This study provide empirical evidence whether bias in the standard errors of Jensen’s alpha explains conflicting results in the extant literature in real estate funds. Significant alphas in real estate mutual funds and REITs are compared with heteroskedasticity consistent covariance matrix estimators (HC1, HC2 and HC3), Newey-West standard errors, a robust regression tempering the effect of high leverage points, a GARCH model, and a HC3 adjusted wild bootstrap. In the analysis of real estate mutual funds and a separate sample set of REITs, the HCCME had a minimal impact attenuating the number of firms with excess returns. Contrary to expectations the differences from HC1 to HC2 to HC3 were also negligible. The Newey-West standard error provided highly variable results when compared with the OLS results particularly in the REIT sample. Of the techniques to adjust for bias in the standard error, the wild bootstrap with HC3 adjustment to the standard error provided the most conservative result to the number of real estate mutual funds and REITs with significant alphas. The co-movement of real estate funds suggests common exogenous influences. Including state variables such as the changes in unexpected inflation, term spread, default spread, market skewness and industrial production growth in a multi-factor model is used to identify systemic economic factors in significant alphas. The significant alphas varied with the inclusion of these variables, the time period and the bias adjustment.

This dissertation consists of three essays. In the first essay, I estimate a high dimensional covariance matrix of returns for 88 individual stocks from the S&P 100 index, using daily return data for 1995-2005. This study applies the two-step estimator of the dynamic conditional correlation multivariate GARCH model, proposed by Engle (2002b) and Engle and Sheppard (2001) and applies variations of this model. This is the first study estimating variances and covariances of returns using a large number of individual stocks (e.g., Engle and Sheppard (2001) use data on various aggregate sub-indexes of stocks). This avoids errors in estimation of GARCH models with contemporaneous aggregation of stocks (e.g. Nijman and Sentana 1996; Komunjer 2001). Second, this is the first multivariate GARCH adopting a systematic general-to-specific approach to specification of lagged returns in the mean equation. Various alternatives to simple GARCH are considered in step one univariate estimation, and econometric results favour an asymmetric EGARCH extension of Engle and Sheppard’s model. In essay two, I aggregate a variance-covariance matrix of return risk (estimated using DCC-MVGARCH in essay one) to an aggregate index of return risk. This measure of risk is compared with the standard approach to measuring risk from a simple univariate GARCH model of aggregate returns. In principle the standard approach implies errors in estimation due to contemporaneous aggregation of stocks. The two measures are compared in terms of correlation and economic values: measures are not perfectly correlated, and the economic value for the improved estimate of risk as calculated here is substantial. Essay three has three parts. The major part is an empirical study of the aggregate risk return tradeoff for U.S. stocks using daily data. Recent research indicates that past risk-return studies suffer from inadequate sample size, and this suggests using daily rather than monthly data. Modeling dynamics/lags is critical in daily models, and apparently this is the first such study to model lags correctly using a general to specific approach. This is also the first risk return study to apply Wu tests for possible problems of endogeneity/measurement error for the risk variable. Results indicate a statistically significant positive relation between expected returns and risk, as is predicted by capital asset pricing models. Development of the Wu test leads naturally into a model relating aggregate risk of returns to economic variables from the risk return study. This is the first such model to include lags in variables based on a general to specific methodology and to include covariances of such variables. I also derive coefficient links between such models and risk-return models, so in theory these models are more closely related than has been realized in past literature. Empirical results for the daily model are consistent with theory and indicate that the economic and financial variables explain a substantial part of variation in daily risk of returns. The first section of this essay also investigates at a theoretical and empirical level several alternative index number approaches for aggregating multivariate risk over stocks. The empirical results indicate that these indexes are highly correlated for this data set, so only the simplest indexes are used in the remainder of the essay.

