INTRODUCTION
Research Problem
A robust financial system is essential for economic stability and prosperity, with banks playing a crucial role in this framework They enhance the flow of funds by lending to those in need while providing liquidity to savers Additionally, banks facilitate the payment and settlement processes, ensuring efficient transfer of goods and services By investing capital productively, banks contribute to economic growth and job creation, fostering the development of new sectors However, the diverse activities of banks expose them to liquidity risk, as unexpected withdrawals by depositors can lead to asset fire sales, ultimately impacting profitability.
In recent years, the banking industry has experienced significant growth, marked by a rapid increase in capital value, leading to enhanced lending opportunities However, this expansion brings potential risks, particularly liquidity risk, which can profoundly impact the safety and stability of individual banks and the overall financial system of the country.
In banking operations, factors such as credit risk, exchange rates, and interest rates typically exhibit a time lag, whereas bank liquidity is immediate and rarely aligns perfectly with demand Consequently, addressing liquidity deficits or surpluses is a constant challenge for commercial banks Prolonged capital shortages can harm a bank's market reputation, hinder capital raising efforts, and diminish profitability Commercial banks engage in maturity transformation by accepting short-term deposits and converting them into long-term loans, which introduces liquidity risk According to Casu et al (2006), a bank's liquidity is defined by its ability to meet both expected and unexpected short-term obligations Thus, maintaining adequate liquidity is essential for individual banks to mitigate liquidity risk, and supervisory authorities emphasize the importance of sufficient liquid assets for overall financial stability.
In response to the 2007 global financial crisis, the Basel Committee on Banking Supervision established regulations to mitigate systemic risks, particularly liquidity risk, to prevent bank failures In 2013, the committee introduced the Liquidity Coverage Ratio and liquidity risk monitoring tools, followed by the Net Stable Funding Ratio in 2014 The financial meltdown highlighted inadequate liquidity management among banks, underscoring the need for effective policies to avert future crises Research by Aiyar, Ivachina, and Shufsten indicates that liquidity risks can significantly impact bank performance, influenced by factors such as industry size, ownership structure, and banking concentration.
In recent times, some banks in Vietnam have experienced liquidity stress due to insufficient cash supply to meet mass withdrawals, particularly amid banking-related rumors A notable instance occurred in 2012 at Asia Commercial Joint Stock Bank (ACB), where panic led to a rush of withdrawals following the arrest of its former leader The banking system had already been grappling with liquidity issues from 2008 to 2011, marked by high loan-to-deposit ratios (LDR) ranging from 96% to 107%, and interbank rates soaring to 18% per year Although liquidity problems were addressed after 2012, they pose a renewed threat to the banking system The State Bank of Vietnam (SBV) has minimized liquidity risks through measures such as controlling ceiling interest rates and urging larger banks to support smaller ones However, the potential for liquidity risk remains significant, and the SBV's monitoring of these risks has not yet met expectations.
The Covid-19 pandemic, which originated in Wuhan, China, at the end of 2019, rapidly escalated into a global crisis, severely impacting the socio-economic landscape of countries worldwide, including Vietnam It disrupted supply chains, drained national resources, and hindered economic growth, posing significant challenges to global economic activities Among the sectors most adversely affected, the banking industry has faced particularly severe repercussions due to the pandemic.
During the Conference on implementing banking industry tasks for 2022, held by the State Bank of Vietnam on December 29, 2021, in Hanoi, SBV Standing Deputy Governor Dao Minh Tu highlighted several challenges facing the banking sector.
The ongoing epidemic has significantly impacted the economy over the past two years, resulting in challenges such as slow capital turnover, disrupted cash flow, and reduced enterprise revenues, which are expected to increasingly affect banking performance by 2022 The expansion of credit and excessive support policies, if not properly addressed through fiscal measures, may jeopardize the system's safety in the medium to long term Despite the stock market's growth, the banking system remains the primary source of capital for the economy, particularly for medium and long-term needs, leading to heightened maturity and liquidity risks Additionally, the practice of extending debt rescheduling may obscure actual customer risk levels, potentially creating hidden negative risks for the banking system in the medium term.
The pandemic's deferred impacts on the banking industry may emerge later than in other sectors, raising potential concerns for the future Consequently, banks must prioritize their liquidity management, as upcoming market shocks could significantly influence their financial stability.
Analyzing the factors influencing bank liquidity risk is crucial for ensuring the safety of banking operations and the stability of the financial system This research aims to explore the determinants of liquidity risk in commercial banks in Vietnam, focusing on the period before and during the Covid-19 pandemic.
Objective and Scope of Study
Research Subject: The determinants of Liquidity risk of Commercial Banks in Vietnam
(1) Reviewing the theoretical basis on the The determinants of Liquidity risk of Commercial Banks in Vietnam
(2) Measuring the impact of factors on liquidity risk of commercial banks in Vietnam
(3) Proposing solutions based on the model’s conclusions to reduce the impact of the factors in the future
- About space: 28 commercial banks in Vietnam
Research structure
Chapter 2: Literature review and situation of liquidity in Commercial banks in Vietnam
Background of the research
The liquidity of economic banks is often in a dynamic state, influenced by various factors, and the literature on liquidity risk is extensive Research by Acharya and Naqvi (2012) expands the definition of liquidity risk and offers management techniques to stabilize banks Ismal (2010) highlights the importance of liquidity risk management in Indonesia's Islamic banks, recommending policies to enhance their practices Effective liquidity risk analysis is essential for the ongoing operations of banks, with findings indicating that Islamic banks are well-equipped to handle both internal and external liquidity risks However, a study conducted in Pakistan from 2005 to 2009 revealed that conventional banks excel in liquidity management compared to their Islamic counterparts Additionally, credit risk is recognized as a significant factor impacting bank performance, as noted in various studies globally.
A study by Aspachs et al (2005) revealed that the liquidity of British banks from 1985 to 2003 positively correlates with the equity ratio, capital support from the State bank, and loan ratio to total assets, while negatively correlating with short-term interest rates and the 2-week repo rate Lucchetta (2007) analyzed data from 5066 European banks between 1998 and 2004, finding that interbank average interest rates significantly influence bank liquidity, measured by the ratio of loans to total assets, and are affected by interbank market behavior, government interest rates, non-performing loan ratios, and bank size Bunda & Desquilbet (2008) examined liquidity risk determinants in emerging economies, indicating that larger banks and higher equity-to-assets ratios enhance liquidity risk, particularly during liquidity crises, with varying impacts based on exchange rate regimes; banks in floating exchange rate countries experience less liquidity risk compared to those in intermediary mechanism countries.
A study by Koziol et al (2008) utilized a regression model to assess the probability of bank failures in Brunei's Islamic banks, identifying risk identification, risk assessment, and risk analysis as the key influential variables Additionally, Chung-Hua Shen et al (2009) developed a liquidity risk causal model based on data from the commercial banking systems of 12 major economies between 1994 and 2006.
A remarkable result is that the variable of total asset size has a nonlinear effect on bank liquidity risk, at the first stage when increasing assets liquidity risk reduced
An increase in total assets can elevate liquidity risk, as evidenced by the positive correlation between the funding gap and the ratio of own capital to total assets, along with a reliance on external funding sources Conversely, liquidity reserves and economic growth exhibit an inverse relationship with the funding gap Notably, while inflation does not impact liquidity risk in the current year, it is expected to reduce liquidity risk in the following year A study by Hackethal et al (2010), which analyzed 1,107 commercial banks across 36 emerging economies from 1997 to 2006, found that macroeconomic factors, particularly tight monetary policies, adversely affect bank liquidity through interest rates To counteract high unemployment, stimulating job demand via credit growth is essential for economic health, despite its negative implications for liquidity The study concluded that macroeconomic factors and monetary policy are significantly linked to liquidity risk, while bank-specific factors like size and performance show no correlation.
Akhtar (2011) explores the link between liquidity risk and the solvency of financial institutions, comparing conventional and Islamic banks in Pakistan from 2006 to 2009, finding a positive yet minimal relationship with bank size and net-working capital In contrast, Ogol (2011) focuses on liquidity risk management in Kenyan microfinance institutions through a descriptive research design, highlighting that previous studies on Kenyan commercial banks (Giannotti et al., 2010; Angora & Roulet, 2011; Giordana & Schumacher, 2012) often overlook the Net Stable Funding Ratio (NSFR) and consider only one study that includes the Liquidity Coverage Ratio (LCR) These two liquidity measures, integral to the Basel III framework, are evaluated in Ogol's research, which utilizes time-series cross-section data to assess their impact on financial performance.
Vodova (2012) investigates the factors of Czech banks’ liquidity risk between
Between 2006 and 2011, various studies explored the relationship between liquidity risk and balance sheet metrics in banks Key findings include a significant link between the loan-to-deposit ratio and the assets-to-deposit ratio, as well as a positive correlation between liquidity, capital adequacy, and interbank transaction interest rates Kurnia and Muharam (2012) highlighted that return on equity positively impacts liquidity risk in Islamic banks while negatively affecting conventional banks Iqbal (2012) found that capital adequacy ratio, return on assets, return on equity, and bank size significantly influence liquidity risk in both Pakistani conventional and Islamic banks Additionally, Anam et al (2012) identified that net working capital, capital adequacy ratio, and return on assets positively affect liquidity risk management in Bangladeshi banks from 2006 to 2010.
Muriithi & Kennedy (2017) analyzed the impact of liquidity risk on the financial performance of 43 commercial banks in Kenya from 2005 to 2014, finding that liquidity risk negatively affects financial performance In a similar vein, Faruque and Ahamed (2021) investigated the factors influencing liquidity risk in 23 commercial banks in Bangladesh from 2005 to 2018, revealing that asset size negatively correlates with liquidity risk, indicating that larger banks tend to have better liquidity positions Their study also found that while liquidity concerns have a positive but insignificant relationship with return on equity and capital adequacy, macroeconomic factors play a significant role; specifically, inflation negatively impacts liquidity risk, whereas GDP and domestic credit positively influence it Additionally, the expansion of domestic credit can deplete liquidity and potentially lead to insolvency, as the loan outstanding to asset ratio inversely affects banks' liquidity risk To enhance profitability, banks often increase loan disbursement, which can exacerbate liquidity risk.
