Department of Accountancy

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Browsing Department of Accountancy by Author "Obadire, Ayodeji Michael"

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    Basel III regulatory requirements and the performance efficiency and capital structure of selected listed African banks
    (2022-11-10) Obadire, Ayodeji Michael; Moyo. V.; Munzhelele, N. F.
    This study examined the impact of Basel III regulatory requirements on the financial performance, stability, efficiency, capital structure and risk-taking behaviour of selected listed African banks. The research hypotheses were formulated and tested using the Blundell and Bond system of Generalised Methods of Moment (GMM), pooled Ordinary Least Squares (OLS), Random Effects (RE), and Fixed Effects (FE) estimators. The study further used a panel data of 45 listed banks from six African countries that had adopted the Basel III Accord for the period 2010 to 2019. The system GMM estimator was used to estimate the impact of the Basel III regulatory requirements on the capital structure decisions of the selected African banks. Robustness tests were performed by using the two-step Blundell and Bond system GMM procedure. The robust results showed that the selected African banks were highly leveraged with a positive relationship between the Basel III minimum capital requirement, capital adequacy ratio, capital buffer premium and the bank leverage measured by the ratio of Tier 1 capital to total exposure. Furthermore, the study revealed that the bank specific capital structure determinant such as the bank size, asset tangibility and profitability had a significant and positive impact on African banks’ observed leverage and were important determinants of the discretionary capital. The trade-off, pecking order and agency cost theories were the three underpinning capital structure theories that complimentarily explained the financing behaviours of the selected African banks. Furthermore, the study used the pooled OLS, FE and RE estimators where appropriate to fit the models testing the impact of Basel III regulatory requirements on the financial performance, stability, efficiency and risk-taking behaviour of the selected African banks. Robustness tests were performed by conducting diagnostics tests such as the F- test, Breusch and Pagan test and the Hausman specification test. These tests were conducted to select the appropriate estimator amongst the pooled OLS, FE and RE estimators. To test the banks’ financial performance, the RE and FE estimators were used to fit the ROE and ROA models respectively whilst the pooled OLS estimator was used to fit the banks stability model. Moreover, to test the banks’ efficiency, vi the pooled OLS and RE estimators were used to fit the NIMR and OETA models respectively, whilst the RE estimator was used to fit the banks’ risk-taking behaviour models. Furthermore, the study showed that the capital adequacy ratio had a significant positive effect on the financial performance of the selected African banks, whilst the liquidity requirement was positively correlated to bank stability. In addition, the capital buffer premium had a significant positive impact on both measures of bank efficiency, whilst the liquidity requirements showed a more significant impact, and was consistent across all the three measures of the risk-taking behaviour of the selected African bank. The current study contributes to the body of knowledge in eight significant ways and most importantly proposes an optimum model and mix of regulatory capital requirements that can maximise the financial performance, stability and efficiency of the selected African banks.
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    The impact of macroeconomic variables on the equity market risk premium in South Africa
    (2018-09-21) Obadire, Ayodeji Michael; Moyo, V.; Mache, F.
    The relationship between the Equity Market Risk Premium (MRP) and macroeconomic variables has been a subject of extensive discussion in the finance literature. The MRP is a central component of the main asset pricing models which are used to estimate the cost of equity which is mainly used in investment appraisal, performance measurement and valuation of equity assets. Past studies have identified inflation rate, interest rate, foreign exchange rate and political risk as the key macroeconomic variables that determine the size of the MRP. The test of the impact of these variables on the MRP have however been based mainly on data from developed countries and a few emerging countries. To the researcher’s knowledge, there are no studies that have investigated the impact of these macroeconomic variables on the MRP in South Africa. It is necessary to test the impact of these variables in the context of South Africa as these variables vary across countries. Using time series secondary data that was obtained from the SARB database, JSE database and World Bank database for the period 2002 to 2017, this study investigated the impact of these variables on the MRP in South Africa. A total of 192 observations per series of the inflation rate, interest rate, foreign exchange rate, political risk, JSE-ALSI and 91-days Treasury bill was used in the study. The data used were tested for possible misspecification errors that could arise from using a time series secondary data and the regression model was fitted using the Ordinary Least Square (OLS) estimator. The misspecification tests and models were both implemented on STATA 15 software. The results shows that inflation rate, interest rate and foreign exchange rate have a negative impact on the MRP whilst political risk has a positive impact on the MRP. Furthermore, the result shows that the inflation rate is the only variable amongst other variable tested that has a significant influence on the MRP for the study period. The study, therefore, concludes that inflation rate has the highest impact on the MRP in the context of South Africa. The study recommends that inflation rate should be monitored and kept within its target of 3-6% amongst other variables tested in order to increase investors’ confidence in the security market and also foster economic growth. The main limitations to the study were the limited data sources and insufficient funds.