Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006. / Source: Dissertation Abstracts International, Volume: 67-11, Section: A, page: 4257. Adviser: Anju Seth. Includes bibliographical references (leaves 187-192) Available on microfilm from Pro Quest Information and Learning.

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Neural networks have been shown to be a promising tool for forecasting financial times series. Numerous research and applications of neural networks in business have proven their advantage in relation to classical methods that do not include artificial intelligence. What makes this particular use of neural networks so attractive to financial analysts and traders is the fact that governments and companies benefit from it to make decisions on investment and trading. However, when the number of inputs to the model and the number of training examples becomes extremely large, the training procedure for ordinary neural network architectures becomes tremendously slow and unduly tedious. To overcome such time-consuming operations, this research work focuses on using various Higher Order Neural Networks (HONNs) which have a single layer of learnable weights, therefore reducing the networks' complexity. In order to predict the upcoming trends of univariate financial time series signals, three HONNs models; the Pi-Sigma Neural Network, the Functional Link Neural Network, and the Ridge Polynomial Neural Network were used, as well as the Multilayer Perceptron. Furthermore, a novel neural network architecture which comprises of a feedback connection in addition to the feedforward Ridge Polynomial Neural Network was constructed. The proposed network combines the properties of both higher order and recurrent neural networks, and is called Dynamic Ridge Polynomial Neural Network (DRPNN). Extensive simulations covering ten financial time series were performed. The forecasting performance of various feedforward HONNs models, the Multilayer Perceptron and the novel DRPNN was compared. Simulation results indicate that HONNs, particularly the DRPNN in most cases demonstrated advantages in capturing chaotic movement in the financial signals with an improvement in the profit return over other network models. The relative superiority of DRPNN to other networks is not just its ability to attain high profit return, but rather to model the training set with fast learning and convergence. The network offers fast training and shows considerable promise as a forecasting tool. It is concluded that DRPNN do have the capability to forecast the financial markets, and individual investor could benefit from the use of this forecasting.

Small, Medium and Micro Enterprises (SMMEs) make a significant contribution to the South African Economy. Regardless of size, these businesses have the ability to create employment, make a generous contribution to tax collections, uplift communities and serve as a beacon of hope for those trapped in the cycle of poverty and unemployment. However, SMMEs lack access to much-needed financial resources that are critical for their growth. Development Finance Institutions (DFIs) aim to bridge the gap between the SMME’s financial needs and the development of the respective SMME businesses, by providing funding to entrepreneurs with potentially viable businesses and ideas. Debt funding to these SMMEs are based on sound commercial lending principles that take various non-quantitative variables into account. The sustainability of SMMEs is a primary concern to all participants in the economy, as it is known that SMME failure rates are high Therefore, the primary objective of this study was to investigate the impact that the credit risk management practices of DFIs have on the sustainability of SMMEs, by examining a case study of a typical DFI. An electronic questionnaire survey was considered as an appropriate measurement method for this study. The targeted population of the study included SMMEs in the Eastern Cape that are Trust for Urban Housing (TUHF) clients and 23 SMMEs were identified as part of the study sampling frame. A total number of 14 questionnaires were returned out of the 23 targeted SMMEs - giving a response rate of 61%. The quantitative data was processed using the STATISTICA program, leading to appropriate descriptive statistical analyses. In order to better understand the impact of credit risk management practices on the sustainability of SMMEs, a hypothesis was formulated and linear regression analysis was used to establish the statistical significance of certain credit risk principles and sustainability characteristics. The results of the empirical study revealed that credit risk management practises do impact on the sustainability of SMMEs. Further, by testing the hypothesis, it was also revealed that certain sustainability variables are regarded as more important than others.

M.Com. (Business Management) / Statistics have shown that 227 companies and close corporations were liquidated during 1993. In addition 386 private persons, sole proprietors and partnerships were adjudged insolvent. These liquidations and insolvencies came about in all industries. By making use of ratio analysis, management can identify early danger signs and determine the presence of weaknesses in their business. There are some other critical factors and aspects that become evident from everyday trading activities that also point to danger signs. Management should be mindful and become aware of the danger signs at an early stage so that corrective action may be taken during a recessionary period. Numerous management aids in the field of financial discipline are at the disposal of management when applying corrective action. The core principles of effective asset management covering cash flow management, credit control, stock control and asset control should be employed to ensure survival during difficult times. Furthermore it is of critical importance that management makes use of the correct sources of financing and knows where to obtain it. It is also important that management addresses the other functional disciplines within the business. Management should continue the function of marketing and selling its products. Checklists containing useful questions should be applied to generate maximum sales. Production and sales should, however, be synchronised. Effective production management aids should be applied to create this harmony. It is also necessary that products be continually developed and that research into new areas be conducted. Management should handle labour relations and political and legal aspects with great sensitivity during recessionary periods. All employees deserve fair treatment and should be respected for their convictions. Appropriate general management principles should be applied at all times including effective leadership, motivation, communication and company philosophy. By making use of the proposed management aids, management can considerably improve the chances of the undertaking to survive a recession.

