M.Com. (Econometrics) / This dissertation investigates the ability of different models to predict a recession in South Africa (SA) by choosing a best performing model based on the smallest prediction errors made by the models. One of the purposes of using econometric models is to predict a recession, with the goal to uncover the probability of a recession or real GDP growth rate as accurately as possible. Although linear and non-linear models prediction strength is frequently compared, none of the studies within SA compare the prediction ability of the four models used in this dissertation. The intent of this research is to ascertain the best prediction model for SA so as to advise policy makers on the soundest model to use if there is suspicion that SA could enter a recession in the future due to global and domestic uncertainty. This is done by comparing the prediction ability of the linear ARIMA, VAR and ARMV models’ and non-linear dynamic probit model; thereby contributing toward the standing literature. It is verified which model outperforms the others in predicting future real GDP growth by comparing the Mean-Square-Error (MSE), Mean-Absolute-Error (MAE) and RMSE percentage. The importance of predicting real GDP growth is accentuated so that policy makers are in the position to develop or apply policies that can stimulate growth in the economy, should a recession occur. By adding dynamics to the system, predictions are improved. The linear VAR model outperforms the other linear and non-linear model based on the RMSE, MAE and RMSE percentage.

No description available.

M.Com. (Economics) / Please refer to full text to view abstract

M. Tech. Business Administration / Financial distress and bankruptcy is one of the most significant threats to the going concern of many businesses, irrespective of their size and nature of operations. Research in corporate financial distress and corporate failure prediction dates back to the mid-sixties, and the bulk of the studies have been conducted within the context of highly developed market economies. Very little research has been conducted within the context of emerging markets, and using small and medium-sized firms. This therefore encouraged the author of this research report to conduct a study, applying a model specifically developed for emerging economies to predict financial distress of small and medium-sized South African listed firms. The main purpose of this study is to examine whether a model designed for financial distress prediction and credit scoring in emerging markets is reliable, and can be accurately applied in South Africa.

Thesis (D.Tech degree in Information Technology)--Tshwane University of Technology, 2012. / In this study an interactive scenario analysis technique was developed and tested to forecast e-skills development in South Africa. The developed technique integrates qualitative and quantitative assumptions to improve the forecasting process. Improving the forecasting process is generally an open discourse, given that many organizations use techniques that were rejected from an academic perspective. The extant scenario analysis techniques that integrated quantitative and qualitative assumptions often will trade-off participation of decision makers and rely on experts. The conception of this work was based upon the preliminary analysis conducted on the strengths and weaknesses encountered in the previous forecasting studies. The goal was to evolve a new technique that demonstrates how scenario-based forecasting process can be practically improved by the inclusion of constructs that promote a comprehensive participatory model. The integration of constructs to support a team of decision makers and experts to engage in a participatory forecasting process has demonstrated considerable improvement and acceptance of results by decision makers. The cardinal contributions of this study are the merging of qualitative intuitive logic and quantitative cross-impact analysis to improve forecasting process, the quantification of scenarios to better convey meaningful information and the unique application of the developed technique to forecast demand-supply of e-skills development in South Africa.

M.Comm. / The fundamental objective of this paper is to effectively analise and forecast currency option volatility in the South African derivative market. The study of Dollar/Rand volatility is based in the domain of quantitative and international economics. It focuses on the monetary aspect of international finance, where currency volatility is of critical significance in the hedging of open currency option positions used in investment strategies as well as in active currency risk management. Topics covered in this study include firstly a theoretical discussion of option pricing and volatility to provide the necessary financial and statistical background: Advanced volatility issues are secondly addressed to define the volatility matrix and to explain the appearance of volatility smiles and cones as well as the characteristics of the time structure of volatility. The use of volatility as an important risk management tool is also depicted. Various time-series techniques such as the Box Jenkins methodology and decomposition of Dollar/Rand historical and implied volatility are assessed and used to forecast volatility. Univariate and multivariate regression analysis is in addition described and used to find the best estimate for subsequent Dollar/Rand volatility. Finally, the paper is concluded by an analysis of time varying stochastic volatility models such as the models for autoregressive conditional heteroscedasticity. The techniques apply a regression on the variance and include a function to allow for the asymmetric nature of movements in Dollar/Rand volatility. Up to date, no formal in-depth academical research on high frequency currency volatility has been conducted in the South African derivative market. It is therefor crucial to research the unique characteristics of Dollar/Rand option volatility. If the study concludes that Dollar/Rand volatility is predictable, it will have important implications for currency option pricing and portfolio management. Investors seeking to avoid risk, may choose to adjust their portfolios by reducing their commitments to assets whose volatilities are predicted to increase, or by using dynamic diversification approaches to hedge predicted volatility increases. This is particularly true of currency derivative markets where the volatility of the underlying asset has a profound effect on the value of the derivative.

