Submitted by Sara Ribeiro (sara.ribeiro@ucb.br) on 2017-06-12T14:43:29Z No. of bitstreams: 1 LilianSantosMarquesSeverinoDissertacao2016.pdf: 852227 bytes, checksum: a6811612b93a51167387d223e191b16c (MD5) / Approved for entry into archive by Sara Ribeiro (sara.ribeiro@ucb.br) on 2017-06-12T14:43:48Z (GMT) No. of bitstreams: 1 LilianSantosMarquesSeverinoDissertacao2016.pdf: 852227 bytes, checksum: a6811612b93a51167387d223e191b16c (MD5) / Made available in DSpace on 2017-06-12T14:43:48Z (GMT). No. of bitstreams: 1 LilianSantosMarquesSeverinoDissertacao2016.pdf: 852227 bytes, checksum: a6811612b93a51167387d223e191b16c (MD5) Previous issue date: 2016-12-16 / This study aims to analyze the behavior of the real estate market in the Brazilian cities of S??o Paulo and Rio de Janeiro from 2008 to 2016 as seen through the analysis of monthly pricing data for both sales and rental markets, apparent consumption, stock of properties, and market return (IBOVESPA). Two models were estimated, the first, the CAPM, aimed at analyzing how return from investment in housing in both cities compared to the market return (IBOVESPA). The second model, the CCAPM was modified to suit the presence of preference for ownership of property. This study concludes that regarding the change-over of the return rates in Rio de Janeiro and S??o Paulo, investment in the housing market in both cities is negatively affected by the change-over of the return in investments on the whole stock market. Moreover, when we include the consumption in the pricing model, there is an intertemporal discount factor for consumption of roughly 0,98 per month for both cities, which confirms that Brazilian real estate buyers are more impatient than their American counterparts, and that the percentage of their income spent on consumption and investment in housing varies from one city to another. / O presente trabalho trata do comportamento do mercado imobili??rio nas cidades de S??o Paulo e Rio de Janeiro no per??odo de 2008 a 2016, analisando dados mensais de pre??os de venda e de aluguel de im??veis, consumo aparente, estoque de im??veis e taxa de retorno de mercado (IBOVESPA). Foram estimados dois modelos, o primeiro, o CAPM, visou analisar o comportamento do retorno do investimento imobili??rio das duas localidades em rela????o ao retorno de mercado e o segundo modelo, o CCAPM modificado para exist??ncia de prefer??ncias pela propriedade de im??veis. O estudo conclui, em rela????o ??s taxas de retorno, que a varia????o do investimento no mercado imobili??rio, tanto no Rio de Janeiro quanto em S??o Paulo, ?? afetada de forma negativa pela varia????o do retorno de mercado. Al??m disso, quando inclui o consumo no modelo de precifica????o, observa-se um fator de desconto intertemporal do consumo em torno de 0,98 ao m??s para as duas cidades, confirmando que o consumidor brasileiro ?? mais impaciente que o americano, e que os percentuais da sua renda destinada ao consumo e ao investimento imobili??rio diferem de uma cidade para a outra.

Die Wahl risikoadäquater Kapitalkosten ist Voraussetzung für eine Investitionsentscheidung im Interesse der Investoren. In der Energiewirtschaft wird die Ermittlung der Eigenkapitalkosten mit Hilfe des Capital Asset Pricing Models (CAPM) infolge fehlender Kapitalmarktdaten für Investitionen in regenerative Energien sowie durch die Existenz neuer Marktakteure mit eingeschränkter Risikostreuung allerdings mehr und mehr erschwert. Der vorliegende Beitrag beschreibt ein Forschungsvorhaben zur Entwicklung eines modellbasierten Ansatzes, der die veränderten Bedingungen durch den Wandel in der Energiewirtschaft aufgreifen und damit verbundene Problemfelder lösen soll.

The most widely used Cost of Capital model is the Capital Asset Pricing Model. The Beta, Which is a key input into the model has proven to be unreliable and provides no correlation with systematic risk. As risk increases, so should the cost of capital of the firm. The Beta is a historic measure of risk and does not capture the future outlook of risk. The future of an organisation and its risk may look very different to the past and therefore the need to calculate the Cost of Capital of a firm based on the future outlook of the firm. The aim of this research was to analyse the different methodologies used to determine the Cost of Capital of a firm in order to determine which models are better ex ante predictor of Cost of Capital in the South African context. Regression analysis was used to make statistical inferences between the measure of risk used and the Cost of Capital model in question. The results of the research has shown that Market Capitalisation and Price to Book ratio are the best proxies for risk when comparing it with the ex ante Cost of Capital models. However, the Three Factor Pricing Model is shown to be the best Cost of Capital model to capture the future outlook of risk. / Dissertation (MBA)--University of Pretoria, 2010. / Gordon Institute of Business Science (GIBS) / unrestricted

