M.Com. / In this treatise, research is done into the various theories with regard to the business phenomenon and the various phases of the business cycle according to various economic indicators. A characteristic of the South African economy as well as other capitalistic systems, is that business indicators have a unstable tendency. Times of prosperity are followed by times of recession when unemployment, production, prices, profits and economic welfare, decline. The recession is again followed by times of prosperity which are characterised by increases in job opportunities as well as rising prices, profits and living standards. This wave like movement in economic activity is known as the business phenomenon. There are certain forces which directly affect the business cycle - some of them force it upwards while others force it downwards. The direction of the business cycle depends on the dominant forces. As soon as the forces are exhausted, a turn in the cycle results. The series regarding the business cycle are classified according to specific schools of thought in order to investigate their development as well as the main causes of the wave like motion in economic activities. A simple classification can be made by dividing the theories into those which preceded the publication of J.M. Keynes' General Theory of Employment, Interest and Money in 1936 as the Classical or Pre-Keynesian, and those which form the Keynesian school of thought and which appeared since the thirties as the Post-Keynesian theories. Firstly the Pre-Keynesian business cycle theories are discussed with reference to amongst others the demand theories, supply theories, the monetary theories and. the impulse theories. Thereafter the Post-Keynesian business cycle theories are discussed, that is those of Hicks, Kalecki, Goodwin and Duesenberry. An examination of the different phases of the business cycle implies a study of the movement of economic data in a upward and downward direction. Four phases can be discerned within the business cycle namely: the upward phase, the upper turning point, the downward phase and the lower turning point. The position of the various indicators will determine in which phase a country's economy finds itself. Economic activities are never stagnant, with the result that a period of prosperity may be followed panicking or a pez'Lod of depression. Several economic indicators may indicate this sequence, for instance unemployment, declining output and profit margins, and the resulting loss of income on the national level. As soon as the lower turning point is reached, the economy starts to recover and a period of prosperity again follows. It can thus be argued that the business cycle is a result of interaction between demand and supply. The business cycle has a significant result on the economy as a whole. It influences the prosperity of the country and even that of the undertaking, its manpower position, its capacity occupation and its factors of production. Every individual is effected to the extend that his disposable income is directly determined by the position of the business cycle. The phases of the business cycle and the inclining and declining motion of economic data contains the nucleus of the effect of the external environment on the undertaking.

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

M.Comm. / There are many different opinions among economists around the validity and existence of the business cycle. It varies from the total nullification of the existence of a business cycle to the founding of a working definition in this regard. One of the characteristics of the South African economy and similar capitalist systems is an unstable business environment. Periods of economic growth are followed by periods of economic recession when employment, production, prices, profits and general economic welfare are in decline. These phases are known as the business cycle. Economists differ from the early days with relation to the factors that led to changes in total economic activity. Classical economists focussed on the supply side factors as the main cause of the business cycle. John Keynes criticized the early models and presented a model in which change in output is largely dependent on changes in aggregate demand. The latest theory is known as the Real Business Cycle and includes both the supply and demand side factors. The emphasis is, however, on the supply side and argues that changes in the aggregate supply are the main determining factor in economic contraction or expansion. Between 1946 and 1996, 14 complete cycles occurred in the South African economy. The total cycle comprises of the first upward phase, the second upward phase, the first downward phase and the second downward phase. Specific indicators are present during each phase. Car sales are determined by demand. The demand include consumer preference, income, the price of competing or similar goods, expectations of the consumer, availability of credit, consumer confidence as well as the price of the product. The single most important influence on car sales is political stability, economic growth and interest rates. These factors determine the extent of consumer confidence. The occurrence of business cycles in the South African economy and the cyclical tendency of car sales are largely in tandem. Of the 14 upward and onward phases since 1960, 12 phases show positive correlations. This means that car sales represent an adequate barometer with regard to the state of economic activity as a whole in the country. It is also an effective barometer regarding expected future developments on the economic front. The state of the business cycle can be of tremendous value regarding planning in the motor manufacturing industry. The specific phase in which the business cycle is, will provide a sound indication of what kind of success might be anticipated with regard to future sales.