Thesis (MBA)--Stellenbosch University, 2008. / ENGLISH ABSTRACT: Internationally, a number of studies on property cycles have been undertaken. In contrast very little academic research has been undertaken in South Africa. The importance of the subject is once again become evident given the recent global turbulence in both property and credit markets. The central hypothesis of this study is that there exists a residential property cycle in South Africa and that it can be identified and that furthermore there are indicators that can identify the various stages that the property market finds itself in and that these indicators can be used to forecast the property cycle. A number of potential drivers of the property cycle were identified and analysed. These drivers collectively propel the property cycle through its various cycle stages. Not one of the drivers in isolation has the ability to move the cycle; it is rather the correct combination of drivers at the right time that have the necessary impact to make the changes in property price levels. The study has identified the historical residential property cycle in South Africa and identified the primary drivers of the property cycle. It was found that Interest Rates, GOP, Population, Household Debt to Disposable Income ratio, Quantity of Building Plans Approved and Building Cost Escalation are all material drivers in defining the property cycle. A statistical analysis in the form of multiple regression was applied to the above variables and a statistical model was developed to forecast the property cycle. It was found that the model has significant explanatory powers when the goodness of fit was tested. / AFRIKAANSE OPSOMMING: Die sentraal onderstelling van hierdie studie is dat daar 'n residensiele eiendom kringloop in Suid-afrika bestaan en dat dit geidentifiseer kan wees en dat bowendien daar aanwysers wat die verskeie stadiums van die eiendom mark kan identifiseer vind en dat hierdie aanwysers gebruik kan word vir voorspelling van die eiendom kringloop. 'n Aantal potensiele drywers van die eiendom kringloop was geidentifiseer en gean ali seer. Hierdie drywers gesamentlik dryf die eiendom kringloop deur sy verskeie kringloop stadiums voort. Nie een van die drywers in isolasie het die vermoe om die kringloop te beweeg nie; dit is liewer die korrekte kombinasie van drywers op tyd wat die nodige impak het om die veranderinge in eiendom prys vlakke te maak. Die studie het die historiese residensiele eiendom kringloop in Suid-afrika geidentifiseer en die primere drywers van die eiendom kringloop. Dit was gevind dat Rentekoerse, GOP, Populasie, Huishouding Skuld tot Weggooibare Inkomste Verhouding, Hoeveelheid van Gebou Pia nne Goedgekeur en Gebou Kos Eskilasie is almal materiaal drywers in definieer van die eiendom kringloop. 'n Statisties analisering was aangewend aan die bo onkonstante en 'n statistiese skema was ontwikkel om voorspelling van die eiendom kringloop te bepaal. Dit was gevind dat die skema beduidende verduidelike kragte het wanneer die goedheid van pas getoets was.

Thesis (MBA)--Stellenbosch University, 2001 / ENGLISH ABSTRACT: The subject of prediction of business failure from an academic point of view dates back to the turn of the century with the development of a single ratio, the current ratio, as an evaluation of credit-worthiness. Subsequently studies conducted have become complex using different statistical techniques and more than one variable to predict failure. The challenge in these studies has been to establish a reliable model to predict failure. The aim of this report was to find out which financial factors best predicted failure in the South African environment using a matched study by refining some elements of the study conducted by Court (1993). The data used was similar to that of Court (1993), which was independently obtained from the Bureau of Financial Analysis of the University of Pretoria. The variables used in the study were then computed from this raw data. The variables were then imputed into the stataΤΜ statical software package to run a conditional logistic regression model. As a result of a small sample size and a substantial number of missing variables in the sample size, the study did not reveal an accurate indication of the important variable. It was also found that with the instability and general complexity of conditional logistic regression the study need not have been a matched study. The recommendation is that future research be done with a larger sample size using the same methodology. It is also recommended that the data include non-financial variables. / AFRIKAANSE OPSOMMING: Die voorspelling van besigheidsmislukkings as 'n akademiese onderwerp, dateer vanaf die begin van die vorige eeu met die ontwikkeling van 'n enkele verhouding, die bedryfsverhouding, as maatstaf van kredietwaardigheid. Die toepassing van statistiese tegnieke en inkorporasie van meerdere veranderlikes het aan verdere studies 'n hoë mate van kompleksiteit verleen. Die gevolglike uitdaging was om 'n betroubare model te ontwikkel om besighiedsmislukkings akkuraat te kan voorspel. Die doel van hierdie verslag is om aan te dui welke finansiele faktore mees gepas sal wees om besigheidsmislukkings in die Suid Afrikaanse omgewing te voorspel. Die verslag gee weer die bevindinge van 'n gepaarde studie wat gegrond is op 'n verfyning van sekere elemente soos geneem uit die Court studie van 1993. Die data gebruik, is baie soos die wat die Court studie onderlê en is onafhanklik verkry vanaf die Bureau vir Finansiele Analise (Universiteit van Pretoria). Die veranderlikes wat in die studie gebruik is gebaseer op hierdie rou data en is ingesleutel en verwerk deur die stataΤΜ statistiese sagteware program na 'n kondisionele, logiese regressie model. As gevolg van 'n klein steekproef en 'n beduidenswaardige aantal ontbrekende veranderlikes in hierdie steekproef, kon die studie nie 'n belangrike veranderlike met akkuraatheid aandui nie. Dit is ook bevind dat die onstabiliteit en algemene kompleksiteit van die kondisionele, logiese regressie model die gebruik van 'n gepaarde studie onnodig gelaat het. Die aanbeveling is dat verdere navorsing dieselfde metodologie sal toepas op 'n groter steekproef. Dit word ook aanbeveel dat nie-finansiele veranderlikes by die data ingesluit word.

