Khóa luận tốt nghiệp Ngân hàng: The Influence of asset-liability management on profitability of Vietnam listed commercial banks

Nasif & Shubiri 2010 demonstrated in their study in Jordan the significant positive relationship between internal ALM factors and bank profitability, emphasizing the role of asset and li

BANKING ACADEMY OF VIETNAM

BANKING FACULTY -

GRADUATION THESIS

TOPIC:

THE INFLUENCE OF ASSET-LIABILITY MANAGEMENT

ON PROFITABILITY OF VIETNAM LISTED COMMERCIAL BANKS

Student name: Pham Ngoc Binh

Class: K22CLCA Faculty: Banking Student Code: 22A4011424 Supervisor & Instructor: Assoc Prof PhD Nguyen Thuy Duong

Hanoi 2024

Student

Pham Ngoc Binh

ACKNOWLEDGEMENTS

Throughout the course of study and training at the Banking Academy, the professors have been dedicated in teaching, imparting fundamental knowledge in the field to the author, providing a solid foundation for future professional endeavors

During the research and thesis writing process, I have received enthusiastic support from friends, colleagues, and the Academy The author would like to express gratitude to Assoc Prof PhD Nguyen Thuy Duong, who provided direct guidance, meticulous instructions, guidance, and facilitated the most favorable conditions throughout the research and completion of the thesis

The author sincerely thanks friends and colleagues for their encouragement and assistance in providing materials, useful documents for students to serve the research topic of this thesis

Thank you sincerely!

Student

Pham Ngoc Binh

ABSTRACT 5

1.1.3 The influence of Asset-liability management on Profitability of

a) Overview of approaches to assessing the impact of Asset-liability

b) Return on Assets (ROA) 30

ABSTRACT

The commercial banking sector plays a pivotal role in the economy, managing

deposits and allocating credit across sectors (Mishkin, 2007; Fama, 1980) Effective

asset and liability management is critical for banks to maximize profitability, especially

during financial crises (Tektas et al., 2005) This involves balancing costs from

liabilities, like client deposits, with income from assets such as loans Strategic asset

and liability management is essential for banking harmony, performance enhancement,

and profit maximization (Lileikienė, 2008) Bank profitability is crucial for both

individual institutions and the overall sector health (Onaolapo & Adegoke, 2020; Tee,

2017; Belete, 2013) Shrestha (2016) emphasizes profitability's dual role in fostering

competition and stability while cautioning against potential market distortions

Asset-liability management stands out as a significant determinant among various factors

influencing profitability

Currently, banks in Vietnam have established comprehensive systems of

policies, procedures, guidelines, and limits to identify, measure, monitor, and control

risks in accordance with international frameworks such as Basel II and towards meeting

Basel III requirements, as well as complying with State Bank of Vietnam regulations

outlined in Circular 13/2018/TT-NHNN Specific timely actions such as implementing

risk management tools, setting limits on interest rate risk on bank books in governance

activities, and considering the economic value of shareholders' equity, as well as

utilizing appropriate derivative instruments to mitigate the negative impact of interest

rate fluctuations, are being actively pursued by banks

This study investigates the potential relationship between ALM practices and

banks' profitability It focuses on 18 listed Vietnam commercial banks in HOSE from

2013 to 2023 The analysis measure profitability by ROE that reveals a positive

correlation between bank asset management and profitability, whereas liability

management shows a negative influence Descriptive analysis provides insights into the

sample, while the GLS regression method is employed to address any issues identified

in model suitability Overall, the empirical findings contribute valuable insights into the

interplay between profitability and ALM, considering both bank-specific factors and

macroeconomic variables These findings are pertinent for internal management, aiding

in the development and enhancement of operational efficiency, and informing future

adoption of Basel II, III frameworks, and compliance with Circular 13/2018/TT-NHNN

LIST OF ACRONYMS

SCA Statistical Cost Accounting model

SME Small and Medium-sized Enterprises

LIST OF TABLES

Figure 1 Research process

Table 1 List of commercial banks in sample

Table 2 Variables description

Table 3 Descriptive statistics

Table 4 Pearson's correlation test

Table 5 Variance Inflation Factor test

Table 6 The Pooled OLS, Fixed and Random Effect Regression Model Table 7 Breusch & Pagan Lagrangian multiplier test for random effects

Table 9 Modified Wald test for groupwise heteroskedasticity in fixed effect

regression model Table 10 Wooldridge test for autocorrelation in panel data

Table 11 Cross-sectional time-series FGLS regression

Table 12 Variables description & Results relationship with profitability

INTRODUCTION

1 Background of the thesis

The commercial banking sector plays a crucial role in the economy by managing deposits and allocating credit across different sectors Mishkin (2007) outlines how commercial banks offer a range of banking services and raise funds through various deposit types Fama (1980) describes banks' fundamental function of accepting deposits

as liabilities and extending loans as assets These liabilities mainly include current, savings, and fixed deposits, along with shareholder equity, while assets consist of investments, loans, and advances Effective asset and liability management is crucial for banks to maximize profitability, especially during financial crises Tektas et al (2005) This management involves balancing costs incurred on liabilities, such as client deposits, with income generated from assets, like loans Key objectives for banks include profit maximization, risk mitigation, liquidity and capital adequacy, and market share expansion However, challenges arise from liquidity issues with credit assets during economic downturns and pressures from competition and fluctuating interest and exchange rates Strategic asset and liability management, as advocated by Lileikienė (2008), is essential for achieving banking harmony, enhancing performance, and realizing profit maximization and desired liquidity preferences