Thesis (PhD)--Stellenbosch University, 2014. / ENGLISH ABSTRACT: This dissertation considers the use of Dynamic Stochastic General Equilibrium (DSGE) models for the analysis of South African macroeconomic business cycle phenomena. It includes four separate, but interrelated parts, which follow a logical sequence. The rst part motivates the use of these models before establishing the theoretical foundations for these models. The theoretical foundations are accompanied by detailed derivations that are used to construct a model for a small open economy. The second part considers the properties of South African macroeconomic data that may be used to estimate the parameters in these models. It includes a discussion of the variables that may be included in such a model, as well as various methods that may be used to extract the business cycle. Thereafter, the sample size for the dataset is established, after investigating for possible structural breaks in the rst two moments of the data, using various univariate and multivariate techniques. The nal chapter of this part contains an investigation into the measures of core in ation, whereby a comparison of trimmed means, dynamic factor models and various wavelet decompositions are applied to data for South Africa. The third part considers the application of the dataset that was identi ed in part two, in a DSGE model that incorporates features that are typical of small open economies. It includes a discussion that relates to the role of the exchange rate in these models, which is found to contain key information. In addition, this part also includes a optimal policy investigation, which considers the reaction function of central bank. The nal part of this thesis considers more recent advances that have been applied to DSGE models for the South African economy. It includes an example of a nonlinear model that is estimated with the aid of a particle lter, which is then used for forecasting purposes. The forecasting results of both linear and nonlinear versions of the model are then compared with the results from various Vector Autoregression (VAR) and Bayesian VAR models. / AFRIKAANSE OPSOMMING: Hierdie proefskrif oorweeg die gebruik van Dinamiese Stogastiese Algemene Ewewig (Engels: Dynamic Stochastic General Equilibrium (DSGE)) modelle vir die analise van besigheidsiklus gebeure in die Suid Afrikaanse makroekonomie. Dit bestaan uit vier aparte dog onderling verwante dele wat in « logiese ontwikkeling vorm. Die eerste deel motiveer die gebruik van dié modelle en daarna word die teoretiese onderbou van die modelle daargestel. Die teoretiese onderbou word aangevul met gedetaileerde stappe van die a eiding van die verhoudings wat gebruik word om « model vir « klein oop ekonomie saam te stel. Die tweede deel oorweeg die eienskappe van Suid Afrikaanse makroekonomiese data wat relevant is vir « ekonometriese model in hierdie konteks. Dit sluit « bespreking in van die veranderlikes wat vir so « model gebruik kan word, asook « bespreking van die verskeie metodes wat gebruik kan word om die besigheidsiklus uit die data te identi seer. Die steekproefgrootte van die data word dan vasgestel, ná die moontlikheid van strukturele onderbrekings van tendens in die eerste en tweede momente van die data ondersoek is met behulp van verskeie enkel en meervoudige-veranderlike tegnieke. Die laaste hoofstuk van dié deel is « studie van verskeie maatstawwe van kern in asie (core in ation), waar « vergelyking getref word tussen die resultate van die volgende metodes toegepas op Suid Afrikaanse data: afgesnede gemiddeldes (trimmed means), dinamiese faktor modelle en verskeie golfvormige onderverdelings (wavelet decompositions). Die derde deel gebruik die datastel, wat in deel twee ontwikkel is, in die passing van « DSGE model wat die tipiese eienskappe van « klein oop ekonomie inkorporeer. Dit sluit « bespreking in van die rol van die wisselkoers in hierdie tipe modelle, en daar word empiries bevind dat die wisselkoers belangrike inligting bevat. Hierdie deel sluit ook « ondersoek in van optimale beleid in terme van die reaksie funksie van die sentrale bank. Die laaste deel van die proefskrif bestudeer die resultate van onlangse ontwikkellinge in DSGE modelle wat toegepas word op die Suid Afrikaanse ekonomie. Dit sluit « voorbeeld van « nie-liniêre model wat met behulp van « partikel lter (particle lter) geskat word en gebruik word vir vooruitskattings. Die vooruitskattings uit beide die liniêre en nie-liniêre modelle word dan vergelyk met dié verkry uit verskeie Vektor

