The efficient market hypothesis and behavioural finance have been the cause of much debate for decades, with one theory advocating market efficiency and the other opposing it. The efficient market hypothesis (EMH) assumes that investors always act rationally and stock prices adjust rapidly to new information and should reflect all available information. In contrast, behavioural finance suggests that markets are not rational and investors make irrational decisions, which may lead them to over- or under-price stocks. Researchers for years have been empirically testing these assumptions in stock markets. However, there has been no consensus on which asset-pricing models perform better in capturing the effect of market anomalies and what impact these market anomalies have on the expected returns of different stock market’s sectors. The aim of the study was to test the effect of selected market anomalies on expected return in different sectors of the Johannesburg Stock Exchange (JSE). More specifically, the study aimed to compare the performance of different asset-pricing models and their ability to account for market anomalies in different sectors of the JSE. Additionally, this study tested the applicability of the recent Fama and French five (FF5-factor) model, in estimating the expected return on the JSE. The study used a quantitative approach with secondary data over a period of 12 years starting from January 2002 to December 2014. The sample used in the study consists of monthly data obtained from McGregor BFA and the South African Reserve Bank. The study examined for the effects of size, value, January and momentum variables across six sectors of the JSE. This was accomplished by the use of various asset-pricing models such as the Capital asset pricing model (CAPM), the Fama and French three-factor model (FF3-factor), the Carhart four-factor model (C4F) and the recent five-factor model of Fama and French (FF5-factor). The study showed that whenever the asset-pricing models were not restricted, they tend to capture the market anomalies in four out of the six sectors examined. However, no market anomalies were found present in two of the six sectors analysed. In contrast, when the asset-pricing models are restricted, the asset-pricing models only seem to capture the effects of market anomalies in one of the six examined sectors. The findings in this study suggest that market anomalies are sensitive to model specifications, as restricting the models tends to capture the different market anomalies across the sectors of the JSE. The study also found that market anomalies differ across sectors and that some sectors are more efficient than others. The study also reveals that the FF5-factor model is able to account for expected returns on the JSE. In addition, the FF5-factor model tends to perform better when the model is restricted. It is also evident from the findings presented in this study, that the value anomaly loses its predictive power when profitability and investment variables are included in the model. Overall, the study illustrated that market anomalies have an effect on returns of the JSE, that the model specifications play an important role in an asset-pricing model and that the FF5-factor model is applicable on the JSE, however, it is not certain whether four or five factors apply to the South African market.

Texas’ Mass Emission Cap and Trade program is a mandatory Nitrous Oxide (NOx) abatement program for medium and large stationary sources located in the Houston-Galveston ozone non-attainment area. Effected companies are required to upgrade equipment to meet the current best achievable NOx control technology (BACT) standards or to purchase emission credits in sufficient quantity to cover the difference in emissions between existing equipment and equipment meeting the BACT standard. With over 260 participating companies, the market for emission credits is ever changing, making it difficult to evaluate whether the lowest cost decision is to upgrade equipment or to purchase NOx emission credits. Because equipment upgrades are capital investments, a well informed, rational decision can have a significant impact on the corporate balance sheet. The objective of this research is to aid the decision maker by predicting credit prices based on a Geometric Brownian Motion model based on historical NOx emission credit transactions. The predicted credit price is useful in evaluating the likelihood of the equipment upgrade option being a favorable or unfavorable decision. For the examined cases, modeled results indicate that equipment upgrade is the more cost effective option. / text

The importance of a well-functioning housing market has been proposed for long within economics, economic geography and urban planning.  A high mobility on the housing market most likely positively affects the dynamics of the labor market, a dynamic important for economic growth. Mobility defined as the link between the worker and the workplace in terms of transportation and housing are most likely essential components of a dynamic and well-functioning labor market. The Oswald hypothesis states that positive relationship between homeownership and unemployment exists, the lower mobility in the homeownership housing stock compared to the rental housing stock affects labor market mobility in a negative way which can be noted if European countries are compared. My thesis explores this relationship in a Swedish context by mobilizing a quantitative approach with aggregate data on municipal level ranging from 1998 to 2013. The Swedish housing market is in a deregulation process since 1992, a conversion process from public rental housing to homeownership co-op apartments has taken place and public policies now favor homeownership over renting. Municipal data on unemployment, homeownership of apartment, rental tenant and control variables for economy and personal characteristics are applied in Pooled OLS, random effects and fixed effects regression models. The results from the Pooled OLS and the Random effects model confirms the positive relationship proposed by Oswald for homeownership of apartment but not for homeownership of detached housing. Also rental tenant show a positive relationship. The results from the fixed effect estimation rejects the hypothesis altogether and show a negative relationship.

This study is concerned with developing a new methodology or "tool" with the use of existing market, research techniques which should enable a firm to measure its market potential and test the validity of its existing market segments.

