The thesis focuses on risk assessment of selection of chosen company suppliers. It evaluates the quality of suppliers using principles of fuzzy logic and the determining rules. The evaluation of suppliers is conducted using programs MS Office Excel and MATLAB. The thesis contains a comparison of results of these two programs.

Operational risk has become an increasingly important topic within financial institutions of late, resulting in an increased spend by financial service organisations on operational risk management solutions. While this move is positive, evidence has shown that information technology implementations have tended to have low rates of success. Research highlighted that a series of defined critical success factors could reduce the risk of implementation failure. Investigations into the literature revealed that no critical success factors had been defined for the implementation of an operational risk management system. Through a literature study, a list of 29 critical success factors was identified. To confirm these factors, a questionnaire was developed. The questionnaire was distributed to an identified target audience within the South African financial services community. Reponses to the questionnaire revealed that 27 of the 29 critical success factors were deemed important and critical to the implementation of an operational risk management system. / Business Management / M. Com. (Business Management)

In a country like Ethiopia, where information and communication systems are in the early stage of development, software projects may face several challenges. Projects may suffer from schedule or budget overrun or unmet specifications, leading to failure. Risk is one of the factors that challenges project performance, and even causes failure. Hence, risk management helps project managers to control the effect of risks. However, risk management appears to be the least practiced component of project management. This study aims at assessing the risk management practice in the Ethiopian software projects. This study was undertaken using a survey conducted on 45 banks, insurance companies and UN agency offices in Addis Ababa, Ethiopia. The findings of the study suggest that formal risk management is not widely practiced in Ethiopian software projects. Only 16% of organisations reported that they applied one or more documented formal risk management techniques. Overall, 67% of organisations were found to exercise one or more risk management process steps. Though the risk management practice was found to be reasonably high, the proportion of organisations that carry out all the risk management process phases, through formal or informal methods, was only 27%, showing that risk management practice in Ethiopia cannot be considered adequate. The study thus recommends that Ethiopian software project managers should give more emphasis for risk management in their project management. The risk items that Ethiopian software projects face most were found to be technical complexity risks, with the highest risk item being use of new technology. This may be an indication that project managers should give adequate attention to the risks arising from technical complexity. No statistically significant relationship was observed between formal risk management and project success, and also between risk management practice and project success. / College of Engineering, Science and Technology / M.Sc. (Computing)

This study investigates the use of derivatives by firms listed on the Johannesburg Stock Exchange (JSE) during 2005 to 2017, and the disclosure of derivative financial instruments on the financial statements of these entities. The study can be broadly divided into two parts: the first part investigates the determinants of corporate hedging practices by JSE-listed firms, while the second part analyses the value relevance of derivatives disclosures. The first part of the study thus answers the question ‘Why do companies use derivatives?’ with reference to JSE-listed companies for the period 2005 to 2017. The second part of the study answers the question ‘Does the disclosure of derivatives in the financial statements have an impact on firm value?’ for the same companies and period. Binomial logistic regression analyses were done to assess the determinants of the corporate hedging practices employed by JSE-listed firms. Multiple linear regression analyses were used to determine the value relevance of derivatives disclosures. The results of the study suggest that firm size, growth prospects, leverage and managerial risk aversion are important determinants of JSE-listed firms’ hedging decisions. Furthermore, the findings suggest that the disclosure of firms’ use of derivatives in the financial statements is value relevant and that companies listed on the JSE are associated with a higher Tobin’s Q if they disclose a derivatives amount. This study also investigates whether the value relevance of derivatives disclosure is influenced differently under different conditions during different economic periods and whether the level of quality of the disclosure influences the value relevance of derivatives disclosure. The data show that the value relevance of risk disclosure companies depend on different economic periods, and that the level of higher quality risk disclosure has a negative impact on the value relevance of derivatives disclosures: firms are valued lower where the level of quality of derivatives disclosures is higher. / Thesis (PhD)--University of Pretoria, 2020. / Financial Management / PhD / Unrestricted

This research examines the risk management practices prevalent in the South African construction industry. This was necessitated by the dearth in effective risk management in the construction industry particularly in developing countries such as South Africa. A comprehensive literature review was conducted to establish the risk management practices in use. Based on the literature, a questionnaire was developed and administered electronically to contractors operating in South Africa. The study established that contractors face a significant number of risks, chief among them, high competition in bids, political instability, payment delays, corruption and bribery and an overbearing influence of bureaucratic processes from government aligned agencies. Furthermore, it was also established that risk management amongst South African contractors is largely informal due to a mediocre appreciation of risk management. It also emerged that risk management implementation is perceived to be an expensive venture that erodes the marginal profits contractors aim to make. Resultantly, risk management practices implementation is low amongst the contractors. Based on the findings, the study concludes that the South African construction industry suffers from ineffective risk management implementation. To improve the implementation of risk management practices amongst contractors, it is recommended that contractors increase their risk management awareness through risk management training and risk knowledge management. Overall, this will be beneficial for their operations as risk management has been found to yield a positive effect on the meeting of project objectives. Furthermore, private and public sector clients are also encouraged to demand evidence of risk management competency from contractors upon engaging them for work.