Munteanu (2012) conducts a study on the determinants of credit risk in Romanian banks by dividing a dataset of 27 banks into two periods: before the 2002-2007 crisis and after the 2008-2010 crisis The research utilizes five bank-specific variables—capital adequacy ratio, asset quality, interbank financing, financing cost, and total cost over income—alongside five external variables, including the ROBOR rate, credit risk ratio, inflation rate, GDP growth rate, and unemployment rate Two dependent variables are measured: L1 (real loans/total assets) and L2 (current assets/deposits and short-term financing), with multivariable regression analysis revealing that L2 is the most appropriate for assessing liquidity risk The findings indicate that the stability factor of the banking industry, represented by the Z-score, significantly impacts bank liquidity risk during the crisis years of 2008-2010.
Cucinelli (2013) addresses previous research gaps by examining liquidity measurement methods in accordance with Basel III regulations The study utilizes two dependent variables—LCR and NSFR—alongside six independent variables to analyze the determinants influencing liquidity in the euro region.
A study of 1,080 observations highlights key insights into the liquidity crisis in banking It reveals that larger banks tend to exhibit lower liquidity levels, while those with higher capital ratios experience improved liquidity Additionally, the financial crisis is shown to have only a temporary effect on banks' liquidity.
A study by Abdullah et al (2012) analyzes liquidity risk management in domestic versus foreign banks in Pakistan from 2001 to 2010, revealing a negative correlation between bank size and liquidity risk; larger banks with more liquid assets experience lower liquidity risk Additionally, the research indicates that higher profitability, as measured by Return on Equity (ROE), is associated with reduced liquidity risk, suggesting that banks can leverage profitability to manage liquidity In a separate study, Lei et al (2013) explore the relationship between liquidity creation and bank capital structure in China, finding that domestic banks with lower capital structures face challenges in mobilizing funding sources for liquidity creation The findings suggest that banks with higher capital ratios tend to attract funding from highly liquid deposits, resulting in lower liquid assets, thereby confirming the hypothesis that higher capital ratios correlate with lower liquidity.
Research indicates that "financial fragility," represented by the ratio of capital and liquidity, is negatively correlated (Berger & Bouwman, 2013) A study by Adia, Singh, and Sharma (2016) analyzed the liquidity factors of 59 Indian banks from 2000 to 2013, revealing that larger bank size and economic growth adversely affect liquidity Conversely, profitability, capital adequacy ratio, the mobilized capital to total capital ratio, and inflation positively influence liquidity Additionally, a study on Tunisian commercial banks from 2000 to 2012 by Belaid et al also examined factors impacting liquidity risk.
A study conducted in 2016 identified a positive correlation between the non-performing loan (NPL) ratio, capital adequacy ratio, management quality, business model, and liquidity risk, while noting that asset size negatively affects liquidity risk In Malaysia, research by Said (2014) from 2005 to 2011 utilized Pooled Ordinary Least Squares (POLS) and Fixed Effect Model (FEM) to analyze the influence of the Net Stable Funding Ratio (NSFR) on the profitability of commercial banks, highlighting its relationship with performance metrics such as return on equity (ROE), return on assets (ROA), and net interest margin (NIM) Additional studies by Giannotti et al (2010), Angora and Roulet (2011), and Giordana and Schumacher (2012) further contribute to this body of research.
Research on factors affecting commercial bank liquidity in Vietnam is limited, with Vu (2015) being one of the pioneering studies This empirical research analyzed the influence of internal variables on liquidity across 37 Vietnamese commercial banks from 2006 to 2011 Utilizing statistical analysis, disproportionate correlation, and fixed effect regression, the study identified several significant factors It found that the equity ratio, Non-Performing Loan (NPL) ratio, and profit ratio positively correlated with liquidity, while the loan-to-deposit ratio had a negative correlation However, the study did not find evidence of loan loss provisions or bank size impacting liquidity conditions.
Van Dan Dang (2015) examined the factors influencing liquidity risk in 15 major commercial banks in Vietnam from 2007 to 2014, revealing that liquidity risk is inversely related to total asset size and positively correlated with the loan-to-total assets ratio Larger banks tend to have lower liquidity risk due to increased market competitiveness, while a higher loan-to-total assets ratio diminishes liquidity reserves, thereby elevating liquidity risk Additionally, extending credit raises credit risk, further contributing to liquidity risk Building on these findings, Nguyen Thi Ngoc Diep & Nguyen Thanh Lam (2016) utilized a regression model and ordinary least squares (OLS) to identify key predictors of commercial bank liquidity in Vietnam from 2006 to 2013, concluding that bank size, loan-to-deposit ratio, and equity-to-asset ratio significantly affect liquidity.
LITERATURE REVIEW AND SITUATION OF LIQUIDITY
LITERATURE REVIEW
Liquidity in banking refers to a bank's capacity to support asset growth and meet both expected and unexpected cash and collateral needs without incurring significant losses When a bank cannot fulfill these obligations without compromising its financial stability, it faces liquidity risk Effective management of liquidity risk is crucial for ensuring that banks can meet their commitments on time while minimizing the likelihood of a liquidity crisis This is particularly important in emerging economies, where banks serve as the main financial intermediaries, as a liquidity crisis can lead to severe systemic repercussions.
Liquidity in economic terms refers to an economic agent's ability to convert wealth into goods, services, or other assets It is primarily considered as a flow concept, emphasizing the unrestricted movement of funds among participants in the financial system, particularly between the central bank, commercial banks, and markets Additionally, liquidity encompasses the risk associated with the inability to execute these financial flows.
If a financial entity is unable to meet its obligations, it risks becoming illiquid This situation can be exacerbated by knowledge asymmetries and the existence of incomplete markets, which hinder its ability to navigate financial challenges effectively.
Banks need liquidity to manage both anticipated and unexpected fluctuations in their balance sheets and to support growth initiatives This liquidity reflects a bank's capability to effectively manage deposit withdrawals and other liabilities while also funding increases in loans and investments A bank demonstrates adequate liquidity when it can quickly access necessary funds at reasonable costs, whether through raising liabilities, securitization, or asset sales The cost of liquidity is influenced by prevailing market conditions and the perceived risk associated with the borrowing institution.
Liquidity risk, a critical concern for commercial banks, encompasses various risk types and can trigger a liquidity crisis Despite the financial stability of these institutions, liquidity risk can lead to insolvency, potentially resulting in bankruptcy While business operations may not immediately suffer losses, the threat of insolvency looms, highlighting the importance of effective liquidity management.
Liquidity risk, as defined by Diamond (1991), refers to the potential loss of expected earnings due to premature excessive withdrawals by investors Papavassiliou (2013) elaborates that it encompasses the inability to buy or sell assets at market price when necessary, and is categorized into financing liquidity risk and market liquidity risk Market liquidity risk involves a bank's struggle to sell illiquid assets promptly at market value, while funding liquidity risk pertains to a bank's failure to meet the liquidity needs of its fund providers (IFSB, 2012; Haan and End, 2013) This study specifically focuses on funding liquidity risk, which is characterized by a bank's inability to fulfill its obligations on time (The European Central Bank, 2009) Giannotti et al (2010) further describe liquidity risk as the likelihood that a bank cannot meet its obligations within a specified timeframe, emphasizing that liquidity is crucial for a bank to satisfy the financing needs of asset growth and to honor financial obligations as they become due without incurring excessive costs.
Liquidity risk is the possibility that a bank may fail to meet its obligations promptly, leading to potential losses and negatively impacting its earnings and capital Effective management of liquidity risk is crucial for ensuring the availability of funds for both providers and borrowers, and it should be monitored alongside market and credit risks as part of an enterprise-wide risk management strategy This risk is inherent in banks due to their role in financing long-term assets with short-term liabilities, making it unavoidable Additionally, liquidity risk can affect portfolio diversification and investment activities, ultimately influencing asset values and a bank's overall performance and reputation Timely access to funds is essential; failure to provide this can erode trust and damage a bank's standing in the market.
Liquidity risk in commercial banks refers to the likelihood that a bank may struggle to meet its financial obligations promptly within a specific timeframe This risk is closely associated with the bank's funding capabilities It primarily arises from management's failure to effectively anticipate and strategize for fluctuations in funding sources and financial requirements.
Effective liquidity management is crucial for optimizing revenues, requiring banks to maintain sufficient cash reserves while strategically investing excess funds According to Goodhart (2008), liquidity risk encompasses two key elements: maturity transformation, which relates to the timing of a bank's liabilities and assets, and inherent liquidity, defined by how easily an asset can be sold without significant value loss Banks with easily sellable assets face less concern regarding maturity transition, while those with shorter-maturing assets may have reduced needs for liquid assets (Ahmed et al., 2015).
The Basel Committee (2015) defines liquidity as a bank's capacity to fulfill its financial obligations during business operations, serving as a qualitative measure of its financial strength Liquidity risk arises when a financial institution cannot meet its obligations without adversely affecting its daily operations or overall financial health Consequently, banks may struggle to provide sufficient cash for immediate liquidity needs, such as converting assets into cash or borrowing, or they may be compelled to obtain liquidity at a significantly higher cost.
The interconnectedness of banks in the interbank market creates a domino effect, where the insolvency of one bank can lead to liquidity issues for others The extent of contagion is influenced by the size of transactions between banks Additionally, when depositors withdraw funds from one bank, it can trigger panic among others, leading to widespread withdrawals and further destabilizing the banking system This chain reaction can cause significant turmoil across the entire financial sector.