Research paper for the degree of Master of Management in Finance & Investment / With a globalised system, the credit crunch of 2007/2008 rippled through the global economy quickly and turned a global financial crisis into a global economic crisis, vulnerabilities in the economy surfaced when it hit and these still continue to plague South Africa today. According to the World Bank, South Africa’s real GDP growth estimates are 0.8% in 2016/2017 and 1.1% in 2017/2018. Increasing uncertainty in global financial markets and banking systems, sharp declines in commodity prices, subdued global trade, currency pressure, as well as domestic constraints such as a current account deficit, a negative inflation outlook and high levels of unemployment, lead to increased financial stress in South Africa making the country more vulnerable in the event of an adverse scenario. Clearly, being cognizant of determinants of financial stress in South Africa is of paramount importance to policy makers as it allows them to assess potential risks to financial system stability and to consider timely and appropriate counteractions while maintaining a financial system that is resilient to systemic shocks. (South African Reserve Bank Financial Stability Review, 2016) This study aims to construct a financial stress index using Principal Component Analysis to identify key determinants of financial stress in South Africa. Several variables that have been identified in standing literature as being able to capture certain symptoms of financial strain in emerging market economies are estimated then aggregated into an index using the principal component analysis method. The usefulness of the index in identifying past crises is then assessed, moreover its performance is contrasted against the financial stress index constructed by South African Reserve Bank as well as against a South African composite business cycle leading indicator. Finally, the ability of the index to predict economic activity is examined. / MT2017

A research report submitted to the Faculty of Commerce, Law and Management, University of the Witwatersrand, in partial fulfilment of the requirements for the degree of Master of Management, specialising in Entrepreneurship and New Venture Creation Johannesburg, 2017 / This study examined the relationship between business failure and macroeconomic fluctuations within business cycles of South Africa’s economy for the time period 1980 to 2016. The study also sought to understand where, if any, immediate and lag correlations between fluctuations and business failure could be established. To understand this connection, this study used longitudinal data sets of different macroeconomic factors and studied their influence on business failure. The vector error correction model (VECM) was used to determine the long-term relationship between failure and each of the other variables. Additionally, Granger Causality was applied to establish whether the macroeconomic variables investigated in this study can be constructed to predict the probability of business failures. Three classes of macroeconomic predictor variables were considered. Firstly, well-known international variables in the form of GDP and CPI were used. Secondly, the study incorporated the three Composite Business Cycle indicators- leading, coincident and lagging. Lastly, behavioural indicators were used to incorporate the views of the actual businesses and their customers, which for this the study were the Business and Consumer Confidence Indices. After examining the effects the 7 macroeconomic variables had on business failure, the study found that there is a long-run relationship between the Composite Lagging Business Cycle indicator, the Business Confidence and Consumer confidence, which influenced Business Failure. Additionally, it was noted that Business Failure influence the Composite Lagging Business Cycle indicator in the long-run. The study additionally found that Business Failure may Granger Cause the Composite Leading Business Cycle indicator Outcomes of the study are potentially vital for entrepreneurs to understand the timing of entry into markets based on macroeconomic fluctuations through their cycles in certain industries. Business owners can make proactive financial and strategic decisions vital for survival of their business through the expansion and especially in the contraction cycles of the macroeconomic environments. / MT2017