Commercial banks play a crucial role in the economic development of nations, acting as catalysts for growth by fostering saving habits and mobilizing funds from households and businesses across wide geographical regions (Ayadi et al., 2015; Goodhart, 2004) These funds are directed towards productive endeavors in agriculture, industry, and trade, driving economic expansion Challenges within the banking system can significantly impact a nation's economic health and stability Thorough evaluation

of banks' performance is essential to maintain a robust financial system and promote efficiency within the economy (Gupta, 2014) Understanding these dynamics is crucial for stakeholders like central banks, governments, and financial authorities, as it aids in formulating policies to enhance the financial performance of the banking sector, thus contributing to overall economic advancement Key metrics for analysis include profitability, growth, and liquidity, with profitability being particularly important for the smooth functioning of the financial system (Tektas et al., 2005)

The profitability and performance of commercial banks are vital indicators not only for individual institutions but also for the overall health and growth of the banking sector Scholars and practitioners have extensively studied the complex dynamics underlying bank profitability, considering both internal and external factors Onaolapo

& Adegoke (2020) highlights profitability as a central component of performance, intertwined with factors like capital structure and credit risk Tee (2017) and Belete (2013) discuss internal and external determinants, such as asset-liability management culture and macroeconomic indicators Shrestha (2016) examines micro and macro-level implications, emphasizing profitability's dual role in fostering competition and stability while cautioning against excessive profitability's potential market distortions While these studies share a focus on profitability, they differ in emphasis, enriching our understanding of bank profitability and performance dynamics Among the myriad factors influencing profitability, asset-liability management stands out as a significant determinant

Asset-Liability Management is crucial in banking for managing risks associated with assets and liabilities Scholars like Nasif & Shubiri (2010), Onaolapo & Adegoke (2020), Tee (2017), Belete (2013), and Shrestha (2016) highlight its importance in achieving financial goals, particularly optimizing net interest income (NII) ALM involves planning, organizing, and controlling assets and liabilities to mitigate risks related to liquidity, interest rates, and market fluctuations Scholars distinguish between defensive and aggressive ALM approaches, with defensive control focusing on stability and aggressive control aiming to maximize net interest margin ALM is seen as a dynamic process, requiring adaptation to changing market conditions and integrating risk management beyond interest rate fluctuations Challenges in ALM implementation include the need for understanding ALM concepts, robust information systems development, and effective decision-making processes led by Asset Liability Committees (ALCOs) Quantifying, assessing, and managing various risk categories are crucial for successful ALM practices

The influence of ALM on bank profitability has been extensively explored in various countries, as evidenced by a series of studies analyzed in this review Nasif & Shubiri (2010) demonstrated in their study in Jordan the significant positive relationship between internal ALM factors and bank profitability, emphasizing the role of asset and liability management in influencing operating income Similarly, Najimi et al (2022) highlighted the importance of incorporating macroeconomic factors in understanding ALM dynamics and profitability, particularly in the case of Afghanistan Gessesow & Venkateswarlu (2023) further emphasized the direct influence of ALM on bank performance, particularly in Ethiopia, where effective management of assets and liabilities played a crucial role in enhancing profitability In Nigeria, Onaolapo & Adegoke (2020) identified both positive and negative effects of ALM on profitability, underscoring the interconnectedness of internal and external factors, while Njogo & Ohiaeri Nomisakin (2014) found a positive influence of ALM on Nigerian banks'

performance, reinforcing the importance of effective asset and liability management strategies in enhancing bank profitability across diverse geographical and institutional settings Tee (2017) focused on Ghana's banking sector, revealing complexities in the relationship between ALM and profitability, especially concerning macroeconomic variables Similarly, Belete (2013) provided insights into the Ethiopian banking sector, highlighting the significance of specific asset and liability categories in influencing profitability Shrestha (2016) explored the Nepalese context, uncovering positive relationships between certain assets and profitability

The empirical examination of ALM in developing Southeast Asian economies like Vietnam is notably limited, unlike in developed economies Consequently, research findings from other countries may not be readily applicable to Vietnam due to disparities in economic structure and policies Therefore, there is a pressing need to investigate the specific influence of asset liability management on the profitability of commercial banks in Vietnam

2 Objectives of the thesis

- Firstly, analyzing the theoretical framework overview of the influence of liability management on bank profitability

asset Secondly, identify the influence of assetasset liability management, and assess the degree/mechanism to which these elements influence the banks' profitability in Vietnam

- Thirdly, propose internal management recommendations aimed at enhancing banks' profitability

3 Research object and scope

- Research object: The influence of asset-liability management on banks’ profitability of Vietnam listed commercial banks

- Research scope:

+ In terms of space: 18 Vietnam listed commercial banks in HOSE

+ In terms of time: Annual data from 2013 to 2023

4 Research methodology

- Topic selection: The author reviews the global banking system, with a focus on

Vietnam, to formulate a research topic: "The influence of asset-liability

management on banks’ profitability of Vietnam listed commercial banks."

