M.Comm. (Economics) / The recent global financial and economic crisis has brought about renewed interest in the nexus between credit markets and monetary policy. This research aims to contribute to the understanding of the factors that drive the demand for credit on an aggregate level, and the household and corporate sectors for the South African economy. The study assessed the equilibrium determinants of the aggregate and sectoral demand for credit in South Africa by making use of a cointegrated vector autoregression (CVAR) methodology. In addition, the periods of debt overhang and short-falls, at aggregate and sectoral levels in the credit market, are derived from these equilibrium levels. The estimated models indicate the existence of long-run relationships for the aggregate credit demand equation, a classic demand-type relationship linking aggregate credit with gross domestic product (GDP) and the lending rate is established. For credit extended to the corporate sector, the results indicate that in the long-run it is determined by investment expenditure, operating surpluses and the lending rate. Whereas for credit extension to the household sector, it was found that the lending rate, disposable income and household debt were its important long-run determinants. All the results of the estimated equations are in line with a demand-type relationship and the traditional hypothesis that credit is demanded to finance real economic transactions, namely for liquidity purposes and to finance working capital. The results of the short-term dynamics indicate that credit extension variables are the equilibrium variables, although the speed of adjustment parameter is found to be sluggish, which shows that the slow adjustment to equilibrium from shocks to the credit markets is attributable to the existence of stronger frictions and transaction costs in credit markets. These findings justify the persistent periods of credit overhang and short-falls in South Africa that this study derives from the equilibrium coefficient terms. The study shows that periods of credit overhang and short-falls are linked to the business cycle phases in South Africa.

Man Po Kong = 信貸相聯票據和住宅按揭的預期損失之估值 / 文普綱. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2004. / Includes bibliographical references (leaves 85-86). / Text in English; abstracts in English and Chinese. / Man Po Kong = Xin dai xiang lian piao ju he zhu zhai an jie de yu qi sun shi zhi gu zhi / Wen Pugang. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- The Structural model --- p.3 / Chapter 2.1 --- Merton's model --- p.3 / Chapter 2.2 --- The term structure of interest rate --- p.7 / Chapter 2.3 --- The default-triggering mechanism and derivations from strict priority rule --- p.9 / Chapter 2.4 --- Stationary leverage ratio --- p.11 / Chapter 2.5 --- The three-factor structural model --- p.12 / Chapter 3 --- Credit-linked Notes with early default risk --- p.18 / Chapter 3.1 --- Introduction to credit-linked notes --- p.18 / Chapter 3.2 --- The pricing of credit-linked notes --- p.20 / Chapter 3.3 --- Non mean-reverting leverage ratios --- p.21 / Chapter 3.3.1 --- Special case (pQv=0) --- p.23 / Chapter 3.4 --- Mean reverting leverage ratios --- p.25 / Chapter 4 --- Numerical results and discussion --- p.28 / Chapter 4.1 --- Exact solution (KQ=kv=PQv=PVr=0) --- p.31 / Chapter 4.2 --- "Lower bound approximation (kQ,kv≠0,pQr,pvr≠0)" --- p.37 / Chapter 4.2.1 --- Effect of interest rate --- p.43 / Chapter 4.3 --- Monte Carlo simulation (PQV≠0) --- p.47 / Chapter 5 --- Expected loss of residential mortgage loans --- p.56 / Chapter 5.1 --- Introduction to residential mortgage loans --- p.56 / Chapter 5.2 --- Calculation of expected loss of residential mortgage loans --- p.59 / Chapter 6 --- Numerical results and discussion --- p.65 / Chapter 6.1 --- Numerical results --- p.65 / Chapter 7 --- Conclusion --- p.73 / Chapter A --- Methodology --- p.75 / Chapter A.1 --- Monte Carlo Simulation --- p.76 / Chapter A.2 --- Finding lower and upper bound approach --- p.79 / Chapter A.2.1 --- Single stage approximation --- p.79 / Chapter A.2.2 --- Multistage lower bound approximation --- p.82 / Bibliography --- p.85