Thesis (MBA)--Stellenbosch University, 2000. / ENGLISH ABSTRACT: In this paper the effectiveness of "transplanting" a particular methodology of a probabilistic approach is assessed in a South African economic context. The methodology makes use of leading indicators which are used in regression models, with a dichotomous response variable, assuming values of 0 or 1 to indicate expansion or contraction of economic activity. The backbone of the study closely replicates the work of Nazmi (1993) and his work on turning point prediction. The recorded results indicate an ability of the model to accurately forecast businesscycle turning points in the 1980s. In the period of the 1990s, the model displays a diminished capacity to forecast the turning points with acceptable accuracy. Leading indicators, in the South African experience, show a reliable leading relationship to the composite coincident index in the current study period between 1970 and 1980 and thereafter this relationship decreases, impacting negatively upon the forecasting ability of the model. / AFRIKAANSE OPSOMMING: In hierdie studie word die doeltreffende 'oorplanting' van 'n bepaalde metodologie van 'n waarskynlikheidsbenadering tot ekonomiese vooruitskatting in 'n Suid-Afrikaanse konteks assesseer. Die metodologie benut leidende aanwysers wat in regressiemodelle gebruik word, met 'n tweeledige responsveranderlike wat die waardes 0 of 1 aanneem om die uitbreiding of inkrimping van ekonomiese aktiwiteit aan te dui. Die kern van hierdie studie reflekteer tot 'n groot mate die werk van Nader Nazmi oor draaipunt voorspellings. Resultate toon aan dat Nazmi se model wel sakesiklusse se draaipunte akkuraat voorspel het gedurende die 1980's. Gedurende die 1990's het hierdie model se voorspeIlingsakkuraatheid egter afgeneem. In die Suid-Afrikaanse omstandighede dui leidende/rigtinggewende aanwysers op 'n betroubare verhouding wat betref die saamgestelde meelopende indeks vir die tydperk 1970 tot 1980 in die onderhawige studie. Daarna is daar 'n afname in die verhouding, wat 'n negatiewe impak het op die voorspellingsvermoe van die model. In hierdie studie word die doeltreffende 'oorplanting' van 'n bepaalde metodologie van 'n waarskynlikheidsbenadering tot ekonomiese vooruitskatting in 'n Suid-Afrikaanse konteks assesseer. Die metodologie benut leidende aanwysers wat in regressiemodelle gebruik word, met 'n tweeledige responsveranderlike wat die waardes 0 of 1 aanneem om die uitbreiding of inkrimping van ekonomiese aktiwiteit aan te dui. Die kern van hierdie studie reflekteer tot 'n groot mate die werk van Nader Nazmi oor draaipunt voorspellings. Resultate toon aan dat Nazmi se model wel sakesiklusse se draaipunte akkuraat voorspel het gedurende die 1980's. Gedurende die 1990's het hierdie model se voorspeIlingsakkuraatheid egter afgeneem. In die Suid-Afrikaanse omstandighede dui leidende/rigtinggewende aanwysers op 'n betroubare verhouding wat betref die saamgestelde meelopende indeks vir die tydperk 1970 tot 1980 in die onderhawige studie. Daarna is daar 'n afname in die verhouding, wat 'n negatiewe impak het op die voorspellingsvermoe van die model.

Dissertation (PhD)--University of Stellenbosch, 2001. / ENGLISH ABSTRACT: Financial performance ratios are generally based on a set of financial statements without taking cognisance of other factors that could affect the measurement of performance. The behaviour of financial performance indicators during an upswing and decline phase of the economic cycle, together with the nature and scope of an enterprise's activities may have an effect on the manner in which financial performance indicators are used by an enterprise. The question may arise whether or not a ratio's behaviour for capital intensive (CI) and labour intensive (LI) enterprises could capture the essence of external factors such as an upswing or decline in the economic cycle as measured by the Gross Domestic Product (GOP). In this study an upswing phase (1987-1989) of three years and a decline phase (1990-1992) of three years have been selected after an analysis of the economic cycle over the period 1970 to 1996. The distinction between the capital and labour intensity of an enterprise is based on an analysis of the total assets, fixed assets and number of employees of industrial enterprises listed on the Johannesburg Stock Exchange (JSE). The initially selected 62 financial performance indicators categorised under profitability, growth, cash flow, value-added and inflation-adjusted ratios are calculated for each enterprise of the CI (33) and LI (36) groups and for each year of the research period. The primary objectives of the research are: • To distinguish between the CI and LI nature of enterprises listed in the industrial sector of the JSE by using measures of capital and labour intensity; • To obtain patterns and identify differences in the behaviour of the selected financial indicators between CI and LI enterprises during an upswing and decline phase of the economic cycle, as measured by the GOP; • To analyse and investigate patterns and differences