[pt] Esta tese é composta por dois ensaios sobre finanças empíricas. O primeiro se concentra nos mercados de câmbio e apresenta medidas de mudanças na inclinação da estrutura de curto prazo das taxas de juros para os EUA e outros países de G10, usando contratos de futuros de 3 e 6 meses. Essas mudanças na inclinação têm impacto imediato nos retornos da moeda e também forte efeito retardado nas semanas seguintes, o que implica que as moedas são previsíveis tanto dentro quanto fora da amostra. Os investidores que condicionam na inclinação para negociar taticamente uma carteira comprada em moedas G10 contra o Dólar americano melhoram os índices de Sharpe para 0,4-0,9, em relação a 0,15 de uma estratégia de buy and hold. Uma carteira de moeda neutra em dólares que classifica as moedas dos países do G10 de acordo com a inclinação no cross-section também oferece índices de Sharpe mais altos do que outras estratégias de moeda como o carry trade. Essas descobertas são compatíveis com uma reação defasada do mercado de câmbio às informações sobre taxas de juros. O segundo ensaio propõe uma nova medida que usa apenas informações de dispersão cross-section de betas do modelo CAPM para prever retornos agregados de mercado para os EUA. Esta escolha de preditores é baseada em argumentos teóricos simples de que as medidas associadas à dispersão dos betas do CAPM, em alguns cenários, devem ser relacionadas aos retornos futuros de mercado esperados. Essas medidas de dispersão de fato prevêem o prêmio de risco de mercado em vários horizontes e fornecem alto poder preditivo dentro e fora da amostra. O R2 fora da amostra atinge até 10 porcento na frequência anual (0,7 porcento mensal) e são robustos a diferentes janelas de estimação. Ao contrário da maioria das medidas encontradas na literatura, a nossa não é baseado em preço ou valuation ratios. Nossas medidas variam com o ciclo econômico e se correlacionam com outras variáveis de previsão comumente usadas, como razões de dividendo-preço e consumo-riqueza, mas fornecem poder explicativo acima e além dos preditores padrão. Nossos resultados fornecem evidências adicionais de que a dispersão dos betas ao longo do tempo é função da variação temporal do prêmio de risco de mercado. / [en] The thesis is composed of two essays on empirical finance. The first focuses on FX markets and presents measures of interest rates shortterm structure slope changes for the US and other G10 countries using 3- and 6-month futures contracts. These changes in slopes have immediate impact on currency returns but also a strong delayed effect over the following weeks, implying that currencies are predictable both in and outof-sample. Investors that condition on slope to tactically trade a long G10 portfolio improve Sharpe ratios to 0.4-0.9, relative to 0.15 for a buy-andhold strategy. A dollar-neutral currency portfolio that sorts G10 country currencies on the cross-section slope also deliver higher Sharpe ratios than other currency strategies, such as the carry trade. These findings are compatible with delayed currency market reaction to information in interest rates. The second essay proposes a novel measure that solely use crosssectional dispersion information on CAPM betas to forecast aggregate market returns for the US. This choice of predictors is based on simple theoretical arguments that measures associated with the dispersion of CAPM betas, in some settings, should be related with expected future market returns. We find that these dispersion measures do indeed forecast market risk premium over multiple horizons and deliver high in-sample and out-of-sample predictive power: out-of-sample R2 reaches up to 10 percent at the annual frequency (0.7 percent monthly) and are robust to different estimation windows. Unlike most measures in the literature, ours is not a price- or valuation-based ratio. Our approach is also an alternative to models that use the cross-section of valuation ratios to infer the conditional market risk premium. Our measures vary with the business cycle and correlate with other commonly used forecasting variable such as dividend-price or consumption-wealth ratios, but they provide explanatory power above and beyond the standard predictors. Our findings provide additional evidence that the betas dispersion across time is a function of time varying risk premium.