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This study is aimed at investigating the effect of mergers and acquisitions on the share prices and dividends involving South African companies in the food and beverage industry. A sample of 79 mergers from 1999 to 2005 was used. The data was analysed using the event study methodology and descriptive statistics. In addition, the paired t-test was also conducted to test the significance of the results. The results were presented using graphs, tables and charts. The results showed that target companies obtained negative abnormal returns during the announcement of mergers while acquiring companies on the other hand received positive abnormal returns. The results imply that it can no longer be generalized that target companies always win and acquiring companies lose during the merger activity. On the other hand, the dividends for target companies increased significantly after the merger, while the dividends for acquiring companies remained insignificantly negative after the merger. / Graduate School of Business Leadership / MBL

Thesis (MCom)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: “Within the context of the current market conditions, SCF may be one of the most attractive tools for companies to diversify funding basis, enrich and solidify their relationships with suppliers and their core banks.” – Michiel Steeman (Executive Director – Supply Chain Finance Community). (ING Group, 2013b). Insufficient cash flow is one of the major reasons for business failure in the current business environment. The spotlight is on collaboration between supply chain management and finance to release tied up cash in supply chains. Supply Chain Finance is a financial tool to help improve cash flow and optimise working capital to operate more efficiently. South Africa is one of the leading fruit exporters in the world with complex supply chains and even more complex financial arrangements. The need for Supply Chain Finance is aggravated by the long distances to overseas markets, and thus the long delay in payments after goods have been shipped. Supply Chain Finance is beneficial to the supplier, buyer and the financial service provider, creating a win-win-win situation. During this research the table grape export supply chain of Denau Farming is investigated to develop an explorative case study to implement Supply Chain Finance into their business model. During the research the problem of late payment received by buyers is explored by means of interviews and existing literature. A Concept Model is developed by adapting the Supply Chain Operations Reference Model (SCOR®) and the Management for Supply Chains (M4SC™) framework to identify the supply chain strategy during the current as-is physical and financial flow and to identify the gap in the supply chain. Two Supply Chain Finance solutions are identified based on Denau Farming’s financial needs in order to develop the to-be physical and financial supply chains and the resource changes required to facilitate the respective implementation. The final result determines how the proposed Supply Chain Finance solutions affect the expected cash-to-cash cycle time and the expected Economic Value Added (EVA®) in the case study. / AFRIKAANSE OPSOMMING: “Within the context of the current market conditions, SCF may be one of the most attractive tools for companies to diversify funding basis, enrich and solidify their relationships with suppliers and their core banks.” – Michiel Steeman (Executive Director – Supply Chain Finance Community). (ING Group, 2013b). Onvoldoende kontantvloei is een van die vernaamste redes waarom besighede in die huidige sakeomgewing misluk. Die kollig val op samewerking tussen voorsieningskettingbestuur en finansiering om kontant wat vasgevang is in voorsieningskettings te kan vrystel. Voorsieningsketting-finansiering is ‘n finansiële instrument wat kan help om kontantvloei verbeter en bedryfskapitaal te optimeer om meer doeltreffend te bedryf. Suid Afrika is een van die voorste vrugte-uitvoerders in die wêreld met komplekse voorsieningskettings en nog meer komplekse finansiële reëlings. Die behoefte vir voorsieningskettingbestuur-finansiering word vererger deur die lang afstande na oorsese markte, en dus die lang vertraging vir betaling nadat goedere reeds verskeep is. Voorsieningsketting-finansiering is voordelig vir die verskaffer, koper, en die finansiële diensverskaffer deur die skep van ‘n wen-wenwen situasie. As deel van hierdie navorsing is die tafeldruif-uitvoer voorsieningsketting van Denau Boerdery ondersoek as deel van die ontwikkeling van ‘n verkennende gevallestudie om sodoende voorsieningsketting-finansiering in hul sake-model te implementeer. Tydens die navorsing is die problem van laat betaling ontvang vanaf kopers in oorsese markte verder ondersoek deur middel van onderhoude en bestaande literatuur. ‘n Konsep model is ontwikkel deur die toepassing en aanpassing van die Supply Chain Operations Reference Model (SCOR®) en die Management for Supply Chains (M4SC™) raamwerk beginnende met die identifisering van ‘n voorsieningskettingstrategie tydens die huidige fisiese en finansiële vloei en die begin van ‘n gapings-identifisering vir die voorsieningsketting. Twee voorsieningsketting-finansiering oplossings is geidentifiseer gebaseer op Denau Boerdery se finansiële behoeftes en die ontwikkeling van ‘n verwagte toekomstige fisiese en finansiële voorsieningsketting asook die hulpbronveranderinge benodig wat die onderskeie implementerings kan help fasiliteer. Die finale navorsingsresultate bepaal tot watter mate die voorgestelde voorsieningsketting-finansiering oplossings die verwagte kontant-tot-kontant siklustyd asook die verwagte Ekonomiese Waarde Toevoeging (EVA®) in die gevallestudie beïnvloed.

