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No description available.

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Economia, Administração e Contabilidade e Gestão de Políticas Públicas, Programa de Pós-Graduação em Ciências Contábeis, 2017. / Submitted by Raquel Almeida (raquel.df13@gmail.com) on 2018-03-15T20:13:01Z No. of bitstreams: 1 2017_VanessaRodriguesdosSantosCardoso.pdf: 1204775 bytes, checksum: b3244b57ef40e149d2c2d5bba50d6d27 (MD5) / Approved for entry into archive by Raquel Viana (raquelviana@bce.unb.br) on 2018-04-24T20:13:04Z (GMT) No. of bitstreams: 1 2017_VanessaRodriguesdosSantosCardoso.pdf: 1204775 bytes, checksum: b3244b57ef40e149d2c2d5bba50d6d27 (MD5) / Made available in DSpace on 2018-04-24T20:13:04Z (GMT). No. of bitstreams: 1 2017_VanessaRodriguesdosSantosCardoso.pdf: 1204775 bytes, checksum: b3244b57ef40e149d2c2d5bba50d6d27 (MD5) Previous issue date: 2018-04-24 / Os modelos de precificação de ativos são utilizados por investidores como base para a tomada de decisões, pois estimam qual seria o seu retorno em função do risco que estão dispostos a tomar. Embora o CAPM seja o modelo mais utilizado, diversos autores defendem que o seu único fator de risco não captura anomalias existentes na precificação de ativos. Nos últimos anos tem sido crescente o interesse da academia por anomalias, de forma que em 2012 já existiam 313 delas na literatura. Este estudo objetivou investigar se os recentes modelos que consideram anomalias na precificação de ativos ajustam-se satisfatoriamente ao mercado acionário brasileiro. Como objetivo secundário, o estudo também verificou se modelos com anomalias eram superiores ao CAPM quando aplicado ao setor elétrico, pois o modelo é utilizado pela Agência Reguladora para estimar o retorno sobre o capital a ser pago aos investidores pelos consumidores de energia. Para tanto, os modelos de cinco fatores de Fama e French (2015), o de quatro fatores de Hou, Xue e Zhang (2014a) e outro alternativo com seis anomalias foram testados e comparados com o CAPM, por meio de regressões de séries temporais estimadas com dados contábeis e do mercado de ações no período de junho de 2010 a dezembro de 2016. Os resultados demostram que os três modelos com anomalias testados se ajustam satisfatoriamente à variação nos preços dos ativos no Brasil e no setor elétrico. Dentre eles, o de cinco fatores de Fama e French (2015) é superior em termos de poder explicativo no mercado acionário, enquanto o modelo alternativo se mostrou superior ao CAPM no setor elétrico. Especificamente quanto às anomalias, verifica-se que tamanho, valor, investimento, rentabilidade, momento, alavancagem operacional e fricções de mercado possuem relação estatisticamente significante com o retorno dos ativos no mercado brasileiro. Entretanto, os prêmios de risco dessas anomalias foram negativos e/ou estatisticamente não diferentes de zero, indicando que estratégias de investimentos baseadas nesse tipo de risco não foram recompensadas no Brasil no período analisado. / Asset pricing models are used by investors as a basis for decision-making because they estimate how much they would return based on the risk they are willing to take. Although CAPM is the most widely used model, several authors argue that its single risk factor does not capture existing anomalies in asset pricing. In recent years the interest of the academy on anomalies has increased, so that in 2012 313 of them have been already reported in the literature. This study aimed to investigate whether recent models that consider anomalies in asset pricing fits satisfactorily to the Brazilian stock market. As a secondary objective, the study also verified whether models with anomalies were superior to CAPM when applied to the electric sector, since the model is used by the Regulatory Agency to estimate the return on capital to be paid to investors by energy consumers. To do so, the Fama and French (2015) five-factor model, the Hou, Xue and Zhang (2014a) four-factor model and an six-factor alternative model were tested and compared with CAPM, using time series regressions estimated with accounting and stock market data from June 2010 to December 2016. The results showed that the three models with anomalies tested fit satisfactorily in explaining asset price movements in Brazil and its electric industry. Among them, the Fama and French (2015) five-factor is superior in terms of explanatory power in the stock market, while the alternative model proved to be superior to CAPM in the domestic electric industry. Specifically, regarding the anomalies, we find that size, value, investment, profitability, moment, operating leverage and market frictions have a statistically significant relation with asset returns in the Brazilian market. However, the risk premiums for these anomalies are negative and / or statistically nonzero, indicating that investment strategies based on this type of risk are not rewarded in the Brazilian market in the analyzed period.

In this paper, I examine the top ten historical upward and downward daily shocks in the Dow Jones Industrial Average, and test whether industry specific abnormal returns can be explained by industry specific leverage ratios on those days. I use modified versions of the Capital Asset Pricing Model and the Fama French 3 Factor regression to examine within-industry abnormal returns. I then proceed to rank the industry abnormal returns and industry leverage ratios, from high to low, on days corresponding to these large shocks. Finally, I examine the correlation between these ranks on the days corresponding to the large moves. The results show that on upward moving days, there is no relationship between industry abnormal returns and industry leverage. However, on downward moving days, there is moderate negative correlation between industry abnormal returns and leverage, suggesting that higher leverage leads to lower abnormal returns. This paper explains these results in further detail, and discusses the implications to the greater field of financial economics.

Med hjälp av årlig prisstatistik avseende försäljningar av skogsfastigheter (1995-2020) bedömer studien skogliga investeringars marknadsrisk samt estimerar dess diskonteringsränta. Analysen sker inom de teoretiska ramverken Capital Asset Pricing Theory (CAPM) samt Arbitrage Pricing Theory (APT). Utöver korrelation med marknaden analyseras ett antal riskfaktorer så som inflation, förändringar i bostadspriser, BNP samt förändringar i virkespriser. CAPM beräknas för olika löptider där den riskfria räntan matchas mot investeringens tidshorisont. Resultatet ligger i linje med tidigare forskning och visar att skogliga investeringar har en låg marknadsrisk och troligen kan ge ett skydd mot inflation. Val av korrekt löptid för den riskfria räntan har betydande effekt på den estimerade diskonteringsräntan.

The stock market have received a fair amount of attention in the media recently as a result of the ongoing covid-19 pandemic. The question arouse if there is one month in the year that outperforms all other months in the stock market. A well known anomaly in the world of finance referred to as, the January effect, came up to discussion. Earlier studies of this subject have achieved different results and conclusions. Therefore, this study aims to examine if the January effect exists on mid cap and large cap companies on the Swedish stock market. To achieve this, one large cap portfolio and one mid cap portfolio both equally weighted with ten companies each were created. These two portfolios were analyzed with, among others, a well known regression model for season anomalies. The results of this study concludes that the January effect does not exist in neither of the portfolios.