Yeung Kin Bong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 69-73). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Credit risk modeling --- p.3 / Chapter 1.2 --- Uniqueness of bi-directional: hybrid system --- p.4 / Chapter 1.3 --- Scope of the study --- p.5 / Chapter 2 --- Literature Review --- p.6 / Chapter 2.1 --- Statistical / Empirical approach --- p.6 / Chapter 2.2 --- Structural approach --- p.8 / Chapter 3 --- Background --- p.10 / Chapter 3.1 --- Merton structural default model --- p.10 / Chapter 3.2 --- Cross-sectional regression analysis (CRA) --- p.15 / Chapter 3.3 --- Neural network learning (NN) --- p.16 / Chapter 3.3.1 --- Single-layer network --- p.17 / Chapter 3.3.2 --- Multi-layer perceptron (MLP) --- p.20 / Chapter 3.3.3 --- Back-propagation network --- p.22 / Chapter 3.3.4 --- "Supervised, unsupervised and combine unsupervised-supervised learning" --- p.23 / Chapter 3.4 --- Weaknesses of uni-directional modeling --- p.23 / Chapter 4 --- Methodology --- p.26 / Chapter 4.1 --- Bi-directional modeling --- p.26 / Chapter 4.2 --- Asset price estimation --- p.31 / Chapter 4.3 --- Quantifying accounting data noise --- p.33 / Chapter 5 --- Proposed Model --- p.37 / Chapter 5.1 --- Core of the model --- p.37 / Chapter 5.2 --- Feature selection --- p.41 / Chapter 5.3 --- Bi-directional default neural system --- p.44 / Chapter 6 --- Implementations --- p.49 / Chapter 6.1 --- Data preparation --- p.50 / Chapter 6.2 --- Experiment --- p.51 / Chapter 6.3 --- Empirical results --- p.61 / Chapter 6.3.1 --- Predicted spreads from the uni-directional models --- p.61 / Chapter 6.3.2 --- Predicted spreads from the proposed bi-directional model --- p.63 / Chapter 6.3.3 --- Performance comparison --- p.64 / Chapter 7 --- Conclusions --- p.67 / Bibliography --- p.69

The objective of this research proposal is to explore the extent to which credit derivatives can be used effectively by domestic financial institutions, in particular, Commercial Banks to hedge the credit risk associated with lending to the Small, Medium and Micro enterprise (SMME) market segment, thereby making lending to this market segment an attractive and viable banking proposition. The financial services sector in South Africa has come under severe criticism from Government, trade unions and the unbanked, low income earners for not fulfilling their social responsibility, in terms of, not banking the Small, Medium and Micro enterprise (SMME) customer base. In particular, financial institutions have been accused of ignoring or not giving sufficient attention to the financial/credit needs of this market segment. These parties have argued that many of the domestic financial institutions are applying standard credit criteria to this market segment, which they feel is incorrect. This has often resulted in SMME's having their requests for credit facilities declined by domestic financial institutions and then having to resort to approaching unscrupulous "loan sharks" for credit facilities, which facilities are often made available to them at exorbitant interest rates. The alleged reluctance on the part of domestic financial services institutions to make available credit facilities, in the form of start-up business loans and asset-based finance to the SMME segment has possibly hindered economic growth, productivity, employment and resulted indirectly in a host of other social anomalies. Alister Ruiters of the Department of Trade and Industry has been publicly vociferous in his attack on domestic financial institutions (Business Day, August18, 1999). It would appear these financial institutions are only prepared to do business with this market segment in partnership with Government, where Government bears a large proportion of the risk by providing guarantees or indemnities on behalf of the client. Examples of such guarantees include Khula and Sizabantu guarantees issued by agencies controlled within the ambit of the Department of Trade and Industry. Financial service institutions have defended their actions by countering that the credit risk attached to making loans available to the SMME market segment is often unacceptable to them. Many of these potential clients are characterised by adverse credit records, show little stability, in terms of, employment and domicilium and often do not have any tangible collateral available to support their loan requests. That is, the risk from lending to this market segment far outweighs the potential returns. Further, these financial institutions have argued that with South Africa having been accepted into the international fold and following the accelerated pace of globalisation, new markets have opened up for their shareholders. Hence, shareholders are requiring improved returns (capital gains and/or dividends); else they are at liberty to move their funds to other investment destinations. The pressure on domestic financial institutions to deliver consistently better returns on equity has been and continues to be a difficult one. This is exacerbated by the increasing competitive pressure from both retail competitors who are now offering financial services, such as Pick 'n Pay Financial Services, Woolworth's, and foreign financial institutions, who have entered the domestic scene. For many of the retail competitors the offering of financial services is seen merely as an extension of their product line. Existing infrastructure, in the form of, branches /outlets and technology are largely already in place. Further, they are not bound by the same liquidity reserve requirements imposed by the South African Reserve Bank (SARB), as are the domestic financial institutions they now compete against. Hence, the retail competitors' profit margins are likely to be higher. Further, as many of the foreign financial institutions are not constrained by the same social responsibility obligations local financial institutions face and as they have not invested substantially in branch networks and other infrastructure in South Africa, their profit margins are higher and hence their returns on equity is likely to be significantly higher than the domestic financial institutions. Following the increasing popularity of Credit Derivatives in countries, such as, the United States of America, the United Kingdom and India, it is my intention to explore whether this instrument can be used effectively by domestic financial institutions as an hedging tool to insure against what they might otherwise consider unacceptable risk in the SMME market segment. That is, will the use of credit derivatives make the lending of funds to this client base an acceptable or attractive proposition to domestic financial institutions. However, we first need to define credit risk and credit derivatives before we proceed further. Creditex (Commentary, May 2001) defines credit risk as: "the risk of loss following default. " PriceWaterhouseCoopers defines a credit derivative as : "a credit risk management instrument that allows a financial institution to transfer credit risk to another party". Having, in simple terms, defined what we mean by credit risk and credit derivatives, we proceed by suggesting how credit derivatives can be used as an effective hedging tool and also some of the possible shortcomings that may be associated with the use of credit derivatives in South Africa. Cheow and Chiu (Managing Credit Risks, May 23,2001) suggest credit derivatives have the potential to transform the way in which Commercial Banks do business. The impact of credit derivatives is likely to result in changes in Bank's operating and credit models of assessment, pricing policies and offer insight into how products and services may be developed and implemented. Traditionally Banks appear to have been involved in all aspects of lending from origination to administration, monitoring and collection. These authors suggest the resulting credit model emanating from the use of credit derivatives is likely to only concentrate on origination of the loan with the view of later selling-off the book itself or insuring the credit risk. This latter alternative involves credit derivatives. We turn our attention to highlighting some possible constraints to the effective use of credit derivatives in South Africa. These are as follows :  Lack of effective infrastructure  Lack of liquidity  Lack Of Transparency  Restrictive Central Bank regulations and exchange controls  limited number of large financial institutions. / Thesis (MBA)-University of Natal, Durban, 2002.