This dissertation consists of three essays. In the first essay, I estimate a high dimensional covariance matrix of returns for 88 individual stocks from the S&P 100 index, using daily return data for 1995-2005. This study applies the two-step estimator of the dynamic conditional correlation multivariate GARCH model, proposed by Engle (2002b) and Engle and Sheppard (2001) and applies variations of this model. This is the first study estimating variances and covariances of returns using a large number of individual stocks (e.g., Engle and Sheppard (2001) use data on various aggregate sub-indexes of stocks). This avoids errors in estimation of GARCH models with contemporaneous aggregation of stocks (e.g. Nijman and Sentana 1996; Komunjer 2001). Second, this is the first multivariate GARCH adopting a systematic general-to-specific approach to specification of lagged returns in the mean equation. Various alternatives to simple GARCH are considered in step one univariate estimation, and econometric results favour an asymmetric EGARCH extension of Engle and Sheppard’s model. In essay two, I aggregate a variance-covariance matrix of return risk (estimated using DCC-MVGARCH in essay one) to an aggregate index of return risk. This measure of risk is compared with the standard approach to measuring risk from a simple univariate GARCH model of aggregate returns. In principle the standard approach implies errors in estimation due to contemporaneous aggregation of stocks. The two measures are compared in terms of correlation and economic values: measures are not perfectly correlated, and the economic value for the improved estimate of risk as calculated here is substantial. Essay three has three parts. The major part is an empirical study of the aggregate risk return tradeoff for U.S. stocks using daily data. Recent research indicates that past risk-return studies suffer from inadequate sample size, and this suggests using daily rather than monthly data. Modeling dynamics/lags is critical in daily models, and apparently this is the first such study to model lags correctly using a general to specific approach. This is also the first risk return study to apply Wu tests for possible problems of endogeneity/measurement error for the risk variable. Results indicate a statistically significant positive relation between expected returns and risk, as is predicted by capital asset pricing models. Development of the Wu test leads naturally into a model relating aggregate risk of returns to economic variables from the risk return study. This is the first such model to include lags in variables based on a general to specific methodology and to include covariances of such variables. I also derive coefficient links between such models and risk-return models, so in theory these models are more closely related than has been realized in past literature. Empirical results for the daily model are consistent with theory and indicate that the economic and financial variables explain a substantial part of variation in daily risk of returns. The first section of this essay also investigates at a theoretical and empirical level several alternative index number approaches for aggregating multivariate risk over stocks. The empirical results indicate that these indexes are highly correlated for this data set, so only the simplest indexes are used in the remainder of the essay.

近年來由於市場型式為開放主體，在財務整合，商品區隔的環境下，投資人在進行投資時，應考量全方面的訊息，亦即國家內外部所有會影響股票市場的風險因子。而風險與報酬之間是否存在抵換關係，一直以來皆為備受討論的議題，從過去的文獻當中，研究者多以變異數作為衡量風險的代理，再透過各種不同的研究方法來估計風險報酬係數，但實證上並未獲得一致的結果。本文以1981年1月至2008年7月為研究期間，台灣與韓國之股價指數月資料為樣本，所使用之模型參考Turan G. Bali & Liuren Wu(2010)的研究論文，利用簡化過後的雙變量BEKK-GARCH(1，1)模型進行估計，探討台灣與韓國股票市場跨期收益與風險之關係。本文主要分為三大部分，首先先將台灣及韓國的股價指數以美元計價，針對全球市場觀察其風險以及持續性，並且利用共變異數來判別兩國股市分別為高風險或是低風險，再者，將台灣及韓國的股價指數分別以自己國家之幣別計算，將計算出之殘差估計個別國家股市風險，看是否兩國家內部的非經濟因素，例如:政治及軍事等，會影響股市的表現。最後一部份為前兩部分的整合，比較個別國家風險與全球市場風險對台灣及韓國股市的影響以及超額報酬與風險之間的抵換關係。實證結果顯示，不論就台灣或者是韓國而言，全球市場風險的風險與報酬係數皆為正向顯著，其中又以台灣之係數較為高，透露出若在承擔相同的全球市場風險時，台灣的投資人會較韓國的投資人要求較高的報酬。在匯率風險方面，本文採Turan G. Bali & Liuren Wu(2010)所使用的研究方法，將風險與報酬的抵換關係建立在不同國家的幣別之下進行估計，由結果發現，若以美元為單位來衡量風險報酬係數，則不論是台灣或韓國，在全球市場風險下，係數皆較小；若以個別貨幣來衡量，其台灣的風險與報酬抵換係數較大，韓國之係數則是由正值轉變為負值，代表匯率的確會對市場風險值有所影響，匯率風險是可以被定價的。 / In recent years, due to the opening of the markets, there are more and more choices in the investments. Investors should consider all aspects of information in this world with financial market integration but goods market segmentation. The intertemporal relation between risk and return in the stock market has been one of the most extensively studied topics in financial economics. The risk-return coefficients across different currency denomination change when considering different specification for the conditional covariance process. We used the bivariate BEKK-GARCH (1,1) model as the basic used in the reference by Turan G. Bali & Liuren Wu (2010) estimating the risk-return coefficients and measuring how this risk aversion estimate varies with different currency denominations. We started our analysis using monthly data from January 1981 to July 2008 on the Standard & Poor's 500 index, Taiwan stock exchange corporation and Korea composite stock price index. This article was divided into three parts. First, we computed monthly returns on the indices based on U.S. dollar denomination and calculated the excess returns as the index return minus the short-term interest rate. Second, we estimated the conditional covariances between the excess returns on the world market portfolio and the excess returns on two country indices using a bivariate GARCH specification. Third, we estimated the common relation of the equations implied by the international version of the intertemporal capital asset pricing model between the expected excess returns on those two country indices and the corresponding conditional covariances. After repeating the above procedure and estimating the intertemporal risk-return relation under different currency denomination, the empirical results showed that the risk-return coefficients in the world market portfolio was significantly positive in Taiwan and Korea. We also found that the coefficient was different based on different currency denominations on behalf of the exchange rate risk can be priced.