- Information collection: The author gathers and analyzes existing literature on asset-liability management and banks’ profitability, aiming to identify gaps in knowledge for further investigation

- Methodology & Hypothesis development: The methodology is chosen based on empirical tests from previous studies, ensuring suitability for the research context Hypotheses are developed regarding the relationship between ALM and banks’ profitability

- Data collection: Data is sourced from reliable online databases, including level data from Vietstock website and macro-level data from the World Bank database

bank Data analysis: Stata software version 17.0 is used for analysis Descriptive analysis characterizes the input sample, followed by empirical tests using three models: Random Effects Model (REM), Fixed Effects Model (FEM), and Ordinary Least Squares (OLS) Model suitability is verified through tests such

as the Hausman test for FEM and REM Generalized Least Squares (GLS) regression is employed to address any identified issues

- Result interpretation and Recommendations: The obtained results are interpreted for significance, and recommendations are formulated for internal bank management and regulatory governance based on the findings from the models

5 Thesis structure

The thesis is organized as follows:

- Chapter 1: Literature review and theoretical basis

- Chapter 2: Research data and methodology

- Chapter 3: Findings and discussion

- Chapter 4: Recommendations

6 Thesis contribution

Examine and evaluate the various factors influencing the profitability of banks, with a primary focus on ALM Through an analysis of these factors, this study aims to demonstrate the potential influence of ALM practices on the profitability of commercial banks in Vietnam Consequently, the thesis intends to provide management recommendations for banks and propose policy adjustments for governments and policymakers to align regulatory frameworks with practical industry dynamics By enhancing the operational efficiency of commercial banks, these proposed measures aim to stimulate growth within both the banking sector and the broader economy

This study addresses aspects that have not received adequate attention in previous research and aims to conduct a comprehensive investigation over an extended timeframe to facilitate comparisons with earlier studies

CHAPTER 1: LITERATURE REVIEW AND RESEARCH GAP

1.1 The review of previous studies

1.1.1 Asset-liability management of commercial bank

Asset-liability management is universally acknowledged as a dynamic and essential process within the banking sector, aiming to strategically manage the balance between assets and liabilities to achieve financial goals However, the literature reveals nuances in the emphasis placed on different aspects of ALM across various studies On one hand, scholars like Onaolapo & Adegoke (2020) underscore the critical role of ALM in mitigating risks inherent in banking operations Their focus lies on the proactive management of interest rate risk, liquidity risk, and other financial uncertainties According to this perspective, ALM serves as a shield against potential threats to the bank's stability and ensures that the institution is well-prepared to weather adverse market conditions By prioritizing risk mitigation, Onaolapo & Adegoke highlight ALM as a defensive mechanism that safeguards the bank's interests and fosters resilience in the face of market volatility On the other hand, Tee (2017) and similar scholars emphasize a different aspect of ALM, placing greater emphasis on profitability and balance sheet optimization From this viewpoint, ALM is not only about risk management but also about strategically leveraging assets and liabilities to maximize returns and enhance the bank's financial performance Tee contends that proper ALM allows institutions to capitalize on opportunities, optimize resource allocation, and ultimately drive profitability By aligning assets and liabilities in a manner that enhances the net interest margin and minimizes costs, Tee positions ALM as a proactive tool for enhancing the bank's competitive position and ensuring long-term sustainability Thus, while all studies acknowledge ALM as a dynamic process, they diverge in their emphasis, with some prioritizing risk mitigation as the primary objective, while others underscore the importance of profitability and balance sheet optimization These differing perspectives reflect the multifaceted nature of ALM and the various strategic objectives that banks seek to achieve through effective balance sheet management

Overall, the discussion of defensive and aggressive control strategies by Nasif & Shubiri (2010), alongside the insights provided by Belete (2013) and Shrestha (2016)

on the evolution of ALM models, highlights the importance of flexibility and adaptability in ALM practices Nasif & Shubiri (2010) delineate two fundamental approaches in ALM: defensive and aggressive control strategies These strategies are designed to address the challenge of managing interest rate risk within banking institutions Defensive control focuses on insulating the net interest margin from fluctuations in interest rates In essence, it aims to maintain stability in the face of

market volatility, ensuring that the bank's profitability is not unduly affected by external economic shifts This approach involves adopting conservative measures to protect the bank's balance sheet, such as employing hedging instruments or diversifying asset portfolios On the other hand, aggressive control aims to maximize the net interest margin by actively restructuring the bank's balance sheet Unlike defensive control, which prioritizes stability, aggressive control seeks to capitalize on market opportunities

to enhance profitability This may involve taking calculated risks, such as increasing exposure to higher-yielding assets or adjusting the mix of liabilities to reduce funding costs However, it also entails greater exposure to market fluctuations and requires a proactive approach to monitoring and managing risk.Belete (2013) and Shrestha (2016) further elaborate on these approaches by discussing the evolution of ALM models in response to changing market dynamics As financial markets evolve and become increasingly complex, traditional ALM frameworks may become inadequate in addressing emerging risks Therefore, banks must continuously adapt their ALM strategies to remain resilient in the face of evolving economic conditions This adaptation may involve incorporating more sophisticated risk management techniques, leveraging advanced analytics and modeling tools, and aligning ALM practices with broader strategic objectives

Njogo & Ohiaeri Nomisakin (2014) underscore the multitude of challenges and risks that banks encounter in the realm of ALM Among these challenges, two prominent issues stand out: information gathering and regulatory changes Information gathering poses a significant hurdle for banks engaged in ALM Managing assets and liabilities effectively requires comprehensive and accurate data on various financial instruments, market conditions, and customer behaviors However, collecting this information can be a daunting task, particularly in an environment characterized by data complexity and volume Banks must invest significant resources in data collection, processing, and analysis to ensure they have a solid foundation for making informed ALM decisions Moreover, the quality and reliability of the gathered data are paramount, as erroneous or incomplete information can lead to flawed risk assessments and suboptimal strategic choices Additionally, regulatory changes represent a constant challenge for banks navigating the landscape of ALM Regulatory bodies frequently introduce new rules and guidelines governing financial institutions, including requirements related to capital adequacy, liquidity management, and risk mitigation These regulatory changes can significantly influence ALM strategies, necessitating adjustments in asset and liability structures, risk management practices, and compliance procedures Adapting to regulatory shifts requires banks to stay abreast of evolving regulatory frameworks, invest in compliance infrastructure, and allocate resources to

ensure adherence to regulatory requirements Failure to effectively navigate regulatory changes can expose banks to compliance risks, penalties, and reputational damage, underscoring the importance of proactive regulatory compliance within the ALM framework

