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The financial performance of banks relies heavily on properly utilizing their capital. However, bank ownership can have varying effects on the relationship between financial performance and capital. This study delves into this relationship by examining the impact of ownership on financial performance and bank capital. The study analyzes data from 44 commercial banks in Bangladesh and uses a two-step system generalized method of moments to address heteroscedasticity and autocorrelation issues. Unlike previous studies, this study confirms the significant effect of ownership on the relationship between bank financial performance and bank capital. The study's main findings are: (1) an inverted U-shaped relationship exists between bank capital and financial performance, implying that increasing capital can improve and reduce financial performance. (2) Private and Islamic commercial banks perform better than state-owned and conventional banks. (3) private-owned and Islamic commercial banks with higher capital are more likely to achieve higher profitability and financial success, while state-owned and conventional commercial banks with higher capital show lower profitability and weaker financial performance. Overall, this study offers significant practical implications for academics, researchers, and regulators interested in leveraging these findings.

This paper attempts to reveal how several credit risk factors are affecting the profitability of commercial banks considering the econometric models estimated with Random effect, Fixed effect, Pooled OLS and Cross-sectional Generalized least square (GLS) method followed by dynamic panel data model estimated with one-step GMM (generalized methods of moments) approach to incorporate the issue of endogeneity, unobserved heterogeneity and profit persistence of data set collected from annual report of banks covering from year 2010 to 2019 in Bangladesh. We have also adopted several diagnostic checks such as Model specification test, test of heteroskedasticty, cross sectional dependence test followed by test of autocorrelation and unit root test to examine the validity of the models selected for this study. The first part of our empirical investigation of the estimated models considering all methods reveals that out of all the independent credit risk factors such as Total loans to total assets ratio, Total loans to equity ratio, NPL to total loans, NPL to Total equity ratio, Provision for loan losses to total equity, total equity to total assets ratio, Total loans to total deposits ratio and provision for loan losses to NPL ratio, only provision for loan losses to NPL ratio is significantly affecting the dependent variable measured with NIM (Net interest margin) ratio of banks under fixed effect method. The next part of our empirical results of estimated models considering same methods divulges that NPL to total loans ratio, NPL to Total equity ratio and Provision for loan losses to total equity are also significantly affecting the dependent variable measured with ROE (Return on equity) of banks. The third segment of our empirical findings of estimated models considering same approaches shows that only NPL to total loans ratio is statistically significant under all methods but the NPL to total equity ratio is significant under fixed effect and GLS method and Provision for loan losses to total equity is significant under GLS method only in explaining the changes in ROA (Return on equity) measuring profitability of banks. Further investigation reveals that the dynamic impact of the said credit risk factors on profitability measured with ROE of banks has been successfully adopted by one-step system GMM approach considering all conditions required for estimation.