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Risk management in portfolio construction is a widely discussed topic and the tradeoff between risk and return is always considered before an investment is made. Modern portfolio theory is a mathematical framework which describes how a rational investor can use diversification to optimize a portfolio, which suggests using variance to measure financial risk. However, since variance is a symmetrical metric, the framework fails to correctly account for the loss aversion preferences most investors exhibit. Therefore, the use of downside risk measures were proposed, which only measures the variance of the portfolio below a certain threshold, usually set to zero or the risk-free rate. This thesis empirically investigates the differences in performance between the two risk measures when used to solve a real world portfolio optimization problem. Backtests using the different measures on all major Nordic equity markets are performed to highlight the dynamics between the frameworks, and when one should be preferred over the other. It is concluded that the optimization frameworks indeed provides a useful tool for investors to construct great performing portfolios. However, even though the downside risk framework is more mathematically rigorous, implementing this risk measure instead of variance seems to be of less importance for the actual results. / Riskhantering för aktieportföljer är mycket centralt och en avvägning mellan risk och avkastning görs alltid innan en investering. Modern Portföljteori är ett matematiskt ramverk som beskriver hur en rationell investerare kan använda diversifiering för att optimera en portfölj. Centralt för detta är att använda portföljens varians för att mäta risk. Dock, eftersom varians är ett symmetriskt mått lyckas inte detta ramverk korrekt ta hänsyn till den förlustaversion som de flesta investerare upplever. Därför har det föreslagits att istället använda olika mått på nedsiderisk (downside risk), som endast tar hänsyn till portföljens varians under en viss avkastningsgräns, oftast satt till noll eller den riskfria räntan. Denna studie undersöker skillnaderna i prestation mellan dessa två riskmått när de används för att lösa ett verkligt portföljoptimeringsproblem. Backtests med riskmåtten har genomförts på de olika nordiska aktiemarknaderna för att visa på likheter och skillnader mellan de olika riskmåtten, samt när det enda är att föredra framför det andra. Slutsatsen är att ramverken ger investerare ett användbart verktyg för att smidigt optimera portföljer. Däremot verkar den faktiska skillnaden mellan de två riskmåtten vara av mindre betydelse för portföljernas prestation. Detta trots att downside risk är mer matematiskt rigoröst.

Consumer sentiment has the ability to provide researchers with many avenues to test existing Finance and Economic theories. Chapter 1 introduces the issues that I seek to explore within the area of Behavioral Finance. Chapter 2 utilizes thirty years of consumer sentiment data to explore extant economic theories and hypotheses. In particular, I study the Prospect Theory and the Life Cycle Investment Hypothesis. In addition, I also study how changes in consumer sentiment can foretell future stock returns for firms in different industries and of different sizes. By studying how individuals of different ages display optimism and pessimism through consumer sentiment surveys, I am able to contribute to the literature by shedding additional light on just how the important age is with respect to a person's economic outlook. One particular phenomenon that I discuss in this chapter is downside risk. I will provide further support to the existing literature which shows that gains and losses are not viewed equally by individuals. To account for this discrepancy, this paper models the time series relationship between consumer sentiment and stock returns using asymmetric response models. Chapter 3 builds upon the previous chapter's findings by using consumer sentiment to explore if this index can forecast housing market variables such as changes in home sales and home prices. Given the recent financial market turmoil that stemmed from the U.S. housing market debacle, this chapter is timely. Using widely cited housing indices, I explore regional differences in the U.S. housing market and how the sentiment of local consumers can possibly affect their housing markets. I also include analyses in which the age of the consumer is accounted for to see if evidence of the Life Cycle Investment Hypothesis emerges. This theory postulates that younger individuals are more likely to demand housing as a financial asset and if this were true, I hypothesize that changes in younger individuals' sentiment would have more forecasting power with respect to future housing sales and price changes. Lastly, I conclude this dissertation with Chapter 4 which includes additional discussions of the issues studied.