The role of asset-liability management in profitability is a central focus in banking literature, with several studies highlighting its potential to enhance financial performance through the efficient management of assets and liabilities Onaolapo & Adegoke (2020) and Njogo & Ohiaeri Nomisakin (2014) assert that ALM plays a crucial role in driving profitability by optimizing the allocation of resources, balancing risk exposures, and ensuring that the institution's financial objectives are met By effectively managing the mix, volume, maturities, yield, and costs of assets and liabilities, banks can achieve a specified net interest income and improve overall profitability These studies suggest that ALM enables banks to align their balance sheet structure with their strategic goals, thereby maximizing returns while minimizing risks

By actively monitoring and adjusting asset and liability portfolios in response to changing market conditions, banks can capitalize on opportunities for profit generation while safeguarding against potential losses However, Belete (2013) introduces a nuanced perspective by highlighting conflicting views regarding the influence of liability management on profitability While effective management of liabilities is generally seen as integral to ALM, Belete suggests that certain strategies may not always translate into immediate or significant improvements in profitability Factors such as market dynamics, regulatory constraints, and competitive pressures can influence the effectiveness of liability management practices in driving profitability

1.1.2 Profitability of commercial bank

a) Foreign Research

The concept of performance in the banking sector is a subject of significant research interest, with scholars examining various dimensions and determinants of bank profitability This review explores multiple studies conducted to understand the factors influencing bank performance, particularly focusing on internal management practices, external economic conditions, and their implications at both micro and macro levels

In their study, Onaolapo & Adegoke (2020) provide a nuanced understanding of performance in the banking sector, emphasizing its multifaceted nature They argue that performance cannot be reduced to a single dimension but rather encompasses both operational and financial aspects This recognition suggests that evaluating a bank's performance requires consideration of various factors beyond just financial metrics The subjective nature of performance is heavily influenced by the objectives set by the firm This implies that different banks may prioritize different aspects of performance based

on their strategic goals and market positioning For instance, a bank aiming for rapid expansion might prioritize revenue growth over profitability in the short term, while a conservative bank may prioritize stability and risk management Furthermore, they stress the significance of financial performance measures, particularly profitability and liquidity, in assessing a bank's past performance and current position Profitability metrics such as return on assets (ROA) and return on equity (ROE) provide insights into how efficiently a bank is utilizing its assets to generate profits Liquidity measures, on the other hand, indicate the bank's ability to meet its short-term obligations without jeopardizing its long-term financial health By highlighting the multifaceted nature of performance and emphasizing the subjective aspect influenced by firm objectives, Onaolapo & Adegoke contribute to a more comprehensive understanding of performance evaluation in the banking sector Their insights underscore the importance

of considering both operational and financial aspects, as well as aligning performance metrics with strategic objectives, in assessing a bank's overall performance and competitive position

In their respective studies, both Tee (2017) and Belete (2013) extensively explore the factors influencing bank profitability, shedding light on the intricate interplay between internal management practices and external economic conditions They draw upon the research conducted by Alper and Anbar (2011) and Ramlall (2009), which underscores the significance of various determinants such as asset-liability management, GDP, inflation rate, and market interest rates in shaping bank profitability Tee (2017) specifically highlights the utilization of statistical cost accounting models

as a methodological approach to dissect the influence of ALM on profitability By employing quantitative techniques, Tee offers empirical insights into how different aspects of ALM, such as the management of assets and liabilities, influence a bank's financial performance This analytical framework allows for a nuanced understanding

of the relationship between ALM practices and profitability dynamics within the banking sector On the other hand, Belete (2013) takes a broader perspective, emphasizing the dynamic nature of ALM in driving commercial bank profitability Rather than focusing solely on statistical modeling, Belete delves into the underlying mechanisms through which ALM strategies interact with macroeconomic factors to shape bank profitability over time By adopting a more qualitative approach, Belete provides a comprehensive examination of the multifaceted nature of ALM and its implications for commercial banks in navigating economic fluctuations and market dynamics

In Shrestha (2016) study, the significance of bank profitability is thoroughly explored, examining its implications across both micro and macro levels within the banking sector At the micro level, profitability is identified as a fundamental factor in sustaining competitiveness among individual banks Profits serve as a critical metric for assessing the health and efficiency of banking institutions, enabling them to attract capital, invest in technology and innovation, and offer competitive products and services Moreover, profitability acts as a key determinant of a bank's ability to withstand competitive pressures within the financial market Furthermore, Shrestha's analysis extends beyond the micro-level implications to emphasize the broader macroeconomic significance of bank profitability At the macro level, profitable banks play a crucial role in fostering financial stability within the broader economy The profitability of banks contributes to overall economic resilience by ensuring the availability of credit, facilitating investment, and promoting economic growth Soundly profitable banks are better equipped to absorb financial shocks, thereby enhancing the stability of the financial system as a whole However, this study also highlights a potential downside to excessively high levels of bank profitability While profitability

is generally viewed as a positive indicator of bank performance, excessively high profitability can raise concerns regarding market power and its influence on financial intermediation Banks with significant market power may exploit their dominant position to extract higher fees and interest rates from customers, potentially hindering the efficient allocation of capital and resources within the economy Moreover, excessively high profits may signal inefficiencies or distortions within the financial system, leading to concerns about fairness and competitiveness