to determine whether or not there is specific justification(s) for the behaviour exhibited by the CI and LI enterprises for a particular ratio during either or both the upswing and decline phases of the economic cycle; • To identify key financial indicators, which could possibly be used by CI and LI enterprises to forecast financial performance and to identify lead and lag patterns in the economic cycle. An elaborate statistical analysis is conducted of the ratios to satisfy the objectives stipulated above. The first part of the analysis is based on a single representative measure, which represents an average of the three-year upswing and three-year decline phases respectively. Mean and median values are calculated for the CI and LI enterprises for both the upswing and decline phases. A profile analysis based on Hotelling's T2 test is used for the analysis of ratios that exhibit approximate normal distributions. Non-parametric tests, Mann-Whitney Utest and Wilcoxon matched-pairs test, are used for the analysis of ratios that do not indicate approximately normal distributions. The second part of the study focuses on an analysis of the ratios based on the individual years of the research period. The statistical techniques used for the analysis of the ratios based on a single representative measure are also used in the analysis of the ratios based on the individual years. The limitations identified during the analysis based on a single representative measure are addressed to a large extent in this section of the statistical analysis. By analysing the mean and median values based on the individual years, it is possible to classify the ratios as one of five pattern groups exhibited by the CI and LI enterprises, i.e. normal expected, lag, lead, cyclical and mixed. The patterns of the various ratios within each of the pattern groups are also analysed from a financial management perspective. The findings of the study confirm the stated hypothesis that there are differences in the behaviour of financial indicators based on a single representative measure and over the individual years of the research period between CI and LI enterprises during either or both an upswing and decline phase of the economic cycle. Furthermore, the analysis highlights several ratios based on a single representative measure that could not be used universally by all enterprises to measure financial performance and only during either an upswing or decline phase of the economic cycle. Ratios which are part of this category include return on total net assets (before tax), return on total net operating assets, dividend per share, sales to total net assets and interest-bearing debt to total shareholders' interest. The results based on the individual years of the analysis indicate that a large number of ratios exhibit normal expected patterns. Among the traditional profitability indicators, 80% exhibit normal expected patterns for the CI and LI enterprises during the upswing and decline phases. Traditional profitability ratios such as return on total net assets, return on net operating assets, return on total shareholders' interest and the value-creation ratio, economic value added form part of the normal expected group of patterns. All the inflation-adjusted ratios indicate normal expected patterns. These ratios indicate relative stability over the economic cycle and may be appropriate for the purposes of medium- and long-term financial forecasting as they follow the trade cycle. Approximately 39% of the ratios indicate mixed patterns, i.e. different patterns for the CI and LI enterprises. The growth in attributable earnings, cash flow to interest payments, market value of equity to book value of equity and market value added ratios indicate behaviour patterns for the CI and LI enterprises which may lead the economic cycle. These ratios may indicate the possibility of anticipating upswing and decline phases in the economic cycle. The relevance of the results for a CI enterprise alludes to the use of more debt financing during the decline phase to cover costs and working capital requirements when demand for products and services decreases as a result of a slow-down in the economy. The pattern exhibited by EPS may allude to an anticipated upswing phase in the economic cycle. An increase in the cash flow to interest payments ratio during the decline phase may indicate an imminent change in the cycle of the economy. The relevance of the results for LI enterprises indicates that an upswing in the economic cycle may be anticipated by an increase in the working capital to operating cash flow ratio. More debt financing is used during the upswing period, which may be attributed