Liquidity risk primarily arises from a mismatch in the duration of assets and liabilities, as highlighted by Duttweiler (2009) This occurs when banks mobilize and borrow short-term funds while extending loans and credit over longer periods Such discrepancies between the maturity of assets and debts create an imbalance in the source and use of capital, contributing significantly to liquidity loss.
Managing liquidity risk is one of the most challenging tasks for financial intermediaries like banks, as it is essential for their daily operations and their role in providing liquidity to the financial system Liquidity refers to a bank's ability to maintain a stable balance by effectively managing inflows and outflows This risk can emerge from a mismatch between the demand for and supply of funds, with banks sourcing funds through deposits, credit repayments, and short-term borrowing from the money market and central bank Customer withdrawals, credit facilities, and other expenses drive the demand for funds, creating a net liquidity position that banks must carefully manage to prevent shortages and mitigate liquidity risk.
Liquidity risk is a crucial factor in the banking industry that significantly influences financial stability, profitability, and customer satisfaction It is also a primary trigger for other risks that adversely affect banking operations Consequently, among the various risks that banks encounter, liquidity risk stands out as the most critical, as it can ultimately lead to insolvency.
In this study, liquidity risk is identified as a significant concern in the financial sector, arising when a bank is unable to access sufficient funds or short-term assets to satisfy the demands of depositors and borrowers This deficiency in available funds can be interpreted in two distinct ways.
- Or the lack of reserves at the bank
- Or can not raise capital right away
2.1.1.2 Measurement of Liquidity and Liquidity Risk
CURRENT SITUATION OF LIQUIDITY IN COMMERCIAL
2.2.1 Overview of Vietnam’s commercial banking system
Over 30 years of operation, Vietnam’s banking system has made positive improvements and made great contributions to the development of the country’s economy According to data compiled by the author on the website of the State Bank of Vietnam, in the period 2010 - 2021, Vietnam’s banking system is divided into four main groups: State-owned commercial banks (SOCB), 100% State-owned commercial banks (100% SOCB), Joint stock commercial banks (JSCB) and Joint venture commercial banks (JVCB) In which, the majority of the financial market share focuses on four Stated-owned commercial banks, namely Vietnam Joint Stock Commercial Bank for Industry and Trade (Vietinbank); Joint Stock Commercial Bank for Foreign Trade of Vietnam (Vietcombank); Vietnam Bank for Agriculture and Rural Development (Agribank); Joint Stock Commercial Bank for Investment and Development of Vietnam (BIDV); and 10 Joint stock commercial banks are Vietnam Technological and Commercial Joint Stock Bank (Techcombank); Military Commercial Joint Stock Bank (MBBank); Vietnam Prosperity Joint Stock Commercial Bank (VPbank); Asia Commercial Joint Stock Bank (ACB); Tien Phong Commercial Joint Stock Bank (TPbank); Saigon Hanoi Commercial Joint Stock Bank (SHBHo Chi Minh City Development Joint Stock Commercial Bank (HDBank); Sai Gon Thuong Tin Commercial Joint Stock Bank (Sacombank); Vietnam International Commercial Joint Stock Bank (VIB); Vietnam Maritime Commercial Joint Stock Bank (MSB); Saigon Commercial Joint Stock Bank (SCB)
Due to the adverse impact of the global economic recession after the 2008-
2009 financial crisis and the internal inadequacies of the economy, in the years 2011-
In 2016, Vietnam's economy encountered significant challenges, including soaring inflation rates that escalated from 9.2% in 2010 to 18.7% in 2011 The money, foreign exchange, and gold markets experienced considerable fluctuations, with lending interest rates reaching as high as 20-25% per year This situation strained the liquidity of credit institutions, while the Vietnamese dong faced devaluation pressures Additionally, state foreign exchange reserves plummeted, and the lack of strict market discipline among credit institutions raised concerns about the potential collapse of the banking system.
“crisis storm” when most banks, including large banks are at risk of insolvency
In an effort to control inflation and stabilize the macro-economy, the banking sector and credit institutions are actively aligning with the directives of the Party, National Assembly, and Government They are focused on implementing solutions to alleviate challenges faced by production and business activities, thereby supporting sustainable economic growth while ensuring safety and security Additionally, there is a strong emphasis on fostering creativity and responsibility within the business sector, alongside enhancing collaboration with ministries, branches, and localities to effectively achieve their political objectives.
The restructuring of Vietnam's credit institutions from 2011 to 2015, known as Project 254, significantly transformed the commercial banking system State-owned and major joint-stock banks actively collaborated with the State Bank and relevant authorities to implement essential strategies, focusing on mergers, consolidations, and acquisitions This initiative aimed to address the challenges faced by weak credit institutions while also tackling ownership issues, ultimately leading to the emergence of large, regionally competitive banks As a result, the synchronized solutions under Project 254 have enhanced operational quality and safety within credit institutions, aligning with the government's vision to streamline the structure of commercial banks by reducing the number of joint-stock banks.
The number of commercial banks has shifted from 37 to 38, while joint venture commercial banks decreased from 5 to 3 Conversely, the count of state-owned commercial banks increased from 5 to 7, and 100% foreign-owned commercial banks rose from 5 to 6.
Vietnam's economy has faced significant challenges recently, impacted by global economic fluctuations that have disrupted both supply and demand Factors such as declining labor productivity, worsening natural disasters, and health crises have exacerbated these issues Additionally, increased trade tensions between the United States and China, along with rising populism and shifts in trade policies, have further complicated Vietnam's economic landscape.
In early 2020, the Covid-19 pandemic severely impacted countries worldwide; however, Vietnam emerged as one of the few nations to effectively manage the crisis By implementing successful containment measures, Vietnam prevented widespread community transmission of the virus and achieved a positive GDP growth rate of 2.91% in 2020, ensuring overall economic stability.
The financial sector has experienced rapid and unusual market shifts, prompting central banks to maintain a loose monetary policy In response, the State Bank of Vietnam (SBV) has proactively implemented adaptive measures, utilizing a range of monetary policy tools to ensure liquidity and stabilize the market These actions have significantly contributed to controlling inflation and achieving economic stability.
The State Bank of Vietnam has set credit management targets aimed at aligning with macroeconomic balances and addressing the capital demands of the economy This approach emphasizes enhancing credit quality, prioritizing the banking sector's support for production and business, while also maintaining strict control over risk-prone areas.
The restructuring of credit institutions has led to significant improvements in bad debt settlement, banking inspection, and overall system safety, promoting monetary and credit security Compliance with Basel II regulations has been seriously implemented, resulting in enhanced governance standards aligned with international practices Currently, nearly all credit institutions have undergone rectification and consolidation, while non-banking credit entities, such as people's credit funds and microfinance institutions, are now operating healthily with reduced instances of black credit The scale of the credit institution system continues to expand, with a gradual increase in financial capacity and charter capital over the years Additionally, the quality of banking governance has improved, as commercial banks establish modern corporate governance frameworks that regulate the roles and relationships among the executive board, board of directors, and shareholders in accordance with international corporate governance standards.
The commercial banking system in Vietnam is undergoing significant restructuring, marked by an increase in the number of fully foreign-owned commercial banks, rising from six to nine This shift accompanies a slight decline in state-owned and joint-stock commercial banks as the industry trends towards consolidation and mergers to enhance competitiveness Consequently, Vietnam now has a total of 46 commercial banks.
Table 1: Number of Vietnamese commercial bank in period 2010-2021
State-owned commercial banks (SOCB) in Vietnam play a crucial role in the financial system, alongside joint stock commercial banks (JSCB) and joint venture commercial banks (JVCB) The distinction between 100% SOCB and other banking entities highlights the varying degrees of state ownership and control in the banking sector Understanding these categories is essential for navigating Vietnam's banking landscape and recognizing the unique functions and contributions of each type of bank.
Source: Annual report of The State Bank of Vietnam in period 2010-2021
2.2.2 Current situation of liquidity of commercial banks in Vietnam
2.2.2.1 Current situation of capital of commercial banks in Vietnam
Between 2010 and 2015, capital growth in Vietnam's banking sector experienced a significant decline, reflecting the cautious approach of commercial banks amid economic challenges However, the implementation of Project 254 in 2011 led to notable improvements within the credit institution system By the end of 2012, the total charter capital reached 392.15 trillion VND, marking an 11.29% increase from 2011, although this was the lowest growth rate in recent years, with state-owned commercial banks (SOCB) and joint-stock commercial banks (JSCB) contributing 28% and 8.1% to this increase, respectively The system's own capital saw a modest rise to 425.9 trillion VND, an 8.9% increase compared to the previous year, while total assets grew to 5,085.7 trillion VND, up 2.54% In 2013, the charter capital of the industry increased by 9.13%, primarily driven by a 16.8% rise from SOCB However, the last two years of Project 254 recorded the lowest growth rates of 3.33% and 3.17% for charter capital Despite these challenges, banks enhanced their financial capacity and improved capital utilization efficiency by divesting from high-risk investments, leading to a stabilization of liquidity and significant improvements in solvency indicators across the credit institutions.
Between 2016 and 2021, the capital mobilization scale of the banking system showed significant growth, building on the progress made during 2010-2015 The restructuring of the credit institution system during this period yielded positive outcomes, with the total charter capital of the industry rising from 451.5 trillion VND in 2016, marking a 6.23% increase from 2015 This trend continued, leading to a substantial increase in the charter capital of Joint Stock Commercial Banks (JSCB), which reached 368,642 trillion VND by 2021, representing 51.49% of the total charter capital in the system as of the third quarter of 2021.
In 2021, the charter capital of state-owned commercial banks in Vietnam surged to 180.191 trillion VND, marking a 16.05% increase from the previous year This growth was facilitated by government support and the State Bank of Vietnam (SBV), which enabled these banks to successfully raise their capital Notably, Agribank received an additional 3.500 billion VND, while VietinBank, Vietcombank, and BIDV were permitted to distribute high stock dividends The SBV recently issued Decision No 422/QD-NHNN, outlining an action plan to enhance the banking sector in line with Government Resolution No 11/NQ-CP A key initiative includes increasing the charter capital of joint-stock commercial banks, where the State holds over 50% of the capital, utilizing after-tax profits and state budget resources Overall, this presents a significant opportunity for state-owned banks to expand their charter capital in the coming years.
