In financial markets, momentum effect can be defined as the tendency of prices to maintain their short term movements. On the other hand, reversal effect is usually understood to be the change in direction of long term price movements. This paper examines whether momentum and reversal effects were in evidence in the Brazilian stock market between January 1999 and June 2012. After calculating 1296 trading strategies, no evidence of reversal effect is found. With regard to momentum effect, some weak evidence is presented for the very short term. Exposure to risk factors can explain returns on strategies, including returns on momentum strategies. The results are borne out with different market proxy specifications and size subsamples. When compared to previous studies, the results raise the question of whether the reversal effect is vanishing from the Brazilian stock market and whether the traces of momentum are sufficient to confirm its existence. Furthermore, evidence of seasonality is found for June in momentum strategies and for November in both reversal and momentum strategies. Subsequent tests reveal that the effects of seasonality are limited to small stocks. / Nos mercados financeiros, o efeito momento pode ser definido como a tendência dos preços em manter seus movimentos de curto prazo. Por outro lado, o efeito contrário é geralmente entendido como a mudança na direção dos movimentos de longo prazo dos preços. O presente trabalho examina a existência dos efeitos momento e contrário no mercado acionário brasileiro no período compreendido entre janeiro de 1999 e junho de 2012. A partir do cálculo de 1296 estratégias de investimento, nenhuma evidência de efeito contrário é encontrada. Com relação ao efeito momento, observou-se apenas uma fraca evidência no curtíssimo prazo. A exposição aos fatores de risco é capaz de explicar os retornos das estratégias, inclusive os retornos das estratégias de momento. Os resultados são robustos ao se utilizar diferentes especificações de proxy de mercado e subamostras de valor de mercado. Quando comparados a trabalhos anteriores, os resultados colocam em questão se o efeito contrário está desaparecendo no mercado acionário brasileiro e se as fracas evidências do efeito momento são suficientes para confirmar sua existência. Ademais, são observadas evidências de sazonalidade no mês de junho nas estratégias de momento e, no mês de novembro, em ambas as estratégias. Testes posteriores revelam que esses efeitos de sazonalidade estão restritos à subamostra de baixo valor de mercado.

[pt] O estudo das anomalias existentes no mercado de capitais brasileiro vem ganhando força em pesquisas recentes, tanto pela curiosidade de pesquisadores como pela necessidade de pessoas do mercado em entender alguns fenômenos que persistem em ocorrer, mesmo com a disseminação da informação por todo o mercado, contrariando os pressupostos da eficiência de mercado. Dentro deste contexto, esta tese se propôs a estudar alguns deles, e também realizar modificações em modelos já consolidados. Foram feitas aqui três modificações na maneira tradicional de análise de modelos de anomalias, dentro de quatro capítulos distintos, porém inter-relacionados, além da introdução e da conclusão. O primeiro capítulo se propõe a verificar dois pressupostos básicos de modelos estatísticos, que são a normalidade e a estacionariedade da série de retornos de ações no Brasil. O segundo capítulo modifica a metodologia tradicional de formação de carteiras, aplicando uma técnica conhecida como análise de cluster em detrimento das medidas de posição. A terceira parte apresenta uma modificação do modelo de Grinblatt e Moskowitz (2004), analisando os aspectos que seriam importantes para o mercado brasileiro nos retornos futuros das ações. Por fim, é feita uma modificação importante no Modelo de Multifatores de Fama e French (1996), incorporando elementos da variância condicional, através da modelagem ARCH e GARCH na equação do modelo. Concluí-se que o mercado brasileiro apresenta algumas anomalias comuns a outros mercados, e que uma melhoria pode ser realizada nos modelos tradicionais, levando-se em consideração características específicas do caso brasileiro. / [en] The anomalies that exist in the Brazilian Capital Markets have been increasingly discused in recent research, as much for the curiosity of researchers as for the need of the market to understand some phenomena that persist in occurring, opposing the assumptions of market efficiency. In this context, this thesis aimed at studying some of them, and also to carry through some modifications in consolidated models. Three modifications were made in the traditional analysis of anomalies models, resulting in four distinct chapters, but interrelated, and the introduction and conclusion. The first study verified two estimated assumptions of statistical models, that are the normality and the stationarity of returns of the shares in Brazil. The second study modifies the traditional way of portfolio formation, applying the cluster analysis technique instead of by the ranking of position. The third study presents a modification of the Grinblatt and Moskowitz Model (2004), analyzing the aspects that would be important for the Brazilian market in determines the returns of the shares. Finally, in the fourth study, an important modification in the Multifactor Model of Fama and French (1996) is proposed, incorporating elements of the conditional variance, through applying modeling; ARCH and GARCH in the equation of the model. It can be concluded that the Brazilian market presents some common anomalies to other markets, and that an improvement can be implemented in the traditional models.

