ABSTRACT The topic " FACTORS INFLUENCING THE LIQUIDITY OF COMMERCIAL BANKS IN VIETNAM" is based on previous researches related to factors affecting the liquidity of Vietnamese commercial
INTRODUCTION
I NTRODUCTION
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Liquidity is a vital factor for the safety and stability of commercial banks, as a lack of liquidity can trigger a chain reaction affecting the entire banking system The 2008 global financial crisis exemplified this, highlighting how liquidity shortages at banks can lead to widespread defaults, bank failures, and mergers despite central bank interventions Even profitable banks can face liquidity crises due to challenges in asset and capital management, emphasizing the importance of effective liquidity management In response to such crises, Basel III was introduced in 2013, implementing stringent liquidity regulations aimed at reducing the risk of future financial system shocks and minimizing economic damage.
In Vietnam, the State Bank has implemented regulations to enhance liquidity for commercial banks According to Circular No 22/2019/TT-NHNN, issued on November 15, 2019, by the State Bank of Vietnam, these regulations set limits and ratios to ensure the safe and stable operation of banks and foreign bank branches These measures aim to promote financial stability in the banking sector from January 1.
Since 2020, when Circular 22/2019/TT-NHNN became effective, the maximum loan-to-deposit ratio (LDR) for banks has been set at 85% Additionally, the State Bank initially limited short-term capital used for medium and long-term loans to a maximum of 34%, a regulation that applied from October 1, 2021, until September 30, 2022 Subsequently, this limit was reduced to 30% starting October 1, 2022, reflecting updated monetary policy measures.
This study investigates the key factors impacting the liquidity of Vietnam's commercial banking system amidst the rapidly changing and volatile financial environment Understanding these determinants is essential for ensuring banking stability and sustainable growth in Vietnam’s evolving financial sector The research aims to provide insights into how current economic fluctuations influence banking liquidity, offering valuable guidance for industry stakeholders and policymakers.
Banks are essential to a country's economy, serving a vital role in regulating macroeconomic stability through credit financing and supporting the integration of economic and production activities Effective banking governance is crucial for governments to oversee and manage financial institutions, with liquidity management being the top priority to ensure financial stability and prevent crises.
Liquidity is crucial for the survival and growth of commercial banks and the entire banking system Recent global economic challenges, such as the Russia-Ukraine conflict and rising commodity prices, have impacted liquidity conditions worldwide High inflation over the past decade prompted central banks to aggressively increase interest rates to control inflation In Vietnam, post-pandemic economic reopening led banks to disburse credit rapidly, depleting their credit room from early 2022 and prompting requests to the State Bank for additional credit capacity Continuous rapid credit growth poses risks to future liquidity stability and banking governance amidst today’s volatile global economy Liquidity challenges in Vietnamese commercial banks remain a key focus each year, as maintaining good liquidity is essential for ensuring bank stability, stabilizing financial markets, and supporting smooth economic operations.
3 the author has chosen to study the topic " Factors affecting liquidity at commercial banks in Vietnam " for the graduation thesis.
T HE NOVELTY OF THE TOPIC
This article examines how the Vietnamese banking sector navigated the post-COVID recovery period, highlighting the State Bank of Vietnam’s proactive monetary policies and interest support packages implemented to stimulate economic growth after pandemic-induced stagnation Despite economic shutdowns, commercial banks rapidly disbursed credit up to their regulated limits, resulting in record profits and maintained liquidity levels The analysis explores how factors influencing bank liquidity evolved before and during the pandemic, all while sustaining high profitability The insights provided serve as a foundation for bank leaders to adopt recommended strategies, enhancing safety within the Basel framework, improving profitability, and strengthening the reputation and position of Vietnamese commercial banks in the global financial landscape.
T HE AIM OF THE THESIS
This study aims to identify the key factors influencing the liquidity of commercial banks in Vietnam Understanding these factors is essential for developing effective strategies to manage bank liquidity efficiently The research provides practical solutions and recommendations to enhance liquidity management, ensuring the stability and sustainability of Vietnamese commercial banks.
Determining the factors impacting the liquidity of commercial banks in Vietnam
Measuring and assessing the impact direction of each factor influencing the liquidity of commercial banks in Vietnam
Proposing recommendations to manage the liquidity of Vietnamese commercial banks to ensure both liquidity and profitability.
T HE RESEARCH QUESTIONS
Based on the particular objectives mentioned above, the thesis will, in turn, answer the following questions:
What factors affect the liquidity of commercial banks in Vietnam?
What is the impact level and direction of these factors on the liquidity of Vietnam's commercial banks?
What are suggestions that can manage the liquidity of Vietnamese commercial banks to meet both liquidity and profitability?
S UBJECT AND SCOPE OF THE RESEARCH
Research subject: Factors influencing the liquidity of commercial banks
Research scope: samples were collected from financial statements of 25 Vietnamese commercial banks listed on the Stock Exchange in the period 2012 -
2021 The criteria needed for the study are shown in the financial statements of the banks.
M ETHODOLOGY
Qualitative method: analyze and evaluate the situation of domestic and foreign research related to the research thesis and synthesize the necessary theoretical bases, test the research's hypothesis
This study utilizes a quantitative method based on data extracted from banks' annual financial statements It applies established panel data estimation models, including fixed effects regression (FEM), random effects regression (REM), and the pooled ordinary least squares (POLS) model To ensure model accuracy, relevant tests and corrective measures are employed to address potential issues and identify the most suitable regression approach.
R ESEARCH CONTENT
This study assesses the key factors influencing the liquidity of Vietnamese commercial banks from 2012 to 2021 Using econometric models, it evaluates the impact and significance of these factors on bank liquidity, providing insights based on the industry's actual operational data The research aims to identify critical determinants affecting liquidity and offers practical solutions to enhance the efficiency and safety of Vietnamese commercial banks.
C ONTRIBUTION OF THE THESIS
This research contributes to developing an empirical model to analyze the financial and macroeconomic factors influencing the liquidity of commercial banks in Vietnam The findings provide valuable insights that pave the way for future, more detailed investigations in this field.
Analyzing the key factors that influence liquidity in Vietnamese commercial banks reveals the complex relationships and the extent of their positive or negative impacts on bank liquidity Understanding these dynamics is essential for developing effective solutions and management strategies to ensure stable and healthy liquidity levels Implementing targeted policies based on these insights can help Vietnamese commercial banks maintain strong liquidity positions, supporting their overall financial stability and growth.
T HE PROPOSED LAYOUT OF THE THESIS
This chapter highlights the urgent need for the thesis by outlining its main purpose and scope of research It reviews both domestic and international studies to provide context and demonstrates the significance of the research topic Additionally, a brief overview of the research methods employed is presented to guide readers through the methodology.
Presents basic concepts and underlying theories
This study employs a structured research methodology, outlining the comprehensive research process, including the formulation of clear hypotheses and specific research conditions The sampling procedure involves carefully selected data sources to ensure accuracy and reliability, with input data collected through systematic methods such as surveys, interviews, or secondary data analysis The study emphasizes rigorous data validation techniques to determine the value and relevance of collected data, focusing on key variables that influence the research outcomes Various statistical and analytical test methods are applied to analyze the data, ensuring the robustness and validity of the research findings This methodological framework aims to provide a thorough understanding of the research process, supporting valid and actionable conclusions.
- Chapter 4: Data analysis, Findings, and Discussion
Mainly focus on discussing experimental research results in chapter 3
Briefly present the results obtained from the study From that, gives conclusions and recommendations
Chapter 1 points out the importance and urgency of analyzing the factors affecting the liquidity of Vietnamese commercial banks The thesis gives 3 particular research objectives from the general research objective and will be solved through 3 corresponding research questions Next, the topic presents the research's object and scope, which are 25 Vietnamese commercial banks from 2012 to 2021 The thesis uses qualitative research methods and quantitative research methods based on inheritance and expands previous studies to update factors affecting liquidity that can change over time Finally, this chapter will present the structure of the thesis consisting of 5 chapters and a summary of the main content of each chapter
THEORETICAL FRAMEWORK
L IQUIDITY OF COMMERCIAL BANKS
Liquidity refers to an asset's ability to be quickly converted into cash without significantly impacting its value An asset is deemed liquid when it has sufficient quantity available for buying or selling, active markets for trading, adequate time to execute transactions, and is priced reasonably Understanding asset liquidity is essential for assessing financial flexibility and managing risk effectively.