By 2021, commercial banks will basically have their own capital according to Basel
II standards and some banks are moving towards Basel III such as ABBank
Figure 1: Total Authorized capital of SOCB and JSCB during 2010-2021
Source: Annual report of The State Bank of Vietnam in period 2010-2021 2.2.2.2 Current situation of liquidity risk of commercial banks in Vietnam
RESEARCH METHODOLOGY
Research hypotheses
This section will formulate hypotheses for the research model, drawing on a comprehensive review of theoretical and empirical literature, previous studies, and the specified variances outlined in the research.
Hypothesis 1: The larger the size of bank, the lower the liquidity position of the bank, the reduced liquidity risk
Hypothesis 2: ROA and ROE have a negative impact on liquidity risk of commercial banks
Hypothesis 3: NIM positively impact on the liquidity risk
Hypothesis 4: Capitalizatiion has opposite effect on liquidity risk
In Vietnam, banks primarily concentrate on lending, resulting in a high non-performing loan (NPL) ratio This phenomenon occurs because rising credit risks prompt banks to increase risk provisions, subsequently diminishing profits To counteract this profit decline, banks often reduce their liquid assets and extend more loans, consequently heightening their liquidity risk.
Hypothesis 5: Credit risk has negative impact on liquidity risk
Hypothesis 6: Higher the GDP growth, lower the risk of liquidity
Hypothesis 7: Inflation has negative impact on liquidity risk
The Covid-19 pandemic presents a unique challenge, lacking established theoretical frameworks and research on liquidity risk specific to this crisis Existing studies, such as those by Yusuf and Ichsan (2021), focus on the performance of Indonesian banks, examining credit loan risk factors and customer solvency Additionally, a report from SSI Securities Corporation (2021) indicates that the banking sector will face short-term negative impacts due to the global spread of Covid-19, with potential long-term repercussions.
This research aims to evaluate the impact of Covid-19 on the liquidity risk of Vietnamese commercial banks by incorporating a dummy variable, Covid19, into the model.
Hypothesis 8: Covid-19 has positive impact on liquidity risk
Table 2: Variables, Measurement and Expected Relationship
Expected sign of independent variables
= (Average Loan - Average deposit) / Average total asset
SIZE Bank size: Logarithm of total asset
(2000), Iannotta et al (2007) and Truong & Phan
ROA Return on asset: Net profit after tax to total asset
(2005), Choon et al (2013), and Vodova (2011)
ROE Return on equity: Net profit after to total equity
Kim (2012) and Al-Homaidi et al
Net interest margin Different between interest receives and interest paid
Naceur and Kandil (2009), and Wójcik- Mazur et al
Capitalization: Equity (accounting value) /total assets
Dinger (2009) and Deléchat et al (2014)
Credit risk is measured by the ratio of loan loss provision to gross loans
Dummy sujbect: In covid-19 year (2020, 2021), Covid19 1; in other years Covid19 = 0
Empirical model
Finally, the report proposes a research model based on the inheritance of previous research
Where 𝐿𝐼𝑄 𝑖,𝑡 is the dependent variable which measures the Liquidity risk of banks;
• ROA and ROE are Return on Assets and Return on Equity, respectively, which are measures of bank’s profitability;
• NIM is Net interest margin of bank being used to estimate the opportunity cost of maintaining liquid assets;
• CAP is capitalization of bank;
• CR is Credit risk of bank;
• GDPg is the growth GDP of Vietnam;
• Covid19 is dummy variable for Covid-19 year (2020, 2021) In covid-19 year, Covid19 = 1; in other years Covid19 = 0
The intercept and slope coefficients of the explanatory variables are represented by the symbol ∝ Additionally, 𝜇 𝑖 denotes the unobserved bank-specific effect, while 𝜀 𝑖,𝑡 signifies the error term, which is independently and identically distributed across banks and years.
Research design
This study conducted a cross-sectional analysis of data from 28 commercial banks in Vietnam, covering the period from 2010 to 2021 It employed a panel data regression model utilizing three widely recognized methods: Pooled Ordinary Least Squares (OLS), Fixed Effects Model (FEM), and Random Effects Model (REM) Ultimately, the most suitable model was selected to assess the influence of independent variables on the liquidity risk faced by commercial banks in Vietnam.
The LM (Breusch-Pagan Lagrange Multiplier) test helps determine whether to use Pooled Ordinary Least Squares (POLS) or Random Effects Model (REM), while the Hausman test is utilized to differentiate between REM and Fixed Effects Model (FEM) Additionally, the Variance Inflation Factor (VIF) is applied to assess multicollinearity, the Breusch-Pagan Lagrange Multiplier test evaluates variable variance, and the Wooldridge test checks for autocorrelation in the data.
Data collection method
Between 2010 and 2021, selected banks in Vietnam are required to maintain operational continuity and disclose adequate financial statements to the public The author’s research excludes fully disclosed and merged banks, focusing instead on a sample of 28 commercial banks Data was gathered from annual financial statements available on the banks' websites, along with information from Vietstock finance and CafeF, with additional calculations performed by the author.
GDP growth: annual growth rate of gross domestic product is collected from the report of the General Statistics Office of Vietnam
Inflation ratio is collected from Worldbank’s information page.
RESULTS AND DISCUSSION
Descriptive statistics
This stage presents descriptive statistics for the analyzed variables from the selected banks, which supports in the development of a better understanding of the sampled institutions’s liquidity
Variable Obs Mean Std.Dev Min Max
Source: Author’s calculation basing on dataset
According to Table 2, the dependent variable LIQ has a mean of -0.1874 and a standard deviation of 0.1100, indicating that the liquidity risk of Vietnamese commercial banks is stable and within a normal range The LIQ variable exhibits a highest value of -0.5723 and a lowest value of 0.1227, with SeAbank recording the minimum LIQ value.
Between 2011 and 2012, SeAbank experienced a notable increase in deposit values while loan values saw a slight decline This trend stemmed from the bank's efforts to raise deposits from all customer segments and increase borrowing from state banks during the period from 2011 to 2015 A high funding gap, indicated by the ratio of total loans minus total deposits to total assets, serves as a warning sign of potential liquidity risks, suggesting reduced liquidity reserves However, overall liquidity risk within Vietnamese commercial banks remains under control.
The size of Vietnamese banks, indicated by the variable SIZE, exhibits significant variability with a high standard deviation of 0.5065, reflecting the diverse total assets among these institutions Over the years, banks have consistently engaged in system restructuring, contributing to this variation The average SIZE is recorded at 8.0436, with a maximum of 9.2359 and a minimum of 6.9152.
The standard deviations of Return on Assets (ROA) and Return on Equity (ROE) for Vietnamese banks are 1.37% and 8.62%, respectively, indicating modest yet consistent profitability The average ROA stands at 0.96% with low variance, while the mean ROE is 9.96% Additionally, the significant difference between the maximum and minimum values of both ROA and ROE suggests a wide range of performance among these banks.
The mean Net Interest Margin (NIM) for Vietnamese banks is 0.0314, with a standard deviation of 0.0118, indicating comparable funding costs across different bank groups In contrast, the Capital Adequacy Ratio (CAP) shows a high mean of 9.20% and a significant standard deviation of 4.07%, revealing substantial asymmetry in capitalization levels and suggesting that banks generally have low equity capital Additionally, the Capital Ratio (CR) ranges from 0 to 23.82%, with a mean of 1.08% and a standard deviation of 1.47%, highlighting Vpbank and Saigon Bank as having the highest CR values.
The analyzed countries where the investigated banks operate exhibit an average real GDP growth rate of 5.72%, ranging from a minimum of 2.58% to a maximum of 7.76%, highlighting diverse economic conditions that may influence their liquidity risk exposure Additionally, the inflation (INF) variable averages 5.49%, with a standard deviation of 4.74%, and fluctuates between a low of 0.63% and a high of 18.68% The peak inflation rate in 2011 was attributed to excessive money supply growth relative to goods production, indicating ineffective capital utilization.
The correlation matrix presented in Table 3 illustrates the relationships between the dependent variable and the explanatory factors, revealing a notably low degree of correlation among the regressors, with all correlation coefficients falling below 0.65 This indicates that the model is free from multi-collinearity issues.
The analysis reveals a significant positive correlation between liquidity (LIQ) and net interest margin (NIM), with a correlation coefficient of 0.301, indicating that NIM is a crucial factor in explaining the variance in LIQ Conversely, GDP growth (GDPg) and inflation (INF) exhibit negative correlations with LIQ, suggesting that their coefficients in regression analyses will be negative Additionally, the correlation between LIQ and bank size (SIZE) is 0.226, highlighting the importance of bank size in understanding liquidity In contrast, the capital ratio (CR) shows a weak correlation of 0.075 with LIQ, suggesting its limited utility in explaining liquidity Importantly, the findings imply that provisions for non-performing loans (NPL) may satisfy regulatory requirements without adversely impacting a bank's loan disbursement or liquidity, particularly when accompanied by a stringent collection policy (Maaka, 2013).
LIQ SIZE ROA ROE NIM CAP CR GDPg INF
Table 3 reveals that the CAP variable exhibits the strongest negative correlation with the SIZE variable at -0.632 Additionally, the GDPg variable shows a negative correlation with all variables in the model, although the strength of these correlations is minimal.
Profitability can be assessed through Return on Equity (ROE), Return on Assets (ROA), and Net Interest Margin (NIM), which are interconnected While NIM measures the opportunity cost of holding liquid assets, its correlation with ROE and ROA is below 0.85 Therefore, it is feasible to incorporate ROE, ROA, and NIM into the same analytical model.