b) Domestic Research

Bank profitability is a crucial aspect of the financial sector, attracting significant attention from researchers aiming to understand the various factors influencing it This literature review examines four studies focusing on Vietnamese commercial banks and other developing countries, utilizing diverse methodologies to analyze profitability determinants Many studies under review center on the investigation of profitability determinants within the banking sector, with a specific focus on Vietnamese commercial banks Le (2017) delves into this analysis, scrutinizing the factors influencing profitability in Vietnamese commercial banks from 2005 to 2015 (Nguyen

et al., 2018) extend this inquiry through a regression analysis of panel data spanning 13 Vietnamese commercial banks across the period 2006 to 2015 Ngoc Nguyen (2019) broadens the scope by exploring the relationship between revenue diversification, risks, and profitability across 26 Vietnamese commercial banks from 2010 to 2018 Meanwhile, Dao & Nguyen (2020) expand the analysis to encompass Asian developing countries, examining profitability determinants in Vietnam, Malaysia, and Thailand from 2012 to 2016 Despite variations in methodology, certain factors consistently emerge as significant determinants of bank profitability across the studies Bank size, liquidity risk, and credit risk are identified as key factors influencing profitability in Vietnamese commercial banks Le (2017) highlights these factors, along with loan size and diversification, as critical elements impacting profitability This finding is echoed

in the studies by Nguyen et al (2018) and Ngoc Nguyen (2019), reinforcing the importance of these variables in determining bank profitability

Differences in findings regarding the influence of specific factors on profitability emerge across the studies under review Le (2017) posits a positive relationship between being listed on the stock exchange and bank profitability In contrast, Nguyen et al (2018) present findings that do not establish a linear relationship between state ownership and macroeconomic factors, such as GDP growth rate and inflation, with bank profitability This discrepancy underscores the nuanced nature of the relationship between institutional factors and profitability, suggesting that contextual factors may play a crucial role in shaping these dynamics Moreover, the interpretation of the relationship between revenue diversification and profitability varies across the studies While Ngoc Nguyen (2019) suggests that revenue diversification may lead to increased risks but improved revenue sustainability, the extent of these effects is subject to debate

Le (2017) also touches upon revenue diversification but focuses more on its potential

to enhance income opportunities, particularly in the retail segment These divergent interpretations highlight the complexity of revenue diversification as a profitability determinant, suggesting that its may be contingent on various contextual factors and

management strategies within individual banks Furthermore, Dao & Nguyen (2020) present contrasting findings regarding the influence of CAR and credit risk on bank profitability While some studies have suggested a positive relationship between CAR and profitability, this findings challenge this notion by indicating a negative association Similarly, their study highlights a positive relationship between credit risk and profitability, contrary to the negative influence typically associated with higher credit risk levels These disparities underscore the multifaceted nature of profitability determinants across different contexts and suggest that the relationship between risk management practices and profitability may vary significantly among banks operating

in diverse economic environments

1.1.3 The influence of Asset-liability management on Profitability of commercial bank

a) Overview of approaches to assessing the impact of Asset-liability management on bank profitability

Various studies have examined the influence of ALM on bank profitability across different countries and time periods This literature review aims to compare and contrast the findings of several research studies focusing on ALM and its effects on bank profitability

Nasif & Shubiri (2010) investigated the influence of asset liability management, along with external factors such as market concentration and inflation rate, on the profitability of selected commercial banks in Bangladesh They analyzed data from the financial statements of 14 Jordanian commercial banks listed on the Amman Stock Exchange over the period 2005–2008 Their study revealed a significant relationship between various asset variables (such as loans, bills discounted and purchased, deposits with other banks, and government securities) relative to a bank's average total assets, and liability variables (including fixed/time deposits, saving deposits, current and non-interest bearing liabilities, and other borrowings) with operating income, with statistical significance at the 1% level across all years Additionally, incorporating non-balance sheet variables, the study found a highly significant relationship between the Herfindahl Index and inflation, also at the 1% level The Assets and Liabilities Committee (ALCO) emerged as a crucial component within this framework, bearing significant responsibility for formulating general strategy and overseeing the overall function of assets and liabilities management

Shrestha (2016) study focuses on asset liability management and its influence on the profitability of commercial banks in Nepal Using correlation, regression, and descriptive analysis, the study examined the relationship between ALM and commercial banks over the period of 2007-08 to 2013-14 The research holds relevance for bank management, offering insights to identify competitive advantages and disadvantages compared to competitors and informing policy adjustments towards ALM Additionally, the study contributes to the existing literature on banks' ALM practices and holds significance for policymakers in evaluating financial sector policies and regulations The findings of the multiple regression analysis indicate a significant relationship between asset liability management and the financial performance of commercial banks in Nepal, with a correlation coefficient of 0.475 Specifically, asset variables such as loans, advances and bills purchase, fixed assets, and other assets positively influence profitability, while liability variables such as deposits and other

liabilities have a negative impact Moreover, the study examines the impact of macroeconomic variables, revealing that both GDP and inflation negatively influence commercial banks' profitability However, it acknowledges the broader implications of these variables in the economic development of Nepal

Najimi et al (2022) aimed to assess the influence of asset-liability management and macroeconomic factors on the profitability of banks while controlling for various variables They utilized panel data spanning from 2011 to 2021, focusing on seven domestic commercial banks in Afghanistan The study examined various asset items including loans and advances, cash equivalents, investments, property and equipment, and other assets, alongside liability items such as current deposits, saving deposits, fixed deposits, and other liabilities for asset-liability management Additionally, macroeconomic factors like GDP growth rate and inflation rate were incorporated, with bank age and bank size serving as control variables Profitability was measured using the return on assets (ROA) ratio The findings supported the central hypothesis to some extent, revealing that the return rate on liabilities varied across different categories, with about half showing a negative impact Similarly, the return rate on assets also exhibited variations across different asset categories The null hypothesis regarding macroeconomic factors was accepted, indicating a significantly positive contribution to the ROA ratio Regarding control variables, bank age did not significantly influence profitability, whereas bank size had a notable positive effect on the ROA ratio The study underscored the influence of balance sheet items and macroeconomic factors on bank profitability, with over fifty percent of regression coefficients being statistically significant Interestingly, the analysis suggested that while assets did not significantly affect profitability, more than half of the studied liability categories positively influenced the ROA ratio in the Afghan context This outcome could be attributed to factors such as uncertainty in future investments, high rates of credit defaults, and legal issues prevailing in the region