Liquidity, as defined by the Basel Committee on Banking Supervision, is a crucial technical term that signifies a bank’s ability to meet its operational needs by effectively utilizing available capital Ensuring liquidity is vital for maintaining business activities such as deposit payments, lending, daily transactions, and capital transfers Maintaining strong liquidity positions helps banks remain resilient and operationally sound at all times, supporting their ongoing financial stability and regulatory compliance.
Throughout history, Basel's understanding of liquidity has evolved, but it is broadly defined as the ability to enhance asset funds and fulfill obligations reliably while maintaining acceptable costs.
High-liquidity assets include valuable papers like Treasury bills, certificates of deposit, promissory notes, and bills of exchange, which can be quickly converted into cash In contrast, low-liquidity assets such as real estate, machinery, equipment, and production lines typically require more time to liquidate and convert into cash Understanding the liquidity levels of different assets is essential for effective financial management and investment planning.
Bank liquidity refers to a financial institution's ability to promptly meet its operational obligations, including deposit payments, lending activities, and other financial transactions According to Basel (2008), bank liquidity is defined as the ability to both increase assets and meet debt obligations as they become due without incurring significant losses Ensuring sufficient liquidity is crucial for maintaining stability and operational efficiency in the banking sector.
9 payments and financial transactions entirely and on time, it means that the bank is insolvent in liquidity” (Bessis, 2012)
Bank liquidity is the ability of a bank to fully and promptly meet its financial obligations, including paying deposits at maturity, disbursing loans, and processing payments efficiently Maintaining liquidity ensures the bank can conduct financial transactions at a reasonable cost, minimizing potential losses that could threaten its solvency Proper management of liquidity is essential for preventing insolvency and ensuring stable banking operations.
2.1.3 Supply and demand of liquidity and net liquidity position
2.1.3.1 Supply and demand of liquidity
Liquidity supply refers to a bank's capacity to provide cash to meet customer payment demands promptly A strong liquidity supply enhances the bank's overall liquidity position, ensuring financial stability It is generated from various sources, including available cash and assets that can be quickly mobilized, enabling banks to maintain operational efficiency and confidence.
Liquidity demand represents the immediate or short-term disbursement and payment needs of customers that banks are required to fulfill promptly It signifies the portion of the bank’s cash resources that will be impacted or reduced due to customer withdrawals and payments Managing liquidity demand is essential for maintaining financial stability and ensuring the bank can meet its disbursement obligations efficiently.
Table 2.1: Banking activities forming the supply and demand for liquidity
Accepting deposits Customers withdraw deposits
Loans are repaid Payment of due loans
Proceeds from providing products and services
Money market loans Cash dividend payment
Proceeds from property sales Disbursing new loans or investment
Paying costs incurred in the process of providing products and services
The combination of a bank's liquidity supply and demand will make up its Net Liquidity Position (NLP) which is calculated according to Nguyễn Văn Tiến (2015) as follows:
When NLP exceeds zero or liquidity supply surpasses liquidity demand, the bank is experiencing a liquidity surplus, indicating positive current liquidity However, this also suggests that the bank's profitability potential remains underutilized Causes of a liquidity surplus may include proactive accumulation of liquidity reserves, inefficient investments, a stagnant economy with limited investment opportunities, or excessively rapid capital growth.
When NLP is less than zero, indicating that liquidity supply is smaller than liquidity demand, the bank experiences a liquidity deficit, which poses significant risks to its operations A minor liquidity deficit can hinder a bank's ability to function effectively, underscoring the importance of maintaining balanced liquidity levels for stability and risk management.
A significant liquidity deficiency can lead to severe issues such as losing customers, business opportunities, and markets, as well as diminishing public confidence (Trương Quang Thông, 2010) To mitigate liquidity shortages, necessary actions include selling illiquid assets, utilizing required reserves, borrowing from the interbank market, and seeking emergency funding from lenders of last resort.
When NLP equals zero or liquidity supply matches liquidity demand, the bank is in a state of liquidity equilibrium, which is the primary goal for bank administrators However, maintaining liquidity equilibrium in practice is challenging due to market fluctuations and operational complexities Achieving this balance ensures optimal liquidity management and financial stability for the bank.
L IQUIDITY MEASUREMENT METHOD
Vodova (2011) offered two methods to measure liquidity: measurement by liquidity gap and measurement by liquidity ratios
The liquidity gap measurement method is a method of measuring the difference between capital and assets at present and in the future
Liquidity ratios are a method of calculating various ratios collected from balance sheet data, thereby predicting liquidity movements
The liquidity gap, defined as the difference between the average total loan balance and the average total mobilized capital, serves as a crucial indicator of a bank’s financial health It signals potential future liquidity risks, acting as a warning sign for stakeholders to assess the bank's ability to meet its obligations Monitoring and managing the liquidity gap is essential for maintaining optimal liquidity levels and ensuring banking stability.
A positive and substantial liquidity gap forces the bank to reduce cash reserves, liquid assets, or borrow additional funds in the money market, thereby increasing its liquidity risk (Đặng Văn Dân, 2015) Measuring liquidity through the liquidity gap is considered the most effective quantitative method, with the liquidity gap index providing a clear indication of the bank’s core liquidity position.
There are various methods to assess a bank's liquidity, with Rose (2004) utilizing the widely recognized liquidity index method This approach has been adopted by numerous researchers, including Vodova (2011) and Bunda & Desquilbet (2008) The liquidity index method evaluates a bank's liquidity using four key indicators, providing a comprehensive measure of financial stability.
Liquid assets in Level 1 encompass cash, trading securities, and deposits with central banks or other credit institutions, reflecting the bank’s immediate liquidity A higher level of liquid assets indicates a strong liquidity position and low risk of insolvency, ensuring the bank can meet short-term obligations However, an excessively high ratio may suggest operational inefficiency, as the bank holds a large volume of low-profitability or unprofitable assets, potentially impacting overall profitability Optimizing liquidity while maintaining profitability is crucial for sound financial management.
The liquidity ratio L2 measures the proportion of liquid assets to deposits and mobilized capital, indicating a bank's ability to meet its short-term obligations Similar to L1, a higher L2 ratio—equal to or exceeding 100%—signifies a strong liquidity position, highlighting the bank's capacity to cover its liabilities comfortably Maintaining an L2 ratio at or above this threshold is essential for ensuring financial stability and confidence among depositors and stakeholders.
The loan-to-asset ratio indicates the proportion of a bank's total assets that are composed of outstanding loans A higher ratio suggests that the bank has leveraged more of its assets into loans, which can reduce its liquidity levels Reduced liquidity increases the bank's exposure to liquidity risk, potentially impacting its ability to meet short-term obligations Monitoring this ratio is essential for understanding a bank's financial stability and risk profile.
This ratio is similar to the L3 index The higher the ratio, the lower the bank's liquidity
L1 and L2 indexes measure absolute liquidity, while L3 and L4 indexes measure relative liquidity
Many studies, such as Vodova (2011), Aspachs et al (2005), and Vũ Thị Hồng (2015), utilize all four liquidity ratios to evaluate bank liquidity; however, the L1 index is often preferred due to its comprehensive view of both short- and medium- to long-term liquidity The L1 index measures the proportion of a bank’s total assets held in liquid form, allowing it to hedge against liquidity risk effectively In Vietnam, banks facing sudden liquidity shortages can borrow via the interbank market or receive support from the Lender of Last Resort to avoid bankruptcy, although this incurs high costs and can significantly impact profitability Over time, sustained liquidity shortfalls can jeopardize a bank's operational efficiency, potentially leading to bankruptcy or government intervention, such as the Vietnam State Bank repurchasing the bank at zero dong Consequently, the L1 index is considered superior to other ratios for assessing bank liquidity across different timeframes.
F ACTORS INFLUENCING BANK LIQUIDITY
2.3.1 Group of factors inside the bank
Bank size, measured by the natural logarithm of total assets, significantly influences bank liquidity According to Signaling Theory (Spence, 1973), an increase in bank size sends a positive signal to the market, encouraging greater capital mobilization and enhancing liquidity Conversely, larger banks, especially those deemed "too big to fail" (Grey, 2009) and receiving government support during crises, may experience reduced liquidity due to the perception of diminishing returns on expansion.