Regression results
The author, having confirmed the absence of multicollinearity among the variables, utilizes Pooled Ordinary Least Squares (POLS) to assess the effect of the independent variable on the bank's liquidity.
Note: ***, ** and * indicates level of significance at 1%, 5% and 10% respectively
According to Table 5, the R-squared value for the POLS model is 25.27%, indicating that 25.27% of the variability in LIQ can be attributed to the nine factors included in the model, while the remaining 74.73% is influenced by random and external factors Additionally, most of the variables in the model are not statistically significant, as evidenced by P-values greater than 0.1 Therefore, the author concludes that the POLS model, based on the collected data, is inappropriate and unreliable.
The author used Breusch and Pagan Lagrangian multiplier test (LM test) to choose between POLS and REM model The following pair of hypotheses:
𝐻 0 : POLS is appropriate and effective
𝐻 1 : REM is appropriate and effective
The result from Stata indicates that Prob > chibar2=0,0000 < 0,05 with 95% confidence, so, author rejected 𝐻 0 , accepted 𝐻 1 Therefore, between POLS and REM, REM is appropriate and effective
To determine the appropriate model between Fixed Effects Model (FEM) and Random Effects Model (REM), the Hausman test is utilized If the p-value from the Hausman test exceeds the significance level of 0.05, the null hypothesis (H0) is accepted, indicating that REM is suitable Conversely, if the p-value is 0.05 or lower, FEM is deemed more appropriate.
𝐻 0 : REM is appropriate and effective
𝐻 1 : FEM is appropriate and effective
The test results indicate that Prob > chi2 = 0.9961, which is greater than 0.05, leading us to accept the null hypothesis (H0) Consequently, the Random Effects Model (REM) is deemed more suitable and effective than the Fixed Effects Model (FEM) In conclusion, the REM is the most appropriate model for analyzing the dataset of 28 commercial banks in Vietnam over a 12-year period.
Table 6: Resutls for FEM and REM
Test results
Following the basic investigation, the research continues on to the test of REM with Test for Multicollinearity, Test for Heteroskedasticity and Test for Autocorrelation
Testing for multicollinearity of the model by using VIF (Variance Inflation Factor) on Stata, obtaining the following result:
The VIF index, with a mean of 3.57 and individual values below 10, suggests a low likelihood of multicollinearity in the regression model, as indicated by Hair et al (2010) Consequently, the analysis confirms that there is no multicollinearity among the variables in the model.
Testing for Heteroskedasticity by using Breusch - Pagan Lagrangian multiplier (LM) test, the results are in table 7:
Table 8: Breusch and Pagan Lagrangian multiplier test
The Breusch - Pagan Lagrangian multiplier test for the REM gives the results that Prob > Chi bar2 = 0,000 < α = 0,05, so the model has Heteroskedasticity
Wooldridge test used to test for autocorrelation in panel data and obtain the following results: Prob > F = 0.0000 < 0,05 which suggests that autocorrelation is an issue
The test results revealed that the REM estimation exhibited defect variance, along with issues of heteroskedasticity and autocorrelation To address these defects, the author employed the FGLS model with panel (h) and corr (ar1) selection, yielding significant results.
The independent variables in the model demonstrate statistical significance ranging from 0.1% to 5%, indicating their ability to explain variations in LIQ Key conclusions derived from the regression analysis are summarized below.
The size of a bank, indicated by the logarithm of total assets, significantly influences its liquidity, with a coefficient of 0.104 at a 0.1% confidence level This suggests that as a bank's size increases by 1%, its liquidity risk also rises by 10.4%, aligning with findings from Kashyap & Stain (2000) and others Larger banks typically enjoy advantages such as lower capital mobilization costs, enabling them to engage in high-risk, high-return lending activities Consequently, these banks face higher liquidity risks compared to smaller institutions However, research by Lucchetta (2007) and Vodova (2011, 2012) indicates that larger total assets can lead to lower liquidity risks due to easier capital acquisition and support from central banks In Vietnam, most banks have a higher volume of loans than deposits, indicating that larger banks positively affect their liquidity risk.
The Return on Assets (ROA) is statistically significant at the 1% level, with a coefficient of 1.125 This indicates that a 1% increase in ROA leads to a 1.125-unit rise in the liquidity risk of banks, aligning with the findings of Waemustafa & Sukri.
Research indicates a significant trade-off between profitability and liquidity security in banks, with Return on Assets (ROA) heavily influencing liquidity risk As banks improve operational efficiency, public confidence rises, facilitating the mobilization of larger capital sources and enhancing their reputation Furthermore, Return on Equity (ROE) is statistically significant at the 0.1% level, revealing that a 1-unit increase in ROE correlates with a 0.247-unit decrease in liquidity risk, aligning with Moussa’s findings (2015) but contradicting Hackethal et al (2010) and Vovada (2013) In Vietnam, despite economic fluctuations, banks with high profit rates maintain strong liquidity, reflecting effective credit management The discrepancies between these profitability measures highlight the unstable performance and limited equity of Vietnamese banks.
The Net Interest Margin (NIM) exhibits a statistically significant positive relationship with liquidity (LIQ) at a 5% level, indicating that a 1% increase in NIM leads to a 1.003 unit rise in liquidity holdings This positive significance suggests that as NIM increases, liquidity risk also escalates, potentially due to earnings distortions from mismatches in asset and obligation maturities (Angbazo, 1997) This finding aligns with Wójcik-Mazur et al (2015), highlighting that banks with diverse income streams may experience a higher maturity mismatch index, reflecting their diversification structure Naceur and Kandil (2009) note that banks holding substantial illiquid assets in loans tend to earn more interest compared to those with fewer illiquid assets, a result that contrasts with findings from Deléchat et al (2014) and Aspachs et al.
Traditional banks excel in generating net interest income from loans, which helps them manage short-term maturity dates effectively In Vietnam, the net interest margin (NIM) has a positive and significant impact on various dependent variables An increase in NIM, whether through rising loan interest rates or falling deposit rates, encourages banks to increase lending and take on greater risks However, these risky loans can negatively affect the bank's liquidity, resulting in heightened liquidity risk.
Fourth, CAP variable has a positive impact on liquidity risk and is statistically significant at 0,1% If CAP increased by 1%, LIQ increase by 0,963% Dinger
Research by Deléchat et al (2009), Vodova (2013), and Bonner et al (2014) indicates that an increase in a bank's equity may lead to higher investments in high-risk assets in pursuit of greater returns, which can offset the rising capital costs associated with increased equity However, excessive equity capital in commercial banks poses potential risks, including liquidity risk In Vietnam, banks can raise equity through share issuance, convertible bonds, or by paying dividends in shares This can create pressure on bank managers from shareholders to boost profits through more aggressive lending at higher interest rates Consequently, banks may convert liquid assets into long-term loans and investments to achieve better returns Larger equity capital can diminish customer deposits, necessitating increased liquidity reserves, while banks reliant on mobilized capital may experience reduced liquidity reserves, heightening their liquidity risk (Diamond and Rajan, 2001; Vodová, 2013a; Wilbert, 2014).
The loan loss provision to total loan ratio (CR) shows a negative but insignificant relationship with banks' liquidity status, indicating that CR does not impact bank liquidity This finding challenges the common belief that CR adversely affects liquidity Supporting this conclusion, Vodová (2012) examined the liquidity determinants of commercial banks in Slovakia from 2001 to 2009, while Imbierowicz and Rauch (2014) further explored this topic.
From 1998 to 2010, US commercial banks were analyzed to understand the relationship between credit and liquidity risk at the institutional level and its impact on default probabilities, revealing no significant reciprocal relationship between these risks In Vietnam, the non-performing loan (NPL) ratio remains high, particularly exacerbated by the Covid-19 pandemic over the past two years, prompting banks to increase their provisioning to address bad debts This heightened caution in provisioning helps mitigate credit risk while ensuring liquidity for banks Additionally, the State Bank of Vietnam (SBV), as the central authority, plays a crucial role in overseeing banking operations and implementing policies to support banks in maintaining liquidity.
The study found no statistically significant evidence linking GDP growth (GDPg) to liquidity risk in Vietnam, indicating that the relationship remains unclear This contradicts the hypothesis that higher GDP growth reduces liquidity risk Supporting this, Waemustafa & Sukri (2016) noted a positive but insignificant relationship between GDP and money supply in Islamic banks Similarly, Ahamed (2021) identified a strong yet insignificant connection between GDP growth and liquidity risk in Bangladeshi commercial banks Additionally, Nga & Huong (2018) reported that GDP growth rate lacked statistical significance regarding the liquidity risk of commercial banks in Vietnam.
The INF variable has a coefficient of -0.191, indicating statistical significance at 5% This suggests that a 1% increase in the inflation rate results in a 0.191% decrease in bank liquidity, highlighting a low level of impact The research indicates that higher inflation facilitates loan repayment for customers, as it diminishes the real value of loans, mitigates liquidity risk, and lowers unemployment (Castro, 2013) These findings align with the results of Vodova.
Research by Cucinelli (2013) and Sudirman (2015) highlights the significant welfare impacts of adjusting inflation targets, which are crucial for central banks Existing monetary theories indicate that rising inflation increases the opportunity cost of holding liquidity, leading to resource allocation distortions As inflation rises, individuals often withdraw deposits from commercial banks, opting to invest in gold and foreign currencies, further straining bank liquidity In response to higher inflation rates, banks, such as the Joint Stock Commercial Bank for Foreign Trade of Vietnam (VCB), have sought to bolster their liquidity reserves For instance, between 2010 and 2011, the inflation rate surged from 9.2% to 18.7%, prompting VCB to reduce its liquidity risk ratio by 0.12 units, a trend mirrored by other banks like Tien Phong Commercial Joint Stock Bank (TPB).
The study reveals that the Covid-19 dummy variable exhibits a negative but insignificant relationship with liquidity risk, indicating that the research did not identify any significant impact of Covid-19 on the liquidity risk of commercial banks in Vietnam.
