Liquidity Risk Management: A Study on Selected Banks in Bangladesh

Abstract

Liquidity is regarded as one of the most essential challenges in banking. The greater a bank's exposure to this risk, the more vulnerable it may become. As a result, understanding the primary drivers of increased and decreased liquidity risk is critical in the banking business. The study aims to determine the effects of several variables related to liquidity risk over seven years (2018 2024) between twenty-three Bangladeshi banks. The report's goal is to demonstrate which factors alone affect liquidity risk and what steps can be taken to reduce and manage the risk. The paper found that the liquid position of banks has followed a downward trend throughout the years. Bangladesh's economic downturn is likely the cause of it. Whereas the logarithm size of the banks has increased slightly. Banks diversification into new product categories or geographical markets, which would increase their overall size. Regretfully, the non-performing loan (NPL) ratio has increased sizably which is very alarming. In addition to that, the study found that ROA is trending somewhat lower, much like the ROE. In 2019, it was at its lowest point. And capital adequacy ratios (CARs) are trending increasing, meaning that they are holding more capital about their risk-weighted assets (RWAs). The paper found that multicollinearity may not be a significant issue in the dataset as the average VIF is 2.27, and the values vary from 1.13 to 4.65. To deal with heteroskedasticity The Breusch Pagan test has been conducted. The p-value is less than 0.0000 demonstrating the presence of heteroscedasticity. To deal with this, the robust standard errors approach has been used. Similarly, to determine the best estimating approach, a Hausman test was carried out. And test suggests that the random-effects model is unlikely to be relevant, whereas the fixed-effects model is favored. After applying the robust fixed effect model, the R-squared is found to be 0.4563. the result suggests that the logarithm size of the banks as well as the capital adequacy ratio are significant at a 95% confidence interval. Both of them have shown a positive correction with the liquidity risk (Cash to Total Assets). This means that banks with higher Asset bases as well as higher Capital adequacy ratios are better in terms of their liquid position. Overall, the study shows the probable gap in the liquidity risk management of banks as well as the probable measures to take to tackle those gaps efficiently.