Belete (2013) and Gessesow & Venkateswarlu (2023) study delved into assessing the influence of asset liability management on the profitability of private commercial banks in Ethiopia Belete's study utilized balanced panel data from eight commercial banks spanning the period from 2005 to 2010 The empirical findings revealed that the profitability of commercial banks in Ethiopia was positively influenced

by asset management, including deposits in other banks, other investments and debit balances, and loans and advances However, fixed assets had a negative impact on profitability On the other hand, liability management, including demand deposits, saving and fixed deposits, and other liabilities and credit balances, negatively affected profitability Additionally, macroeconomic variables such as the real growth rate in

GDP and the general rate of inflation were incorporated into the study model The findings indicated that both variables had a negative effect on commercial banks' profitability Specifically, the real growth rate in GDP exhibited a significant negative effect, contingent upon prevailing economic conditions Favorable economic conditions were found to positively impact the demand and supply of commercial banking services, thereby enhancing profitability Employing a panel data approach, Gessesow & Venkateswarlu (2023) analyzed time series data spanning from 2013 to 2022 from 14 private commercial banks in Ethiopia Pearson correlation analysis revealed that all types of assets included in the study exhibited a positive correlation with profitability (ROA), while all types of liabilities showed a negative correlation with bank profitability (ROA) Notably loans and advances, deposits in foreign banks, investments

in securities, and net fixed assets, positively impacted profitability and exhibited variations across asset categories Conversely, all types of liabilities, particularly savings deposits, demand deposits, fixed deposits, and other liabilities, negatively affected profitability and varied across liability categories These findings offer valuable insights to bank management by highlighting assets with the highest return on bank profitability and identifying the most cost-effective sources of funds from liabilities In conclusion, the study emphasizes the significance of ALM and suggests that enhancing focus on this aspect can contribute to improving bank profitability

Njogo & Ohiaeri Nomisakin (2014) and Onaolapo & Adegoke (2020) conducted

an empirical investigation into the influence of asset liability management on the performance in Nigeria of fourteen listed deposit money banks over a period of 14 years, from 2005 to 2018; and of 15 Nigerian banks from 2008 to 2012; respectively In contrast to the traditional focus on financial institutions, Njogo & Ohiaeri Nomisakin (2014) study explored the adoption of ALM techniques and processes by corporations beyond the financial sector The findings of the study revealed that all parameters related to asset and liability management, including Total asset per shareholders fund, Total liability per shareholders fund, and Customer deposit per shareholders fund, had

a positive and significant impact on profitability during the study period This suggests that the ALM practices implemented by Nigerian banks, as guided by regulatory authorities, were effective in enhancing profitability The study underscores the importance of effective ALM practices not only within the financial sector but also across various corporations It highlights the significance of regulatory oversight in guiding ALM strategies and ensuring their effectiveness in optimizing profitability Overall, the findings contribute to a broader understanding of ALM's role in driving financial performance and its applicability beyond traditional financial institutions Onaolapo & Adegoke (2020) utilized loan and advance (LOA), non-performing loan

(NPL), borrowing (BTA) as proxies for ALM, while return on asset (ROA) and return

on investment (ROI) served as performance indicators The study established a significant relationship between ALM proxies, and performance indicators Notably, the study found that ROA, NPL, and bank size (BSZ), which are control variables, were statistically significant in examining the impact of asset management on the profitability

of deposit money banks in Nigeria The results indicated that an increase in LOA and BSZ led to a significant increase in ROA, while a continuous increase in NPL drastically reduced ROA In line with the study's outcomes, it is recommended that every deposit money bank establishes a comprehensive Asset Liability Management policy framework, driven by a dynamic and proactive asset liability management committee (ALCO) constituted by the board This committee should play a vital role in regularly evaluating the appropriate mix of assets and liabilities to maximize bank profitability, thereby consistently enhancing performance and creating value for shareholders

In Tee (2017) study, an examination of seven banks listed on the Ghana Stock Exchange from 2008 to 2012 revealed that bank profitability is adversely affected by liabilities, while effective asset management positively influences commercial banks' profitability The logarithm of total bank assets has a significantly positive impact on the profitability Conversely, the logarithm of total liability has a significantly negative effect on profitability Furthermore, the study incorporated macroeconomic variables such as the real interest rate and the general rate of inflation While the interest rate showed no significant effect on profitability, the inflation rate had a negative impact on commercial banks' profitability However, the influence of inflation rate on profitability was contingent upon the predictive capabilities of bank managements When predictions were accurate and adjustments in interest rates were aligned with inflation expectations, profitability could be enhanced Consequently, correct predictions led to

a positive effect on bank profitability

b) Overview of methodology

The studies reviewed employ various research designs including cross-sectional, time series, and panel data analyses, each offering unique insights into the dynamics of ALM in the banking sector Nasif & Shubiri (2010) and Belete (2013), utilize cross-sectional analysis, which involves examining data collected at a single point in time from multiple banks This approach allows researchers to compare different banks at a specific moment, providing a snapshot of ALM practices and their influence on profitability Other studies, like Gessesow & Venkateswarlu (2023) and Shrestha (2016), adopt time series analysis, which focuses on examining data collected over a

period of time from a single bank or multiple banks This longitudinal approach enables researchers to assess trends and changes in ALM strategies and profitability over time Najimi et al (2022) and Onaolapo & Adegoke (2020) utilize panel data analysis, combining both cross-sectional and time series data This approach allows researchers

to analyze the same banks over multiple time periods, providing a comprehensive understanding of the relationship between ALM and profitability while controlling for individual bank characteristics

