M.Sc.

While the Efficient Market Hypothesis (EHM) has been widely accepted as robust by many researchers in the field of capital markets, the hypothesis’ robustness has been under increased scrutiny and question lately. In the light of the concerns over the robustness of the EMH, the weak form efficiency of the JSE is tested. Stock returns used in the analysis were controlled for thin trading and it was discovered that once returns are controlled for thin trading, they are independent of each other across time. Some of the previous studies found the JSE to be inefficient in the weak form but this research found that the JSE is efficient in the weak form. A comparison is also made between the JSE and four other African stock markets and the JSE is found to be more efficient than the other markets. The developments on the JSE, which have improved information dissemination as well as the efficiency of trading, contributed to the improvement of the JSE’s efficiency. The improvement in operational efficiency and turnover from the late 1990s has also made a major contribution to the improvement in the weak form efficiency of the JSE. Theory proposes that if markets are efficient then professional investment management is of little value if any; hence the position of professional investment managers in efficient markets is investigated. Although the JSE is found to be efficient, at least in the weak form, it is argued that achieving efficiency does not necessarily make the investment manager’s role obsolete. Investment managers are needed even when the market can be proved to be efficient.

The nation’s economy depends heavily on mobility of goods and people. As communities look to improve mobility, many options can be considered, including roadway improvements, congestion-pricing options such as dynamic tolling and toll lanes, and public transit. Investment in public transit services can come in the form of increased and enhanced bus services, including bus rapid transit (BRT), as well as rail transit investments. As BRT continues to grow in popularity in the United States, a better understanding of the mode’s impacts on land uses and economic development is needed. One method of assessing the mode’s impacts is by examining the market value of properties with access to BRT stations. Based on land-rent theory, it is hypothesized that people will be willing to pay a premium for convenient and reliable access via BRT to the central business district (CBD) or other locations with employment, educational, recreational, and shopping opportunities. Very little research has been conducted on BRT as it operates in the present day in the United States. For this work, the hypothesis is that the BRT stations have a positive impact on the market value of residential properties. To test this hypothesis, hedonic price regression models are used to estimate the impact of access to BRT stations on the sale prices of surrounding single-family homes using a case study of the HealthLine BRT system in Cleveland, Ohio that began operating in 2008. Three time periods were examined: 2004, the year construction began; 2008–2009, after the HealthLine BRT service began operation; and 2010–2011, the latest year for which sales data are available. Despite a documented decline in median sale prices of single-family homes in the city of Cleveland from 2005 to 2011, overall results of the analysis were mixed. Although it was prior to the opening of the BRT system, the 2004 data did not show any impacts of the stations on surrounding home sale prices. For the 2008–2009 data, positive and statistically significant impacts were found; however, the positive impacts did not persist in the 2010–2011 data. It would likely be necessary to seek out additional years of data to fully answer the question posed by this research. It is important for decision-makers to have the most accurate and most recent information on the benefits and costs of all transportation alternatives, including BRT. The research presented herein makes a significant contribution to filling the current gap in quantitative research on the subject and provides planners, policymakers, and the transit industry with the best information possible to make sound transit investment decisions in their communities.

Whether investor sentiment has any authority over financial markets has long been a topic of discussion in the field of finance. This study investigates the relationship between investor sentiment and share returns in South Africa. Determining this relationship will add to the existing work which has documented important determinants of share returns on the stock exchange in South Africa, as well adding to the inconclusive link between sentiment and the South African financial markets. Does sentiment influence share returns or do share returns influence sentiment? Using quarterly data for the period 1996-2010, the study makes use of the FNB/BER Consumer Confidence Index as a proxy for investor sentiment, and the FTSE/JSE All Share Index to represent the South African financial markets. A regression analysis was conducted along with granger-causality tests, impulse response functions and variance decompositions in order to determine the nature of this relationship. The results showed that investor sentiment has a statistically significant relationship with share returns in South Africa. However, sentiment is only able to account for a very small portion of the variation in returns, with returns able to account for a larger portion of the variation in sentiment. Therefore investor sentiment is not a suitable predictor of share returns in South Africa. In addition, granger-causality tests indicate that returns are actually the leading indicator, suggesting that changes in South African investors’ confidence levels occur following changes in the state of the JSE. The limitations of the study include the infrequent nature of the sentiment measure used, thereby failing to capture important changes in sentiment and their immediate impact on financial markets. In addition, the sentiment of foreign investors must be taken into account due to the large foreign investment in the JSE.

Stock return volatility has been shown to occasionally exhibit discrete structural shifts. These shifts are particularly evident in the transition from ‘normal’ to crisis periods, and tend to be more pronounced in developing markets. This study aims to establish whether accounting for structural changes in the conditional variance process, through the use of Markov-switching models, improves estimates and forecasts of stock return volatility over those of the more conventional single-state (G)ARCH models, within and across selected African markets for the period 2002-2012. In the univariate portion of the study, the performances of various Markov-switching models are tested against a single-state benchmark model through the use of in-sample goodness-of-fit and predictive ability measures. In the multivariate context, the single-state and Markov-switching models are comparatively assessed according to their usefulness in constructing optimal stock portfolios. It is found that, even after accounting for structural breaks in the conditional variance process, conventional GARCH effects remain important to capturing the heteroscedasticity evident in the data. However, those univariate models which include a GARCH term are shown to perform comparatively poorly when used for forecasting purposes. Additionally, in the multivariate study, the use of Markov-switching variance-covariance estimates improves risk-adjusted portfolio returns when compared to portfolios that are constructed using the more conventional single-state models. While there is evidence that the use of some Markov-switching models can result in better forecasts and higher risk-adjusted returns than those models which include GARCH effects, the inability of the simpler Markov-switching models to fully capture the heteroscedasticity in the data remains problematic.