The All-Electric Vehicle (AEV) industry development has intensified and is connected to governmentefforts to minimize greenhouse gas emissions and encourage people to buy electric vehicles. This hasled to all the lights turning on newly established all-electric vehicle makers and some older players. Thegrowth of these companies is depicted in their market capitalization, which has seen an unprecedentedrun. However, one can notice a knowledge gap in the analysis of factors affecting such companies'expected rate of return. This research focuses on analyzing the factors from three of the most knownasset pricing models - CAPM, Fama-French 3 Factor, and Fama-French 5 Factor models. It shows whichof these factors are significant in estimating the expected return rate for nine chosen companies and theimpact of each considerable factor on the return rate.Additionally, we calculate the expected return rate using the beforementioned models to verify whetherthere is an uptrend or not in the electric vehicle market. The current research is limited to companieslisted on the US stock market, with only all-electric vehicle production lines. We make an introductionto the AEV theoretical aspects and related market structure. We also present theoretical concepts behindthe expected rate of return perception.The analysis showed that the market risk premium impacts 100% of the companies. The SMB factorinfluences 55% of the companies while the HML factor only 11%. Finally, RMW affects 66% of thechosen dataset and CMA 77%. For all companies, there is a positive expected return rate. Looking atthe significant coefficients for each model, the results are the following: we can observe that for CAPMand all the companies, 100% of the coefficients are positive. For FF3FM, 93% of the significant factorsare positive, while only 7% are negative. Finally, for FF5FM, out of the 28 significant factors, 65% ofthe coefficients are positive, and 35% are negative.

[pt] O presente estudo busca analisar a existência de prêmio de risco para o fator Quality minus Junk (QMJ) e seus componentes, assim como a interação da qualidade com outras anomalias documentadas na literatura, como: Tamanho, Valor e Momento para o mercado acionário brasileiro. A análise para o mercado brasileiro é feita com base nos dois artigos de Asness, Frazzini e Perdersen, Quality Minus Junk e Size Matters if You Control Your Junk . Ao adotar uma estratégia comprada em ações com pequeno valor de mercado e vender empresas com alto valor de mercado, uma estratégia baseada em tamanho está potencialmente comprada no prêmio de tamanho, mas também vendida em um prêmio de qualidade, o que acaba criando distorções nos resultados esperados dado que existe a interação de outra variável. Procuramos também através da utilização de um conjunto de regressões mensurar se o fator Qualidade apresentado por Asness et al. (2014) e o modelo de precificação de Fama e French (2016) poderiam nos ajudar a encontrar um alfa para o prêmio de tamanho mais significante e quanto o fator qualidade é capaz de explicar o prêmio de risco presente na anomalia de tamanho. / [en] The present study seeks to analyze the existence of a risk premium for the Quality minus Junk (QMJ) factor and its components, as well as an interaction of quality with other anomalies documented in the literature, such as: Size, Value and Momentum to the Brazilian stock market. The analysis for the Brazilian market is made based on the two articles by Asness, Frazzini and Perdersen, Quality Minus Junk and Size Matters if You Control Your Junk . Adopting a strategy long in stocks with small market value and short in stocks with high market value, a strategy based on size, is potentially long at the size premium, but also short at a quality premium, which ends up creating distortions in the expected results since there is an interaction with another variable. We also seek through a set of regressions to measure whether the factor presented by Asness as QMJ and the pricing model by Fama and French (2016) can help us to find an alpha more significant for the size premium, and how much the quality factor is able to explain the risk premium present in the size anomaly.