Banks are increasingly investing in riskier assets to boost profits, which can lead to potential losses and decreased liquidity This dynamic suggests that larger banks, due to their scale, may have better capacity to manage these risks, indicating a positive relationship between bank size and liquidity.
Equity-to-total assets ratio (CAP)
The capital adequacy ratio, measured by dividing a bank's equity by its total assets, reflects the bank's financial safety, soundness, and stability A low ratio indicates high financial leverage, which increases risk and may lead to decreased profits when borrowing costs rise This ratio can serve as an alternative to Basel's Capital Adequacy Ratio (CAR) within capital regulation frameworks Core capital acts as a crucial buffer, serving as the last line of defense against various banking risks.
Research by Vodova (2011) indicates that banks with low equity are more focused on liquidity risk management and tend to hold larger volumes of liquid assets to ensure stability In contrast, Vũ Thị Hồng (2015) found a positive correlation between bank equity and liquidity, suggesting that higher capital levels reduce default risk, enhance the bank’s reputation, and attract substantial customer deposits, thereby improving liquidity.
Loan-to-deposit ratio (LDR)
The loan-to-capital ratio is calculated by dividing total loans by total mobilized capital, with capital mobilization based on Circular 13/2010/NHNN The prudential ratio limit for banks is set at 80%, measuring the outstanding balance of loans supported by stable capital, such as customer deposits and non-financial institution funds When loans surpass mobilized capital, banks face a funding gap, forcing them to quickly seek liquidity through borrowing in the financial market A large funding gap indicates high dependence on market capital, which comes at a higher, more expensive cost.
A higher Loan Deposit Ratio (LDR) indicates increased liquidity risk for banks, as lending exceeds mobilized capital When banks face liquidity difficulties, excessive lending hampers their ability to attract inexpensive capital, significantly reducing overall liquidity Research by Aspachs et al (2005) demonstrates a negative correlation between the LDR ratio and bank liquidity, highlighting the risks associated with high LDR levels.
Return on Equity (ROE) is a key financial ratio calculated by dividing net earnings after tax by shareholders' equity, reflecting how efficiently a bank's management utilizes its equity to generate profits Numerous studies, including those by Bunda and Desquilbet (2008) and Vũ Thị Hồng (2015), demonstrate a positive relationship between ROE and bank liquidity, indicating that higher profitability can enhance liquidity levels Conversely, some research, such as Aspachs et al (2005), identify a negative impact of ROE on liquidity, suggesting that increased profitability may sometimes reduce the bank's capacity to maintain sufficient liquidity.
Non-performing loan ratio (NPL)
The non-performing loan ratio is calculated by dividing non-performing loans by total loans An increase in this ratio prompts banks to adopt more cautious lending practices and prompts central banks to limit that bank’s lending activities Consequently, banks seek to boost profits through alternative methods such as mobilizing capital and promoting additional services, which enhances liquidity Studies by Vodova (2011) and Vũ Thị Hồng (2015) consistently show that a higher non-performing loan ratio positively impacts bank liquidity.
2.3.2 Group of factors outside the bank
Economic growth is measured by the annual GDP growth rate, reflecting the country's economic progress over time This data is sourced from the General Statistics Office of Vietnam (gso.gov.vn), ensuring accurate and official statistics on Vietnam’s economic performance Tracking GDP growth helps assess economic development trends and inform policy decisions.
During a recession, banks typically increase their holdings of liquid assets to mitigate higher lending risks, ensuring financial stability during economic downturns Conversely, during periods of strong economic growth, banks usually reduce their liquid asset reserves to expand lending capacity and capitalize on emerging opportunities This strategic shift helps banks balance risk management with profit maximization across different economic cycles.
Mobilization may decrease, leading to an increased funding gap and a rise in liquidity risk (Shen et al., 2009) Conversely, during periods of economic growth, enterprises tend to operate more effectively, resulting in greater financial resources and an improved ability to meet debt obligations This enhanced financial health subsequently increases the liquidity supply available to banks, supporting overall financial stability.
Inflation is typically measured by the growth rate of the Consumer Price Index (CPI) Low inflation levels contribute to a stable economic environment with less volatility, making it less risky for investors and consumers Conversely, high inflation can deteriorate the macroeconomic landscape, leading to reduced bank liquidity and increased economic instability (Vodova, 2011).
E MPIRICAL RESEARCH OVERVIEW
The study by Aspachs et al (2005) analyzes factors influencing the liquidity of 57 UK commercial banks from 1985 to 2003, identifying both internal and external determinants Internal factors, like Return on Equity (ROE), negatively impact bank liquidity, as higher asset holdings to meet liquidity needs typically reduce profitability Conversely, external factors such as central bank support significantly influence liquidity, with greater perceived support decreasing banks' incentive to hold liquid assets for profitable investments.
A study by Bunda & Desquilbet (2008) examined the relationship between liquidity risk and bank-specific characteristics across 1,308 banks in 36 developing countries from 1995 to 2004 The research aims to understand how exchange rate fluctuations impact the liquidity of commercial banks in these emerging markets Their findings highlight the significant influence of national exchange rate dynamics on bank liquidity, emphasizing the importance of currency stability for maintaining healthy banking sector liquidity in developing economies.
Research indicates that bank size, lending interest rates, and perceptions of a financial crisis negatively impact bank liquidity Conversely, factors such as equity ratio, inflation, and economic growth have a positive influence on maintaining liquidity levels These findings highlight the importance of managing these variables to ensure financial stability and liquidity in banking sectors.
Chung-Hua Shen et al (2009) analyzed bank liquidity risk and performance across 12 major economies, including Australia, Canada, France, Germany, Italy, Japan, Luxembourg, the Netherlands, Switzerland, Taiwan, the UK, and the USA, covering the period from 1994 to 2006 Their study employed the funding gap method to measure liquidity risk, considering variables such as total assets size, loans to total assets ratio, liquidity reserve to total assets ratio, equity to total capital ratio, provisions for credit risks, economic growth, and inflation The findings highlight the significant impact of these factors on the liquidity risk of commercial banks in the examined economies.
Vodova (2011) examined the determinants of bank liquidity in Czech commercial banks from 2001 to 2009, utilizing multiple coefficients for a comprehensive and objective assessment The study highlights the significant impact of macroeconomic factors, particularly the global financial crisis, inflation rate, and economic growth (GDP), which negatively affected bank liquidity Additionally, the research reveals a positive correlation between liquidity and the capital adequacy ratio as well as interbank lending rates, emphasizing the importance of both internal bank capital and market conditions in liquidity management.
Bonfim & Kim (2012), with the topic "Liquidity risk in banking: Is there herding?" studied the impact of internal and external factors on the liquidity risk of the
This study analyzes the 500 largest banks across 43 countries in Europe and North America, focusing primarily on major banks in Canada, France, the USA, the UK, the Netherlands, Germany, Italy, and Russia between 2002 and 2009 The research compares two distinct periods: before and during the global economic crisis Findings reveal that, alongside internal bank factors, external macroeconomic influences significantly impact bank performance and stability during these periods.
18 liquidity risk, which banks often ignore Therefore, to manage liquidity risk well, banks need to pay attention to both internal and external factors
Moussa (2015) examined the determinants of commercial bank liquidity in Tunisia using a sample of 18 banks from 2000 to 2020 The study found that higher return on equity and GDP growth positively influence bank liquidity, indicating that profitability and economic expansion boost banks’ ability to maintain liquidity Conversely, larger bank size, a higher ratio of equity to total assets, and increased inflation rates were identified as negative factors affecting bank liquidity, highlighting the importance of these variables in liquidity management.
Ahmad and Rasool (2017) conducted an empirical study on the determinants of liquidity in commercial banks They analyzed a sample of 31 listed commercial and state-owned banks out of a total of 37 banks in Pakistan Their research provides valuable insights into the factors influencing bank liquidity in the Pakistani banking sector.
Between 2005 and 2014, regression analysis revealed that the ratio of equity to total assets (CAP) and economic growth rate (GDP) positively influence bank liquidity, indicating that higher capital adequacy and favorable economic conditions enhance liquidity levels Conversely, total asset size (SIZE) was found to have a negative impact on bank liquidity, suggesting that larger banks may face challenges in maintaining sufficient liquidity during this period.