Thesis (MComm (Business Management))--University of Stellenbosch, 2010. / ENGLISH ABSTRACT: The determinants of capital structure form an important part of the finance profession. Contemporary capital structure theory began in 1958 when Modigliani and Miller indicated that in a perfect capital market, the value of a firm is not influenced by its capital structure. However, when considering, inter alia, the effect of taxes, bankruptcy costs and asymmetric information, the value of a firm could be affected by its leverage. Capital structure theory offers two contrasting capital structure models, namely the trade-off and pecking order models. According to the trade-off model, firms trade-off the costs and benefits of debt financing in order to reach an optimal capital structure. According to this model, a positive relationship exists between leverage and profitability. In contrast, the pecking order model indicates that firms use a financing hierarchy where internal funds are preferred above debt and equity usage. This model indicates a negative relationship between leverage and profitability. However, in practice, firms often deviate from these models to incorporate the benefits of the other model or to adapt to changing circumstances. Firms' financing decisions may be influenced by both firm-specific and economical factors within the country where they are operating. Therefore, a firm's managers should consider the growth rate, interest rate, repo rate, inflation rate, exchange rates and the tax rate when conducting finance decisions, since these factors could influence the cost and availability of capital. In addition, these economical factors often have a significant influence on each other. Prior capital structure research mainly focused on developed countries. However, South Africa provides the ideal environment to consider the effect of economic changes on capital structure within a developing country, due to South Africa's profound economic changes during 1994 and the years to follow. The primary objective of this study was thus to determine whether the capital structures of South African listed industrial firms are influenced by changes in the South African economical environment. The effect of economic changes on capital structure was examined by using a TSCSREG (time-series cross-section regression) procedure. The regression model is based on a model developed by Fan, Titman and Twite (2008). One-period lags were built into the model to make provision for the effect of economic changes that often only occur after some time. The study was conducted on a sample of firms listed on the industrial sector of the Johannesburg Securities Exchange (JSE Ltd) over the period 1989 to 2008. The data, required to calculate the measures, were obtained from the South African Reserve Bank, the South African Revenue Service and the McGregor BFA database. This database contains standardised financial statements for both listed and delisted South African firms. In an attempt to reduce the possible skewing of results due to survivorship bias, both listed and delisted firms were included in the sample. In order to reflect its true nature, data should be available for consecutive years. Therefore, only firms with data available for more than five years were included in the final sample. The resulting sample consisted of 320 firms and 4 172 observations. The sample was also divided into years before and years after 1994, in order to determine the effect of the economic changes during 1994 and the years to follow on the firms' capital structures. The results of this study indicated that some of the economic factors influenced the D/E ratio as well as each other. However, the effect of economic changes often only occurred after a lagged period. A strong relationship was indicated between the tax rate and the repo rate, which influenced the significance of the regression results. Support was found for both the trade-off and the pecking order models. The combined profitability variable ROA-ROE also had a significant effect on the other variables. Based on these results, the claim that economic changes have an impact on capital structure is supported. The effect is often only indicated after a certain period. It also seems that the combination of the two capital structure models have a significant effect on leverage. Firms therefore appear to consider a combination of these models when conducting finance decisions. / AFRIKAANSE OPSOMMING: Die determinante van kapitaalstruktuur speel belangrike rol in die finansiële professie. Hedendaagse kapitaalstruktuurteorie het in 1958 tot stand gekom toe Modigliani en Miller aangedui