The pricing of total liquidity risk is studied in the cross-section of stock returns. The study suggests that there is a positive relation between total volatility of liquidity and expected returns. Our measure of liquidity is based on Amihud (2002) and its volatility is measured using daily data. Furthermore, we document that total volatility of liquidity is priced in the presence of systematic liquidity risk: the covariance of stock returns with aggregate liquidity, the covariance of stock liquidity with aggregate liquidity, and the covariance of stock liquidity with the market return. The separate pricing of total volatility of liquidity indicates that idiosyncratic liquidity risk is important in the cross section of returns. This result is puzzling in light of Acharya and Pedersen (2005) who develop a model in which only systematic liquidity risk affects returns. The positive correlation between the volatility of liquidity and expected returns suggests that risk averse investors require a risk premium for holding stocks that have high variation in liquidity. Higher variation in liquidity implies that a stock may become illiquid with higher probability at a time when it is traded. This is important for investors who face an immediate liquidity need and are not able to wait for periods of high liquidity to sell.

The Modern Portfolio Theory (MPT) argues that all unsystematic risk can be diversified away thus there should be no relationship between idiosyncratic risk and return. Ooi, Wang and Webb (2009) employ the Fama-French (1993) three-factor model (FF3) to estimate the level of nonsystematic return volatility in REITs as a proxy for idiosyncratic risk. They find a significant positive relationship between expected returns and conditionally estimated idiosyncratic risk contrary to the MPT. In this research, I examine other potential sources of systematic risk in REITs which may explain the seeming violation of the MPT found by Ooi et al (2009). I re-examine the proportion of idiosyncratic risk in REITs with Carhart’s (1997) momentum factor, which is largely applied on the FF3 to control for the persistency of stock returns as supplemental risk in the finance literature. Next, I conduct cross-sectional regression and test the significance of the relationship between idiosyncratic risk and expected returns. I further analyze the role of property sector on idiosyncratic risk as well as on its relationship with expected returns. I argue three conclusions. First, momentum has a relatively minor effect on the idiosyncratic risk consistent with the financial literature. Second, the effect of momentum is not strong enough to cause a significant change in the relationship between idiosyncratic risk and expected returns. Third, a REIT portfolio diversified across property sectors neutralizes the relationship between idiosyncratic risk and expected returns, though the contribution of each property sector is not statistically significant.

The low-volatility anomaly can be described as the unexpected outperformance of low-volatility stocks compared to high-volatility stocks over the long-term. This dissertation investigates the low-volatility anomaly and its presence on the Johannesburg Stock Exchange (JSE). Possible reasons behind why low-volatility stocks consistently outperform their high volatility counterparts, as well as their own expected return, over the long-term are discussed. This includes analysing how financial risk is measured and whether this plays a role in obscuring the expected risk-return relationship, in addition to other fundamental factors impacting expected returns. It is found that the low-volatility anomaly is present on the JSE and that using a number of different risk metrics does not significantly change where a stock is ranked on the risk spectrum. Additionally, including an interest rate exposure factor, a value factor and a momentum factor lowers the unexpected portion (Alpha) of the returns of low volatility stocks, at the same time as narrowing the gap between the unexpected performance of the lowest and highest volatility stocks.

This thesis examines the performance of different models of conditional betas and higher comoments in the context of the cross-section of expected stock returns, both in-sample and out-of-sample. I first examine the performance of different conditional market beta models by using monthly returns of the Fama-French 25 portfolios formed by the quintiles of size and book-to-market ratio in Chapter 3. This is a cross-sectional test of the conditional CAPM. The models examined include simple OLS regressions, the macroeconomic variables model, the state-space model, the multivariate GARCH model and the realized beta model. The results show that the state-space model performs best in-sample with significant betas and insignificant intercepts. For the out-of-sample performance, however, none of the models examined can explain returns of the 25 portfolios. Next, I examine the recently proposed realized beta model, which is based on the realized volatility literature, by using individual stocks listed in the US market in Chapter 4. I extend the realized market beta model to betas of multi-factor asset pricing models. Models tested are the CAPM, the Fama-French three-factor model and a four-factor model including the three Fama-French factors and a momentum factor. Realized betas of different models are used in the cross-section regressions along with firm-level variables such as size, book-to-market ratio and past returns. The in-sample results show that market beta is significant and additional betas of multi-factor models can reduce although not eliminate the effects of firm-level variables. The out-of-sample results show that no betas are significant. The results are robust across different markets such as NYSE, AMEX and NASDAQ. In Chapter 5, I test if realized coskewness and cokurtosis can help explain the cross-section of stock returns. I add coskewness and cokurtosis to the factor pricing models tested in Chapter 4. The results show that the coefficients of coskewness and cokurtosis have the correct sign as predicted by the higher-moment CAPM theory but only cokurtosis is significant. Cokurtosis is significant not only in-sample but also out-of-sample, suggesting cokurtosis is an important risk. However, the effects of firm-level variables remain significant after higher moments are included, indicating a rejection of higher-moment asset pricing models. The results are also robust across different markets such as NYSE, AMEX and NASDAQ. The overall results of this thesis indicate a rejection of the conditional asset pricing models. Models of systematic risks, i.e. betas and higher comoments, cannot explain the cross-section of expected stock returns.