This thesis investigates different aspects of the impact of extreme downside risk on stock returns. We first investigate the impact at market level, where the return of the stock market index is expected to be positively correlated to its tail risk. More specifically, we incorporate Markov switching mechanism into the framework of Bali et al. (2009) to analyse the relationship between risk and returns under different market regimes. Interestingly, although highly significant in calm periods, the tail risk-return relationship cannot be captured during turbulent times. This is puzzling since this is the time when the distress risk is most prominent. We show that this pattern persists under different modifications of the framework, including expanding the set of state variables and accounting for the non-iid feature of return process. We suggest that this result is due to the leverage and volatility feedback effects. To better filter out these effects, we propose a simple but effective modification to the risk measures which reinstates the positive extreme risk-return relationship under any state of market volatility. The success of our method provides insights into how extreme downside risk is factored into expected returns. In the second investigation, this thesis explores the impact of extreme downside risk on returns in a security level analysis. We demonstrate that a stock with higher tail risk exposure tends to experience higher average returns. Motivated by the limitations of systematic extreme downside risk measures in the literature, we propose two groups of new ‘co-tail-risk’ measures constructed from two different approaches. The first group is the natural development of canonical downside beta and comoment measures, while the second group is based on the sensitivity of stock returns on innovations in market systematic crash risk. We utilise our new measures to investigate the asset pricing implication of extreme downside risk and show that they can capture a significant positive relationship between this risk and expected stock return. Moreover, our second group of ‘co-tail-risk’ measures show a highly consistent performance even in extreme settings such as low tail threshold and monthly sample estimation. The ability of this measure to generate a number of observations given limited return data solves one of the most challenging problems in tail risk literature. In the last investigation, this thesis examines the influence of extreme downside risk on portfolio optimisation. It is motivated by the evidence in Chapter 4 regarding the size pattern of the extreme downside risk impact on stock returns where the impact is larger for small stocks. Accordingly, portfolio optimisation practice that focuses on tail risk should be more effective when applied to small stocks. In comparing the performance of mean-Expected Tail Loss against that of mean-variance across size groups of Fama and French’s (1993) sorted portfolios, we confirm this conjecture. Moreover, we further investigate the performance of different switching approaches between mean-variance and mean-Expected Tail Loss to utilise the suitability of these optimisation methods for specific market conditions. However, our results reject the use of any switching method. We demonstrate the reason switching could not enhance performance is due to the invalidity of the argument regarding the suitability of any optimisation method for a specific market regime.

Portfolio diversification has been a subject frequently addressed since the publications of Markowitz in 1952 and 1959. However, the Modern Portfolio Theory and its mean variance framework have been criticized. The critiques refer to the assumptions that return distributions are normally distributed and the symmetric definition of risk. This paper elaborates on these short comings and applies a heuristic downside risk approach to avoid the pitfalls inherent in the mean variance framework. The result of the downside risk approach is compared and contrasted with the result of the mean variance framework. The return data refers to the real estate sector in Sweden and diversification is reached through property type and geographical location. The result reveals that diversification is reached differently between the two approaches. The downside risk measure applied here frequently diversifies successfully with use of fewer proxies. The efficient portfolios derived also reveals that the downside risk approach would have contributed to a historically higher average total return. This paper outlines a framework for portfolio diversification, the result is empirical and further research is needed in order to grasp the potential of the downside risk measures.

[pt] O conceito de risco é definido como a distribuição de resultados inesperados devido a alterações nos valores das variáveis que descrevem o mercado. Entretanto, o risco não é uma variável observável e sua quantificação depende do modelo empregado para avaliá-lo. Portanto, o uso de diferentes modelos pode levar a previsões de risco significativamente diferentes.O objetivo principal desta dissertação é realizar um estudo comparativo dos modelos mais amplamente utilizados (medição de variância amostral nos últimos k períodos, modelos de amortecimento exponencial e o GARCH(1,1) de Bollerslev) quanto à capacidade preditiva da volatilidade.Esta dissertação compara os modelos de estimação de volatilidade citados acima quanto à sua capacidade preditiva para carteiras compostas por um conjunto de ações negociadas no mercado brasileiro. As previsões de volatilidade desses modelos serão comparadas com a volatilidade real fora da amostra. Como a volatilidade real não é uma variável observável, usou-se o mesmo procedimento adotado pelo RiskMetrics para o cálculo do fator de decaimento ótimo: assumiu-se a premissa que o retorno médio de cada uma das carteiras de ações estudadas é igual a zero e,como conseqüência disso, a previsão um passo à frente da variância do retorno realizada na data t é igual ao valor esperado do quadrado do retorno na data t.O objetivo final é concluir, por meio de técnicas de backtesting, qual dos modelos de previsão de volatilidade apresentou melhor performance quanto aos critérios de comparação vis-à-vis ao esforço computacional necessário. Dessa forma, pretende-se avaliar qual desses modelos oferece a melhor relação custo-benefício para o mercado acionário brasileiro. / [en] The risk concept is defined as the distribution of the unexpected results from variations in the values of the variables that describe the market. However, the variable risk is not observable and its measurement depends on which model is used in its evaluation. Thus, the application of different models could result in significant different risk forecasts.The goal of this study is to carry out a comparison within the largest used models (sample variance in the last k observations, exponentially smoothing models and the Bollerslev s model GARCH(1,1)). The study compares the models mentioned above regarding its forecast capability of the volatility for portfolios of selected brazilian stocks. The volatility forecasts will be compared to the actual out of sample volatility. As long as the actual volatility is not an observable variable, the same procedure adopted by RiskMetrics in the calculation of the optimum decay factor will be used: it assumes the premise that the average return of which one of the stock portfolios is equal zero and, as the consequence of this fact, the one step variance forecast of the portfolio return carried out on date t is equal to expected value of the squared return of date t.The final objective is to conclude, using backtesting techniques, which of the forecasting volatility models show the best performance regarding the comparison criterions vis-a-vis the demanding computer efforts. By this way, it was aimed to evaluate which of them offer the best cost-benefit relation for the brazilian equity market.