Det finns ett ökat fokus på hållbarhet på grund av miljömässiga utmaningar vi som global gemenskap ställs inför, såsom klimatuppvärmning. Det har dock funnits en brist på ekonomiska incitament att åtgärda detta. Nu finns det studier som påvisar marknadsfördelar för företag som är mer miljömedvetna - och de som yrkar på motsatsen. Uppsatsen ämnar att kvantitativt studera om det finns en förändring i totala aktieavkastningen när företag i OMXS30 får högre hållbarhetsbetyg inriktade på miljö. Denna uppsats använder sig av Refinitivs Environmental Pillar (EP) betyg. Sambandet mellan avkastning och EP-betyg undersöks med hjälp av regressionsmodeller baserade på Fama-French trefaktormodell, där EP-betyg lagts till som ytterligare en faktor. Regressioner genomförs för OMXS30 företagen. Det sammanställda resultatet är ej statistiskt signifikant, men tyder på att det finns ett negativt samband mellan EP-betyg och aktieavkastning. / There is an increased focus on sustainability due to the environmental challenges that we as a global community are facing, such as global warming. There has however been a lack of economic incentive to do this. There are now studies that demonstrate market advantages for companies that are more environmentally conscious - and those that implore the opposite. This essay aims to quantitatively study if there is a change in total stock return when companies in the OMXS30 score higher in sustainability ratings focused on the environment. The essay uses Refinitiv’s Environmental Pillar (EP) scores. The relationship between return and EP-score is examined with the help of regression models based on the Fama-French three factor model, where EP scores are added as an additional factor. Regressions are performed for OMXS30 companies. The compiled results are not statistically significant; however, they suggest a negative relationship between EP scores and stock returns.

The three-factor model of Fama and French has proved to be a seminal contribution to asset pricing theory, and was recently extended to include two more factors, yielding the Fama-French five-factor model. Other proposed augmentations of the three-factor model includes the introduction of a momentum factor by Carthart. The extensive use of such factors in asset pricing theory and investing motivates the study of the distributional properties of the returns of these factors. However, previous studies have focused on subsets of these six factors on the U.S. market. In this thesis, the distributional properties of daily log-returns of the five Fama-French factors and the Carthart momentum factor in European data from 2009 to 2019 are examined. The univariate distributional dynamics of the factor log-returns are modelled as ARMA-NGARCH processes with skewed t distributed driving noise sequences. The Gaussian and t copula are then used to model the joint distributions of these factor log-returns. The models developed are applied to estimate the one-day ahead Value-at-Risk (VaR) in testing data. The estimations of the VaR are backtested to check for correct unconditional coverage and exponentially distributed durations between exceedances. The results suggest that the ARMA-NGARCH processes are a valid approximation of the factor log-returns, and lead to good estimations of the VaR. The results of the multivariate analysis suggest that constant Gaussian and t copulas might be insufficient to model the dependence structure of the factors, and that there might be a need for more flexible copula models with dynamic correlations between factor log-returns. / Fama och Frenchs trefaktormodell har blivit en populär modell för aktieavkastning, och utvidgades nyligen av Fama och French genom att två ytterligare faktorer lades till för att skapa en femfaktormodell. Carthart föreslår en annan modell där trefaktormodellen kompletteras med en momentumfaktor. Då dessa faktorer används inom både akademiska sammanhang och kapitalförvaltning finns det ett tydligt behov av att undersöka vilka egenskaper fördelningen av faktorernas avkastning har. Dock har tidigare sådan forskning inte undersökt detta för alla sex faktorer, och endast använt data från USA:s marknad. I detta examensarbete undersökt därför sannolikhetsfördelningen för den logaritmiska dagliga avkastningen av de fem Fama-French-faktorerna och Cartharts momentumfaktor i europeisk data från åren 2009 till 2019. De endimensionella sannolikhetsfördelningarna modelleras som dynamiska med hjälp av ARMA-NGARCH-processer med feltermer som är fördelade enligt en generaliserad t-fördelning som tillåter skevhet. För att modellera multivariata fördelningar används en Gaussisk copula och en t-copula. De erhållna modellerna används sedan för att uppskatta daglig Value-at-Risk (VaR) i testdata. Dessa uppskattningar av VaR genomgår sedan statistiska test för att undersöka om antalet överträdelser är korrekt och tiderna mellan varje överträdelse är exponentialfördelade. Resultaten i detta examensarbete tyder på att ARMA-NGARCH-processer är en bra approximation av faktorernas logaritmiska dagliga avkastning, och ger bra uppskattningar av VaR. Resultaten för den multivariata analysen tyder på att en konstant copula kan vara en otillräcklig modell för beroendestrukturen mellan faktorerna, och att det möjligen finns ett behov av att använda mer flexibla copula-modeller med en dynamisk korrelation mellan faktorernas logaritmiska avkastning.

