Determination of net interest margin drivers for selected financial institutions in South Africa : a comparison with other capital markets
- Authors: Mudzamiri, Kizito
- Date: 2013-05-01
- Subjects: Banks and banking - South Africa , Financial institutions - South Africa , Net interest margins , Classical Linear Regression Model , Ordinary Least Squares data estimating technique , Bank profits - South Africa , Interest rates - South Africa
- Type: Thesis
- Identifier: http://ujcontent.uj.ac.za8080/10210/379972 , uj:7473 , http://hdl.handle.net/10210/8331
- Description: M.Comm. (Financial Management) , There is a wide perception that bank net interest margins (NIMs) in Sub-Saharan Africa in general and South Africa in particular, are higher compared to other regions. The study investigates four commercial banks in South Africa with the aim of identifying the relevant factors affecting the behaviour of NIMs in commercial banking in South Africa, and draws comparisons with other markets. The study employs the Classical Linear Regression Model (CLRM) using the Ordinary Least Squares (OLS) data estimating technique to analyse net interest margins over the period 2000 to 2010. The study takes note of Ho and Saunders’s seminal work produced in 1981, and subsequent extensions and modification by other authors and researchers. Net interest margins are modeled in a single-step together with explanatory variables driven from the theoretical model. Using data obtained from the Bankscope data base, the variables examined in the study are; competitive structure of the market, average operating costs, management’s propensity for risk aversion, credit risk exposure, the quantum of the bank’s operations, short-term money market interest rate volatility, the opportunity cost of holding reserves and quality of management running the institution. The findings of the study suggest that market power, average operating costs, degree of risk aversion, credit risk exposure, and size of operations are major factors explaining the behaviour of NIMs in South Africa. These variables are major in terms of the number of banks that exhibit statistical significance. Market power, interest rate volatility and opportunity cost of holding reserves are also relevant factors, although they affect fewer banks than the major factors. Comparison of South African net interest margins determinants with those from other regions reveals some fundamental differences. These differences indicate that banks from different countries and regions are faced with different operating environments and risk profiles that drive net interest margins.
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- Authors: Mudzamiri, Kizito
- Date: 2013-05-01
- Subjects: Banks and banking - South Africa , Financial institutions - South Africa , Net interest margins , Classical Linear Regression Model , Ordinary Least Squares data estimating technique , Bank profits - South Africa , Interest rates - South Africa
- Type: Thesis
- Identifier: http://ujcontent.uj.ac.za8080/10210/379972 , uj:7473 , http://hdl.handle.net/10210/8331
- Description: M.Comm. (Financial Management) , There is a wide perception that bank net interest margins (NIMs) in Sub-Saharan Africa in general and South Africa in particular, are higher compared to other regions. The study investigates four commercial banks in South Africa with the aim of identifying the relevant factors affecting the behaviour of NIMs in commercial banking in South Africa, and draws comparisons with other markets. The study employs the Classical Linear Regression Model (CLRM) using the Ordinary Least Squares (OLS) data estimating technique to analyse net interest margins over the period 2000 to 2010. The study takes note of Ho and Saunders’s seminal work produced in 1981, and subsequent extensions and modification by other authors and researchers. Net interest margins are modeled in a single-step together with explanatory variables driven from the theoretical model. Using data obtained from the Bankscope data base, the variables examined in the study are; competitive structure of the market, average operating costs, management’s propensity for risk aversion, credit risk exposure, the quantum of the bank’s operations, short-term money market interest rate volatility, the opportunity cost of holding reserves and quality of management running the institution. The findings of the study suggest that market power, average operating costs, degree of risk aversion, credit risk exposure, and size of operations are major factors explaining the behaviour of NIMs in South Africa. These variables are major in terms of the number of banks that exhibit statistical significance. Market power, interest rate volatility and opportunity cost of holding reserves are also relevant factors, although they affect fewer banks than the major factors. Comparison of South African net interest margins determinants with those from other regions reveals some fundamental differences. These differences indicate that banks from different countries and regions are faced with different operating environments and risk profiles that drive net interest margins.
