A comparative study of performance of commercial banks in ASIAN developing and developed countries

Abstract

The main focus of this study is to investigate the impact of non-performing loans (NPLs) and other bank specific factors on the financial performance of commercial banks in Asian developing and developed countries due to an alarmingly high ratio of non-performing loans.The bank specific factors that are used in this study are cost efficiency ratio (CER), capital adequacy ratio (CAR), size of the bank, sales growth (SG) and proxies of financial performance (FP) are return on equity (ROA) and return on asset (ROE). Secondary Panel data of ten years (2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) has been used for this empirical analysis and 19 commercial banks from developing countries of Asia (Pakistan and India), while 17 commercial banks from developed countries of Asia (Japan and Saudi Arabia) are selected. Generalized method of moment is used for the coefficient estimation to overcome the effects of some endogenous variables. NPLs and CER are significantly negatively related to the financial performance (ROA and ROE) of developing and developed countries commercial banks. There is a negative relationship of bank size with most of financial performance variables. Sale growth and capital adequacy ratio has significant positive relationship both measures of financial performance (ROA and ROE) in both pools. Due to the importance of commercial banks in the overall economy of a country, there is a need for management of commercial banks and regulatory authorities to undertake policies that ensure efficiency in banking operations.

Key determinants of deposits volume using CAMEL rating system: The case of Saudi banks

“…[ 49 ] determined the cost-efficiency ratio and non-performing loans are significantly negatively related to financial performance. [ 50 ] indicated that bank size and the number of bank branches were important drivers of bank efficiency and further found that capital, asset, and earnings of banks were essential factors for technical efficiency and pure technical efficiency of the banks.…”

The possibilities and consequences of investment decisions by stepwise optimization

“…However, the initially created mean-variance portfolio has been further developed into three following directions: 1) simplifying the required data and decreasing its amount; 2) inclusion of alternative risk measures; 3) inclusion of additional criteria or constraints. After analysing portfolio optimization literature, it can be seen that scientists often conclude that the portfolio selection problem should include additional parameters besides return and risk (Meghwani & Thakur, 2017;Sanchez-Roger et al, 2020;Siddique et al, 2020;Steuer et al, 2008). Examples of such criteria are liquidity (Al Janabi et al, 2019;Jana et al, 2009;Li & Zhang, 2021), skewness (Kerstens et al, 2008;Konno & Yamamoto, 2005;Pahade & Jha, 2021;Saborido et al, 2016), conditional value at risk (CVaR) (Aboulaich et al, 2010;Najafi & Mushakhian, 2015;Strub et al, 2019).…”

A Comparative Examination of Non-Performing Asset Management of Banks in India

“…Singh (2016) found that the NPA level of Indian banks is higher associated with overseas banks and the delinquent of repossession is not with small borrowers only, but with big debtors also. Siddique et al (2020) examined the act of nonperforming advances and bank precise issues distressing the economic recital of commercial banks in emerging and advanced nations in the Asian continent due to the surge in NPAs globally. The study used panel data for 10 years from 2006 to 2015 for studying the performance of banks.…”