South Africa is rich in platinum group metals (PGMs) and these metals are important in providing jobs as well as investments some of which have been seen in the Johannesburg Securities Exchange (JSE). In this country this sector has experienced some setbacks in recent times. The most notable ones are the 2008/2009 global nancial crisis and the 2012 major nationwide labour unrest. Worrisomely, these setbacks keep simmering. These events usually introduce jumps and breaks in data which changes the structure of the underlying information thereby inducing spurious long memory (long range dependence). Thus it is recommended that these two phenomena must be addressed together. Further, it is well-known that nancial returns are dominated by stylized facts. In this thesis we carried out an investigation on distributional properties of platinum returns, structural changes, long memory and stylized facts in platinum returns and volatility series. To understand the distributional properties of the returns, we used two classes of heavy tailed distributions namely the alpha-Stable distributions and generalized hyperbolic distributions. We then investigated structural changes in the platinum return series and changes in long range dependence and volatility. Using Akaike information criterion, the ARFIMA-FIAPARCH under the Student distribution was selected as the best model for platinum although the ARCH e ects were slightly signi cant, while using the Schwarz information criteria the ARFIMA-FIAPARCH under the Normal distribution. Further, ARFIMA-FIEGARCH under the skewed Student distribution and ARFIMA-HYGARCH under the Normal distribution models were able to capture the ARCH effects. The best models with respect to prediction excluded the ARFIMA-FIGARCH model and were dominated by ARFIMA-FIAPARCH model with non-Normal error distributions which indicates the importance of asymmetry and heavy tailed error distributions. / Statistics / M. Sc. (Statistics)

M.Phil. / Coal is today providing more than seventy-five percent of South Africa's energy requirements and will, to a large extent, remain so in the future. It is thus important to evaluate the adequacy of the country's available coal resources against expected future demand. The main objective of this study, which was done under the supervision of Prof. D. J. Kotze, was therefore to analyse the specific consumption of coal in the various consumption sectors in order to establish historical trends. The specific comsumption of coal is defined as the amount of coal used to produce a unit of final product. The factors attributing to these observed trends were determined and their future role evaluated in order to establish whether it was possible to extrapolate historical trends into the future. By means of curve fitting to the observed data and extrapolation it was possible to obtain future values of specific coal consumption for each of the sectors. These values, together with the production output forecasts for the various sectors were then used to calculate the total coal requirements for three reference years, namely, 1990, 1995 and 2000. The role of coal prices in explaining trends in specific coal consumption of various sectors was also analised separately. Information to conduct the study was obtained mainly from the various coal producers' associations as well as from individual producers and other organizations such as Escom, Sasol and Iscor, the Department of Hineral and Energy Affairs and the Hinerals Bureau. In some instances private firms and producers' associations were also consulted as well as a wide variety of literature on the subject. The principal finding of the study was that coal was substituted or was still being substituted by electricity in most final applications because of the convenience of use. Coal, however, still plays and probably will continue to play an important role in future in basic industries such as the metallurgical industry. Coal prices have not up to now played a very important role in the overall specific consumption of coal which can probably be attributed to the relatively low prices of coal on the inland market. It was also found that it was not desirable to do away with the present system of price control entirely as a certain measure of control was still necessary to safeguard the usuage of coal in certain applications for which there were no other substitutes. It was further concluded that South Africa does not have the vast quantities of coal commonly thought and that measures have to be taken in order to ensure that the country's coal resources are conserved and that optimum use is made of available resources.