Although several studies have investigated commercial farmers’ risk preferences, there is still lack of information on the risk attitudes and risk preferences of smallholder farmers in South Africa. Risks associated with the adoption of new agricultural technology need to be explored in order to address the transition from homestead food gardening to smallholder irrigated farming. This study seeks to understand risk perception of smallholder irrigation farmers by linking constraints to commercialisation, adoption of new agricultural technologies and risk preferences of smallholder farmers in the Eastern Cape Province of South Africa. The overall objective of this research is to determine risk preference patterns and attitudes that influence the transition from homestead food gardening to irrigated farming of smallholder farming systems in the Eastern Cape province of South Africa. Specifically the study was to pursue the following objectives: (i) describe the demographic and socio-economic characteristics of smallholder farmers; (ii) describe existing farming systems among smallholder farmers in the study area; (iii) analyse the adoption of new agricultural technology by smallholder irrigation farmers; (iv) assess the risk perception of smallholder irrigation farmers and elicit farmers risk preferences, and (v) empirically analyse farmers sources of risk and risk management strategies. The outcome of this will inform policy formulation that have implications for technology adoption, increase smallholders capacity to bear risk and enable government and other role players have a clear understanding of smallholder farmers decisions. A total of 101 respondents were surveyed, consisting of 38 smallholder farmers and 63 homestead food gardeners in the Eastern Cape. Questionnaires were used to record household activities, socio-economic and institutional data as well as household demographics through personal interviews. The ordered probit model was applied due to the ordered nature of the dependent variable. The analysis was used to empirically analyse the determinants of farmers ‘risk preference status. The ordered probit model successfully estimated the significant variables associated with the farmer‘s adoption decisions. These were the farmer‘s age, household size, land size, locational setting, risk attitude, number of livestock (goats and chicken) and asset ownership. Homestead food gardeners were less risk averse that the smallholder farmers. Farmers who reside in the sub-wards Binfield and Battlefield were more likely to take risk than those who reside in Melani. This suggests the presence of local synergies in adoption which raises the question about the extent to which ignoring these influences biases policy conclusions. The negative correlation between land size and adoption implies that smaller farms appear to have greater propensity for adoption of new agricultural technology. This finding is supported by several studies reviewed in the literature that allude to the fact that homestead food gardeners tend to be smaller than smallholder farmers. By means of the Principal Component Analysis (PCA), seven principal components (PCs) that explained 66.13 percent of the variation were extracted. According to the loadings, the factors 1 to 7 can best be described as ‘financial and incentives index’, ‘input-output index’, ‘crop production index’, ‘labour bottleneck index’, ‘lack of production information index’, ‘lack of market opportunity index’, and ‘input availability index’ respectively. In general, price, production and financial risks were perceived as the most important sources of risk. Socio economic factors having a significant effect on the various sources of risk are age, gender, education, location, information access and risk taking ability. The most important traditional risk management strategies used by the surveyed smallholder farmers in Eastern Cape are crop diversification, precautionary savings and participating in social network. The findings are consistent with economic theory which postulates that in the absence of insurance markets, poor farm households tend to be risk averse and are reluctant to participate in farm investment decisions that are uncertain or involve higher risk.

