Electronic Theses and Dissertations (Masters/MBA)

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Browsing Electronic Theses and Dissertations (Masters/MBA) by Author "Alovokpinhou, Sedjro Aaron"

Now showing 1 - 6 of 6
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    A comparative study of housing affordability in South Africa using the adjusted Debt-Service Ratio and Price-Income Approach
    (University of the Witwatersrand, Johannesburg, 2021) Mmesi, Lesotla; Alovokpinhou, Sedjro Aaron
    This study compares the adjusted Debt-Service Ratio (DSR) model and the widely used Price-Income Ratio (PIR) in the South African context to establish which of the measuring approaches give better and reliable results over time. In South Africa, housing unaffordability remains a challenge and accurately quantifying the extent of the problem is of key importance. The adjusted DSR model was seen as an appealing housing affordability measure to be explored as it corrects for household income changes and net financing cost of the mortgage loan thereof giving a refined calculation for housing affordability. The research also explores the relationship of both the adjusted DSR and PIR to key macroeconomic variables, that is, economic growth (EG), mortgage rate (MR), unemployment rate (MR) and house price (HPI). The findings show that the PIR is the better measure of housing affordability than the adjusted DSR. The PIR accurately parallels other banking sector data regarding housing affordability, whereas the adjusted DSR tends to underestimate housing affordability in the South Africa context. Another key finding is that, on average, the housing prices are too high for an economy like South Africa, which is still battling with, low GDP growth rate, high unemployment rate, inequality and poverty
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    Climate Mitigation Disclosure on Financial Performance and Market Stability: Evidence from South Africa
    (University of the Witwatersrand, Johannesburg, 2023) Ramafoko, Mokate George; Alovokpinhou, Sedjro Aaron
    This paper investigates the impact of climate risk disclosure in South Africa on the market stability and performance. The main proxies of climate risk used in the study are greenhouse gas emission intensity and environmental performance rating. The study uses a difference-in-difference method to isolate the effect of climate risk disclosure on a portfolio of highly exposed firms. Firstly, the results show that high greenhouse gas emitting firms have lower returns and higher volatility before and after controlling for time effects. However, the difference-in-difference coefficient from the analysis shows evidence of a weak correlation at a 10% significance level between disclosure of climate risk on the market performance of high greenhouse gas emitting firms relative to low emitters. Secondly, the study could not establish evidence that stocks of high greenhouse gas emitting firms experience higher volatility after the disclosure of their emission inventory. Results of the impact of environmental ratings on stock returns after adjusting for the time effect show that firms rated by the Climate Disclosure Project have lower returns than highly rated firms. However, the difference-in-difference coefficient is weak at a 10% significance level. The results are inconsistent with previous studies in developed countries where a strong correlation between climate risk and stock performance has been established. The findings from the study highlight that either climate risk is already factored into the stock prices, or the risk is viewed as immaterial to have an immediate impact on the equity market. The study addresses the existing literature gap on the effect of climate risk on developing countries' market stability and performance. Future work is required considering the evolving global focus on climate risk as a priority and the potential financial impact on firms’ sustainability
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    Predicting Systematic Risk Using Artificial Neural Networks
    (University of the Witswatersrand, Johannesburg, 2023) Setloboko, Thabiso; Alovokpinhou, Sedjro Aaron
    Financial institutions and investors are always investigating mathematical models that can enable them to make accurate predictions of time varying variables. For the longest time, statistical and autoregressive models have been at the forefront of forecasting. However, these are only accurate in short horizons; that is, these models are more accurate in daily, weekly, and monthly forecasts. This paper seeks to investigate long-horizon (yearly) forecasts using machine learning models called Artificial Neural Networks. The network uses neurons similar to biological neurons in living things, allowing them to study complex data patterns and retain pattern behaviors that allow them to make accurate predictions. The paper is based on the novel discovery that in forecasting long-horizon time series data, neural networks outperform statistical models significantly. The paper uses market data from the Johannesburg Stock Exchange