Made available in DSpace on 2016-03-15T19:26:28Z (GMT). No. of bitstreams: 1 Jose Matias Filho.pdf: 472539 bytes, checksum: b16566d14af94e4d158e78a2ec6bb9b3 (MD5) Previous issue date: 2006-04-11 / Innumerous studies have being searching to measure the risk component involved in the expected return for capital investments, remarking decades of hard work of many relevant Financial Theory authors worldwide, while being a common activity between analysts of financial institutions and other parts of the market. The object of this work is to contribute to this search, through the evaluation of alternative methodologies to calculate the CAPM (Capital Asset Pricing Model) when submitted to the Brazilian Stock Market conditions, through the application of four methodologies to determine the Beta, three methodologies to calculate the CAPM and eight distinct macroeconomics scenarios. The purpose is to determine equal relations between a group of distinct expected returns obtained and the effective behavior of the asset returns studied in many periods of measurement. It was used the statistic method known as test for differences in two means to compare many series of expected returns obtained and their respective effective returns, getting results that suggests the use of some methodologies and scenarios as valid tools to predict future returns to some financial assets of our market. / Inúmeros estudos têm sido feitos procurando mensurar o componente de risco envolvido no retorno esperado em investimentos de capital, cuja busca já remonta várias décadas e tem tido o envolvimento dos principais autores mundiais em teoria financeira, além de ser atividade obrigatória nas mesas de operações das instituições financeiras e demais participantes do mercado. O objetivo deste trabalho é de contribuir com essa busca, através da avaliação de metodologias alternativas de cálculo do CAPM (Capital Asset Pricing Model) quando submetidas às condições do mercado de ações brasileiro, através da aplicação de quatro metodologias de determinação do índice beta e três metodologias de cálculo do CAPM diferentes, em 8 cenários macro-econômicos distintos. Busca-se dessa forma determinar relações de igualdade entre o conjunto dos diversos retornos esperados obtidos e o efetivo comportamento de retornos dos ativos estudados em períodos diversos de medição. Foi utilizado o método estatístico conhecido como Teste de Hipóteses de Diferença de Médias para comparar as diversas séries de retornos esperados obtidos com os respectivos retornos efetivos, obtendo resultados que sugerem a indicação de algumas metodologias e cenários como ferramentas válidas na predição de retornos futuros de alguns ativos financeiros de nosso mercado.

A valid and accurate capital asset pricing model (CAPM) may help investors and mutual funds managers in determining expected returns and thus, may increase profits which can be reflected on the community resources. The problem is that the traditional CAPM does not accurately predict the expected rate of return. A more accurate model is needed to help investors in determining the intrinsic price of the financial asset they want to sell or buy. The purpose of this study was to examine the validity of the single-factor CAPM and then develop and test the validity of a multifactor CAPM in the Jordanian stock market. The study was informed by the modern portfolio theory and specifically by the single-factor CAPM developed by Sharpe, Lintner, and Mossin. The research questions for the study examined the factors that may explain the variation in the expected rate of return on stocks in the Jordanian stock market and the relationship between the expected rate of return and factors of market return, company size, financial leverage, and operating leverage. A causal-comparative quantitative research design was employed to achieve the purpose of the study by testing the listed companies on the Amman stock exchange (ASE) for the period from 2000 to 2015. Data were collected from the ASE database and analyzed using the multiple regression model and t test. The results revealed that market return, company size, and financial leverage are not predictors of the expected rate of return while operating leverage is a predictor. The results of this study may contribute to positive social change by changing the way the individual investors and mutual funds managers select their investing portfolios which can lead to better resource distribution in the economy.

Die Wahl risikoadäquater Kapitalkosten ist Voraussetzung für eine Investitionsentscheidung im Interesse der Investoren. In der Energiewirtschaft wird die Ermittlung der Eigenkapitalkosten mit Hilfe des Capital Asset Pricing Models (CAPM) infolge fehlender Kapitalmarktdaten für Investitionen in regenerative Energien sowie durch die Existenz neuer Marktakteure mit eingeschränkter Risikostreuung allerdings mehr und mehr erschwert. Der vorliegende Beitrag beschreibt ein Forschungsvorhaben zur Entwicklung eines modellbasierten Ansatzes, der die veränderten Bedingungen durch den Wandel in der Energiewirtschaft aufgreifen und damit verbundene Problemfelder lösen soll.

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.

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...

Thoroughbred racing is referred to as “the sport of Kings”, because historically it was a leisure activity of the upper-class. Thoroughbred breeding on the other hand has transformed from a hobby of the upper-class to a worldwide agricultural industry. With the deep involvement of the royal and rich in the Thoroughbred industry, the auction prices of horses are raised significantly at the top end of the market. Research in the biological sciences suggests there exits correlations between dam age, foal birthrank, and the racing performance of Thoroughbred horses. This study first investigates how the market values these biological factors and whether they are correlated with racehorses’ career earnings. We further test the impact of sire age as there is limited literature related to the subject. By using a Hedonic pricing model, results show that Thoroughbred buyers at Keeneland September Sale are willing to pay more for the yearlings at 1st, 2nd, and 3rd birthranks, yearlings out of younger mares age from 4 to 10, and yearlings by experienced sires age from 12 to 18. Results from multivariate regressions suggest negative correlations between foal birthrank, parent age and career earnings.