In the realm of asset pricing models, the Fama-French five-factor model has become a foundational framework for explaining the variation of excess stock returns. However, as financial markets continue to evolve, there arises a need to explore potential extensions to capture additional sources of risk and return. One such extension involves incorporating the difference between the actual and expected interest rates as an additional factor. This report delves into the empirical testing of this extended model and assesses its implications for explaining the variation of excess returns on the Swedish stock market. The rationale behind introducing such a factor is rooted in its potential to capture variations in excess returns attributed to unexpected changes in interest rates. To evaluate its efficacy, a comprehensive analysis was undertaken, focusing on three key aspects: the statistical significance of the factor, its impact on model fit, and its role in explaining variations in excess returns. Upon conducting time-series regressions across three sets of nine portfolios, it was found that while the factor exhibited notable coefficients with substantial influence on explaining excess returns, it failed to achieve statistical significance. This outcome prompts a crucial question: can an extension with a factor of high explanatory power but low significance truly enhances our understanding of stock returns? The findings suggest that despite its influence, other factors present in the model might already absorb the explanatory potential attributed to the new factor. Further examination of the extended model's performance provides insights into the overall model fit. The GRS statistic indicates that the extended model offers a superior fit compared to the original five-factor model. However, the adjusted R2 values suggest that this enhanced fit is not translated into a meaningful improvement in the model's ability to explain variations in returns. This prompts a nuanced consideration of whether the complexity introduced by the additional factor aligns with its incremental ability to explain variation in returns. / Inom asset pricing models har Fama-French five-factor model blivit ett av de mest grundläggande ramverken för att beskriva variationen i överavkastning. Eftersom finansmarknaderna fortsätter att kontinuerligt utvecklas finns det ett behov av att undersöka potentiella utvidgningar av modellen för att hitta ytterligare källor till risk och avkastning. Ett exempel av en sådan utveckling är att skillnaden mellan faktiska och förväntade räntor läggs till som en ytterligare faktor. I detta arbete utförs empiriska tester för att kunna bedöma om en utvidgad modell kan användas för att kunna beskriva variationen i överavkastning på den svenska aktiemarknaden. Motivation bakom att införa en sådan faktor är dess potentiella kraft i att beskriva variation i överavkastning hänförligt till oförväntade förändringar av räntor. För att utvärdera dess effektivitet utfördes en omfattande analys som fokuserade på tre nyckelaspekter: faktorns statistiska signifikans, dess påverkan på model fit och dess roll för att förklara variation i överavkastning. Efter att ha utfört tidsserieregressioner över tre uppsättningar av nio portföljer, visade det sig att medan faktorn uppvisade anmärkningsvärda koefficienter med betydande inflytande på att förklara variationen i avkastning, var den emellertid ej statistiskt signifikant. Detta utfall ger upphov till en viktig fråga: kan en utvidgad modell med en faktor med stor förmåga att förklara, men med låg signifikans, förbättra vår förståelse av variation i överkastning? Resultaten antyder att trots den nya faktorns förklarande förmåga, har den förklarande förmåga som tillskrivits den nya faktorn redan absorberats av tidigare faktorer i modellen. Vidare undersökning av den utvidgade modellens prestanda ger insikter i hur modellen är anpassad till observationer. GRS-statistiken visar att den utvidgade modellen är bättre anpassad än den ursprungliga modellen. Dock visar adjusted R2 värdena att detta inte översätts till en meningsfull förmåga att beskriva variationen i överavkastning. Detta ger upphov till en diskussion om huruvida den ökade komplexitet som införs är i linje med dess inkrementella värde i att förklara variation i överavkastning.