In addition, the return on equity or inflation rate showed no impact on liquidity
Research indicates that liquidity risk in Vietnam's commercial banking system is influenced by both internal and external factors Trương Quang Thông (2013) found that liquidity risk, measured by the funding gap, depends on internal variables such as equity-to-asset ratio, bank size, and liquidity reserves, as well as external macroeconomic factors like inflation and GDP growth Similarly, Đặng Văn Dân (2015) analyzed 15 banks from 2007 to 2014 and identified bank size as a significant factor affecting liquidity risk, with funding gap remaining a key measure These studies highlight that effective management of internal financial ratios and awareness of macroeconomic conditions are crucial for mitigating liquidity risks in Vietnam’s banking sector.
The analysis reveals that the loan-to-total assets ratio has a positive relationship with the liquidity gap, indicating that higher loan proportions may increase liquidity risks In contrast, bank size shows a negative correlation with the liquidity gap, suggesting larger banks tend to maintain more balanced liquidity positions However, variables such as equity-to-total assets, ROE, GDP, and inflation are not statistically significant in influencing the liquidity gap, highlighting the importance of specific financial ratios over macroeconomic factors in liquidity management These findings provide insights into how bank-specific variables impact liquidity risk in the financial sector.
Vũ Thị Hồng (2015) experimented on 37 Vietnamese commercial banks from
From 2006 to 2011, the study demonstrates that the equity to assets ratio, non-performing loan ratio, and return on equity positively influence bank liquidity, while the loan-to-deposit ratio (LDR) has a negative impact No significant correlation was identified between the credit risk provision ratio, bank size, and liquidity The study assesses bank liquidity using the Liquidity assets to total short-term mobilized capital (L2) index.
Numerous international studies have identified diverse factors influencing the liquidity of commercial banks, varying across countries and time periods These differences lead to distinct policy implications that are often not directly applicable to Vietnamese commercial banks.
Most studies on bank liquidity in Vietnam focus on internal factors within banks, often neglecting external influences, and many of these studies were conducted before 2019, with limited updates on data from 2020-2021 In the post-COVID-19 era, characterized by economic volatility and record-high inflation worldwide, the liquidity challenges faced by commercial banks require urgent and increased attention from researchers and policymakers.
This chapter establishes the essential theoretical foundation for analyzing bank liquidity, enabling a comprehensive understanding of how various factors influence the liquidity of Vietnamese commercial banks It provides the groundwork for developing a research model in Chapter 3, which examines the specific impact of these factors on bank liquidity.
RESEARCH MODEL
A NALYSIS PROCESS
This study investigates the impact direction and magnitude of factors influencing the liquidity of 25 Vietnamese commercial banks from 2012 to 2021 The research follows a systematic process outlined in the accompanying figure, providing insights into key determinants of bank liquidity within this period.
Summary of the theoretical basis and empirical evidence
Determining the research sample, processing research data
Selecting methods and determining research results
No Check for model defects
Discussing, concluding, and providing policy implications
Step 1 : Review the theoretical basis and related previous studies in Vietnam and other countries, then discuss previous studies to identify research gaps and design directions for the research model
Step 2 : Based on the theoretical basis and empirical evidence, the thesis designs a research model, predicts regression equations, explains variables, and builds research hypotheses
Step 3 : Determine the research sample suitable for the research objectives as well as the object and scope of the research, then collect and process data according to the research model in step 2
Step 4: Identify methodology with specific analysis and estimation techniques: descriptive statistics, correlation analysis, and regression analysis of panel data according to OLS, FEM, and REM
Step 5 : Test the research hypotheses, can use F-test or t-test with a significance level of 1%, 5%, or 10% to identify statistically significant independent variables to explain the dependent variable; at the same time, compare the two models Pooled OLS and REM by F test with hypothesis H0: Selection of Pooled OLS model; use Hausman test to compare between 2 models FEM and REM with hypothesis H0: Select REM model, then choose the most suitable model
Step 6 : Carry out testing of model defects, including multicollinearity, autocorrelation, and variable variance; if these defects are not present, then combine with step 5 to perform step 7; if there is one of these defects, it will be solved by GLS method as well as overcome the phenomenon of endogenous variables occurring in the study, and at the same time test the research hypotheses in section 5 and move to step
Step 7 : This is the final step of the process based on the regression results; the topic conducts discussions, draws conclusions, and makes relevant suggestions and policy implications for answering the research questions as well as solving the research objectives set out
S AMPLES AND RESEARCH DATA
The research is conducted based on secondary data collected from audited financial statements and related documents from 2012 to 2021 of 25 commercial banks in Vietnam
This study utilizes secondary data to analyze the impact of micro- and macro-factors on commercial banks in Vietnam, covering the period from 2012 to 2021 Micro-factor data, including dependent and independent variables related to bank performance, are collected from audited financial statements of 25 listed commercial banks Meanwhile, macro-factor data are sourced from official organizations to ensure reliability and accuracy This comprehensive data collection allows for a robust analysis of the influence of various internal and external factors on the banking sector in Vietnam.
The data source for the dependent variable and the independent variables in the group of micro factors belongs to commercial banks: VietstockFinance
Data sources for the independent variables in the group of macro factors: General Statistics Office (GSO) and World Bank
This study analyzes the factors influencing the liquidity of commercial banks in Vietnam using panel data The analysis leverages Excel and Stata 16.0 software to ensure accurate and comprehensive results Our findings highlight key determinants of bank liquidity, providing valuable insights for financial policymakers and banking stakeholders seeking to enhance financial stability.
M ETHODOLOGY
Qualitative research methods are essential for exploring and analyzing the fundamental theories of liquidity and understanding the factors that influence it These methods also enable a comprehensive review of previous studies conducted in Vietnam and other countries on bank liquidity determinants Additionally, qualitative approaches assist in designing research models, formulating and interpreting hypotheses related to independent and dependent variables, and discussing research findings Moreover, they support drawing meaningful conclusions and providing relevant suggestions and recommendations to improve commercial bank liquidity management.
Quantitative research methods are employed to analyze the influencing trends and the impact levels of factors affecting the liquidity of Vietnamese commercial banks These methods utilize specific technical approaches to accurately evaluate and interpret the data, providing valuable insights into the key determinants of liquidity in Vietnam's banking sector.
Descriptive statistics offer essential insights into the variables within the research model, highlighting key indicators such as mean, minimum, maximum, standard deviation, and the number of observations These metrics provide a comprehensive overview of data distribution and variability, facilitating a clearer understanding of the sample characteristics and supporting accurate interpretation of research results.
Step 2: Analyzing the correlation coefficient matrix
Correlation matrix analysis is a vital tool for examining the relationships between independent variables, the dependent variable, and among the independent variables themselves High correlations (coefficients greater than 0.8) between independent variables indicate the presence of multicollinearity, which can impact model accuracy To address multicollinearity, strategies include removing highly correlated variables, applying principal components analysis, or opting to do nothing if deemed appropriate.
Step 3: Regression analysis of panel data
Using multivariable regression estimation to determine the relationship and level of impact of the independent variables on the dependent variable The estimation methods used are:
+ Pooled Ordinary Least Square (Pooled OLS)
At the same time, the tests of Breusch-Pagan (1980), Hausman (1978), and Likelihood Ratio are used to select a suitable model between the pair of estimator models
Step 4: Test the heteroskedasticity and autocorrelation of the selected model Step 5 : Select the model and analyze and comment
R ESEARCH MODEL AND HYPOTHESIS
Based on the authors' research detailed in Chapter 2, the study assesses bank liquidity through liquidity ratio measurement techniques Additionally, the research incorporates both micro-level factors within banks and macroeconomic variables in the proposed model to examine their effects on commercial bank liquidity Consequently, the thesis proposes a comprehensive research model modeled by the following equation to analyze these impacts effectively.