A new hypothesis, The Adaptive Markets Hypothesis (AMH), is applied to the Swedish stockmarket context by testing the variability of the risk-return trade-off over different investment horizons and market environments. Yearly returns and volatility are measured on OMXS30 index between1986 and 2017 over a variety of different investment horizons. Through the sample observations, a number of distinct market environments become apparent. A regression analysis is then used to test the statistical significance of the risk-return relationship. The results show a weak – and varying – statistical relationship between risk and return, implying that risk is not a reliable explanatory variable for average returns. The length of the investment horizon and the market environment the investment is being made in are shown to be influential factors on changes to the risk-return relationship. These findings from the OMXS30 index support the AMH, showing that the risk-return relationship is dynamic and subject to changes over different investment horizons and in different market environments.

Cette thèse est construite autour de trois essais empiriques centrés sur l'efficience rendement risque des banques européennes cotées et sur la tarification des obligations qu'elles émettent. Avec le premier essai, on mesure l'aptitude relative des banques à choisir efficacement le couple rendement / risque. On montre que cette aptitude relative est stable, surtout à court terme et que les banques les plus efficaces dans leurs choix rendement / risque partagent des caractéristiques communes et bénéficient d’une notation de solidité plus avantageuse. Le second essai apporte la preuve que l'introduction de cette mesure d'efficience du choix rendement / risque améliore de manière sensible l'explication de la prime de défaut qu'exigent les investisseurs sur les obligations émises par les banques et que les mesures traditionnelles du risque de défaut ne captent pas à elles seules l’intégralité de la prime de défaut. En outre, la capacité des banques à gérer efficacement le couple rendement / risque s’avère être un élément déterminant de la confiance que mettent les détenteurs d'obligations dans la mesure du risque effectif de défaut des banques. Avec le dernier essai on traite des conséquences d'une éventuelle divergence entre droits de contrôle et droits pécuniaires des actionnaires ultimes des banques sur la tarification des obligations qu'elles émettent. Si les obligataires ne semblent pas sensibles à une telle divergence avant la crise financière, les résultats montrent en revanche qu’ils le deviennent pendant la crise en exigeant un spread d'autant moins élevé que cette divergence est plus prononcée. Il est intéressant de noter que ce résultat ne tient que lorsque les banques font face à un risque de défaut élevé. / This thesis consists of three empirical essays with an emphasis on bank risk-return efficiency and bond pricing. Chapter 1 aims at a better understanding of the quality of banks’ risk management by providing, for a set of European listed banks, a measure of each bank’s relative efficiency in terms of risk-return trade-off. We show that the level of bank risk-return efficiency is quite stable in the short term, whereas in the long term low performing banks are not condemned to remain inefficient. We also identify some common characteristics for the most risk-return efficient banks, which are assigned, by rating agencies, a more attractive financial strength rating. In chapter 2, we investigate the determinants of bank bond spread and we show that bank managerial ability, proxied by bank risk-return efficiency, improves the explanation of the default premium required by bondholders. Our results underline that standard default risk measures do not entirely reflect the default premium and banks’ managerial ability turns out to be a determinant of bondholders’ confidence in the measure of the effective level of bank default. Chapter 3 examines the effect of divergence between control rights and cash-flow rights of ultimate owners in pyramid ownership structure on the pricing of banking bonds. Whereas before the financial crisis such a divergence does not affect bank bond yield spread, during downturns bondholders require a lower spread from banks controlled by an ultimate owner with excess control rights. The investigation on more restrictive subsets underlines that this result is only significant when banks experience a high level of default risk.