het dat die waarde van 'n firma in 'n perfekte kapitaalmark nie deur kapitaalstruktuur beïnvloed word nie. Maar, wanneer die uitwerking van onder andere belastings, die koste van bankrotskap en asimmetriese inligting in ag geneem word, kan die waarde van 'n firma deur sy finansiële hefboomwerking beïnvloed word. Kapitaalstruktuurteorie bied twee kontrasterende kapitaalstruktuurmodelle, naamlik die ruilmodel (trade-off model) en rangorde-model (pecking order model). Volgens die ruilmodel vergelyk firmas die kostes en voordele van finansiering met geleende kapitaal totdat 'n optimale kapitaalstruktuur bereik word. Hierdie model dui op die bestaan van 'n positiewe verband tussen hefboomwerking en winsgewendheid. In teenstelling hiermee dui die rangorde-model aan dat firmas 'n finansieringshiërargie gebruik waar interne fondse verkies word bo skuld en ekwiteit. Hierdie model dui 'n negatiewe verband aan tussen hefboomwerking en winsgewendheid. In die praktyk wyk firmas egter dikwels af van hierdie modelle om die voordele van die ander model te inkorporeer of om by veranderende omstandighede aan te pas. Firmas se finansieringsbesluite kan beïnvloed word deur beide firma-spesifieke en ekonomiese faktore in die land waar hulle sake doen. Daarom moet 'n firma se bestuurders die groeikoers, rentekoers, inflasiekoers, wisselkoerse en die belastingkoers oorweeg wanneer hulle finansieringsbesluite neem, aangesien hierdie faktore moontlik die koste en beskikbaarheid van kapitaal kan beïnvloed. Hierdie ekonomiese faktore het dikwels ook 'n belangrike invloed op mekaar. Vroeëre navorsing insake die kapitaalstruktuur het dikwels op ontwikkelde lande gefokus. Suid-Afrika bied egter die ideale omgewing om die uitwerking van ekonomiese veranderinge op kapitaalstruktuur in 'n ontwikkelende land te ondersoek as gevolg van Suid-Afrika se betekenisvolle ekonomiese veranderinge gedurende 1994 en die daaropvolgende jare. Die primêre doelwit van hierdie studie was dus om te bepaal of die kapitaalstruktuur van genoteerde Suid-Afrikaanse nywerheidsondernemings deur veranderinge in die Suid-Afrikaanse ekonomiese omgewing beïnvloed word. Die uitwerking van ekonomiese veranderinge op kapitaalstruktuur is ondersoek deur gebruik te maak van 'n TSCSREG (tydreeks dwarssnit-regressie)-prosedure. Hierdie regressiemodel is gebaseer op 'n model wat deur Fan, Titman en Twite (2008) ontwikkel is. Enkeltydperk-vertragings is in die model ingebou om voorsiening te maak vir die uitwerking van ekonomiese veranderinge wat dikwels eers ná 'n tydperk sigbaar word. Die studie is uitgevoer op 'n steekproef firmas wat gedurende die tydperk 1989 tot 2008 op die nywerheidsektor van die Johannesburgse Sekuriteitebeurs (JSE Ltd) genoteer is. Die nodige data om die metings te bereken is verkry van die Suid-Afrikaanse Reserwebank (SARB), die Suid-Afrikaanse Inkomstediens (SAID) en die McGregor BFA-databasis. Hierdie databasis bevat gestandaardiseerde finansiële state vir beide genoteerde en gedenoteerde Suid-Afrikaanse firmas. In 'n poging om die moontlike skeeftrekking van resultate as gevolg van die oorlewingsneiging te verhoed, is beide genoteerde en gedenoteerde firmas by die steekproef ingesluit. Data moet vir opeenvolgende jare beskikbaar wees om die ware aard daarvan aan te dui. Daarom is slegs firmas met data beskikbaar vir meer as vyf jaar in die finale steekproef ingesluit. Die steekproef het gevolglik 320 firmas en 4 172 waarnemings behels. Die steekproef is ook in jare voor en jare ná 1994 verdeel, om die uitwerking van ekonomiese veranderinge gedurende 1994 en die daaropvolgende jare op firmas se kapitaalstruktuur te bepaal. Die bevindinge van die studie het daarop gedui dat sommige van die ekonomiese faktore die skuld/ekwiteit (D/E)-verhouding, maar ook elkeen van hulle beïnvloed het. Die uitwerking van ekonomiese veranderinge het egter dikwels eers ná 'n vertraagde tydperk sigbaar geword. 'n Sterk verhouding is aangedui tussen die belastingkoers en die repokoers, wat die betekenisvolheid van die regressieresultate beïnvloed het. Ondersteuning is gevind vir beide die ruilmodel en die rangorde-model. Die gekombineerde winsgewendheidsveranderlike ROA-ROE het ook 'n betekenisvolle uitwerking op die ander veranderlikes gehad. Die bewering dat ekonomiese veranderinge 'n impak op die kapitaalstruktuur het, word ondersteun op grond van die bevindinge van hierdie studie. Die uitwerking daarvan word egter dikwels eers ná 'n tydperk sigbaar. Die gekombineerde kapitaalstruktuurmodelle het moontlik 'n betekenisvolle uitwerking op hefboomwerking. Dit wil dus voorkom of firmas 'n kombinasie van hierdie modelle oorweeg wanneer hulle finansieringsbesluite neem.