The day-of-the-week effect in share prices is one of the most extensively researched anomalies, especially in developed markets. However, emerging African stock markets have received little attention in this regard. This study breaks new ground in using non-parametric tests directly on skewness and kurtosis to examine whether the day-of-he-week effect exists in nine listed stock market sector indices of the JSE Securities Exchange of South Africa (JSE). Different day-of-the-week effects were found to be present in the statistical moments of returns of these nine JSE sectors

This study investigates the existence of the value premium in South Africa’s equity market, and tests extrapolation as a possible explanation for it. The value premium refers to the widely reported superior performance of share price returns of value companies compared to growth companies. The value premium represents an anomaly in mainstream rational finance theory, because it should not persist, unless it could be explained as the result of some composite form of risk. What is highly vexing is the fact that the value premium not only persists in most financial markets over a long period, but that the risk explanation cannot be upheld convincingly. This contributed to the rise of behavioral finance, an approach which introduces psychological factors to provide new explanations for financial phenomena. The behavioral finance explanation for the value premium observation is extrapolation (the tendency to project recent experience too far into the future). This study applies propositions and methods from behavioral finance to investigate the South African equity market. The existence of a value premium in South Africa was investigated by using twenty-nine years’ worth of accounting and share price data. The study employed one- and two-dimensional tests for portfolio formation, and tracked share price returns for up to five years after portfolio formation. The results indicated that a statistically and economically significant value premium existed in South Africa for the period between 1972 and 2001. Extrapolation as a potential explanation for the value premium observation was investigated by applying internationally used methods. Extrapolation was found to provide a robust explanation for the South African value premium.

This paper presents the results of a study dealing with a number of issues regarding real estate investment. Utilizing a data set consisting of real estate transactions, questions relative to the impact of certain variables on the sale price are addressed. This analysis addresses the question of the impact of financial, physical, and location characteristics on the sales price of commercial grade real estate.

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

Sports facilities increasingly feature amongst the most expensive development projects world-wide. One such facility includes world-class stadia. Such facilities tend to commit a considerably large amount of a country's public funds to the project. This public expenditure on new stadia, and the required public taxation, may be economically justified if the benefits from the new stadia outweigh the costs. 15 May 2004 saw South Africa winning the bid to host the FIFA 2010 Soccer World Cup tournament. This mega-event was played in 10 stadia across nine chosen host cities. Five of these stadia were newly constructed, while the other five needed upgrading. Both South Africa's national government and local governments of host cities bore the expenses of the new stadia construction and the upgrading to the existing stadia. This amounted to a total public expenditure of R13.5295 billion on the stadia alone. The Nelson Mandela Bay Stadium on the banks of the North End Lake in Port Elizabeth was amongst the five newly constructed stadia costing R1.7 billion. Many international studies have been conducted to assess the impact of new stadia on the economies of host cities. One particular aspect which has received a lot of attention as far as empirical research is concerned is the impact of stadia on residential property prices (Carlino & Couslon, 2004; Davies, 2005; Tu, 2005; Coates & Humphreys, 2006; Ahlfeldt & Maennig, 2007, 2010; Dehring, Depken & Ward, 2007; Feng & Humphreys, 2008, 2012; Kavetsos, 2010; Ahlfeldt, Maennig & Scholz, 2010; Kiel, Matheson & Sullivan, 2010; Ahlfeldt & Kavetsos, 2011; Coates & Matheson, 2011). The majority of the studies conducted have indicated that the presence of a new stadium in an area has a significantly positive effect on surrounding house values that decays with distance from the facility. As no study has yet been done in South Africa to investigate the impact of the announcement of the construction of new stadia on nearby residential property values, this study examines, by means of the hedonic pricing model, the effect of the announcement to construct the Nelson Mandela Bay Stadium on the banks of North End Lake on adjacent residential property values. The study period for this study was 2004 - 2006. This time period captured the stadium announcement effect. The residential properties in North End that were traded at least once during the period 2004 to 2006 made up the target population. According to the South African Property Transfer Guide (SAPTG), a total of 417 property transactions (excluding repeat sales) took place over the study period (2004 - 2006). The 417 transactions were deemed to be the size of the target population and a list of 100 property transactions were used as the sampling frame. As the study period was from 2004 - 2006, it was necessary to adjust the market prices to constant 2006 prices. For this purpose, data from the Port Elizabeth and Uitenhage section of the ABSA house price indices were used so as to eliminate any inflationary effects on the property values over the study period. The results of the study revealed that the stadium has a statistically significant positive effect on adjacent residential properties situated within a 1 200 metres radius from the stadium. The average owner of a residential property in North End would be willing-to-pay between R10 7898 and R11 704.6 to be situated 435 metres closer to the stadium.