertaken using both asymmetric and symmetric volatility models such as GARCH (1,1) and Threshold ARCH or TARCH (1,1,1) to investigate the volatility behaviour of stock returns. To determine the effect of an exogenous variable on volatility, Brent crude oil price was used in the models formulated as a variance regressor for the assessment of its impact on volatility. The models were then used to forecast the price volatility taking note of the forecasting errors for the determination of the most effective forecasting model. International oil price risk exposure of the oil and gas sector was measured using a multi-factor asset pricing model similar to that developed by Fama and French (1993). Factors used in the asset pricing model are assessed for statistical significance and relevance in the pricing of oil and gas stocks. Data used in the study were mainly the adjusted daily closing prices of oil and gas companies quoted on the exchange. Five indices of FTSE All Share, FTSE 100, FTSE UK Oil and Gas, FTSE UK Oil and Gas Producers, and FTSE AIM SS Oil and Gas were also included in the analysis. Our findings suggest that technical trading rules cannot be used to gain abnormal returns, which could be regarded as a sign for weak form market efficiency. The results from seasonality analysis have not shown any day-of-the-week or monthly effect in stock returns. The pattern of stock returns’ volatility can be estimated and forecasted, although the relationship between risk and return cannot be generalised. On a similar note, the relationship between volatility attributes and the efficient market hypothesis cannot be clearly established. However, we have established that volatility modelling can significantly measure the quantum of risk in the oil and gas sector. Market risk, oil price risk, size and book-to-market related factors in asset pricing models were found to be relevant in the determination of asset prices of the oil and gas companies.

This dissertation describes the development and empirical testing of strategic asset pricing theory (STRAPT). This explains the processes by which investors form ideas and judgments about a given firm‘s competitive strategy, and their ultimate belief about the impact these strategies will have on the firm‘s future stock price. My model explicitly accounts for information investors associate with dimensions of a firm‘s pattern of competitive actions, how investors process and interpret this information, and how they form opinions about the relationship between competitive strategy and future value of the firm‘s equity shares. Thus, by accounting for observed competitive behavior, my model stands in stark contrast to asset pricing theory – which asserts that financial markets are efficient and all investors rational – and instead sides with Hirshleifer (2001) who contends some investors form biases, and that the next stage of asset pricing theory is to look at how investors form opinions about stocks. Drawing from some unique theoretical areas: information perception/salience, information processing, social judgment, and decision making, my dissertation develops a conceptual model of this process by which long-buyers and short-sellers view and react to patterns of competitive actions carried out among rivals. My findings about how long-buyers regard between-firm ―differences‖ in the pattern of competitive actions the firm carries out over time, or strategic heterogeneity, are generally supportive of Miller and Chen (1996), who posited that distinctive processes such as heterogeneous strategies may decrease the ―legitimacy‖ of the firm. They exhibit a negative relationship with stock returns. Due to a different decision-making process, short-sellers come to different conclusions. Strategic heterogeneity exhibits a U-shaped relationship with short interest. My findings pertaining to how long-buyers value the number of strategic moves carried out by a firm generally support Young, Smith, and Grimm (1996) and Ferrier (2001). Specifically, I demonstrate that these investors value exposure to a firm, and this translates into positive stock market returns. Short-sellers, on the other hand, see the value of a large number of strategic actions only to an extent. Through their systematic analysis, they subscribe to the Porter (1980) and Shamsie (1990) viewpoint that more is not always better. This results in a U-shaped relationship with short interest.