Faculty of Commerce, Law and Management (ETDs)
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Item Determinants of credit risk on residential mortgage loans in South Africa(University of the Witwatersrand, Johannesburg, 2020) Mbulana, Alikho; Mthanti, ThantiResidential mortgages are an important asset class for banks as these assets provide the majority of bank’s income. By the nature of issuing loans to customers, this asset class also presents the greatest risk to the banks and as a result, banks need to constantly evaluate and review credit risk in order to ensure dynamic response strategies that curb losses and achieve sustainable profits. This study aims to investigate factors influencing credit risk on residential mortgage loans in South Africa. A regression analysis was conducted to capture the influence of both macroeconomic and bank specific factors on loans that have been in arrears for less than 89 days and on loans that have been in default for more than 90 days; using monthly data from an undisclosed bank over a period of eight years, 2010 to 2018. The results show that Housing Price Index, Unemployment, Household Disposable Income, Bank’s Capitalization and Operational Efficiency are the only significant determinants for non-performing residential mortgage loans that are less than 89 days. Credit Quality, Inflation, Unemployment, Household Disposable Income, Bank’s Capitalization, Operational Efficiency and are the main determinants of the non-performing residential mortgage loans greater than 90 daysItem The impact of climate change on investment risk and credit risk(University of the Witwatersrand, Johannesburg, 2023) Bell, Francesca; Van Vuuren, GaryESG (Environmental, Social, and Governance) factors have evolved from being a minor consid- eration in the 2000s to a major factor for many companies in 2023. Many companies are now assigned ESG grades, which are closely examined by investors. While it would be ideal for re- sponsible firms to be rewarded and culprits to be penalised, this is not always the case in a profit- driven world. Investors are likely to always prioritise profitability, so some compromise is neces- sary. Recent efforts to balance corporate responsibility with portfolio performance are promising. Using Lagrangian calculus, portfolio optimisation techniques have been developed that show re- turns and risk profiles comparable to those of unconstrained portfolios (i.e., ones which did not consider ESG scores). As expected, low ESG scores influence portfolio performance negatively (as measured by the Sharpe ratio), but very high ESG scores have the same effect. Optimal ESG scores are those which represent the turning points of these relationships, i.e., those ESG scores which result in maximal Sharpe ratios. These optimisation techniques are applied to emerging market corporates for the first time. Over time, ESG scores have improved globally, at varying rates, and have resulted in a statistically significant decrease in risk and increase in returns. As volatility increases, optimal ESG grades rise slowly, and associated Sharpe ratios decrease, and it is postulated that this could be due to the option-like relationship between underlying volatility and inherent value. With a better understanding of trends, asset managers who consider ESG met-rics can confidently assert that ESG compliant portfolios do generate healthy risk-adjusted returns (Sharpe ratios) and that these values are improving over time. ESG compliant portfolios are now viable investments that align with responsible investment principles. Firms must estimate expected credit losses (EL) to comply with accounting standards and unex-pected credit losses (UL) to determine regulatory credit risk capital. Both rely on estimates of obligor probabilities of default (PD). Changes in climate, however gradual, increase firm default rates and climate shocks such as floods or droughts exacerbate these impacts. Investors pay close attention to credit ratings which are derived from inter alia default rates, but studies investigating the impact of climate change on PDs are currently limited and data are still relatively scarce. Africa will be most severely impacted by climate change: default rates will deteriorate leading to in- creased PDs, losses given default (LGDs), provision requirements (through increased ELs) and vi regulatory credit risk capital (through increased ULs). To investigate these effects theoretically, corporate equity prices are simulated using Geometric Brownian Motion (GBM) and shocks brought about by climate events of differing frequency and severity are applied to these simulated prices. Post shock prices and return volatilities are differentially affected depending on the nature of the applied shock. These are used as inputs into a well-known Merton (1974) model of corporate default from which market-implied PDs may be extracted. A possible calibration approach is developed for climate event-based impacts on corporate default rates. A scaling factor matrix (an amount by which the unaffected default rate increases after a specified climate event type occurs) can help market participants forecast default rate changes. Climate related impacts have been quan- tified, calibrated, and used to assess credit quality degradatItem Determinants of credit risk on residential mortgage loans in South Africa(2021) Mbulana, AlikhoResidential mortgages are an important asset class for banks as these assets provide the majority of bank’s income. By the nature of issuing loans to customers, this asset class also presents the greatest risk to the banks and as a result, banks need to constantly evaluate and review credit risk in order to ensure dynamic response strategies that curb losses and achieve sustainable profits. This study aims to investigate factors influencing credit risk on residential mortgage loans in South Africa. A regression analysis was conducted to capture the influence of both macroeconomic and bank specific factors on loans that have been in arrears for less than 89 days and on loans that have been in default for more than 90 days; using monthly data from an undisclosed bank over a period of eight years, 2010 to 2018. The results show that Housing Price Index, Unemployment, Household Disposable Income, Bank’s Capitalization and Operational Efficiency are the only significant determinants for non-performing residential mortgage loans that are less than 89 days. Credit Quality, Inflation, Unemployment, Household Disposable Income, Bank’s Capitalization, Operational Efficiency and are the main determinants of the non-performing residential mortgage loans greater than 90 days