<p>The cross-sectional variation of stock returns used to be described by the Capital Asset Pricing Model until the early 90‟s. Anomalies, such as, book-to-market effect and small firm effect undermined CAPM‟s ability to explain stock returns and Fama & French (1992) have shown that simple firm attributes, like, firm size and book-to-market value can explain the returns far better than Beta. Following Fama & French many other researchers examine the explanatory powers of CAPM and other asset pricing models. However, most of those studies use US data. There are some researches done in different countries than US, however more out-of-sample studies need to be conducted.</p><p>To our knowledge there are very few studies using the Swedish data and this thesis contributes to that small pool of studies. Moreover, the studies testing the CAPM use the unconditional version of the model. There are some papers suggesting the use of a conditional CAPM that would exhibit better explanatory powers than the unconditional CAPM. Different ways of conditioning the CAPM have been proposed, but one that we think is the least complex and possible to make use of in the business world is the dual-beta model. This conditional CAPM assumes a different relationship between beta and stock returns during the up markets and down markets. Furthermore, the model has not thoroughly been tested outside the US. Our study is the first to use the dual-beta model in Sweden. In addition, the momentum effect has lately been given some attention and Fama & French‟s (1993) three factor model has not been able to explain the abnormal returns related to that anomaly. We test the Fama & French three factor model, CAPM and Carhart‟s four factor model‟s explanatory abilities of the momentum effect using Swedish stock returns. Ultimately, our aim is to find the best model that describes stock return cross-section on the Stockholm Stock Exchange.</p><p>We use returns of all the non-financial firms listed on Stockholm Stock Exchange between September, 1997 and April, 2010. The number of companies included in our time sample is 366. The results of our tests indicate that the small firm effect, book-to-market effect and the momentum effect are not present on the Stockholm Stock Exchange. Consequently, the CAPM emerges as the one model that explains stock return cross-section better than the other models suggesting that Beta is still a proper measure of risk. Furthermore, the conditional version of CAPM describes the stock return variation far better than the unconditional CAPM. This implies using different Betas to estimate risk during up market conditions and down market conditions.</p>

The cross-sectional variation of stock returns used to be described by the Capital Asset Pricing Model until the early 90‟s. Anomalies, such as, book-to-market effect and small firm effect undermined CAPM‟s ability to explain stock returns and Fama &amp; French (1992) have shown that simple firm attributes, like, firm size and book-to-market value can explain the returns far better than Beta. Following Fama &amp; French many other researchers examine the explanatory powers of CAPM and other asset pricing models. However, most of those studies use US data. There are some researches done in different countries than US, however more out-of-sample studies need to be conducted. To our knowledge there are very few studies using the Swedish data and this thesis contributes to that small pool of studies. Moreover, the studies testing the CAPM use the unconditional version of the model. There are some papers suggesting the use of a conditional CAPM that would exhibit better explanatory powers than the unconditional CAPM. Different ways of conditioning the CAPM have been proposed, but one that we think is the least complex and possible to make use of in the business world is the dual-beta model. This conditional CAPM assumes a different relationship between beta and stock returns during the up markets and down markets. Furthermore, the model has not thoroughly been tested outside the US. Our study is the first to use the dual-beta model in Sweden. In addition, the momentum effect has lately been given some attention and Fama &amp; French‟s (1993) three factor model has not been able to explain the abnormal returns related to that anomaly. We test the Fama &amp; French three factor model, CAPM and Carhart‟s four factor model‟s explanatory abilities of the momentum effect using Swedish stock returns. Ultimately, our aim is to find the best model that describes stock return cross-section on the Stockholm Stock Exchange. We use returns of all the non-financial firms listed on Stockholm Stock Exchange between September, 1997 and April, 2010. The number of companies included in our time sample is 366. The results of our tests indicate that the small firm effect, book-to-market effect and the momentum effect are not present on the Stockholm Stock Exchange. Consequently, the CAPM emerges as the one model that explains stock return cross-section better than the other models suggesting that Beta is still a proper measure of risk. Furthermore, the conditional version of CAPM describes the stock return variation far better than the unconditional CAPM. This implies using different Betas to estimate risk during up market conditions and down market conditions.