Abstract

Objective: The prime objective of the study is to examine the impact of risk management techniques on the financial performance of banks listed in the stock market. The CAMEL model which is one of the widely used models to access the relationship between the bank risk and bank performance has been used to access the bank performance banks listed in the stock market Methodology: Regarding the GMM analysis of the paper, the Arellano-Bond test for the sake of zero autocorrelation was employed, as shown in the table below. The Pearson test was used to determine the cross-sectional dependence for each model. The test findings reveal that the cross-sections are cross-sectionally dependent. We can utilize the Panel Corrected Standard Error (PCSE) and Feasible Generalized Least Squares (FGLS) with balanced panel datasets (PCSE). Due to the unbalanced nature of our panel datasets, we employed the robust clustering option after each model. The data were clustered across banks. Results: Based on the current findings, the CAMEL framework significantly affects the EVA model in assessing financial performance. This implies that the management of banks should concentrate not only on the aspects of ROA and ROE which signify banking profit but also on the EVA model which denotes the maximization of shareholder’s wealth. Implications: The findings of this research illustrated how different risk factors adapted from the CAMEL model of banks determine bank performance. The study will be helpful for policymakers, bankers, and researchers to understand the relationship between bank risk and bank performance. Novelty: This study offers a novel relationship between the CAMEL and bank performance.