The use of the Statistical Cost Accounting model stands as a prominent feature across almost the reviewed studies (Nasif & Shubiri (2010); Najimi et al (2022); Gessesow & Venkateswarlu (2023); Onaolapo & Adegoke (2020); Tee 2017; Belete (2013); Shrestha (2016); Njogo & Ohiaeri Nomisakin (2014)), serving as the cornerstone for investigating the intricate relationship between asset liability management practices and the profitability of commercial banks The SCA model provides a structured framework that enables researchers to analyze the financial performance of banks by imputing rates of return to earning assets and deposit liabilities The SCA model, as described by Hester and Zoellner (1966), facilitates the estimation of rates of return on various components of a bank's balance sheet By attributing differential rates of return to assets and liabilities, the model offers insights into the efficiency and effectiveness of ALM strategies employed by banks This analytical approach allows researchers to delve into the dynamics of interest income and expense, assessing how the management of assets and liabilities influences overall profitability Through the application of the SCA model, researchers gain a comprehensive understanding of the interplay between asset and liability management strategies and their implications for bank profitability This analytical framework offers

a systematic approach to evaluate the efficiency of resource allocation, pricing strategies, and risk management practices within banking institutions As a result, the SCA model emerges as a foundational tool for empirical research aimed at unraveling the complexities of ALM and its influence on the financial performance of commercial banks

Descriptive statistics are frequently employed in research studies to summarize and describe the characteristics of banking data Measures such as mean, standard deviation, minimum, and maximum values are commonly utilized to provide an overview of key variables related to ALM and bank profitability These statistics offer researchers and practitioners a snapshot of the data's central tendency, dispersion, and range, aiding in the interpretation of findings and identification of patterns For example, Belete (2013) utilized descriptive statistics to describe the mean, standard deviation, minimum, and maximum values of explanatory and explained variables in

their study on the effect of ALM on commercial banks in Ethiopia Similarly, Shrestha (2016) applied descriptive statistics to analyze profitability measures using the SPSS version 16.0, offering insights into the profitability of banks in their study

Quantitative methods form the backbone of research endeavors examining the relationship between ALM and bank profitability These methods allow researchers to analyze numerical data, test hypotheses, and establish empirical relationships using statistical techniques Regression analysis is a commonly employed quantitative method that allows researchers to examine the relationship between ALM variables and bank profitability measures By estimating the coefficients of independent variables, regression analysis helps identify the strength and direction of associations, providing insights into the influence of ALM practices on bank profitability Studies such as Nasif

& Shubiri (2010) and Tee (2017) utilized regression analysis to model the relationship between ALM and bank profitability, adapting the SCA model to their specific contexts Panel data analysis is another quantitative approach frequently employed in research studies to account for both cross-sectional and time-series dimensions By utilizing panel data, researchers can capture individual and time effects, offering a more comprehensive understanding of the dynamics between ALM and bank profitability Onaolapo & Adegoke (2020) utilized a panel vector autoregressive framework to analyze the dynamic relationship between ALM and performance variables in their study, aligning with the specification of Abrigo and Love (2015) Correlation analysis

is also a valuable quantitative technique used to assess the strength and direction of relationships between variables By calculating correlation coefficients, researchers can determine the degree of association between ALM indicators and bank profitability measures Gessesow & Venkateswarlu (2023) employed correlation analysis to reveal the associations between profitability (ROA) and asset liability management variables

in their study on bank performance Employing a range of statistical techniques to analyze including fixed effect regression, random effect regression, correlation analysis, and Hausman test, among others Tee (2017) and Njogo & Ohiaeri Nomisakin (2014) utilize fixed effect regression, which accounts for unobserved heterogeneity across banks by including dummy variables for each bank in the regression model This technique helps control for individual bank characteristics that may affect profitability Onaolapo & Adegoke (2020) employ random effect regression, which assumes that individual bank-specific effects are uncorrelated with the independent variables This approach allows for more efficient estimation of coefficients when there is variation in bank characteristics across time periods Several studies, including Gessesow & Venkateswarlu (2023) and Shrestha (2016), conduct correlation analysis to assess the strength and direction of the relationship between ALM variables and profitability

measures This technique provides valuable insights into the linear association between variables Onaolapo & Adegoke (2020) utilize the Hausman test to compare the efficiency of fixed effect and random effect regression models This test helps researchers determine whether the random effect assumption holds true and which regression model is more appropriate for their analysis

1.2 The research gap

a) The research gap in object and scope

Despite the extensive research conducted worldwide on the influence of ALM practices on bank profitability, there is a notable gap when it comes to studying this dynamic in specific regions such as Southeast Asia, including countries like Vietnam This gap indicates a lack of comprehensive understanding of how ALM strategies impact the financial performance of banks in this particular region While there is ample literature available on ALM practices from various parts of the world, including developed economies, limited attention has been given to exploring the unique challenges, opportunities, and strategies faced by banks operating in developing economies, particularly in Southeast Asia This lack of focus on developing economies

is concerning because these regions often present distinct economic, regulatory, and institutional environments that can significantly influence the effectiveness of ALM approaches The significance of this gap becomes evident when considering the differing economic structures, regulatory frameworks, and institutional environments prevalent in Southeast Asian countries These factors can create specific challenges and opportunities for banks in managing their assets and liabilities effectively Therefore, there is a need for research to tailor ALM strategies to the unique context of Southeast Asia, taking into account factors such as currency volatility, diverse market conditions, and regulatory requirements

