Abstract:
The purpose of this study is to investigate into how bank-specific and macroeconomic factors affect Bangladeshi banks' liquidity risk. The relationship between macroeconomic and bankspecific factors and liquidity is demonstrated in this study using the Random Effect Model and the Pooled OLS Model. The Hausman test has been utilized in this study to determine which of the Random Effect Model and Fixed Effect Model is the best. It is evident from the Hausman test results that the random effect model outperforms the fixed effect model. In this context, ten banks' annual reports over the last ten years (2014–2023) have been used. The study shows that bank size and total loan to total asset have a statistically significant relationship with liquidity risk. This is supported by both models (Pooled OLS Model and Random Effect Model). Here, loan to deposit ratio is the measure of liquidity risk. GDP growth and inflation have a statistically significant positive relation with liquidity risk(Loan to Deposit Ratio). This decision is also supported by both models. Return on assets ,capital adequacy ratio and operating expenses to total assets ratio have
statistically insignificant negative relationship with loan to deposit ratio. This study also show descriptive statistics, correlation matrix, multicollinearity test, and heteroscedasticity test .There is no multicollinearity and heteroscedasticity problem in the dataset. Very few studies have been conducted in Bangladesh addressing the issue. Liquidity risk in banks refers to the danger that a bank might not be able to fulfill its financial commitments when they become due, either by liquidating assets or securing new financing, without facing significant losses. This type of risk is critical for banks, as failure to manage it properly can result in insolvency, making it impossible to repay depositors and other creditors. The recent liquidity crisis in Bangladesh raises concerns about how banks handle their liquidity. A thorough examination of the variables influencing liquidity risk in Bangladeshi banks is provided in this study. Additionally, it makes suggestions that can be put into practice to enhance banks' procedures for managing liquidity risk, which will help to maintain the stability and efficacy of the nation's financial system. The information acquired from this study will be useful in understanding the factors that influence banks' liquidity in Bangladesh