L1 it = 0 + 1 SIZE it + 2 CAP it + 3 LDR it + 4 ROE it + 5 NPL it + 6 GDP t + 7 INF t + it
L1 it : Liquidity ratios of banks i year t
SIZE it : Size of commercial bank i in year t
CAP it : The ratio of equity in total assets of commercial bank i in year t
LDR it : Loan-to-deposit ratio of commercial banks in year t
ROE it : Return on equity of commercial bank i in year t
NPL it : Non-performing loan ratio of commercial bank i in year t
GDP t : Economic growth rate in year t
INF t : Inflation rate in year t
With i, t corresponds to the bank and the survey year; 0 is the intercept factor ; 1
- 7 are the slopes of the independent variables, and it is the statistical residual
3.4.2 Description of variables and hypotheses
Table 3.1: Description of variables in the research model
1 The liquidity ratio L1 Liquid assets/Total assets
2 Bank size SIZE Logarithm (Total assets)
3 Equity ratio CAP Total equity/ Total assets
4 Loan-to-deposit ratio LDR Total loans/Total mobilized capital
5 Return on Equity ROE Earning after tax/ Total equity
6 Non-performing loan ratio NPL Non-performing loan/Total loans
7 Economic growth GDP General Statistics Office
8 Inflation rate INF General Statistics Office
Vodova's (2011) and Bunda & Desquilbet's (2008) studies present mixed results regarding bank size and liquidity However, as bank size continues to grow, there is an expected positive relationship between bank size and liquidity This expectation aligns with Signaling Theory, which suggests that larger banks may signal greater stability and efficiency, fostering investor confidence Additionally, this trend supports a positive outlook for the development and expansion of the banking industry in Vietnam's future.
H1: The size of the bank has a positive effect on liquidity
The capital adequacy ratio is a key formula used to assess a bank's financial health and liquidity position A higher ratio indicates that the bank has sufficient capital to ensure stability and reduce liquidity risk Numerous empirical studies, including Vodova (2011), Vũ Thị Hồng (2015), and Aspachs et al (2005), have demonstrated that a strong capital adequacy ratio enhances bank security Consequently, this study hypothesizes a positive relationship between the equity ratio and the liquidity of commercial banks, emphasizing the importance of capital adequacy for financial stability.
H2: Equity ratio has a positive effect on liquidity
Loan-to-deposit ratio (LDR)
A high ratio indicates increased risks of insolvency and illiquidity, as excessive lending surpasses the bank's mobilized capital, leading to liquidity challenges at maturity Rapid credit growth typically results in a rise in illiquid assets, further reducing overall liquidity According to Aspachs et al (2005) and Vũ Thị Hồng (2015), there is evidence of a negative relationship between this ratio and liquidity, and this study anticipates confirming the same negative correlation based on previous research findings.
H3: The loan-to-deposit ratio has a negative effect on liquidity
The bank’s return on equity (ROE) reflects management’s efficiency in utilizing shareholders’ equity to generate profits Typically, banks earn most of their profits from traditional activities like interest rate differentials between lending and capital mobilization Consequently, holding more assets to meet liquidity needs reduces a bank’s profit-generating ability, indicating a negative relationship between liquidity and profitability In Vietnamese commercial banks, profits primarily come from credit activities, where higher profits often mean lower levels of liquid assets Based on theoretical, empirical, and practical insights, it is hypothesized that there is a negative relationship between return on equity and bank liquidity levels, suggesting that increased liquidity may reduce profitability.
H4: Return on equity has a negative effect on liquidity
Non-performing loan ratio (NPL)
Non-performing loans (NPLs) are loans to customers facing significant challenges in repaying principal and interest, typically falling within debt groups 3 to 5 A higher NPL ratio compared to the industry average indicates difficulties in managing loan quality, which can restrict the bank’s lending activities This restriction may lead to increased bank liquidity Consequently, there is an expected positive relationship between the Loan-to-Deposit Ratio (LDR) and bank liquidity, highlighting the impact of non-performing loans on financial stability.
H5: Non-performing loan ratio has a positive impact on liquidity
During an economic recession, banks tend to increase their liquidity reserves to mitigate heightened lending risks, whereas in periods of economic growth, they reduce liquidity to expand lending activities Vodova (2013) and Moussa (2015) identified a positive correlation between economic downturns and higher bank liquidity, highlighting the importance of maintaining adequate reserves during challenging financial periods Conversely, Bunda and colleagues emphasize that during economic expansion, banks typically decrease liquidity levels to capitalize on growth opportunities and maximize profitability This dynamic adjustment of liquidity reserves underscores banks' strategic responses to varying economic conditions, impacting overall financial stability.
Desquilbet (2008), Aspachs et al (2005) found a negative correlation In the study, the author expects a negative relationship between GDP growth and liquidity
H6: Economic growth has a negative effect on liquidity
The inflation rate is measured by the growth of the consumer price index (CPI), which is essential for understanding economic stability Stable inflation supports sustainable economic development, while rising inflation prompts individuals to withdraw bank deposits and seek alternative investments like gold and foreign currencies to hedge against currency devaluation This increased demand for alternative assets forces banks to hold larger amounts of cash to meet customer needs Consequently, there is a hypothesized negative relationship between inflation rate and liquidity, as higher inflation tends to reduce bank liquidity.
H7: The inflation rate has a negative effect on liquidity
Chapter 3 has shown data and research methods to build research models At the same time, it shows the expected impact of independent variables on the liquidity of Vietnamese commercial banks based on theory, theoretical basis, and previous empirical research results of domestic and foreign topics In addition, chapter 3 has also outlined the tests that will be used in the research model The content presented in chapter 4 will be the results obtained from the application of this research method
RESEARCH RESULTS
D ESCRIPTIVE STATISTICS
The results of the descriptive statistics of the measured variables in the regression model are presented in the table below:
Source: Data processing results through Stata 16.0
Table 4 confirms that all variables in the research model are based on balanced panel data, comprising 250 observations from 25 commercial banks over a decade The descriptive statistics for each variable provide valuable insights into the data distribution and variability, ensuring the robustness of the analysis This comprehensive dataset enhances the reliability of the study findings related to banking performance and financial metrics.
The liquidity variable (L1) is assessed by the ratio of Total Liquidity Assets to Total Assets, with an average value of 17.30% and a standard deviation of 7.68%, indicating variability in bank liquidity levels Notably, the bank with the highest liquidity ratio of 52.11% belonged to SSB in 2012, highlighting significant differences in liquidity management among banks.
32 lowest liquidity ratio is STB, with 4.52% in 2017 Vietnamese commercial banks will have the liquidity that changes depending on economic situations in each period
The variable bank size (SIZE) is measured by taking the natural logarithm of total bank assets Analysis of 25 Vietnamese commercial banks from 2012 to 2021 reveals that BID, with total assets of 1,761,696 billion VND in 2021, is the largest bank by asset size Conversely, SGB had the smallest asset size, with VND 14,685 billion in 2013 In 2021, BID, VCB, and CTG ranked as the top three banks in terms of size and exhibited the highest asset growth rates.
The CAP (Capital Adequacy Ratio) is calculated as Total Equity divided by Total Assets, with a mean of 9% and a standard deviation of 3.61% In 2017, BID had the lowest equity ratio at 4.06%, indicating its relative financial vulnerability, while SGB bank boasted the highest equity ratio at 24.19%, reflecting a stronger capital position.
The Loan to Deposit Ratio (LDR) averages 66.63%, remaining below the State Bank's maximum limit of 85% as per the latest circular In 2012, some banks, such as SGB, had a high LDR of 98.45%, indicating aggressive lending practices, while others like SSB maintained a low LDR of 24.73%, reflecting more conservative management The variability in LDR levels is influenced by individual bank management policies concerning assets and capital allocation.
The bank's Return on equity (ROE) shows a mean of 9.63% and a standard deviation of 6.57% In which, there is VIB bank with the highest ROE of 26.39% in
In 2021, NVB Bank recorded the lowest ROE of just 0.03% in 2020, highlighting its minimal profitability The bank's earnings continue to rely primarily on traditional banking activities, specifically the interest rate differential between lending and mobilizing capital This reliance underscores the importance of interest rate margins in driving its financial performance.
The average non-performing loan (NPL) ratio over the period 2012-2021 is 2.13%, with a standard deviation of 1.47%, indicating moderate variability Among the examined banks, BID Bank recorded the lowest NPL ratio at just 0.001% in 2021, reflecting excellent credit risk management Conversely, NAB Bank experienced the highest non-performing loan ratio at 9.19% in 2021, highlighting potential concerns in its loan portfolio performance.
