This thesis is composed of three chapters. The first two chapters provides novel approaches for modeling and estimating the dependence structure for a large portfolio of assets using rating data. In both chapters a natural form of organizing a portfolio in terms of the levels of exposure to economic sectors and geographical regions, plays a key role in setting up the dependence structure. The last chapter investigates weather financial strategies that exploit sector or geographical heterogeneity in the asset space are relevant in terms of portfolio optimization. This is also done in a context of a large portfolio but with data on stock returns.

>Magister Scientiae - MSc / This study examines the relationship between stock returns and market segmentation. Monthly returns of stocks listed on the JSE from 1997-2007 are analysed using mostly the analytic factor and cluster analysis techniques. Evidence supporting the use of multi-index models in explaining the return generating process on the JSE is found. The results provide additional support for Van Rensburg (1997)'s hypothesis on market segmentation on the JSE.

Magister Commercii - MCom / Over the past four decades, size, value and momentum effects have been uncovered on stock markets, and several multifactor asset pricing models have been proposed to explain them. The associated premiums have been found to be time-varying and the explanations behind the effects are still debated. In South Africa, contradictory findings have been reported on the existence of those effects and the explanatory power of multifactor models. More important, the cyclicality of the effects and the risk/mispricing debate have been given little attention. In this regard, this study purports to establish the existence of size, value and momentum effects, investigate the explanatory power of the Fama-French three- and five-factor models (FF3F and FF5F respectively), and Carhart four-factor model (C4F), and examine the cyclicality and risk-based rationale of the style premiums on the Johannesburg Stock Exchange (JSE). Using a research sample comprised of common stocks included in the FTSE/JSE All Share Index (ALSI) for the period 1 January 2002 - 31 December 2018, the study subdivides the examination period into two business cycles, with each cycle including one upward phase and one downward phase

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.

Submitted by Eduardo Alonso Marza dos Santos (eduardo.marza.santos@gmail.com) on 2015-06-21T10:30:55Z No. of bitstreams: 1 Eduardo_A_M_Santos.pdf: 646820 bytes, checksum: aaba122a576d7c75ad0e5803539c25d4 (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2015-06-22T11:46:18Z (GMT) No. of bitstreams: 1 Eduardo_A_M_Santos.pdf: 646820 bytes, checksum: aaba122a576d7c75ad0e5803539c25d4 (MD5) / Made available in DSpace on 2015-06-22T11:56:18Z (GMT). No. of bitstreams: 1 Eduardo_A_M_Santos.pdf: 646820 bytes, checksum: aaba122a576d7c75ad0e5803539c25d4 (MD5) Previous issue date: 2015-05-28 / The dissertation goal is to quantify the tail risk premium embedded into hedge funds' returns. Tail risk is the probability of extreme large losses. Although it is a rare event, asset pricing theory suggests that investors demand compensation for holding assets sensitive to extreme market downturns. By de nition, such events have a small likelihood to be represented in the sample, what poses a challenge to estimate the e ects of tail risk by means of traditional approaches such as VaR. The results show that it is not su cient to account for the tail risk stemming from equities markets. Active portfolio management employed by hedge funds demand a speci c measure to estimate and control tail risk. Our proposed factor lls that void inasmuch it presents explanatory power both over the time series as well as the cross-section of funds' returns. / O objetivo do trabalho é quanti car o prêmio de risco de cauda presente nos retornos de fundos de investimento americanos. Risco de cauda é o risco de perdas excepcionalmente elevadas. Apesar de ser um evento raro, a teoria de apreçamento de ativos sugere que os investidores exigem um prêmio de risco para reter ativos expostos a eventos negativos extremos (eventos de cauda). Por de nição, observações extremas têm baixa probabilidade de estarem presentes na amostra, o que di culta a estimação dos impactos de risco de cauda sobre os retornos e reduz o poder de técnicas tradicionais como VaR. Os resultados indicam que não é su ciente controlar somente para o risco de cauda do mercado de capitais. A gestão ativa de portfólio por parte dos gestores de fundos requer uma medida própria para estimação e o controle de risco de cauda. O fator de risco de cauda que propomos cumpre este papel ao apresentar poder explicativo tanto na série temporal dos retornos quanto no corte transversal.

[pt] Este trabalho tem como objetivo explorar o benefício da inclusão de um novo fator relacionado a juros aos principais modelos de análise do cross-section dos retornos de ações, como o CAPM e o modelo de 3 fatores de Fama & French. O foco em especial é sobre a anomalia dos maiores retornos ajustados ao risco das estratégias de spread entre ações de baixo e alto beta de mercado, que também pode ser visto nos spreads entre ações de baixa e alta volatilidade. A motivação para inclusão deste fator vem da teoria de que o bom desempenho destas estratégias é simplesmente uma exposição a taxa de juros, não capturada pelos modelos usuais. Apesar da literatura apontar que as taxas de juros afetam diversas variáveis econômicas, a maior parte dos trabalhos de análise do cross-section dos retornos de ações é conduzida através de modelos de fatores compostos apenas por ações, sem fatores ou ativos diretamente relacionados a mudança da taxa de juros. A análise é feita com modelos lineares de fatores para o mercado acionário norte-americano entre 1976 até 2015. / [en] The literature shows that interest rates influence different economic variables such as consumption willingness, investment or expected asset returns. Notwithstanding, most works dealing with cross-sectional analysis of stock returns use only stock-based factor models disregarding the effects of interest rate movements. In this work, we explore the benefits of incrementing the traditional cross-sectional analysis (CAPM and Fama-French 3-factor model) with a new factor characterizing interest rate evolution over time. With this new factor, our model aims at better explaining stock return dispersion as well as a known anomaly of high risk-adjusted returns for low-volatility stock portfolios. Empirical analysis of linear factor models are carried out using US stock data using the Kenneth French database and the new factor is constructed using the US Aggregate do Barclays index that measures the return of low-risk assets.

This thesis is composed of three chapters. The first two chapters provides novel approaches for<p>modeling and estimating the dependence structure for a large portfolio of assets using rating data.<p>In both chapters a natural form of organizing a portfolio in terms of the levels of exposure to economic sectors and geographical regions, plays a key role in setting up the dependence structure.<p>The last chapter investigates weather financial strategies that exploit sector or geographical heterogeneity in the asset space are relevant in terms of portfolio optimization. This is also done in a context of a large portfolio but with data on stock returns. / Doctorat en Sciences économiques et de gestion / info:eu-repo/semantics/nonPublished