CONCLUSIONS AND RECOMMENDATIONS
Conclusion
This study examines the factors influencing liquidity risks in 28 Vietnamese commercial banks over a 12-year period from 2010 to 2021 It considers one opportunity cost of holding liquidity, five bank-specific factors, two macroeconomic factors, and one dummy variable The liquidity ratios, measured by the financing gap, were analyzed using panel data regression analysis Model selection tests, including the LM and Hausman tests, indicated that the Random Effects Model (REM) is more suitable than the Fixed Effects Model (FEM) due to a p-value greater than 0.05 Additionally, the Variance Inflation Factor (VIF) index was below 10, confirming no multicollinearity among the variables However, the Wooldridge and Wald tests revealed variable variance and autocorrelation in the REM, prompting the use of the Feasible Generalized Least Squares (FGLS) model with panel (h) and correlation (ar1) selection The findings highlight that six factors significantly affect bank liquidity risk, with Return on Equity (ROE) having the most substantial impact.
The SIZE variable positively influences the liquidity risk of banks from 2010 to 2021, as the growth rate of total bank assets has been slower than the short-term deposit rate Although commercial banks increased their total assets over these 12 years, they primarily invested in liquid assets to generate profit rather than enhance liquidity Larger banks, attracting significant loans and enjoying greater customer trust, experience a decline in liquid assets, thereby heightening their liquidity risk Additionally, rapid expansion can lead to increased costs and management challenges, further exacerbating liquidity risks During the study period, short-term capital mobilized from government and customer deposits grew at a pace surpassing total asset growth, resulting in an inversely proportional relationship between bank size and liquidity risk among Vietnamese commercial banks Overall, while total assets surged, particularly between 2010 and 2015, the corresponding decrease in liquidity has led to increased liquidity risk.
The relationship between Return on Assets (ROA) and liquidity risk is positive, while Return on Equity (ROE) exhibits a negative impact on liquidity Profitable banks, with broader access to capital markets, tend to hold fewer liquid assets, as indicated by ROA (Aspachs et al., 2005) Conversely, a high ROE suggests that banks, despite generating significant profits, may face pressures to cover expenses and debts, leading to a rapid decline in ROE due to competitive interest rate offerings As banks increase their post-tax profits, their reputations improve, boosting depositor confidence and enabling them to attract larger capital inflows This dynamic ultimately stabilizes liquidity through investments in liquid assets, highlighting the negative correlation between ROE and liquidity in Vietnamese commercial banks from 2010 to 2021.
The Net Interest Margin (NIM) positively influences liquidity risk by encouraging banks to prioritize lending, which can lead to reduced liquidity In Vietnam, from 2010 to 2021, joint stock commercial banks experienced a growth in net interest income that outpaced the growth of profitable assets, resulting in a gradual increase in NIM.
There is no correlation between Credit Risk (CR) and Liquidity (LIQ) in Vietnamese commercial banks, primarily due to the high Non-Performing Loan (NPL) ratio in Vietnam, which prompts banks to bolster their provisions Additionally, banks are increasingly cautious about credit risks, as evidenced by the significantly higher rate of short-term capital mobilization compared to the growth of credit risk provisions This lack of relationship persists throughout the research period.
The study reveals that GDP does not influence the liquidity (LIQ) variable in Vietnamese joint stock commercial banks During economic downturns, banks typically increase their liquidity reserves, while in periods of economic growth, they reduce these reserves to seize lending opportunities Vietnam's economic growth rate has remained stable throughout the study period, with a notable decline in GDP over the past two years due to the COVID-19 pandemic Consequently, the findings indicate that bank liquidity has remained stable over the years.
Inflation and macroeconomic policies have negatively impacted certain sectors and markets, leading to significant price declines and reduced transactions This situation has adversely affected outstanding loans from commercial banks, diminishing customers' repayment capabilities and resulting in lower cash flow back to these banks Consequently, liquidity has worsened, increasing the risk of liquidity issues in the financial sector.
Eight, Covid19 does not impact on liquidity risk of commercial banks in
Vietnam's Party, National Assembly, and Government swiftly implemented cohesive, innovative policies to effectively prevent and control the epidemic, while also minimizing its impact on the population.
Recommendations
The Vietnamese government must enhance the internal inspection and supervision of the commercial banking system, focusing particularly on state-owned banks and those that have been equitized but still have majority state ownership These banks consistently exhibit the highest bad debt ratios compared to other commercial and joint venture banks, highlighting the need for improved oversight and management practices.
The government should revise legislative regulations related to bank liquidity risk management to align with international standards for both short- and long-term liquidity issues Additionally, comprehensive regulations must be established to enhance the overall liquidity risk management framework across the banking system.
In response to the COVID-19 pandemic, the Government is implementing fiscal and monetary policies to support the economy, emphasizing the need for close monitoring and safety in banking operations Rising global commodity prices and inflationary pressures are contributing to increased production and business costs, raising concerns about potential inflation in Vietnam To address these challenges, the Government has introduced a policy to support interest rates, as outlined in the banking industry's Action Plan under Resolution No 11/NQ-CP, issued on January 30, 2022, by Decision No 422/QD-NHNN from the State Bank of Vietnam.
The State Bank of Vietnam (SBV) has proposed that the Government extend the application period of Resolution 42 until 2025 and develop a law for managing bad debts, especially as the risk of bad debts rises due to the pandemic's impact on businesses Many enterprises are facing reduced revenues and difficulties in meeting their debt obligations, jeopardizing the target of keeping the bad debt ratio below 3% Immediate measures such as restructuring repayment terms, waiving or reducing interest and fees, and maintaining debt classifications are essential to alleviate the challenges faced by businesses and individuals However, these actions may also heighten bad debt and liquidity risks in the medium term Furthermore, the economy's capital supply, particularly for medium and long-term needs, heavily depends on the banking system, which primarily relies on short-term capital, thus increasing term and liquidity risks for credit institutions.
5.2.2 Recommendations for the State Bank of Vietnam
The SBV must enhance its management and advisory role for commercial banks by consistently synthesizing and analyzing market information to provide objective assessments and forecasts This scientific approach will serve as a valuable reference for banks in formulating their liquidity policies, ensuring sustainable growth while mitigating risks Additionally, the SBV should evaluate the liquidity positions and risk management practices of banks, taking necessary actions when deficiencies are identified.
The State Bank of Vietnam (SBV) must ensure effective oversight of commercial banks to promote sustainable and safe development within the banking sector This includes rigorous supervision of banking operations, especially for major banks where the SBV holds a stake To improve bank liquidity, the SBV and the government should contemplate repealing special legislation that favors state-owned banks and preferential lending policies for state-owned enterprises.
The State Bank of Vietnam (SBV) manages the capital available to commercial banks by utilizing flexible monetary policy tools, including interest rates, reserve requirements, and open market operations, which directly influence bank capital supply To address temporary capital shortages, commercial banks often turn to the interbank market; however, this source can be unreliable due to market volatility Therefore, the SBV needs to establish a more effective refinancing strategy to enhance the liquidity of commercial banks.
To enhance the quality of the banking system's database, it is crucial to address the negative correlation between inflation rates and liquidity risk by accurately forecasting macroeconomic indicators This approach will facilitate the development of scenarios and ensure the reliability of liquidity risk indicators through comprehensive and up-to-date data sources Additionally, the State Bank of Vietnam (SBV) should increase the frequency of data collection to monthly, weekly, or daily intervals, rather than relying on quarterly or annual reports, to effectively signal potential credit risks To achieve this, the SBV must implement modern statistical and data processing methods to minimize errors in data collection and establish a clear reporting system for both periodic and ad hoc reports Furthermore, commercial banks should ensure timely compliance with SBV reporting requirements and adhere to state-prescribed accounting standards to enhance the accuracy and completeness of their data.
To enhance the effectiveness of banking inspections, it is essential to refine the organizational structure of the banking inspection apparatus, ensuring a clear vertical alignment from central to local levels This includes promoting relative independence in management and professional activities within the State Bank's framework Additionally, implementing the core principles of effective banking supervision as outlined by the Basel Committee and adhering to prudent inspection practices are crucial for fostering a robust banking environment.
The SBV must regulate monetary policy and banking activities to ensure liquidity and support credit institutions in providing timely capital for economic recovery It is essential to align operating interest rates with macroeconomic balance, inflation, and market movements while creating conditions to lower capital costs for individuals and businesses Additionally, credit institutions should implement comprehensive solutions to restructure debt repayment terms, exempt and reduce interest rates, and alleviate challenges faced by customers impacted by the COVID-19 pandemic A harmonious balance between economic support and inflation control is crucial, alongside ensuring the safety of the banking system and closely coordinating with ministries to develop effective policy solutions for post-pandemic recovery and development.
5.2.3 Recommendations for Commercial banks of Vietnam
From the research results, the author propose a number of solutions to help Vietnamese commercial banks increase their liquidity, thereby helping banks reduce liquidity risks and increase operational stability
Firstly, Banks need to limit expansion by only focusing on profitable assets, but also need to pay more attention to increasing liquid assets
Merging small banks into larger institutions may not enhance liquidity due to the positive correlation between bank size and liquidity risk Instead of pursuing mergers to increase asset size during liquidity challenges, banks should prioritize raising their liquid assets Consequently, major banks often rely on external financing sources, such as interbank loans or repos, rather than maintaining substantial liquid assets Liquid assets are defined as those that can be swiftly converted into cash at minimal cost, easily tradable on secondary markets or eligible for government discounts The composition of this asset class is influenced by several key factors.
- Regulations on compulsory reserve of the central bank
- The ability of the asset class to generate income
- Actively manage liquid asset portfolio
- Good management of payment funds
Secondly, Banks need to improve the quality of their own capital
The rapid capital growth of joint stock commercial banks has led to complex ownership structures, including cross-ownership and multilateral relationships between banks and businesses This situation can increase the likelihood of bad debts and systemic risks due to liquidity challenges Consequently, it is essential for each bank to adopt tailored capital-raising strategies that mitigate high-risk sources and promote sustainable and stable capital growth.