Vietnam's economic growth rate averaged 5.59% from 2012 to 2019, indicating relatively stable economic development during this period However, between 2019 and 2021, the growth rate declined significantly due to the economic shutdown caused by the COVID-19 pandemic This slowdown highlights the pandemic's impact on Vietnam's economy, resulting in the lowest growth figures in recent years.
GDP was 2.58% in 2021, and the highest in 2018, with 7.08% before the covid pandemic
The average inflation rate (INF) variable for the period 2012-2021 is 3.8%, with a standard deviation of 2.3% The highest volatile inflation rate was 9.095% in 2012, and the lowest was 0.63% in 2015.
R ESEARCH RESULTS
L1 SIZE CAP LDR ROE NPL GDP INF
Source: Data processing results through Stata 16.0
Analysis of the correlation matrix in Table 4.2 indicates that key independent variables such as the equity ratio (CAP) and inflation rate (INF) positively influence bank liquidity (L1) Conversely, variables like bank size (SIZE), loan-to-deposit ratio (LDR), return on equity (ROE), non-performing loans (NPL), and economic growth rate (GDP) negatively impact bank liquidity, highlighting their inverse relationship.
The study reveals a negative correlation between bank size (independent variable SIZE) and bank liquidity (dependent variable L1), with a coefficient of -0.1708 This indicates that as bank size increases, the bank's liquidity tends to decrease Consequently, larger banks may face challenges in maintaining high liquidity levels, highlighting the inverse relationship between these two key financial metrics. -**Sponsor**Need to refine your article and boost its SEO? Let's focus on clarity and impact A key takeaway is that a bank's size negatively impacts its liquidity, with a correlation of -0.1708, indicating that as size increases, liquidity decreases—making this point clear and concise can significantly improve readability and search engine optimization To diversify your investment, see [Freedom24 ETF - English](https://pollinations.ai/redirect-nexad/k1nPLYEE?user_id=983577), where you can invest in ETFs with Freedom24 This will allow you to mitigate risks by tracking a variety of industries, companies, commodities, or indices to expand your portfolio’s reach.
The independent variable CAP (Capital Adequacy Ratio) shows a positive correlation of 0.0010 with the dependent variable L1, indicating that higher equity ratios are associated with increased bank liquidity This suggests that an improvement in a bank's capital adequacy positively impacts its liquidity levels.
The study reveals a significant negative correlation of -0.5572 between the independent variable LDR (Loan-to-Deposit Ratio) and the dependent variable L1, indicating that an increase in the loan-to-deposit ratio is associated with a decrease in bank liquidity This negative relationship suggests that as banks extend more loans relative to their deposits, their liquidity levels tend to decline, highlighting the impact of high LDRs on bank financial stability.
The study reveals that the independent variable Return on Equity (ROE) has a negative correlation of -0.0782 with the dependent variable L1, indicating that higher ROE is associated with decreased bank liquidity This suggests that an increase in ROE negatively impacts the bank’s liquidity position, highlighting an inverse relationship between profitability and liquidity management.
The study reveals a negative correlation between the independent variable NPL (Non-Performing Loans) and the dependent variable L1, with a coefficient of -0.0183 This indicates that an increase in the non-performing loan ratio adversely affects the bank's liquidity Specifically, as the non-performing loan ratio rises, the bank's liquidity tends to decrease, highlighting the negative impact of rising NPLs on financial stability.
The independent variable GDP has a negative correlation with the dependent variable L1 of -0.1268, showing that the economic growth rate and the bank’s liquidity
35 have a negative relationship When the economic growth rate increases, the liquidity ability of the bank will decrease accordingly
The independent variable INF, representing the inflation rate, has a positive correlation of 0.2987 with the dependent variable L1, which measures the bank's liquidity This indicates that higher inflation rates are associated with increased bank liquidity Consequently, an upward trend in inflation is likely to lead to a rise in the bank's liquidity, highlighting a positive relationship between these two financial indicators.
Source: Data processing results through Stata 16.0
The analysis presented in Table 4.3 indicates that the mean Variance Inflation Factor (VIF) for all independent variables in the model is below 10, suggesting that multicollinearity is not a concern This confirms that the variables are sufficiently independent, ensuring the reliability and validity of the regression results.
R EGRESSION RESULTS OF THE RESEARCH MODEL
Table 4.4: Regression results of models
Coefficient t-Statistic Coefficient t-Statistic Coefficient t-Statistic
Note: *** corresponds to the 1% significance level, ** corresponds to the 5% significance level, and * corresponds to the 10% significance level
Source: Data processing results through Stata 16.0
Comparison of regression results between two models, FEM and REM
To identify the most suitable model for the study, the author employs the Hausman test to compare Fixed Effects (FEM) and Random Effects (REM) models The null hypothesis (H0) assumes that selecting the REM model is appropriate, guiding the decision-making process for optimal model selection.
Table 4.6: Hausman test Test: H 0: difference in coefficients not systematic chi2(7) = (b-B)'[(V_b-V_B) ^ (-1)] (b-B) = 33.77
Source: Data processing results through Stata 16.0
With the significance level = 5%, Prob>chi2 = 0.0000 < 5%, thus rejecting hypothesis H 0 In other words, the author chooses the FEM model as the more suitable model
Conclusion: After comparing three models, Pooled OLS, FEM, and REM, the author chooses the FEM model to determine the factors influencing the liquidity of Vietnamese commercial banks.
Defect tests
Implement the Modified Wald test in the FEM model with the following hypothesis:
Hypothesis H 0: there is no heteroskedasticity
Source: Data processing results through Stata 16.0
With the significance level = 5%, Prob>Chi2 = 0.0000 < 5%, thus rejecting hypothesis H 0 In other words, there is heteroskedasticity phenomenon
Implement the Wooldridge test in the FEM model with the following hypothesis: Hypothesis H 0 : there is no autocorrelation
Table 4.8: Wooldridge test Hypothesis H 0 : there is no autocorrelation
Source: Data processing results through Stata 16.0
With the significance level = 5%, Prob>F = 0.0000 < 5%, thus rejecting hypothesis H 0 In other words, there is autocorrelation phenomenon
Conclusion: Through the above tests, it can be seen that the research model both has heteroskedasticity and autocorrelation phenomenon.
Final model
The test results indicate the presence of both heteroskedasticity and autocorrelation in the model, which can impact its reliability To address these issues, the author employs the Feasible Generalized Least Squares (FGLS) method, ensuring accurate and robust estimation By using the FGLS model, the analysis effectively overcomes the problems of heteroskedasticity and autocorrelation, leading to a more reliable final model.
Table 4.9: Regression result of FGLS
Note: *** corresponds to the 1% significance level, ** corresponds to the 5% significance level, and * corresponds to the 10% significance level
Source: Data processing results through Stata 16.0
With the dependent variable L1, after using the Feasible Generalized Least
Squares (FGLS) method to overcome autocorrelation and heteroskedasticity
40 phenomenon, with the significance level = 5% (Prob>Chi2 = 0.0000), the regression model can be written as follows:
L1 it = 0.3273 – 0.3558LDR it + 0.1558ROE it + 0.3753INF t + it
S UMMARY
Table 4.10: Summary of expected hypothesis and experimental results Variable Expected hypothesis Result
SIZE Positive Positive, no statistical significance
CAP Positive Positive, no statistical significance
LDR Negative Negative, 1% significance level
ROE Negative Positive, 5% significance level
NPL Positive Negative, no statistical significance
GDP Negative Negative, no statistical significance
INF Negative Positive, 1% significance level
Source: Data processing results through Stata 16.0
Bank size is measured by the natural logarithm of total assets, which helps to narrow differences in actual asset data among banks The analysis indicates that there is no significant difference in bank sizes when using this calculation Additionally, the study finds a positive relationship between bank size and bank liquidity; however, this correlation is not statistically significant.
In Vietnam, leading commercial banks like BIDV, Vietinbank, and Vietcombank have the largest total assets; however, they do not possess the highest liquidity reserve ratios Typically, banks with superior liquidity reserve ratios are smaller institutions or specialized banks that prioritize maintaining higher cash reserves to ensure financial stability and compliance with banking regulations.
A group of 41 medium-sized banks, particularly large commercial banks with significant state share capital, are poised to strengthen their market position, prestige, and ability to access capital easily in the interbank market Consequently, these larger banks often have less incentive to increase their holdings of highly liquid assets In contrast, medium-sized banks with limited support from the State Bank of Vietnam (SBV) face greater liquidity management challenges, leading them to maintain higher liquidity reserve ratios to ensure financial stability.