The diploma thesis focuses on enterprise performance assessment. Based on financial analysis methods the company's financial health is evaluated. Results are compared with three competing companies. Comprehensive company performance also contains strategic analysis, credit management analysis and analysis of stakeholders' satisfaction. Recommendations and suggestions to sustain company performance are defined at the end of this thesis.

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) / Please refer to full text to view abstract

M. Tech. (Department Management Accounting, Faculty of Management Sciences), Vaal University of Technology. / Municipal debt has been steadily rising year after year, jeopardizing the financial stability of many municipalities. There is a commonly overlooked provision within the Municipal Finance Management Act, section 64(2)(a), that states that the municipal manager must ensure that the municipality has a functional credit management and debt collection system. However, it is also the obligation of municipal residents to ensure that they pay rates and taxes for the services supplied to them in order to ensure the sustainability of service supply. Municipalities rely on revenue collection to ensure their survival and viability. Due to the importance of this sphere of government, this study investigates whether residents respond to the credit management policy of the municipality and whether it is implemented effectively. The study does so by looking at the relationship between credit management policy implementation and service delivery in the selected municipality in Sedibeng District. The study followed a quantitative research methodology, using self-administered hard copy questionnaires to collect data from 510 residents of municipality A of Sedibeng District municipality. Seven (7) different locations with the demographic of municipality A of Sedibeng District were selected to participate in the study, with a response rate of 100%. Data were statistically analysed through SPSS and testing included correlation analysis, factor analysis, frequency counting and ANOVA testing. The data collected revealed that there is a lack of credit management policy implementation and enforcement when it comes to non-payment of municipal outstanding accounts. According to the quantitative findings, residents have a negative attitude towards the credit management policy. However, the findings also showed that there are factors that influence responsiveness such as poverty, (un)employment and educational level. The findings also revealed a significant relationship between credit management policy and service delivery. Failure to pay municipal debts results in poor service delivery by municipalities. because they lack the financial stability necessary to provide a sustainable service supply. In turn, poor service delivery results in residents refusing to pay municipal debts because they are unwilling to pay for poor services. Recommendations such as continuous review of critical debt recovery policies, rebates and discount granted to residents, the introduction of advanced technical systems, quality service delivery, employee training and development and the like will assist municipalities to improve the effectiveness of their credit management policy implementation. The limitations to of study entails difficulty in obtaining municipal ethical clearance, because municipal officers are concerned about confidentiality. Furthermore, there were the COVID-19 regulations posed by the South African government to curb the spread of COVID-19 which also had an impact in collecting data from participants. The findings may not be generalised to a larger population of all South African municipalities.