This study examines the use of leveraged exchange traded funds (LETFs) within a portfolio insurance framework to reduce exposure to downside risk. Investors have learned the importance of mitigating this risk having experienced two “once in a century” events in the last 20 years with the tech crash in the early 2000s and the financial crisis in 2008. Current portfolio insurance strategies are either option based (Leland & Rubinstein, 1976) or constant proportional portfolio insurance (CPPI), (Black & Jones, 1987). The cost of option based strategies can be quite high while a CPPI strategy requires constant rebalancing. This study combines the advantages of each by using LETFs to attain the leverage options provide, while at the same time allowing a greater percentage of the portfolio to be invested in bonds since a position in LETFs relative to a typical market index magnifies equity exposure. Thus, where a standard CPPI strategy may require 50% of the portfolio to be invested in equities, using a 3x LETF only requires approximately 16.7%. Results suggest the use of LETFs within a portfolio insurance framework result in better returns, higher Sharpe, Sortino, Omega, and cumulative prospect values while reducing Value at Risk (VaR) and Excess Shortfall below VaR. This twist on the use of LETFs will be of interest to any investor concerned with mitigating downside risk while allowing participation in increasing markets.

Submitted by Marcos Yoshiro Kawakami (marcos.kawakami@br.bnpparibas.com) on 2012-09-12T22:31:51Z No. of bitstreams: 1 Dissertação - Marcos Kawakami II - V. Final pos banca - ….pdf: 399060 bytes, checksum: d78ebc1a444bdf417b1748e6a6851846 (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2012-09-13T12:40:17Z (GMT) No. of bitstreams: 1 Dissertação - Marcos Kawakami II - V. Final pos banca - ….pdf: 399060 bytes, checksum: d78ebc1a444bdf417b1748e6a6851846 (MD5) / Made available in DSpace on 2012-09-13T13:17:55Z (GMT). No. of bitstreams: 1 Dissertação - Marcos Kawakami II - V. Final pos banca - ….pdf: 399060 bytes, checksum: d78ebc1a444bdf417b1748e6a6851846 (MD5) Previous issue date: 2012-08-15 / The development of financial markets and specially the openness to foreign capital have triggered the development of the corporate governance practices. One of the benefits of the best practice of corporate governance is to reduce the cost of capital of the company. This can generate greater value to the company. This new scenario, the board has an important duty in corporate governance activities, supervise the executive board. This paper investigates if the best practices of corporate governance reduce the risk of companies. Additionally, it analyzes if higher level of education of the board and executive management have impact on the risk. For this, it was adopted the method of least squares to regress the risk, dependent variable, against independent variables: level of corporate governance and education. To calculate the risk we use the methodology presented by Estrada (2007), the downside beta, risk that considers only the negative returns. The study results suggested that a better standard of corporate governance is present in the companies that have an increased risk seen by the market, indicating that companies that need capital, more leveraged firms, are companies that need a higher level of corporate governance. It was also found that firms with higher educational level of the board of directors and executive officers are at higher risk. The companies that need people with more education are companies that want to develop their selves, and therefore riskier. / O desenvolvimento do mercado financeiro e, principalmente, a abertura para o capital externo impulsionaram o desenvolvimento das boas práticas de governança corporativa. Um de seus benefícios é reduzir o custo de captação da empresa e, consequentemente, gerar maior valor para a companhia. Com o novo cenário, o conselho de administração tem um papel fundamental na atividade de governança corporativa, supervisionando a diretoria executiva. O presente trabalho investiga se a adoção de melhores práticas de governança corporativa diminui o risco das empresas. Adicionalmente, analisa se um grau de escolaridade mais alto entre membros do conselho de administração e da diretoria executiva impacta no risco. Para atingir o objetivo, adotou-se o método dos mínimos quadrados para regredir o risco, variável dependente, contra as variáveis independentes nível de governança corporativa e grau de escolaridade. Para o cálculo do risco, utilizaremos a metodologia apresentada por Estrada (2007), o downside beta, ou seja, risco que considera apenas os retornos negativos. Os resultados do estudo sugeriram que um nível de governança corporativa mais alto está presente nas empresas que apresentam um maior risco visto pelo mercado, indicando que as empresas que necessitam de captação, isto é, empresas mais alavancadas, são as empresas que necessitam de um nível de governança corporativa mais alto. Constatou-se, também, que empresas com nível de escolaridade mais alto entre membros do conselho de administração e da diretoria executiva apresentam maiores riscos, pois as empresas que necessitam de pessoas com maior grau de escolaridade são empresas que querem se desenvolver e, portanto, mais arriscadas.

