Risk-return tradeoff and the behaviour of volatility on the South African stock market: Evidence from both aggregate and disaggregate data

The study analyses the nature and behaviour of volatility, the risk-return relationship and the long-term trend of volatility on the South African equity markets, using aggregate-level, industrial-level and sectoral-level daily data for the period 1995-2009. By employing dummy variables for the Asian and the sub-prime financial crises and the 11 September political shock, the study further examines whether the long-term trend of volatility structurally breaks during financial crises and major political shocks. Three time-varying GARCH models were employed: one of them symmetric, and the other two asymmetric. Each of these models was estimated based on three error distributional assumptions. The findings of the study are as follows: Firstly, volatility is largely persistent and asymmetric. Secondly, risk at both the aggregate and disaggregate level is generally not a priced factor on the South African stock market. Thirdly, the TARCH-M model under the Generalised Error Distribution is the most appropriate model for conditional volatility of the South African stock market. Fourthly, volatility generally increases over time and its trend structurally breaks during financial crises and major global shocks. The policy and investment implications of the findings are outlined.Risk-return tradeoff, stock market volatility, asymmetric GARCH models

Adaptive development and maintenance of user-centric software systems

A software system cannot be developed without considering the various facets of its environment. Stakeholders – including the users that play a central role – have their needs, expectations, and perceptions of a system. Organisational and technical aspects of the environment are constantly changing. The ability to adapt a software system and its requirements to its environment throughout its full lifecycle is of paramount importance in a constantly changing environment. The continuous involvement of users is as important as the constant evaluation of the system and the observation of evolving environments. We present a methodology for adaptive software systems development and maintenance. We draw upon a diverse range of accepted methods including participatory design, software architecture, and evolutionary design. Our focus is on user-centred software systems

The Early Development of the Steam Engine: An Evolutionary Interpretation using Complexity Theory

complexity theory, development, steam engine

Data mining technology for the evaluation of learning content interaction

Interactivity is central for the success of learning. In e-learning and other educational multimedia environments, the evaluation of interaction and behaviour is particularly crucial. Data mining – a non-intrusive, objective analysis technology – shall be proposed as the central evaluation technology for the analysis of the usage of computer-based educational environments and in particular of the interaction with educational content. Basic mining techniques are reviewed and their application in a Web-based third-level course environment is illustrated. Analytic models capturing interaction aspects from the application domain (learning) and the software infrastructure (interactive multimedia) are required for the meaningful interpretation of mining results