to greater demand and consequently results in a higher gearing position for LI enterprises. An increase in the cash flow to interest payments ratio during the decline phase may indicate an imminent upswing in the economic cycle. Several limitations of the study include the use of a single upswing and decline phase to represent the movements of the economic cycle; the approach used to distinguish between the CI and LI enterprises requires further analysis, and the large number of ratios could in future research be limited to several indicators. The more important recommendations of the study include the use of multiple upswing and decline phases of the economic cycle; more research into the lags and leads exhibited by the CI and LI enterprises for specific ratios should be conducted; the possibility of adopting a different approach to distinguish between CI and LI enterprises could also be considered; and further research is required to ascertain the reliability of indicators that highlight lead patterns for forecasting an upswing or decline phase in the economic cycle. / AFRIKAANSE OPSOMMING: Finansiele verhoudingsgetalle word algemeen op 'n stel finansiele state gebaseer sonder dat ander faktore wat die meting van prestasie kan beinvloed, in ag geneem word. Die gedrag van finansiele verhoudingsgetalle tydens 'n opswaai en afswaai-fase van die ekonomiese siklus, tesame met die aard en omvang van 'n ondememing se aktiwiteite, mag die manier waarop 'n ondememing finansiele verhoudingsgetalle gebruik, beinvloed, Die vraag mag ontstaan of 'n verhoudingsgetal se gedrag vir kapitaalintensiewe (KI) en arbeidsintensiewe (AI) ondememings die essensie van eksteme faktore soos 'n opswaai en afswaai in die ekonomiese siklus soos gemeet deur die Bruto Binnelandse Produk (BBP), sal kan omvat. In hierdie studie is 'n opswaai-fase van driejaar (1987-1989) en 'n afswaai-fase van driejaar (1990-1992) geselekteer na 'n analise van die ekonomiese siklus vir die peri ode 1970-1996. Die onderskeid tussen die kapitaal- en arbeidsintensiteit van 'n ondememing is op 'n analise van totale bates, vaste bates en die aantal werknemers van nywerheidsondememings wat op die Johannesburg Aandelebeurs (JAB) genoteer is, gebaseer. Die 62 gekose finansiele verhoudingsgetalle wat as winsgewindheid-, groei-, kontantvloei-, toegevoegdewaarde- en inflasie-aangepaste verhoudingsgetalle gegroepeer is, is vir elkeen van die 33 KI ondememings en die 36 AI ondememings, sowel as vir elke jaar van die ondersoekperiode, bereken. Die primere doelstellings van die navorsing is: • Om tussen die KI en AI aard van ondememings wat in die industriele sektor van die JAB genoteer is, te onderskei deur maatstawe van kapitaal- en arbeidsintensiwiteit te gebruik. • Om patrone te verkry en verskille in die gedrag van die gekose verhoudingsgetalle gedurende opswaai- en afswaai-fases van die ekonomiese siklus soos gemeet deur die BBP, tussen KI en AI ondememings te identifiseer. • Om patrone en verskille te ontleed en ondersoek ten einde te bepaal of daar spesifieke regverdiging is vir die gedrag wat deur KI en AI ondememings vir 'n bepaalde verhoudingsgetal gedurende een of albei van die opswaai- en afswaai-fases van die ekonomiese siklus getoon word. • Om bepaalde finansiele verhoudingsgetalle vir KI en AI ondememings te identifiseer wat moontlik gebruik kan word om finansiele prestasie te voorspel en om lei- en sloerpatrone in die ekonomiese siklus te identifiseer. 'n Omvattende statistiese analise van die verhoudingsgetalle is uitgevoer om bogenoemde doelwitte te bevredig. Die eerste deel van die analise is op 'n enkel verteenwoordigende maatstaf gebaseer wat 'n gemiddelde van die drie-jaar opswaai en drie-jaar afswaai-fases onderskeidelik verteenwoordig. Gemiddelde en mediaanwaardes is vir die KI en AI ondememings vir die opswaai- en afswaai-fases bereken. 'n Profiel-analise gebaseer op Hotelling se T2 toets is gebruik om die verhoudingsgetalle wat benaderd normaal verdeel is, te ontleed. Die nie-parametriese toetse "Mann-Whitney U-test" en "Wilcoxon matched-pairs test" is gebruik om die verhoudings wat nie benaderd normaal verdeel is nie, te ontleed. Die tweede dee I van die studie fokus op 'n analise van die verhoudingsgetalle wat op die individuele jare van die navorsingsperiode gebaseer is. Die statistiese tegnieke wat in die analise van die verhoudingsgetalle gebaseer op 'n enkel verteenwoordigende maatstaf gebruik is, is ook vir die analise van die verhoudingsgetalle gebaseer op die individuele jare gebruik. Die beperkings wat deur die analise gebaseer op 'n enkel verteenwoordigende maatstaf geidentifiseer is, word tot 'n groot mate in hierdie afdeling van die statistiese