<p>Hedge funds are a debated subject in today’s financial industry. During 2008, despite hedge funds absolute return target, the global hedge fund industry showed a negative performance whilst the Swedish hedge fund market performed relatively well in comparison. Many studies have been made investigating the effect on incorporating hedge funds in a traditional portfolio though none focused separately on the Swedish market. In a global perspective it is quite easy to invest in hedge fund portfolios due to the existence of investable indices. To invest on the Swedish market is a more complex matter. SIX Harcourt HFXS Index is a Swedish hedge fund index representing the Swedish hedge fund market though it is not investable. Hence it would be interesting to see if it is possible to create an investable version of SIX Harcourt HFXS. When creating an investable index, several administrative costs will arise and in order to cover these costs it would be interesting to see whether or not it possible to optimize SIX Harcourt HFXS Index in purpose of achieving a outperformance which could cover any administrative costs for setting up the investable version. Also, since the optimized version must replicate the standard SIX Harcourt HFXS Index it must maintain a certain level of correlation.</p><p>This thesis, which is based on a positivistic epistemology, is built upon a quantitative case study where SIX Harcourt HFXS Index is optimized in purpose of achieving an outperformance in terms of the risk-adjusted return. The optimization uses an adjusted mean-variance methodology and is limited to a maintained correlation above 0,9 towards the standard SIX Harcourt HFXS Index. The optimization is created through the use of an Excel application created by Harcourt Investment Consulting.</p><p>Also, based on the outperformance by Swedish hedge funds compared to global hedge funds, this study aims to show the effect of incorporating Swedish hedge funds in a traditional portfolio consisting of equities and bonds. This effect is analyzed by the use of several performance-and risk measures.</p><p>The study shows that it is possible to optimize SIX Harcourt HFXS Index and produce an outperformance of approximately 1,5% per annum with a maintained correlation above 0,9. It also shows that the effect of incorporating Swedish hedge funds to a traditional portfolio is positive in regards to both risk and return.</p>

Hedge funds are a debated subject in today’s financial industry. During 2008, despite hedge funds absolute return target, the global hedge fund industry showed a negative performance whilst the Swedish hedge fund market performed relatively well in comparison. Many studies have been made investigating the effect on incorporating hedge funds in a traditional portfolio though none focused separately on the Swedish market. In a global perspective it is quite easy to invest in hedge fund portfolios due to the existence of investable indices. To invest on the Swedish market is a more complex matter. SIX Harcourt HFXS Index is a Swedish hedge fund index representing the Swedish hedge fund market though it is not investable. Hence it would be interesting to see if it is possible to create an investable version of SIX Harcourt HFXS. When creating an investable index, several administrative costs will arise and in order to cover these costs it would be interesting to see whether or not it possible to optimize SIX Harcourt HFXS Index in purpose of achieving a outperformance which could cover any administrative costs for setting up the investable version. Also, since the optimized version must replicate the standard SIX Harcourt HFXS Index it must maintain a certain level of correlation. This thesis, which is based on a positivistic epistemology, is built upon a quantitative case study where SIX Harcourt HFXS Index is optimized in purpose of achieving an outperformance in terms of the risk-adjusted return. The optimization uses an adjusted mean-variance methodology and is limited to a maintained correlation above 0,9 towards the standard SIX Harcourt HFXS Index. The optimization is created through the use of an Excel application created by Harcourt Investment Consulting. Also, based on the outperformance by Swedish hedge funds compared to global hedge funds, this study aims to show the effect of incorporating Swedish hedge funds in a traditional portfolio consisting of equities and bonds. This effect is analyzed by the use of several performance-and risk measures. The study shows that it is possible to optimize SIX Harcourt HFXS Index and produce an outperformance of approximately 1,5% per annum with a maintained correlation above 0,9. It also shows that the effect of incorporating Swedish hedge funds to a traditional portfolio is positive in regards to both risk and return.