有實證研究表明，傳統的信貸風險結構模型顯著低估了違約概率以及信貸收益率差。傳統的結構模型有三個可能的問題：1. 因為正態假設，布朗模型在模擬公司資產價值的過程中未能捕捉到極端事件2. 市場微觀結構噪聲扭曲了股票價格所包含信息3. 在到期日前任何時間，標準BS 期權理論方法不足以描述任何破產的可能性。這些問題在過去的文獻中曾分別提及。而在本文中，在不同的信用風險結構模型的基礎上，我們提出了貝葉斯方法去估算公司價值的跳躍擴散過程和微觀結構噪聲。因為企業的資產淨值不能在市場上觀察，本文建議的貝葉斯方法可對隱藏變量和泊松衝擊作出一定的估算，並就後驗分佈進行財務分析。我們應用馬爾可夫鏈蒙特卡羅方法（MCMC）和吉布斯採樣計算每個參數的後驗分佈。以上的做法，允許我們檢查結構性信用風險模型的偏差主要是來自公司價值的分佈、期權理論方法或市場微觀結構噪聲。我們進行模擬研究以確定模型的表現。最後，我們以新興市場的數據實踐我們的模型。 / There is empirical evidence that structural models of credit risk significantly underestimate both the probability of default and credit yield spreads. There are three potential sources of the problems in traditional structural models. First, the Brownian model driving the firm asset value process may fail to capture extreme events because of the normality assumption. Second, the market micro-structure noise in trading may distort the information contained in equity prices within the estimation process. Third, the standard Black and Scholes option-theoretic approach may be inadequate to describe the consequences of bankruptcy at any time before maturity. These potential problems have been handled separately in the literature. In this paper, we propose a Bayesian approach to simultaneously estimate the jump-diffusion firm value process and micro-structure noise from equity prices based on different structural credit risk models. As the firm asset value is not observable but the equity price is, the proposed Bayesian approach is useful in the estimation with hidden variable and Poisson shocks, and produces posterior distributions for financial analysis. We demonstrate the application using the Markov chain Monte Carlo (MCMC) method to obtain the posterior distributions of parameters and latent variable. The proposed approach enables us to check whether the bias of the structural credit risk model is mainly caused by the firm value distribution, the option-theoretic method or the micro-structure noise of the market. A simulation study is conducted to ascertain the performance of our model. We also apply our model to the emerging market data. / Detailed summary in vernacular field only. / Chan, Sau Lung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves 62-65). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese. / List of Tables --- p.vii / List of Figures --- p.viii / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Background and Intuition --- p.5 / Chapter 2.1 --- Merton Model with Trading Noise --- p.7 / Chapter 2.2 --- Black-Cox Model with Default Barrier --- p.10 / Chapter 2.3 --- Double Exponential Jump Diffusion Model (KJD Model) --- p.11 / Chapter 2.4 --- Equity Value via Laplace Transforms --- p.13 / Chapter 2.5 --- KJD Model with Trading Noises --- p.15 / Chapter 3 --- Bayesian Analysis --- p.17 / Chapter 3.1 --- Gibbs Sampling and Metropolis-Hastings Method --- p.17 / Chapter 3.2 --- Merton Model with Trading Noises (M1) --- p.19 / Chapter 3.2.1 --- Prior Distribution for M1 --- p.19 / Chapter 3.2.2 --- Posterior Distribution for M1 --- p.20 / Chapter 3.3 --- Merton Model with Default Barrier (M2) --- p.22 / Chapter 3.3.1 --- Prior Distribution for M2 --- p.23 / Chapter 3.3.2 --- Posterior Distribution for M2 --- p.23 / Chapter 3.4 --- KJD Model with Trading Noises (M3) --- p.25 / Chapter 3.4.1 --- Prior Distribution for M3 --- p.26 / Chapter 3.4.2 --- Posterior Distribution for M3 --- p.27 / Chapter 3.5 --- KJD Model with Default Barrier (M4) --- p.33 / Chapter 3.5.1 --- Prior Distribution for M4 --- p.34 / Chapter 3.5.2 --- Posterior Distribution for M4 --- p.35 / Chapter 4 --- Numerical Examples --- p.42 / Chapter 4.1 --- Simulation Analysis --- p.42 / Chapter 4.2 --- Empirical Study --- p.46 / Chapter 4.2.1 --- BEA and DBS, 2003-2004 --- p.46 / Chapter 4.2.2 --- HSBC, 2008-2009 --- p.49 / Chapter 5 --- Conclusion --- p.60 / Bibliography --- p.62

Following the recent financial crisis, financial regulators have placed a strong emphasis on reducing expectations of government support for banks, and on better managing and assessing risks in the banking system. This thesis considers three current topics in credit risk and the statistical problems that arise there. The first of these topics is expectations of government support in distressed banks. We utilize unique features of the European credit default swap market to find that market expectations of European government support for distressed banks have decreased -- an important development in the credibility of financial reforms. The second topic we treat is the estimation of covariance matrices from the perspective of market risk management. This problem arises, for example, in the central clearing of credit default swaps. We propose several specialized loss functions, and a simple but effective visualization tool to assess estimators. We find that proper regularization significantly improves the performance of dynamic covariance models in estimating portfolio variance. The third topic we consider is estimation risk in the pricing of financial products. When parameters are not known with certainty, a better informed counterparty may strategically pick mispriced products. We discuss how total estimation risk can be minimized approximately. We show how a premium for remaining estimation risk may be determined when one counterparty is better informed than the other, but a market collapse is to be avoided, using a simple example from loan pricing. We illustrate the approach with credit bureau data.