The equity ratio, calculated as total equity divided by total assets, plays a crucial role in assessing a company's financial stability Research indicates a positive relationship between equity and liquidity ratios, suggesting that higher equity levels may be associated with improved liquidity However, this correlation is not statistically significant, highlighting the need for further analysis to confirm the strength of this relationship Understanding these financial metrics can help investors and stakeholders evaluate a company's overall financial health and stability.
Research by Vodova (2011) and Aspachs et al (2005) highlights that higher bank equity ratios are associated with lower debt burdens and increased liquidity, emphasizing the importance of strong capital adequacy for financial stability During the 2008 global financial crisis, Vietnamese commercial banks with low equity were more vulnerable to economic shocks, evidenced by weak liquidity levels To enhance bank resilience, the State Bank of Vietnam has progressively increased the minimum equity requirement to 3,000 billion VND, reinforcing the critical role of adequate equity in safeguarding banks against financial crises.
4.4.3 Loan-to-deposit ratio (LDR)
Research indicates a significant negative correlation between the loan-to-deposit ratio and bank liquidity; as the loan-to-deposit ratio increases, the bank’s liquidity decreases This finding underscores that higher loan-to-deposit ratios can put financial institutions at greater liquidity risk, highlighting the importance of maintaining balanced lending and deposit practices for optimal liquidity management Understanding this relationship is crucial for banking stability and effective financial planning.
The State Bank of Vietnam has recently issued a circular setting the loan-to-deposit ratio for commercial banks at 85%, aiming to promote financial stability A higher loan-to-deposit ratio indicates that banks are lending more relative to their mobilized deposits, increasing credit expansion However, during economic crises or unpredictable market fluctuations, maintaining this ratio can pose challenges in mobilizing affordable capital and ensuring liquidity.
High liquidity levels are crucial for banks, as short-term capital constitutes a significant portion of total mobilized funds Increased lending activity reduces available funding sources for liquid assets, leading to a notable decline in the bank’s liquidity position Effective management of short-term capital is essential to maintain financial stability and ensure sufficient liquidity for ongoing operations.
Return on equity has a positive relationship with liquidity and is statistically significant
Research by Moussa (2015), Bunda & Desquilbet (2008), and Vũ Thị Hồng (2015) indicate a positive relationship between Return on Equity (ROE) and liquidity When a bank achieves strong profitability, it enhances its liquidity position, boosts its reputation in the financial market, and facilitates easier, low-cost capital raising from external sources This linkage underscores the importance of profitability in strengthening a bank's overall financial stability and market confidence.
4.4.5 Non-performing loan ratio (NPL)
Based on the research results, the non-performing loan ratio has a negative relationship with liquidity However, this relationship is not statistically significant
When a customer fails to repay a loan, the bank incurs capital loss and must set aside provisions, which reduces cash reserves and leads to a decline in total assets A high non-performing loan ratio can also undermine depositor confidence, prompting withdrawals and causing a significant decrease in the bank’s liquidity.
According to the research results, economic growth negatively affects liquidity However, this relationship is not statistically significant
This can be explained by the fact that in each period of economic growth or recession, the State Bank always has adjustment policies to control risks to the
43 economy Therefore, the economic growth rate may have a negligible impact on the liquidity of commercial banks in Vietnam
According to the research results, the inflation rate has a positive relationship with liquidity and is statistically significant
Research by Vodova (2011) and Trương Quang Thông (2013) indicates that rising inflation rates lead banks to tighten credit, reducing lending to control money circulation and curb inflation This reduction in lending causes an increase in bank liquidity, highlighting the inverse relationship between inflation and bank liquidity.
In chapter 4, the author has implemented a regression model with factors influencing the liquidity of commercial banks in Vietnam; the data source is taken from
Between 2012 and 2021, a study analyzed the performance of 25 Vietnamese commercial banks The research employed Stata 16.0 software to conduct comprehensive regression analyses, including Pooled OLS, Fixed Effects Model (FEM), Random Effects Model (REM), and Feasible Generalized Least Squares (FGLS) Various tests were performed to determine the most appropriate estimation model, ensuring accurate and reliable insights into the banking sector's dynamics in Vietnam.
The study reveals that bank size, equity ratio, return on equity, and inflation rate positively influence liquidity, while factors such as the loan deposit ratio, non-performing loan ratio, and economic growth rate negatively impact liquidity Among these, the loan-to-deposit ratio, return on equity, and inflation rate were found to be statistically significant These findings highlight the key determinants of liquidity in banking, underscoring the importance of these variables in financial stability and economic growth.
The results of chapter 4 are the basis for the author to draw conclusions and management implications in chapter 5
CONCLUSION AND POLICY IMPLICATIONS
C ONCLUSION
This study utilizes theoretical research, regression analysis of panel data, and data estimation of 25 Vietnamese commercial banks from 2012 to 2021 to identify the key factors influencing bank liquidity By analyzing this comprehensive dataset, the research provides valuable insights into the determinants of liquidity in Vietnamese commercial banks The findings address critical questions regarding how various financial and economic variables impact bank liquidity in Vietnam over the specified period This research contributes to a deeper understanding of liquidity management in Vietnamese banking, supporting better decision-making and policy development.
Question 1: What factors affect the liquidity of commercial banks in Vietnam?
This study investigates the key factors influencing the liquidity of Vietnamese commercial banks Although seven factors were initially hypothesized in Chapter 3, the research findings reveal that only three variables—Loan-to-Deposit Ratio (LDR), Return on Equity (ROE), and Inflation (INF)—significantly impact bank liquidity These results highlight the critical importance of LDR, ROE, and INF in understanding and managing liquidity risks within Vietnamese banking institutions.
Question 2: What is the impact level and direction of these factors on the liquidity of Vietnam's commercial banks?
Research indicates that a higher Loan Deposit Ratio (LDR) negatively impacts bank liquidity, with a significant reduction of 0.3558 units in liquidity for each 1-unit increase in LDR Conversely, Return on Equity (ROE) positively influences liquidity, where a 1-unit rise in ROE results in a 0.1558-unit increase in bank liquidity at a 5% significance level Additionally, the inflation rate has a significant positive effect on liquidity at the 1% level, indicating that higher inflation rates are associated with increased bank liquidity under constant conditions.
INF increases by 1 unit, the liquidity of banks increases by 0.3753 units
Question 3: What are suggestions that can manage the liquidity of Vietnamese commercial banks to meet both liquidity and profitability?
To answer this question, the topic will give suggestions and propose related policy implications presented in section 5.2.
P OLICY I MPLICATIONS
From the research results, the thesis has provided policy implications and solutions for the SBV and commercial banks in Vietnam to meet both liquidity management and effective profitability
Improving the ability to access capital
Banks must regularly reassess their relationship-building strategies with owners to ensure diversified sources of capital Establishing strong connections with key suppliers creates a vital liquidity buffer, supporting effective liquidity management during financial difficulties Maintaining these relationships is essential for ensuring financial stability and resilient capital structure.
Banks should establish policies to increase charter capital through share issuance and optimize the use of capital to support sustainable growth Additionally, issuing long-term convertible bonds provides a strategic method to access long-term funding without diluting ownership prior to conversion, while also reducing dividend tax liabilities.
Considering the policy of accumulating capital from retained earnings contributes to helping commercial banks increase their solid financial capacity, become more financially autonomous, and improve liquidity
Improving credit quality and controlling loans well
Strengthening the efficiency and effectiveness of banking inspection and supervision to ensure compliance with regulations on banking activities, especially
47 regulations on credit financing, debt classification, provisioning credit risk and restrictions on the safety of credit operations
Banks must prioritize responsible lending by avoiding aggressive sales tactics that lower lending standards and heighten credit risk Developing credit relationships with customers who have strong business backgrounds and stable financial positions is essential for managing risk Building a diversified loan portfolio across various industries and fields helps ensure loan recovery and reduces exposure to sector-specific downturns Distributing risks effectively through portfolio diversification in credit activities safeguards the bank's financial stability and promotes sustainable growth.
Improving operational and cost efficiency
Banks should offer a diverse range of credit products with flexible interest rates tailored to each customer segment and economic period, ensuring profitability and effective risk management Additionally, diversifying revenue streams through various products and services is essential to reduce dependency on credit activities, which often carry significant risk.