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Syfte: Syftet är att testa Fama och Frenchs femfaktormodell på den svenska aktiemarknaden. Detta genom att undersöka huruvida modellen kan statistiskt förklara portföljers genomsnittliga avkastning samt ifall specifika faktorer har statistisk signifikans. Metod: En kvantitativ studie med ett deduktivt förhållningssätt. Undersökningen utför tester på den svenska aktiemarknaden mellan 2015-01-01 och 2019-12-31 genom en regressionsanalys. Upptäckter: Fama och Frenchs femfaktormodell förkastas som helhet men det påvisas däremot att HML är statistisk signifikant inom sex av sex storlekssorterade portföljer, följt av SMB med fyra av sex. Fama och Frenchs femfaktormodellen har svårigheter att förklara avkastningen för mindre företag sorterade utifrån lönsamhet och book-to-market tal. Forskningsimplikationer: Undersöker ett forskningsämne som eftersträvar studier och tester på ett flertal varierande marknader för att förklara aktiers avkastningsmönster. Orginalitet och värde: Studien särskiljer sig på grund av avsaknaden av forskning på den svenska aktiemarknaden. Därtill bidrar studien till ett undersökningsområde för små öppna ekonomier som den svenska marknaden grundas i. / Purpose: The purpose is to test Fama and French's five-factor model in the Swedish stock market. This is done by examining whether the model can explain portfolios' average return and whether specific factors have statistical significance. Method: A quantitative study with a deductive approach. The survey performs tests on the Swedish stock market between 2015-01-01 and 2019-12-31 through a regression analysis. Findings: Fama and French's five-factor model is rejected as a whole, but it is shown that HML is statistically significant in every size-sorted portfolio, followed by SMB with statistical significance in four out of six portfolios. Fama and French's five-factor model have difficulty explaining the returns for smaller companies sorted on profitability and book-to-market ratio. Research implications: Investigates a research topic that strives for an increased number of studies and tests in different markets to explain stock return patterns. Originality and value: The study differs due to the lack of research on the Swedish stock market. In addition, the study contributes to a study area for small open economies in which the Swedish market is based.

The primary objective of this dissertation is to revisit the CAPM and the Fama-French multi-factor models with a view to evaluate the validity of the probabilistic assumptions imposed (directly or indirectly) on the particular data used. By thoroughly testing the assumptions underlying these models, several departures are found and the original linear regression models are respecified. The respecification results in a family of heterogeneous Student's t models which are shown to account for all the statistical regularities in the data. This family of models provides an appropriate basis for revisiting the empirical adequacy of the CAPM and the Fama-French multi-factor models, as well as other models, such as alternative asset pricing models and risk evaluation models. Along the lines of providing a sound basis for reliable inference, the respecified models can serve as a coherent basis for selecting the relevant factors from the set of possible ones. The latter contributes to the enhancement of the substantive adequacy of the CAPM and the multi-factor models. / Ph. D.