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The COVID-19 outbreak has brought disturbances to a large number business as well as whole industries disrupting their supply chains, proving that most of today's companies don't have sufficient systems or strategies to evade or reduce major supply chain disruptions. One industry that was affected heavily is the fashion industry who is characterized by short lead times, globalized supply chains and volatile customer demand. Production stops and lockdowns in the asian region and difficulties with shipping and transportation have led to devastating consequences for a large number of apparel companies. Creating a need for different strategies to enforce the resilience of the supply chains. The procurement process plays a crucial part in this as it refers to the obtaining of materials, products or services and sourcing suppliers, creating a strong link between the resilience of the supply chain and the company's procurement sector.In this paper we aim to explore and provide insight on which procurement risk management strategies brand owning apparel companies in Sweden have utilized in order to reduce the supply disruptions caused by the pandemic, the purpose with our thesis is to provide insight on how these companies have adapted their PRM strategies to be formidable in the more risk-prone environment that COVID-19 has created. Ultimately the goal is to identify success factors and provide theoretical insight and practical recommendations for practitioners in the industry.   We have conducted qualitative research using an inductive approach and explanatory research design. The data derives from interviewing several different swedish brand owning apparel companies and was analyzed using grounded theory. Our findings suggest that supplier diversification has become more usual practice due to the supply disruptions. Mainly nearshoring has become more prevalent than before COVID-19 according to our findings. We also found that apparel companies have increased the usage of agile tools to reduce supply disruptions, referring to more flexible ordering and agile inventory management. We also found that collaborative partnerships were used as a successful strategy to reduce supply disruptions. Lastly we also found several apparel companies digitalizing their procurement process following the restrictions caused by the pandemic. Even though our theoretical frameworks suggest using demand management tools to reduce the impact of supply disruption, our empirical findings did not support such PRM-activity. Our study contributes to the literature by contextualizing various procurement risk management strategies that apparel brands used to reduce the supply disruption, furthermore we also found new trends regarding nearshoring, inventory management and the usage of new technologies to present samples, thus providing new insights to the research area. Our paper also provides practical recommendations to sourcing managers within the apparel industry who are seeking to engage in procurement risk management strategies to reduce supply disruptions, as our findings can be used as a basis for decision making. Furthermore we recommend managers to firstly identify the root of the disruptions to find the proper responsive action using our proposed model to implement both proactive and reactive strategies to reduce the impact of the supply disruptions. Finally, we recommend companies to start the process to digitalize their procurement process. This has been a necessity for most apparel companies during COVID-19 and we believe that it can have a positive effect in the post-covid world as well.

This thesis studies three important topics in modeling financial volatility. First, the jump clustering in ex post variance and its implications on forecasting, second, the underlying distribution of stochastic volatility and third, the role of non-Gaussian multivariate return distribution combined with a realized GARCH framework. The first chapter is on variance jumps. Financial markets present unexpected and large jumps, due to unobserved news flow. I focus on modeling the ex post variance jumps, their time- dependent arrivals and their sizes. I use a discrete-time bivariate model, with two autoregressive components which capture the long and short-run memory of the ex post variance measures. I estimate contemporaneous and time-dependent jumps in the log-measures of realized variance and bipower variation. The results from S&P500 show that the variance jumps are frequent and persistent. I examine the ability of jumps to forecast returns and ex post variance densities over horizons of up to 50 days out-of-sample. Modeling jumps significantly improves ex post variance density forecasts for all horizons and improves forecasts of the returns density. In the second chapter I explore the empirical non-Gaussian features of stochastic volatility. The standard assumption in a stochastic volatility specification is typically a restrictive Gaussian AR(1) structure. I drop this assumption and instead I assume that latent log-volatility follows an infinite mixture of normals with a Dirichlet process prior. The ex post measure of realized variance is used as a source of information to help identify the unknown distribution of log- volatility. Results from major stock indices show strong evidence of non-Gaussian distributional behaviour of volatility. The proposed framework captures asymmetry and thick tails in returns as well as realized variance. In out-of-sample forecasting, the new model provides improved density forecasts for returns, negative returns and log-realized variance. In the third chapter a new approach for multivariate realized GARCH models is proposed. Two new extensions that have non-Gaussian innovations are developed. The first one is a parametric version, with multivariate-t innovations. The second one is a nonparametric approximation of the return distribution using an infinite mixture of multivariate normals given a Dirichlet process prior. The proposed models are based on the assumption that the realized covariance follows an Inverse Wishart distribution with conditional mean set to the conditional covariance of returns. The benefits of the proposed models are demonstrated from density forecasting and portfolio applications. Results from two equity datasets indicate that modeling the tail behaviour improves return density forecasting compared to the Gaussian assumption. The proposed models produce the least volatile global minimum variance portfolios out-of-sample and provide improved forecasts of Value-at-Risk and Expected Shortfall. / Thesis / Doctor of Business Administration (DBA)

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