Enhancing operational efficiency begins with elevating the management level of the executive board to ensure strategic decision-making It is essential to assess and develop employees' professional capacities, fostering a skilled and adaptable workforce Regularly reviewing and controlling costs helps determine appropriate spending levels, while restructuring and reorganizing the operational framework can lead to significant cost savings and improved overall performance.
To enhance profitability, commercial banks should focus on diversifying their revenue streams by expanding non-credit activities and increasing non-interest income, particularly from service segments This can be achieved by actively promoting fee-based services such as insurance, financial consulting, asset management, and investment services Strengthening these areas will help banks build a more sustainable and resilient income base, aligning with industry best practices for growth and competitiveness.
5.2.2 For the State Bank of Vietnam
The State Bank of Vietnam (SBV) must coordinate with authorities to effectively control inflation, ensuring policy measures are suitable for current economic conditions It should actively and flexibly utilize monetary policy tools in tandem with fiscal policies to stabilize the economy Prioritizing the removal of obstacles for production and businesses, the SBV aims to develop the market, boost purchasing power, and promote increased consumption of goods to support sustainable economic growth.
Strengthening inspection and supervision of the banking system
The State Bank of Vietnam (SBV) must develop robust financial analysis and early warning systems to effectively monitor and mitigate systemic risks within the banking sector Ensuring a secure operating environment for commercial banks is essential, which can be achieved through stringent management, strict policies, and high control measures implemented by the SBV to prevent failure contagion across the financial system Additionally, the SBV should establish more detailed and tailored regulations for commercial banks, focusing on liquidity management, alongside conducting comprehensive inspections to enhance the overall stability and resilience of the banking system.
L IMITATIONS OF THE THESIS
Besides the obtained results, the study still has some limitations, as follows:
The research sample includes only 25 Vietnamese commercial banks from 2012 to 2021, which limits the overall comprehensiveness and accuracy of the findings for the entire Vietnamese banking system Additionally, the study focuses solely on domestic joint-stock commercial banks, excluding foreign banks, policy banks, and non-equitized banks such as Agribank, thereby affecting the objectivity of the results Furthermore, the research does not account for the varying impacts on different bank sizes, including small, medium, and large banks, which could influence the study's conclusions.
During the research process, it was identified that bank liquidity is influenced by various factors such as interest rates, exchange rates, money supply, and financial crises However, due to time constraints and data collection challenges from banks over the years, these factors were not included in this study.
The article highlights that the author solely relies on the L1 index (Total Liquid Assets/Total Assets) to assess the bank’s liquidity However, comprehensive liquidity evaluation should incorporate all four fundamental liquidity indicators, offering a more accurate and holistic picture of the bank’s financial health Relying on a single metric may limit the depth of analysis and overlook other critical aspects of liquidity management.
P ROPOSING DIRECTIONS FOR FURTHER RESEARCH
To enhance the comprehensiveness of the study, the research will incorporate a larger sample size, including banks with diverse characteristics beyond JSCBs, such as Agribank and foreign banks operating in Vietnam Additionally, banks will be classified by size to provide more detailed and nuanced insights These approaches aim to produce more objective and representative results that accurately reflect the overall banking industry in Vietnam.
This study examines not only traditional dependent variables influencing bank liquidity but also incorporates less-studied factors such as exchange rates, money supply, interest rates, and financial crises By including these variables, the research aims to provide a comprehensive understanding of the diverse factors impacting bank liquidity Future studies are expected to explore these elements from multiple perspectives, offering a broader analysis of the dynamics that affect bank liquidity in various economic contexts.
Building on the findings from Chapter 4, Chapter 5 offers key policy recommendations for managers of Vietnamese commercial banks to enhance liquidity and improve profitability The chapter also acknowledges the study's limitations, highlighting opportunities for future research in terms of expanded timeframes, broader geographical scope, and more comprehensive research topics These insights aim to guide banking managers in implementing effective strategies while inspiring further scholarly investigation in this field.
Các yếu tố ảnh hưởng đến thanh khoản ngân hàng thương mại cổ phần tại Việt Nam đã được nghiên cứu và phân tích trong các bài viết của Đặng Thị Quỳnh Anh & Trần Lê Mai Anh (2022) cũng như Đăng Văn Dân (2015) Trong đó, bài viết của Quỳnh Anh & Mai Anh tập trung vào các yếu tố tác động đến khả năng thanh toán của ngân hàng, như quản lý tài chính, quy định pháp lý và môi trường kinh tế Còn bài viết của Dân đề cập đến các nhân tố ảnh hưởng đến rủi ro thanh khoản và các biện pháp giảm thiểu rủi ro này trong lĩnh vực ngân hàng Việt Nam Ngoài ra, Nguyễn Văn Tiến (2015) cung cấp kiến thức nền tảng về nguyên lý và nghiệp vụ ngân hàng thương mại, tạo cơ sở cho việc hiểu rõ hơn về các yếu tố ảnh hưởng đến thanh khoản của ngân hàng Các tài liệu này đều nhấn mạnh tầm quan trọng của việc duy trì thanh khoản ổn định để đảm bảo hoạt động ngân hàng bền vững tại Việt Nam.
Bài viết của Phan Thị Mỹ H và Tống Lâ Vy (2019) phân tích các yếu tố ảnh hưởng đến rủi ro thanh khoản của hệ thống ngân hàng thương mại tại Việt Nam Nghiên cứu nhấn mạnh tầm quan trọng của các yếu tố như quản lý tín dụng, chính sách tiền tệ, và điều kiện kinh tế vĩ mô đối với khả năng thanh khoản ngân hàng Các yếu tố này đóng vai trò quyết định trong việc duy trì sự ổn định tài chính của các ngân hàng thương mại Việt Nam Kết quả nghiên cứu cung cấp cái nhìn tổng quan về các yếu tố rủi ro thanh khoản, từ đó đề xuất các giải pháp giảm thiểu rủi ro này, góp phần nâng cao hiệu quả hoạt động của hệ thống ngân hàng quốc gia.
Trương Quang Thông (2013) Các nhân tố tác động đến r i ro thanh khoản c a h thống NHTM Vi t Nam Tạp chí Phát triển Kinh tế, số 276, trang 50-62
Vũ Thị Hồng, (2015) Các yếu tố ảnh hưởng đến thanh hoản c a các ngân h ng thương i Vi t Nam Tạp Chí Phát Triển & Hội Nhập, Số 23 (33)
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Appendix A List of commercial banks in Vietnam in the research sample
1 ABB An Binh Commercial Joint Stock Bank
2 ACB Asia Commercial Joint Stock Bank
3 BAB Bac A Commercial Joint Stock Bank
4 BID Joint Stock Commercial Bank For Investment And Development
5 BVB Viet Capital Commercial Joint Stock Bank
6 CTG Vietnam Joint Stock Commercial Bank For Industry And Trade
7 EIB Joint Stock Vietnam Export Import Commercial Joint Stock
8 HDB Ho Chi Minh City Development Joint Stock Commercial Bank
9 KLB Kien Long Commercial Joint –Stock Bank
10 LPB Lienviet Post Joint Stock Commercial Bank
11 MBB Military Commercial Joint Stock Bank
12 MSB Maritime Commercial Joint Stock Bank
13 NAB Nam A Comercial Join Stock Bank
14 NVB National Citizen Commercial Joint Stock Bank
15 OCB Ocean Commercial Joint Stock Bank
16 PGB Petrolimex Group Commercial Joint Stock Bank
17 SGB Saigon Bank For Industry And Trade
18 SHB Saigon –Hanoi Commercial Joint Stock Bank
19 SSB Southeast Asia Commercial Joint Stock Bank
20 STB Thuong Tin Commercial Joint Stock Bank
21 TCB Vietnam Technology And Commercial Joint Stock
22 TPB Tien Phongcommercial Joint Stock Bank
23 VCB Joint Stock Commercial Bank For Foreign Trade Of Vietnam
24 VIB Vietnam International Commercial Joint Stock Bank
25 VPB Vietnam Prosperity Joint Stock Commercial Bank
TICKER YEAR L1 SIZE CAP LDR ROE NPL GDP INF
Appendix C Regression results with Stata 16.0
Pooled-OLS, FEM, REM regression