analise aangespreek. Deur die gemiddelde en mediaanwaardes gebaseer op die individuele jare te ontleed, is dit moontlik om die verhoudingsgetalle as een van 'n aantal patroongroepe, naamlik normaal verwagte, sloer-, lei-, sikliese en gemengde patrone, vir die Kl en AI ondememings te klassifiseer. Die patrone van 'n verskeidenheid van verhoudingsgetalle binne elk van die patroongroepe word ook uit 'n finansiele bestuursperspektief ontleed. Die bevindings van die studie bevestig die gestelde hipotese dat daar verskille in die gedrag van finansiele verhoudingsgetalle, gebaseer op 'n enkel-verteenwoordigende maatstaf en vir individuele jare van die navorsingsperiode, tussen Kl en AI ondememings gedurende een of albei van die opswaai- en afswaai-fases van die ekonomiese siklus is. Die analise beklemtoon verder dat 'n aantal verhoudingsgetalle wat op 'n enkel verteenwoordigende maatstaf gebaseer is, nie universeel vir alle ondememings en slegs gedurende 6f 'n opswaai- 6f 'n afswaai-fase van die ekonomiese siklus gebruik kan word nie. Verhoudingsgetalle wat deel van hierdie kategorie vorm, sluit ondememingsrentabiliteit (voor belasting), rentabiliteit van totale netto vaste- en bedryfsbates, dividend per aandeel, verkope tot totale netto bates, en rentedraende skuld tot totale aandeelhouersbelang in. Die resultate gebaseer op die individuele jare van die analise toon dat die oorgrote meerderheid van die verhoudingsgetalle normaal verwagte patrone volg. Van die tradisionele winsgewindheidsverhoudingsgetalle vertoon 80% normaal verwagte patrone vir die KI en AI ondememings gedurende die opswaai- en afswaai-fase. Tradisionele winsgewindheidsverhoudingsgetalle soos ondememingsrentabiliteit, rentabiliteit van netto vaste- en bedryfsbates, rentabiliteit van eie kapitaal en die waardeskeppingsverhoudingsgetal EVA, vorm deel van die normaal verwagte groep van patrone. Al die inflasie-aangepaste verhoudingsgetalle toon ook normaal verwagte patrone. Hierdie groep van verhoudingsgetalle toon relatiewe stabiliteit gedurende die ekonomiese siklus en is vir medium- en langtermyn finansiele vooruitskatting geskik omdat hulle die besigheidsiklus volg. Ongeveer 39% van die verhoudingsgetalle toon gemengde patrone, m.a.w. verskillende patrone vir die KI en AI ondememings. Die groei in verdeelbare inkomste, kontantvloei tot rentebetalings, markwaarde van aandeelhouersbelang tot boekwaarde van aandeelhouersbelang en mark-toegevoegde waarde verhoudingsgetalle toon gedragspatrone vir die KI en AI ondememings wat moontlik die ekonomiese siklus kan lei. Hierdie verhoudingsgetalle mag 'n aanduider van verwagte opswaai- en afswaai-fases in die ekonomiese siklus wees. Die relevansie van die resultate vir KI ondememings dui op die groter gebruik van vreemde kapitaal gedurende die afswaai-fase om kostes en bedryfskapitaal behoeftes te dek wanneer die vraag na produkte en dienste afneem as gevolg van 'n daling in die ekonomie. Die patroon wat deur verdienste per aandeel aangedui word, gee 'n moontlike aanduiding van 'n verwagte opswaai-fase in die ekonomiese siklus. 'n Toename III die kontantvloei-totrentebetalingsverhoudingsgetal gedurende die afswaai-fase mag 'n aanduider van 'n naderende opswaai in die ekonomiese siklus wees. Die relevansie van die resultate vir AI ondememings toon dat 'n opswaai in die ekonomiese siklus deur 'n toename in die bedryfskapitaal tot kontant uit ondememingsaktiwiteite verhoudingsgetal verwag kan word. Meer vreemde kapitaal word gedurende die opswaai-fase gebruik wat aan 'n toename in die vraag toegeskryf kan word en gevolglik tot 'n hoer hefboomsituasie vir AI ondememings lei. 'n Toename in die kontantvloei tot die rente betaal verhoudingsgetal gedurende die afswaai-fase mag 'n aanduider van 'n naderende opswaai in die ekonomiese siklus wees. 'n Aantal beperkings van die studie sluit in: die gebruik van 'n enkele opswaai- en afswaaifase wat die ekonomiese bewegings verteenwoordig; die benadering wat gevolg is om tussen die KI en AI ondememings te onderskei benodig verdere ondersoek; en die groot aantal verhoudingsgetalle kan in toekomstige studies tot 'n sekere aantal indikatore beperk word. Die belangrikste aanbevelings van die studie sluit in: die gebruik van veelvoudige opswaai- en afswaai-fases van die ekonomiese siklus; meer navorsing op die sloer- en leipatrone wat deur die KI en AI ondememings vir spesifieke verhoudingsgetalle getoon word; die moontlikheid om 'n ander benadering te volg om tussen KI en AI ondememings te onderskei, kan oorweeg word; en verdere navorsing word benodig om die betroubaarheid te bepaal van die indikatore wat dui op lei patrone wat 'n opswaai- of afswaai-fase in die ekonomiese siklus kan voorspel.