Retained profit serves as a crucial supplement to equity, particularly for banks with a low Capital Adequacy Ratio (CAR), as it allows them to retain all post-tax profits instead of distributing dividends or repurchasing shares Shareholders play a vital role in safeguarding the capital of banks, and while retaining profits enhances the bank's financial capacity, leading to an increase in asset value for shareholders, it may not significantly address the capital growth needs of banks Additionally, this strategy could hinder the reduction of state ownership in commercial banks and diminish the appeal for investors, especially foreign ones.
One effective strategy for increasing tier 1 capital is to pay dividends to shareholders in shares rather than cash This approach should be executed early in a favorable macroeconomic environment and stock market to avoid issuing shares at low prices, as highlighted by Nguyen Ngoc Thach et al (2016) A significant influx of new shares into the domestic market can lead to decreased stock prices due to heightened competition and limited absorption capacity To mitigate this issue, banks can consider issuing shares to foreign investors, which necessitates collaboration among various stakeholders, including government entities and the State Bank Additionally, commercial banks should draw on global experiences, particularly in the privatization of state-owned banks, to inform their strategies.
Tier-2 capital can be enhanced through the issuance of long-term bonds and certificates of deposit (CDs) In 2016, banks like Vietinbank and Vietcombank successfully issued long-term bonds; however, this approach has significant drawbacks Firstly, it only provides a short-term solution for banks Secondly, it raises the cost of capital, as bond interest rates are typically 1-2% higher than standard deposit rates, leading to increased competition for capital from other financial institutions Thirdly, these bonds often result in banks investing in each other, creating heightened cross-ownership among them Lastly, as outlined in Circular 19/2017/TT-NHNN, there are exclusions regarding individual tier-2 capital.
Gap of the research and future research directions
This study examines 28 commercial banks from 2010 to 2021, acknowledging limitations in time, facilities, and data sources It excludes joint venture banks and foreign branches, as well as any banks with incomplete data during the sampling process.
The research has not explored additional factors influencing the bank's liquidity risk, including foreign ownership rates, interbank interest rates, monetary policy, and money supply.
The recent study focuses solely on a single measure of liquidity risk, overlooking other important metrics such as the total liquid assets to total assets ratio, total liquid assets to total deposits ratio, and total loans to total assets ratio Additionally, it does not account for other liquidity regulations like the Liquidity Coverage Ratio (LCR) and the Net Stable Funding Ratio (NSFR).
The author recommends that future research prioritize the creation of theoretical models, dynamic models, and SGMM models incorporating instrumental and lagged variables to identify the factors affecting liquidity risk in Vietnamese commercial banks.
Dang Van Dan, (2015) Factors affecting liquidity risk of commercial banks in Vietnam Finance Magazine November 2015 issue, pages 60-64
Le Thanh Tam & Nguyen Anh Tu (2017) The Determinants of Banks’ Liquidity in
Nguyen Hai Long & Nguyen Minh Phuong (2017) Liquidity risk management at Bank for Agriculture and Rural Development of Vietnam
Nguyen Hoang Phong & Phan Thi Thu Ha (2017) Factors affecting liquidity ratio at Vietnamese commercial banks Economic and Development Review
Pham Thi Hong Diep (2021) Determinants Affecting The Liquidity Of Commercial
Banks In Vietnam: A Longitudinal Analysis
Tran Thi Thanh Nga & Tran Thi Xuan Huong (2018) The determinants of bank liquidity risk empirical evidence from vietnam
Tran Thi Thanh Tu & Long Tran (2019) The determinants of liquidity risk of commercial banks in Vietnam, Banks and Bank Systems
Truong Quang Thong (2013) Causes of liquidity risks for the system of Vietnamese commercial Banks
Vu (2015) Determinants of bank Liquidity in Vietnam Development and Integration Magazine 23
Abdullah, A., & Khan, A Q (2012) Liquidity risk management: a comparative study between domestic and foreign banks in Pakistan Journal of Managerial Sciences
Abreu, M., & Mendes, V (2002) Commercial bank interest margins and profitability: evidence from E.U countries Porto Working paper series
Acharya, V., & Merrouche, O (2010) Precautionary Hoarding of Liquidity and Inter-Bank Markets: Evidence from the Sub-prime Crisis NBER Working Paper
Acharya, V., & Naqvi, H (2012) The seeds of a crisis: a theory of bank liquidity and risk taking over the business cycle J Financ Econ 106 (2), 349–366
Acharya, V.V., & Viswanathan, S.V (2011) Leverage, moral hazard, and liquidity Journal of Finance 66, 99–138
Agenor, P., Aizenmann, V & Hoffmaister, A.W (2004), The Credit Crunch in East
Asia: What Can Bank Excess Liquid Assets Tell Us? Journal of International Money and Finance, Vol 23, pp 27-49
Ahmed, N., Ahmed, Z., & Naqvi, I (2011) Liquidity Risk and Islamic Banks: Evidence from Pakistan Interdisciplinary Journal of Research in Business
Akhtar, M F., Ali, K., & Sadaqat, S (2011) Liquidity risk management: a comparative study between conventional and Islamic banks of Pakistan
Interdisciplinary journal of research in business, 1(1), 35-44
Allen, F., & Carletti, E (2008), The Role of Liquidity in Financial Crises Mimeo
Almeida, H., Campello, M., & M Weisbach (2004) The cash flow sensitivity of cash New York University
Anam, S (2012) Liquidity Risk Management: A Comparative Study Between Conventional and Islamic Banks of Bangladesh Research Journal Economics,
Angora A., & Roulet C (2011) Transformation Risk and its Determinants: A new
Approach Based on Basel III Liquidity Management Framework
Arif, A (2012) Liquidity risk and performance of banking system: Journal of Financial Regulation and Compliance
Aspachs, O., Nier, E., & Thiesset, M (2005) Liquidity, Banking Regulation and the
Macroeconomy London School of Economics, London
Athanasoglou P P., Brissmis S N., & Delis M D (2008) Bank-Specific, Industry-
Specific and Macroeconomic Determinants of Bank Profitability Journal of
International Finance, Markets, Institution and Money, 18, 121-136
Baltensperger, E (1980) Alternative Approaches to the Theory of the Banking Firm Journal of Monetary Economics, Vol 6, pp.1-37
Barth, James, R., Daniel E., Triphon, P., & Glenn, Y (2003) A Cross-Country Analysis of the Bank Supervisory Framework and Bank Performance Financial
Basel Committee on Banking Supervision: Basel III monitoring report (2013) Bank for International Settlements, September
Basel Committee on Banking Supervision: Literature review on integration of regulatory capital and liquidity instruments (2016) Bank for International
Belaid, F., & Bellouma, M (2016) Determinants of loan quality: evidence from the
Tunisian banking sector International Journal of Engineering Research &
Berger, A N., & Bouwman, C H (2009) Bank liquidity creation Review of
Bonfim, D., Barros, P P., Kim, M., & Martins, N C (2011) Estimating the impact of bank mergers: an application to the Portuguese banking system Economic
Bulletin and Financial Stability Report Articles and Banco de Portugal Economic Studies
Bordeleau, É., & Graham, C (2010) The impact of liquidity on bank profitability (No 2010, 38) Bank of Canada working paper
Bourke, P (1989) Concentration and other determinants of bank profitability in Europe, North America and Australia Journal of Banking & Finance, 13(1), 65-79
Bryant J (1980) A model of reserves, bank runs, and deposit insurance Journal of Banking & Finance, 4(4), 335–344
Bunda, I., & Desquilbet J.B (2008) The bank liquidity smile across exchange rate regimes of 36 emerging countries commercial banks International Economic
Casu, B., Girardone, C., & Malyneux, P., (2006) Introduction to Banking, Harlow,
Chaplin, G., Emblow, A & Michael, I (2000) Banking system liquidity: developments and issues Financial Stability Review, December, pp 93-112
Chen, Y.K (2018) Bank Liquidity Risk and Performance Pacific Basin Financial Markets and Policies
The study by Choon et al (2013) investigates the factors affecting liquidity in Malaysian commercial banks, analyzing data from 15 banks The research highlights key determinants that influence liquidity levels and discusses their implications for regulatory bodies and financial institutions in Malaysia This thesis underscores the importance of understanding liquidity dynamics to enhance banking stability and performance in the Malaysian financial sector.
