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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.

Anomalier ligger till grund för investeringsstrategier som används för att förvalta biljontals dollar. Anomalier frångår vedertagen teori som implicerar att abnormal avkastning inte är möjlig över tid. En anomali som bevisats ge långsiktig abnormal avkastning är lågriskanomalin. Det råder brist på studier som undersökt om lågriskanomalin existerar på den svenska aktiemarknaden. En studie inom ämnet är av praktisk relevans då resultaten kan ligga till grund för investeringsstrategier som genererar abnormal avkastning. Denna studies syfte är att undersöka om en lågriskanomali existerar på den svenska aktiemarknaden under tidsperioden 2008/01/07 - 2019/12/27. För studien används totalavkastningsdata för bolag noterade på Stockholmsbörsen. Studien skapar hedgeportföljer och undersöker genom regression av prissättningsmodellen CAPM om lågriskportföljer ger högre signifikant abnormal avkastning än högriskportföljer. Studien finner inga statistiskt säkerställda resultat för en lågriskanomali. Det antyder att lågriskanomalin inte existerar på den svenska aktiemarknaden och därför saknar praktisk relevans som investeringsstrategi på nämnda marknad.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第20350号 / 工博第4287号 / 新制||工||1664(附属図書館) / 京都大学大学院工学研究科都市社会工学専攻 / (主査)教授 小林 潔司, 教授 大津 宏康, 准教授 松島 格也 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

The random walk is a powerful model. Chemistry, Physics, and Finance are just a few of the disciplines that model with the random walk. It is clear from its varied uses that despite its simplicity, the simple random walk it very flexible. There is one major drawback, however, to the simple random walk and the geometric random walk. The limiting distribution is either normal, lognormal, or a levy process with infinite variance. This thesis introduces an new random walk aimed at overcoming this drawback. Because the simple random walk and the geometric random walk are special cases of the proposed walk, it is called a generalized random walk. Several properties of the generalized random walk are considered. First, the limiting distribution of the generalized random walk is shown to include a large class of distributions. Second and in conjunction with the first, the generalized random walk is compared to the geometric random walk. It is shown that when parametrized properly, the generalized random walk does converge to the lognormal distribution. Third, and perhaps most interesting, is one of the limiting properties of the generalized random walk. In the limit, generalized random walks are closely connected with a u function. The u function is the key link between generalized random walks and its difference equation. Last, we apply the generalized random walk to option pricing.

As previous researchers have discussed the paradigm of risk and return, this study also suggests illiquidity as a good proxy for risk. An illiquid asset, thus higher risk, should generate high return. As Amihud (2002) originally applies an illiquidity measure from daily return and turnover, this thesis elaborates on his average market illiquidity measure AILLIQ on assets of Nasdaq First North Growth Market. Over a five-year period returns are estimated using the CAPM together with the illiquidity proxy on Swedish growth assets. Results are in line with intuitive thoughts of a positive relationship between risk and return. The hypothesis of zero impact is rejected and concludes that illiquidity can have an impact on expected return.

The U.S. forest products industry has witnessed an unprecedented period of mergers and acquisitions in the last decades. The overall goal of this thesis is to examine the impact of these activities on the financial performance and market power of the U.S. forest products industry in the last several decades. The first part of this thesis evaluated the mergers by event study. The results revealed that the equity market reacted positively to these mergers; the position of a firm and the relative transaction size explained most of the variations of the cumulative abnormal returns; and the risk for most of the selected 14 acquiring firms had changed after the mergers. The second part examined the market power of the U.S. paper industry by the new empirical industrial organization approach. The results indicated that the oligopoly power remained significant at the 1% level over the whole sample period; whereas the oligopsony power had dropped dramatically and become insignificant at the 5% level in recent 30 years.