The aim of this thesis is to examine the direct effects of labour market institu- tions on unemployment rates in the selected EU Members. For this purpose, we use macroeconomic cross-country, time series analysis for 21 OECD European members over the 2001-2011 period. The results gained from our empirical ana- lysis are rather inconclusive over the possibility to explain the development of European unemployment solely by analysing the effects of labour market insti- tutions. This finding might as well be caused by the volatile evolution of both output and unemployment over the observed period. The importance of busi- ness cycle is confirmed by our results as the measure for the output gap appears highly significant in every model specification. Unlike the majority of previous literature, in our estimates the proxies for macroeconomic shocks do not turn out to be significant. Hence, we decided not to examine mutual interactions between macroeconomic shocks and institutions. JEL Classifications: J08, J30, J51, J64 Keywords: unemployment, labour market institutions, EU, active labour mar- ket policies Author s e-mail: janhnevkovsky@gmail.com Supervisor s e-mail: strielkowski@fsv.cuni.cz 1

The objective of the thesis is to analyze the copper futures market in London Metal Exchange (LME) and to recommend appropriate hedging strategy in copper futures market to the Erdenet Mining Corporation in Mongolia. It uses daily official settlement copper prices of LME in the spot and 3 month futures markets from 2000-2014. Initially, we use cointegration test and ECM to investigate the copper market efficiency. Then OLS, ECM, GARCH, EGARCH and ECM-GARCH models are employed to compute different optimum hedge ratios. Finally, the hedge effectiveness is measured based on minimization of the value of AIC and SBIC. Our result indicate that copper futures market is inefficient. Hedge effectiveness comparison concludes that ECM model gives the best hedging performance. However, ECM-GARCH is accounted to be the best model for hedging strategy since it captures the time-varying conditional heteroscedasticity to ECM model. Powered by TCPDF (www.tcpdf.org)

M.Com. (Investment Management) / When the mechanics of the capital market are researched it is important to emphasize the structure and operations of this market in relation to the financial system in its totality. A clear understanding of the division of the capital market in a fixed-interest rate securities market and a market for variable interest rate securities is of the utmost importance for the insight to the operations of the capital market. Both these divisions of this market are also divided in a primary market as well as a secondary market ...

Thesis (M.M. (Finance & Investment))--University of the Witwatersrand, Faculty of Commerce, Law and Management, Graduate School of Business Administration, 2013. / The evidence put forward by Zhang (2010) indicates that algorithmic trading can potentially generate the momentum effect evident in empirical market research. In addition, upon analysis of the literature, it is apparent that algorithmic traders possess a comparative informational advantage relative to regular traders. Finally, the theoretical model proposed by Wang (1993), indicates that the informational differences between traders fundamentally influences the nature of asset prices, even generating serial return correlations. Thus, applied to the study, the theory holds that algorithmic trading would have a significant effect on security return dynamics, possibly even engendering the momentum effect. This paper tests such implications by proposing a theory to explain the momentum effect based on the hypothesis that algorithmic traders possess Innovative Information about a firm’s future performance. From this perspective, Innovative Information can be defined as the information derived from the ability to accumulate, differentiate, estimate, analyze and utilize colossal quantities of data by means of adept techniques, sophisticated platforms, capabilities and processing power. Accordingly, an algorithmic trader’s access to various complex computational techniques, infrastructure and processing power, together with the constraints to human information processing, allow them to make judgments that are superior to the judgments of other traders. This particular aspect of algorithmic trading remains, to the best of my knowledge, unexplored as an avenue or mechanism, through which algorithmic trading could possibly affect the momentum effect and thus market efficiency. Interestingly, by incorporating this information variable into a simplified representative agent model, we are able to produce return patterns consistent with the momentum effect in its entirety. The general thrust of our results, therefore, is that algorithmic trading can hypothetically generate the return anomaly known as the momentum effect. Our results give credence to the assumption that algorithmic trading is having a detrimental effect on stock market efficiency.

In recent times the emergence of the property cycle and the effects that it has on the property market has caused the relevant parties involved in the market to start placing more emphasis on how these cycle works. The overall objective of this study is to try establish if the interpretation of market related data affects at what position these parties are relative to one another on the property curve. The study concentrates on the use of market indicators, indices and variables in trying to determine an individual’s position on the property market curve. It also concentrates on how this market data is retrieved and what effect it has on how they interpret the data. The methodology adopted for this study involves the collecting and interpretation of market related indices and indicators relevant to the property market over a ten year period from 1996 through to 2006. This data was then used to establish the key indicators used. A questionnaire was sent out to the relevant parties involved in the property market to ascertain the extent of what the main sources of market information are and how this data is collected and interpreted. This was limited to individuals in the Gauteng region. The data was examined and collected in the form of line graphs, histograms and pie charts. The data was then examined and presented in four areas: the major sources of information used by parties for market related data, to try and establish where these parties are relative to one another on the property curve, the effect that the different types of sources of information has on each party and finally to try determine by how much these parties lag or lead one another on the curve.

Faculty of Science School of Statistics and Actuarial science 9802374m nhuang@glenrandmib.co.za / The purpose of this research report is to review the embedded value concept and to examine its practical use in South Africa. Important recent developments relating to the embedded value concept are discussed and compared with the existing embedded value concept. These developments include fair value accounting, market-consistent embedded value and the European Embedded Value Principle. In the second part of the report, the disclosure of the embedded value information of four major South African life assurance companies is examined. It was found that the market capitalisations of these companies were smaller than their embedded values for most of the period under the investigation. Reasons for this phenomenon are considered and tested against the data available. It was found that the risk discount rates used by some life assurance companies in calculating their embedded values may be too low. It appears that a ‘herding’ tendency exists among South African life assurance companies when selecting risk discount rates for the embedded value calculation. It is suggested that a more market consistent approach for the embedded value calculation and a better disclosure for the embedded value reporting should be considered by life assurance companies in South Africa. This should improve investors’ understanding and confidence in the embedded value disclosed, which in turn should help narrow or eliminate the discount of the market capitalisation to the embedded value observed in the market.