Chowdhury, A N., Siddiqua, M H., & Chowdhury, A (2016) Relationship between Liquidity Risk and Net Interest Margin of Conventional Banks in Bangladesh Asian Business Review, 6(3), 175-178
Cole, R.A., & Fenn, G.W (1995) The Role of Commercial Real Estate Investments in the Banking Crisis of 1985–1992 Working Paper
Cucinelli, D (2013) The determinants of bank liquidity risk within the context of euro area Interdisciplinary Journal of Research in Business, 2(10), 51-64
DeHaan, Leo, Willem, J., & End, V.D (2013) Bank liquidity, the maturity ladder, and regulation Journal of Banking & Finance 37: 3930–50
DeJonghe, O (2010) Back to the basics in banking? A microanalysis of banking system stability Journal of financial intermediation, 19(3), 387-417
Deléchat, C., Henao, C., Muthoora, P & Vtyurina, S (2014) The Determinants of
Banks' Liquidity Buffers in Central America Monetoria, II (1), 83-129
Demirguc-Kunt, A., & Huizinga, H (1999) Determinants of commercial bank interest margins and profitability: some international evidence The World Bank
Demirguc-Kunt, A., & Ross, L (2003) The Impact of Bank Regulations, Concentration, and Institutions on Bank Margins Washington: The World Bank
Dermine J (1986) Deposit rates, credit rates and bank capital: The Klein-Monti Model Revisited Journal of Banking & Finance, 10(1), 99–114
DeYoung, R., Distinguin, I., & Tarazi, A (2018) The joint regulation of bank liquidity and bank capital Journal of Financial Intermediation, 34, 32-46
Diamond, D W., & Dybvig, P H (1983) Bank Runs, Liquidity and Deposit Insurance Journal of Political Economy, 91(3), 401–419
Diamond, D.W., & Rajan, R.G (2001) Liquidity shortages and banking crises The Journal of Finance, Vol 60 No 2, pp 615-47
Diamond, D.W., &Rajan, R.G (2005) Liquidity shortages and banking crises
Diep, N.T.N., & Lam, N.T (2017) Determinants of Liquidity of Commercial Banks in Vietnam in the Period 2009-2016 International Journal of Scientific Study, 5(6),
Dinger, V (2009) Do Foreign-owned Banks Affect Banking System Liquidity Risk? Journal of Comparative Economics, Vol 37, pp 647-657
Distinguin, & Amine, T (2013) Bank regulatory capital and liquidity: Evidence from US and European publicly traded banks Journal of Banking and Finance
Drehmann, M., & Nikolaou, K (2009) Funding liquidity risk: definition and measurement ECB Working Paper No 1024
Drehmann, M., & Nikolaou, K (2013) Funding liquidity risk: Definition and measurement Journal of Banking and Finance
Duttweiler, R (2009) Managing Liquidity in Banks: A Top Down Approach John Wiley & Sons Ltd
Eichberger, J., & Summer, M (2005) Bank capital, liquidity, and systemic risk Journal of the European Economic Association, 3(2-3), 547-555
Ahamed, F., (2021) Determinants of Liquidity Risk in the Commercial Banks in Bangladesh European Journal of Business and Management Research
García-Herrero, A., Gavilá, S., & Santabárbara, D (2009) What explains the low profitability of Chinese banks? Journal of Banking & Finance, 33(11), 2080-2092
Gaston A., & Schumacher, I (2012) Bank liquidity risk and monetary policy Empirical evidence on the impact of Basel III liquidity standards International
Giannotti C., Gibilaro L & Mattarocci G (2010) Liquidity Risk Exposure for Specialized and Unspecialized Real Estate Banks: Evidence from the Italian Market
Journal of Property Investment and Finance, 29(2), 98-114
Giordana G & Schumacher I (2011) The Impact of the Basel III Liquidity regulation on the Bank Lending Channel: a Luxemburg Case Study Cahier de Etude, Working
Paper n.61 Banque Centrale Du Luxemburg
Goodhart, C (2008) Liquidity risk management Financial Stability Review
Hadlock, C J., & James, C M (2002) Do banks provide financial slack? The
Halling, M & Hayden, E (2006) Bank failure prediction: a two-step survival time approach C.R.E.D.I.T Conference, Austrian National Bank, Vienna, p 31
Horvàt R., Seidler J & Weill L (2012) Bank’s Capital and Liquidity Creation: Granger Causality Evidence Working Paper Series n 5, Czech National Bank
Hossain, M S., & Ahamed, F (2015) Determinants of bank profitability: A study on the banking sector of Bangladesh Journal of Finance and Banking, 13(1), 43-57
Hutchison, P D., Farris II, M T & Anders, S B (2007) Cash-to-cash analysis and management The CPA Journal, Vol 77 No 8, pp 42-47
Illueca, M., Norden, L., & Udell, G.F (2008) Liberalization, Corporate Governance, and Savings Banks Working Paper, Indiana University
Iqbal, A (2012) Liquidity risk management: a comparative study between conventional and Islamic banks of Pakistan Global journal of management and business research
Ismal, R (2010) Assessment of liquidity management in Islamic banking industry International Journal of Islamic and Middle Eastern Finance and Management
Iyer, R., Puri, M (2012) Understanding bank runs: the importance of depositor-bank relationships and networks American Economic Review 102, 1414–1445
Jedidia, K B., & Hamza, H (2015) Determinants of liquidity risk in Islamic banks:
A panel study Islamic Management and Business, 2(2), 137-146
Jenkinson, N (2008) Strengthening regimes for controlling liquidity risk Euro
Money Conference on Liquidity and Funding Risk Management, Bank of England, London, p 9
Keynes, J.M (1936) The General Theory of Employment, Interest and Money, Macmillan Cambridge University Press
Kiyotaki, N., & Moore, J (2008) Liquidity, Business Cycles and Monetary Policy Technical Paper for Clarendon Lecture, No 2
Kolari, J., Glennon, D., Shin, H., & Caputo, M (2002) Predicting large US commercial bank failures Journal of Economics and Business 54, 361–387
Kosimodou K (2008) The Determinants of Banks’ Profits in Greece during the Period of UE inancial Integration Managerial Finance, 34, 146-159
Kosmidou, K., Tanna, S., & Pasiouras, F (2005) Determinants of Profitability of Domestic UK Commercial Banks: Panel Evidence from the Period 1995-2002
Money Macro and Finance (MMF) Research Group Conference
Koziol, C., & Lawrenz, J (2008) What makes a bank risky? Insights from the optimal capital structure of banks Journal of Banking & Finance, 33(5), 861-873
Kurnia, H P., & Muharam, H (2012) The Influence of Fundamental Factors to
Liquidity Risk on Banking Industry (Case Study between Conventional and Islamic Banks in Indonesia) (Doctoral dissertation, Fakultas Ekonomika dan Bisnis)
Lei, A C., & Song, Z (2013) Liquidity creation and bank capital structure in China Global Finance Journal, 24(3), 188-202
Lucchetta, M (2007) What do data say about monetary policy, bank liquidity and bank risk taking? Economic Notes: Review of Banking, Finance and Moneytary
Malik, M andRafique, A (2013) Commercial banks liquidity in Pakistan Romanian Economic Journal, 16(48), 139-154
Molyneux, P., Thornton, J (1992) Determinants of European Bank Profitability: A
Note Journal of Banking and Finance, Vol 16, 1173-1178
Moussa, M A B (2015) The determinants of bank liquidity: case of Tunisia
International Journal of Economics and Financial Issues, 5(1), 249-259
Mugenyah, L O (2015) Determinants of liquidity risk of commercial banks in Kenya
(Doctoral dissertation, University of Nairobi)
Munteanu, I (2012) Bank liquidity and its determinants in Romania Procedia
Muriithi, J G., & Waweru, K M (2017) Liquidity Risk and Financial Performance of Commercial Banks in Kenya International Journal of Economics and Finance
Nikomaram, H.K., Taghavia, M., & Diman, D.S (2013) The relationship between liquidity risk and credit risk in Islamic banking industry of Iran Management Science
Ogol, G O (2011) Liquidity risk management practices in micro-finance institutions in Kenya (Unpublished Doctoral dissertation) University of Nairobi, Kenya
Papavassiliou, V G (2013) A new method for estimating liquidity risk: Insights from a liquidity-adjusted CAPM framework Journal of International Financial Markets,
Pasiouras, F., & Kosmidou, K (2007) Factors influencing the profitability of domestic and foreign commercial banks in the European Union Research in
Prisman, E.Z., Slovin, M.B., & Sushka, M.E (1986) A general model of the banking firm under conditions of monopoly, uncertainty, and recourse Journal of Monetary
Ramzan, M., & Zafar, M I (2014) Liquidity Risk Management in Islamic Banks: A
Study of Islamic Banks of Pakistan
Rauch, C., Steffen, S., Hackethal, A & Tyrell, M.(2010) Determinants of bank liquidity creation
Roengpitya, R., Nikola, T., Kostas, T., & Alan, V (2017) Bank Business Models:
Popularity and Performance BIS, Working paper 682 Basel: Bank for International
Said, R M (2014) Net Stable Funding Ratio and Commercial Banks Profitability International Proceedings of Economics Development and Research 76 (34)
Samartín, M., 2003 Should bank runs be prevented? Journal of Banking & Finance
Samy, B., Naceura, B., & Kandilc, M (2009) The Impact of Capital Requirements on Banks’ Cost of Intermediation and Performance: The Case of Egypt Journal of
Santomero, A M (1984) Modeling the Banking Firm Journal of Money, Credit and
Saunders, A & Cornett, M.M (2006) Financial Institutions Management: A Risk
Management Approach Mc Graw-Hill, Boston
Shen C., Chen Y., Kao L & Yeh C (2009) Bank Liquidity Risk and Performance
Singh, A., & Sharma, A.K (2016) An empirical analysis of macroeconomic and bank-specific factors affecting liquidity of Indian banks Future Business Journal 2
Sopan, J., & Dutta, A (2018) Determinants of liquidity risk in Indian banks: A panel data analysis Asian Journal of Research in Banking and Finance, 8(6), 47-59
Sukmana, R., & Suryaningtyas, S (2016) Determinants of liquidity risk in Indonesian Islamic and conventional banks Jurnal Ilmu Ekonomi Syariah, 8(2)
Annual report 2009 (2009) The European Central Bank
Vento, Gianfranco A., & Pasquale, L, G (2009) Bank liquidity risk management and supervision: which lessons from recent market turmoil Journal of Money, Investment and Banking 10.10: 78-125
Vodovà P (2011) Liquidity of Czech Commercial Banks and its Determinants International Journal of Mathematical Models and Methods in Applied Sciences
Vodova, P (2012) Determinants of commercial banks’ liquidity in Poland
Waemustafa, W., & Sukri, S (2016) Systematic and unsystematic risk determinants of liquidity risk between Islamic and conventional banks International Journal of
Zaghdoudi, K., & Hakimi, A (2017) The determinants of liquidity risk: Evidence from Tunisian banks Journal of Applied Finance and Banking, 7(2), 71
Zhang, Q., Cagin, T., Van Duin, A., Goddard III, W A., Qi, Y., & Hector Jr, L G
(2004) Adhesion and nonwetting-wetting transition in the Al/α− Al 2 O 3 interface Physical Review B, 69(4), 045423.