Thesis (MBA (Business Management))--University of Stellenbosch, 2007. / AFRIKAANSE OPSOMMING: Verskeie navorsingsprojekte is oor die jare gedoen ten opsigte van die voorspellingsmoontlikhede van kontantvloei en winste, met teenstrydige resultate. Daar is egter weinig navorsing gedoen oor die verhouding wat tussen winste en kontantvloei bestaan. Hierdie navorsingsverslag beoog om ondersoek in te stel na die verhouding tussen kontantvloei en winste, dus om te poog om te bepaal watter een die drywer is, maar ook om te bepaal of die een veranderlike ingespan kan word om vooruitskattings ten opsigte van die ander te kan doen. Aangesien finansiële tydreekse die meeste van die tyd nie-stasionêr is, moet dit in ag geneem word wanneer die kousale verwantskap tussen die twee veranderlikes bepaal word, asook wanneer regressie-analise met die oog op vooruitskatting gedoen word. Daar word egter vermoed dat die aspek van stasionariteit weinig aandag geniet in menige navorsing wat ten opsigte van finansiële tydreekse gedoen word. Die feit dat weinig tydreekse stasionêr is, is bevestig deur te toets vir die bestaan van eenheidswortels in die veranderlikes. Die beste resultate vir stasionariteit is verkry deur die tweede verskille van die veranderlikes te bereken. Daar kon egter nie met sekerheid vasgestel word of winste kontantvloei dryf of andersom nie. Die gevaar van skyn-korrelasie is ook bewys, aangesien 'n groot aantal pare veranderlikes beduidende korrelasies tussen mekaar aandui, maar wanneer hulle stasionariteit en kousaliteit in ag geneem word, is weinig van die pare veranderlikes kousaal verwant aan mekaar. Die toets vir ko-integrasie is ingespan om steun te verleen by die regressie-analise en vooruitskatting van die tydreekse. Die regressie analise van die geko-integreerde tydreekse het in die meeste gevalle 'n hoë R2 en aangepaste R2 gelewer. Die vooruitskattings was egter teleurstellend onakkuraat. / ENGLISH ABSTRACT: Throughout the years a variety of research projects have been done about the predictive ability of cash flow and earnings, with contradictory results. However, limited research has been done about the relationship between cash flow and earnings. The aim of this research report is to investigate the relationship between cash flow and earnings, thus attempting to determine which one is the driver, but also to investigate the ability of one variable to predict the other. Because financial time series are non-stationary most of the time, this fact has to be taken into account when the causal relationship between the two variables is determined, as well as when regression analysis is done with forecasting in view. It is, however, suspected that the fact of stationarity has been neglected in much of the research that has been done on financial time series. The fact that very few time series are stationary has been established by testing for the existence of unit roots in the variables. The best results for stationarity were obtained by calculating the second differences of the variables. It could not be established beyond doubt whether earnings cause cash flows or vice versa. The danger of spurious correlation has been proved, because a vast number of pairs of variables indicates a significant correlation with one another, but when stationarity and causality are taken into account, only a few pairs of variables are truly significantly correlated to one another. The test for co-integration was used to assist in the regression analysis and forecasting of non-stationary time series. The regression analysis of most of the co-integrated variables resulted in a high R2 and adjusted R2. The forecasted values, however, were disappointingly inaccurate. / cmc2010