and the New York Stock Exchange to represent the emerging and advanced markets, respectively. The forecasted data involves pre and post COVID-19. The shock introduced by the coronavirus is investigated to check if the forecasting ability of the model is affected. The empirical results demonstrate that the models accurately forecast systematic risk in the South African market more than in the American market. The accuracy of the model is measured by using root mean square error and mean absolute error. The model produced low error values for both markets, indicating their effectiveness in forecasting. It was expected that the error measures would consistently get lower as the time horizon increased; however, there were inconsistencies. For a portfolio manager, the results obtained in this research are interesting because the model handles large quantities of data and forecasts long-horizon systematic risk with little error. However, further investigation on this model still needs to be done
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    Public Debt and Government Guarantees
    (University of the Witwatersrand, Johannesburg, 2023) Same, Sinethemba; Alovokpinhou, Sedjro Aaron
    The focus of this research paper is to examine the relationship between public debt and government guarantees. The analysis considers various macroeconomic indicators, including short-term and long-term interest rates, budget deficits and real GDP growth rate, as control variables. The study predominantly concentrates on 16 European countries, with South Africa being the only African country in consideration. The study employed Generalized Methods of Moments (GMM) which is a Dynamic Panel Data technique, and Fixed Effect in establishing this relationship. The study found a positive association between public debt and government guarantees, short-term real interest rate, and its lag as estimators using the Fixed Effect model. However, budget deficit, real GDP growth, and long-term interest rates exhibit a negative and significant relationship
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    The Impact of IFRS 15 Adoption on the Financial Performance of JSE-Listed Companies in South Africa
    (University of the Witwatersrand, Johannesburg, 2022) Tchouaken Monkam, Marie Gisele; Alovokpinhou, Sedjro Aaron
    This study investigates whether the adoption of the IFRS 15 standard has influenced the financial performance of firms listed on the Johannesburg Stock Exchange (JSE). The study analysed a sample of 188 firms from 2015 to 2020, using descriptive statistics, correlation and regression analysis to estimate the results. To establish the impact that the IFRS 15 standard has on real returns on equity and return on assets, while controlling other covariates, a Pooled OLS regression and a dynamic panel-GMM analysis were conducted. The IFRS 15 standard was measured as a dummy variable, while the financial performance was measured using accounting measures: Return on Assets (ROA) and Return on Equity (ROE). Endogeneity issues were addressed, and data analysis was performed on an unbalanced panel using the panel pooled OLS and two-step system GMM. The results revealed that the implementation of the IFRS 15 standard in 2018 had a significant impact, either negative or positive, on the financial performance of firms listed on JSE. This suggests that the introduction of new accounting standards impacts the financial performance (ROA, ROE) of companies listed on the JSE
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    The promotion of Corporate Entrepreneurship in the South African financial services organisations
    (University of the Witwatersrand, Johannesburg, 2021) Nhlapo, Simon; Alovokpinhou, Sedjro Aaron
    There has been a growing interest in corporate entrepreneurship in the last four decades. Corporate entrepreneurship has therefore become a necessary attribute that organisations that wish to gain competitive advantage and be market leaders should possess. This study assesses the extent to which corporate entrepreneurship is promoted and encouraged in South African financial services organisations. The research study identifies and investigates organisational internal factors, which affect the promotion of corporate entrepreneurship in South African financial services organisations through administering Corporate Entrepreneurship Assessment instrument (CEAI). The research results indicate that work discretion is the only construct that respondents perceived to be encouraged and promoted. This was further confirmed by higher positive responses on items relating to autonomy and freedom. Participants reflected a neutral sentiment regarding the promotion of corporate entrepreneurship irrespective of gender, age, organisational level, tenure, and overall employment tenure. The research results also suggests that management sentiment is low on time availability for the promoting entrepreneurial activities. Therefore, we conclude that the South African financial services industry still has an enormous task to create an environment conducive for corporate entrepreneurship.