Researchers criticize predominant expected return models for being imprecise and based on fundamentally flawed assumptions. This dissertation evaluates Implied Cost of Capital, CAPM and the Three-Factor model abilities to estimate returns. We study each models expected return association to realized return and test for abnormal returns. Our sample covers the period 2000 to 2012 and includes 2916 US firms. We find that Implied Cost of Capital has a stronger association with realized returns than CAPM and the Three-Factor model. Implied Cost of Capital also has lower abnormal returns not accounted for by expected returns. Our results suggest that we can replace CAPM and the Three-Factor model with Implied Cost of Capital.

x, 94 p. : ill. (some col.) / This paper examines how competition faced by firms affects asset risk and expected returns. Contrary to Hou and Robinson's (2006) findings, I find that cross-industry variation in competition, as measured by the concentration ratio, is not a robust determinant of unconditional expected stock returns. In contrast, within-industry competition, as measured by relative price markup, is positively related to expected stock returns. Moreover, this relation is not captured by commonly used models of expected returns. When using the Markov regime-switching model advocated by Perez-Quiros and Timmermann (2000), I test and find support for Aguerrevere's (2009) recent model of competition find risk dynamics. In particular, systematic risk is greater in more competitive industries during bad times and greater in more concentrated industries during good times. In addition, real investment by firms facing greater competition leads real investment by firms facing less competition, supporting Aguerrevere's notion that less competition results in higher growth options and hence higher risk in good times. / Committee in charge: Dr. Roberto Gutierrez, Chair; Dr. Roberto Gutierrez, Advisor; Dr. Diane Del Guercio, Inside Member; Dr. John Chalmers， Inside Member； Dr. Bruce Blonigen， Outside Member

This thesis analyzes the mean variance optimization problem with respect to cardinalityconstraints. The aim of this thesis is to figure out how much of an impact transactionchanges has on the profit and risk of a portfolio. We solve the problem by implementingmixed integer programming (MIP) and solving the problem by using the Gurobi solver.In doing this, we create a mathematical model that enforces the amount of transactionchanges from the initial portfolio. Our results is later showed in an Efficient Frontier,to see how the profit and risk are changing depending on the transaction changes.Overall, this thesis demonstrates that the application of MIP is an effective approachto solve the mean variance optimization problem and can lead to improved investmentoutcomes.

[pt] Desde sua proposição, na decada de 60, o modelo de apreçamento de ativos de capital e suas expansões, em particular a modelagem proposta por Fama e French entre os anos de 1992 e 2015, causou um entusiasmado debate sobre a interpretação econômica de seus fatores. Foi demonstrado na literatura acadêmica que variaveis que descrevem o conjunto das futuras oportunidades de investimento devem comandar um prêmio de risco e deveriam ser correlacionadas com os fatores de Fama e French. Uma outra questão sempre discutida é a aplicação desse tipo de modelagem à mercados emergentes. Economias mais fracas e menos estruturadas seguiriam a mesma racionalidade de mercados desenvolvidos? As expansões de Fama-French acrescentam ao modelo do CAPM fatores que representam o tamanho, o valor, a lucratividade operacional e a politica de investimento das empresas, em duas versões básicas de modelo. A primeira, proposta em 1993, acrescenta ao excesso de retorno de mercado um fator de tamanho e um fator de valor. É normalmente chamada de modelo de três fatores. A segunda, proposta em 2015, acrescenta a versão de três fatores um fator de lucratividade operacional e um fator de politica de investimentos das empresas. É normalmente chamada de modelo de cinco fatores. Com o uso desses modelos e dos conceitos financeiros envolvidos, esta tese estuda a possibilidade de que as inovações na variância média do mercado, decomposta em dois fatores, um representando a variação média do mercado e outro representando a correlação média do mercado, pudesse aumentar a capacidade explicativa do modelo de três fatores no que se refere aos excessos de retornos de portfólios de ações. Ela também estuda a capacidade do modelo de cinco fatores de melhor explicar o retornos dos portfolios de ações, em blocos econômicos de mercados emergentes, em relação ao CAPM original e ao modelo de três fatores. Finalmente, o estudo mostra que as inovações no indice de inflação e as inovações da inclinação da curva de juros são proxies para os fatores de tamanho, valor, lucratividade e investimento, e, em conjunto com o excesso de retorno do mercado, conseguem explicar o cross-section dos excessos de retornos dos portfólios de ações melhor do que o modelo de cinco fatores. / [en] Since its proposition in the 1960s, the capital asset pricing model and its expansions, in particular the modeling proposed by Fama and French between the years 1992 and 2015, caused an enthusiastic debate about the economic interpretation of its factors. It has been demonstrated in the academic literature that variables describing the set of future investment opportunities should command a risk premium and should be correlated with the Fama and French factors. Another issue that has always been discussed is the application of this type of modeling to emerging markets. Weaker and less structured economies would follow the same rationality of developed markets? Fama-French s expansions add to the CAPM model factors that represent size, value, operating profitability, and corporate investment policy in two basic model versions. The first, proposed in 1993, adds to the excess market return a factor of size and a factor of value. It is usually called the three-factor model. The second, proposed in 2015, adds to the three-factor version a factor of operational profitability and a factor of companies investment policy. It is usually called the five-factor model. With the use of these models and the financial concepts involved, this thesis studies the possibility that the innovations in the average market variance, decomposed into two factors, one representing the average market variation and another representing the average market correlation, could increase the explanatory capacity of the three-factor model with respect to the excess returns of stock portfolios. It also studies the ability of the five-factor model to best explain stock portfolio returns in emerging market economic blocks relative to the original CAPM and the three-factor model. Finally, the study shows that innovations in the inflation index and innovations in the slope of the interest curve are proxies for size, value, profitability, and investment factors, and, together with excess market returns, explains cross-section of excess returns on stock portfolios better than the five-factor model.