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The proposed twin-peaks system for regulating the financial sector of South Africa in comparative perspective
- Authors: Erasmus, Amanda
- Date: 2016
- Subjects: Financial institutions - South Africa , Banks and banking - South Africa , Financial services industry - Law and legislation - South Africa , Banking law - South Africa , Financial crises - Law and legislation - South Africa , Global Financial Crisis, 2008-2009
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/87721 , uj:19615
- Description: Abstract: Please refer to full text to view abstract , LL.M. (Banking Law)
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- Authors: Erasmus, Amanda
- Date: 2016
- Subjects: Financial institutions - South Africa , Banks and banking - South Africa , Financial services industry - Law and legislation - South Africa , Banking law - South Africa , Financial crises - Law and legislation - South Africa , Global Financial Crisis, 2008-2009
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/87721 , uj:19615
- Description: Abstract: Please refer to full text to view abstract , LL.M. (Banking Law)
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Determinants of financial performance of commercial banks and other financial institutions in South Africa
- Authors: Moyo, Irvine Tafadzwa
- Date: 2018
- Subjects: Banks and banking - South Africa , Financial institutions - South Africa
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/296002 , uj:32243
- Description: Abstract: The closure of African Bank Investments Limited (ABIL) in 2014 and also a myriad of challenges facing the commercial banks and other financial institutions led to this research. The major aim was to address the badgering question: What are the drivers/determinants of financial performance of commercial banks and other financial institutions? The main objective of the research is to find these determinants of financial performance of commercial banks and then compare them with other factors found in other financial institutions which are non-commercial banks (i.e. financial institutions which do not have a commercial banking licence, but are still in the same industry). The literature was drawn from South African studies on the financial performance of financial institutions. They included other sources in Africa and also from the rest of the world. The literature helps in building up the appropriate methodology to be used to answer the basic hypotheses questions: Do bank-specific factors determine the financial performance of financial institutions, is it the macroeconomic factors which are the major determinants, or is it both? These hypotheses were broken down into sub-hypotheses (which are anchored on the explanatory variables). The explanatory variables used in the study are: bank-specific factors (i.e. bank size, solvency, capital adequacy, liquidity asset quality, debt management, management efficiency) and macroeconomic factors (economic growth, inflation and interest rates). The dependent variables for the research are: return on equity, return on assets, and net interest margin. The proposed methodology was drawn from three distinct models using the dependent variable – ROE Model, ROA Model and NIM Model. The data range is biannual from 2007:1 to 2017:1. The econometric model employed was the panel regression model, pooling together three commercial banks and three other financial institutions. The panel regression models, i.e. fixed effects and random effects models, were implemented to analyse the relationship between dependent and independent variables. However, the Hausman test on both models was used to determine which of the two regression analysis was more appropriate. In all instances, the fixed effects model was chosen. There were two scenarios which the research employed in order to fully test the hypotheses and also achieve its goal of comparative analysis. Scenario 1 (Combined scenario) was pooling all the financial institutions together in a six cross sectional panel regression analysis. Scenario 2 (Comparative scenario) was pooling three commercial banks and three other financial intuitions separately. The results showed that the financial performance was diverse for both commercial banks and other financial institutions... , M.Com. (Finance)
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- Authors: Moyo, Irvine Tafadzwa
- Date: 2018
- Subjects: Banks and banking - South Africa , Financial institutions - South Africa
- Language: English
- Type: Masters (Thesis)
- Identifier: http://hdl.handle.net/10210/296002 , uj:32243
- Description: Abstract: The closure of African Bank Investments Limited (ABIL) in 2014 and also a myriad of challenges facing the commercial banks and other financial institutions led to this research. The major aim was to address the badgering question: What are the drivers/determinants of financial performance of commercial banks and other financial institutions? The main objective of the research is to find these determinants of financial performance of commercial banks and then compare them with other factors found in other financial institutions which are non-commercial banks (i.e. financial institutions which do not have a commercial banking licence, but are still in the same industry). The literature was drawn from South African studies on the financial performance of financial institutions. They included other sources in Africa and also from the rest of the world. The literature helps in building up the appropriate methodology to be used to answer the basic hypotheses questions: Do bank-specific factors determine the financial performance of financial institutions, is it the macroeconomic factors which are the major determinants, or is it both? These hypotheses were broken down into sub-hypotheses (which are anchored on the explanatory variables). The explanatory variables used in the study are: bank-specific factors (i.e. bank size, solvency, capital adequacy, liquidity asset quality, debt management, management efficiency) and macroeconomic factors (economic growth, inflation and interest rates). The dependent variables for the research are: return on equity, return on assets, and net interest margin. The proposed methodology was drawn from three distinct models using the dependent variable – ROE Model, ROA Model and NIM Model. The data range is biannual from 2007:1 to 2017:1. The econometric model employed was the panel regression model, pooling together three commercial banks and three other financial institutions. The panel regression models, i.e. fixed effects and random effects models, were implemented to analyse the relationship between dependent and independent variables. However, the Hausman test on both models was used to determine which of the two regression analysis was more appropriate. In all instances, the fixed effects model was chosen. There were two scenarios which the research employed in order to fully test the hypotheses and also achieve its goal of comparative analysis. Scenario 1 (Combined scenario) was pooling all the financial institutions together in a six cross sectional panel regression analysis. Scenario 2 (Comparative scenario) was pooling three commercial banks and three other financial intuitions separately. The results showed that the financial performance was diverse for both commercial banks and other financial institutions... , M.Com. (Finance)
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