Thesis (MComm (Economics)--University of Stellenbosch, 2006. / The goal of this thesis is twofold: it aims, firstly, at a description of cycles in South African financial variables and, secondly, at the evaluation of the relationship between cycles in financial variables and the South African business cycle. The study is based on the original business cycle framework of Arthur Burns and Wesley Mitchell, but incorporates recent contributions by Australian economists Don Harding and Adrian Pagan, as well as the work of the Economic Cycle Research Institute in New York. Part I of the thesis is concerned with the characteristics of cycles in financial variables within the South African context. The first chapter presents a taxonomy of the concepts of classical, deviation and growth rate cycles in order to establish a simple reference framework for cycle concepts. At this point the concept of a ‘turning point cycle’ is introduced, with particular focus on the non-parametric method of turning point identification, following Harding and Pagan’s recent translation of the original work of Burns and Mitchell into a modern version with a sound statistical basis. With the turning points identified the dissertation proceeds to an exposition of descriptive measures of expansion and contraction phases. The second chapter entails an empirical report on descriptive results for amplitude and duration characteristics of cycle phases in the different financial variables, with separate reports for classical cycles and growth rate cycles. Chapter two concludes with a series of tables in which the behaviour of cycle phases are compared for different financial variables. Part II considers financial variables as potential leading indicators of the business cycle in South Africa. Chapter 3 introduces the concept ‘leading indicator’ to this end and distinguishes the original concept from modern, econometric versions. The chapter then introduces a framework for evaluating potential leading indicators, which emphasises two requirements: firstly, broad co-movement between cycles in the proposed leading indicator and the business cycle and, secondly, stability in the number of months between turning points in cycles of the proposed indicator and business cycle turning points. The capacity of potential indicators to meet these criteria is measured via the concordance statistic and the ‘lead profile’ respectively. Chapter four provides the statistical basis for the concordance statistic, after which the empirical results (presented separately for classical and growth rate cycles) are presented. The fifth chapter presents the statistical test for the stability of the interval by which cyclical turning points in the potential indicator lead turning points in the business cycle. Empirical results are presented in both tabular form (the ‘lead profile’) and graphical form (the ‘lead profile chart’). As far as can be determined, this analysis represents the first application of the ‘lead profile’ evaluation to financial variables. Chapter six concludes by presenting a summary of the results and a brief comparison with findings from an econometric study of leading indicators for South Africa.

M.Com. (Financial Economics) / The use of the yield curve spread in forecasting future recessions has become popular as it is a simple tool to use, due to the positive relationship between the yield curve spread and economic activity. The inversion or flattening of the yield curve spread usually signals a future recession. This has been the subject of several studies both internationally and in South Africa. This research provides an analysis of the yield curve spread’s ability to accurately forecast future recessions in South Africa through the use of three probit models. Furthermore, the yield curve spread’s ability to estimate is compared to that of share prices, using the JSE All Share Index. This research extends on studies by Khomo and Aziakpono (2006) and Clay and Keeton (2011), who used the static and dynamic probit models to forecast recessions in South Africa. In addition to these models, this research also makes use of the business cycle conditionally independent probit model for estimation. The findings suggest that share prices improve the yield curve spread’s ability to forecast recessions when estimating using the static probit model; however when comparing the results between the financial variables, the yield curve spread continues to produce the best forecast of recessions in South Africa. These results support those of Khomo and Aziakpono (2006) and Clay and Keeton (2011). Of the three probit models, the dynamic probit model estimate using the yield curve spread produced the most accurate forecast of recessions one quarter ahead. Therefore, the yield curve spread continues to provide the most accurate forecast of recessions in South Africa.