The purpose of this investigation was to test the theoretical possibility of an investor earning a positive cash return from the activities of the stock market despite effectively holding no position at all in said market. The sample data were the daily returns for the shares of the 780 companies listed on the NASDAQ and the New York Stock Exchange (“NYSE”), which fell within the top 500 listed companies by market capitalisation between 1 January 2005 and 31 December 2017. The reversal strategy’s performance was evaluated using portfolios constructed as quantiles of 100 or 500 shares, respectively, where the investor had the option of implementing the reversal strategy immediately after an information-gathering period closed or a day thereafter. The time intervals used were 1 January 2005 to 29 September 2008 (the day the Dow Jones Industrial Average crashed by 777.68 points), 29 September 2008 to 31 December 2017 and 1 January 2005 to 31 December 2017. Of the 1000 portfolios tested in each time interval, at least 416 had positive average returns in every time interval. Of the portfolios that had positive average returns over the time intervals, at least 66 had statistically significant average returns in every time interval. The best-performing portfolio for the entire sample period was a combination of the best-performing pre-crash and post-crash portfolios - an investor who held that portfolio realised a cumulative return of approximately $61.39 for every $1 invested. The conclusion was that it was theoretically possible for an investor to earn a positive cash return from the market’s activities despite effectively holding no position at all in the market. Consequently, it was concluded that the strong form of Fama’s (1970) Efficient Market Hypothesis was disproved. Future research should include out-of-sample tests, tests that include restrictions on short selling and tests that consider the impact of trading costs on portfolio performance, to render the conclusions of this investigation more practically applicable to investors.

We uses ESG thematic funds to conduct a detailed statistical profile of their operating status in the Chinese market, including the size, the proportion of different investment types, and the characteristics of return and risk. The OLS model is used to empirically analyze the applicability of the Fama-French five-factor model in the Chinese mutual fund market. Based on the a ESG rating as a starting point, we study the profit improvement mechanism and risk-return characteristics of the ESG portfolios. The main findings are that the five-factor model better explained the excess returns of ESG thematic funds during the entire sample period of the study and can be used for attribution analysis of the performance. It shows that, despite the poor performance of ESG thematic funds in the market during certain periods, there is no significant difference between the performance of ESG thematic funds and the market during the economic crisis. The ROEs and dividend rates of the ESG high-scoring groups are both higher than those of the ESG low-scoring groups. This shows that companies with higher ESG scores have higher and more sustainable profitability and greater willingness to pay dividends. Furthermore, the ESG high-scoring group has better returns and lower risks. / Business Administration/Finance

The main purpose of this dissertation is to lessen the gap in the Islamic finance and investment literature by providing new answers to the most vital question raised in that literature: Is the adherence to the Shariah law associated with at any cost? The first chapter provides a primer on Islamic finance. It discusses several restrictions and necessary adaptations that must be made to have a Shariah-compliant product. The takeaway is that Shariah law mandates is related to fundamentals and, thus has a direct effect on the risk-return profile of all sorts of different products. This is referred to as the “Islamic-effect.” The second chapter investigates that Islamic-effect in a cross-sectional stock return context. This is done in two steps. First, looking at differences in stock returns between Islamic and conventional firms in Saudi Arabia during the period from January 2003 to April 2011. Results indicate that there is a negative relationship between Saudi Islamic firms and average returns. This is referred to as the “negative Islamic-effect.” Second, examine whether that negative Islamic-effect is considered a common, systematic, and undiversified risk factor that affects cross-sectional expected stock returns. Time-series regressions results indicate that the Islamic risk factor (CMI) does indeed capture strong common variation in Saudi stock returns regardless what is included in the model. Also, findings suggest that using a four-factor model that controls for the Islamic-effect is more appropriate than using a single- or a three-factor model in Islamic finance applications that require estimates of expected stock returns. The third chapter investigates the Islamic-effect in a mutual fund context. A unique sample of 143 Saudi mutual funds (96-Islamic and 47-conventional) is used to assess the performance and riskiness of Saudi Islamic funds relative to Saudi conventional funds and relative to different Islamic and conventional indices for the period from July 2004 to January 2010. Findings suggest that there is a benefit (cost) from adhering to the Shariah law when locally-focused (internationally-focused) fund portfolios are investigated. When Arab-focused fund portfolios are investigated, findings suggest that there is neither a cost nor a benefit from adhering to the Shariah law.