Furthermore, existing research tends to concentrate primarily on private and public commercial banks, overlooking the significant presence and influence of state-owned banks in many Southeast Asian economies State-owned banks often operate with different objectives and characteristics compared to their private counterparts, which can significantly impact their ALM practices and financial performance Neglecting to study state-owned banks creates a gap in understanding the full spectrum

of ALM strategies and their effects on bank profitability in the region To address this gap effectively, researchers should broaden their focus to include a wider range of banking institutions, including state-owned banks, in their studies By doing so, they can gain a more comprehensive understanding of the drivers of bank profitability in Southeast Asia and develop tailored ALM strategies that are better suited to the unique challenges and opportunities present in the region

b) The research gap in methodology

The observed gap in research methodology lies in the limited exploration of alternative modeling techniques beyond commonly used methods like descriptive statistics, regression analysis, panel data analysis, and correlation analysis, despite their value in investigating the relationship between asset and liability management (ALM) and bank profitability Notably, the absence of discussion on Generalized Least Squares (GLS) modeling is noteworthy, as GLS can address potential correlation and heteroscedasticity concerns inherent in panel data analysis, providing more robust estimations compared to traditional regression techniques By incorporating GLS and exploring other alternative modeling techniques, researchers can enhance the depth and accuracy of their analyses, potentially uncovering nuanced insights into the complex interplay between ALM practices and bank profitability This adoption of alternative modeling techniques beyond the conventional ones mentioned can significantly bolster the robustness and validity of research findings in the domain of ALM and bank profitability, facilitating the refinement and advancement of knowledge in this field By embracing a broader spectrum of modeling techniques tailored to the unique characteristics of the banking sector in Southeast Asia and similar contexts, we can uncover novel insights and contribute meaningfully to the existing body of literature while enriching the methodological discourse

Additionally, robustness checks play a pivotal role in safeguarding the reliability and validity of research findings, particularly in studies exploring the relationship between ALM practices and bank profitability These checks involve systematically testing the stability of results by varying key variables, methodologies, or assumptions This rigorous approach helps to mitigate the risk of spurious correlations or methodological biases, ensuring that the conclusions drawn from the analysis are robust and trustworthy By conducting thorough robustness checks, we can instill confidence

in their findings and contribute to the accumulation of knowledge in the field of banking and financial management

CHAPTER 2: RESEARCH METHOD AND PROCESS

2.1 Research process

to define the topic

⇩

ALM on banks' profitability

⇩

investigating the chosen topic

⇩

ALM and other factors on banks' profitability

⇩

Interpret results

& Recommendations

Figure 1 Research process

- Step 1: Topic selection

Initially, the research conducts an extensive review of the current state of the

global banking system, focusing particularly on Vietnam Through an examination of prevailing literature and empirical findings, a research topic is formulated after

consultation with the instructor: “The influence of asset-liability management on banks’

profitability of Vietnam listed commercial banks”

- Step 2: Information collection

Following the determination of the research topic, the author proceeds to gather and analyze existing literature related to the influence of asset-liability management on banks’ profitability both internationally and within Vietnam By synthesizing concepts and empirical findings from prior research, the aim is to identify gaps in existing knowledge and orient the study towards addressing these gaps

- Step 3: Methodology & Hypothesis development

The methodology is selected based on empirical tests conducted in previous studies, ensuring suitability for the research context and the ability to address model and variable-related issues Suitable variables are chosen to represent banks’ profitability as dependent variables and their assumed relationship with independent variables related to ALM Additionally, the author outlines expectations regarding the direction of the association between ALM and banks’ profitability

- Step 4: Data collection

Data for the research is sourced from a reliable online database Bank-level data

is obtained from Vietstock website, which compiles financial statement data for each bank into accessible tables Macro-level data is gathered from the World Bank database

- Step 5: Data analysis

To examine the influence of ALM on profitability, Stata software version 17.0

is utilized Descriptive analysis is initially conducted to characterize the input sample Subsequently, empirical tests are performed for the entire sample using three models: Random Effects Model (REM), Fixed Effects Model (FEM), and Ordinary Least Squares (OLS) Model suitability is verified through tests such as the Hausman test for FEM and REM, and Sargan-Hansen and AR Upon selecting the appropriate FEM model, the authors conduct Wald and Wooldridge tests to identify deficiencies, followed by employing Generalized Least Squares (GLS) regression to address any identified issues

- Step 6: Result interpretation and recommendations

The obtained results are interpreted for significance, and recommendations are formulated for internal bank management and regulatory governance based on the findings from the aforementioned models

2.2 Methodology

2.2.1 Research model

To explore how asset liability management influences banks' profitability, incorporating both bank-specific indicators and macroeconomic determinants, we propose the following general research model for Vietnamese banks:

Profitability it = α it + β 1 Bank-specific i,t + β 2 Macro-level i,t + ε it

In where:

- Profitability it is the bank profitability of bank i at time t, which is proxied

by return on assets (ROA);

- Bank-specific i,t denotes the bank’s features indicators of bank i at time t, which includes in the research the following variables:

+ L (The two-year average of Loans advances and finance leases to

customers to Total Assets, %),

+ IS (The two-year average of Investment securities to Total Assets,

%),

+ DC (The two-year average of Deposits and borrowings from other

credit institutions to Total Assets, %),

+ D (The two-year average of Deposits from customers to Total

Assets, %),

+ TAg (The year-on-year growth rate of Total Assets, %)

- Macro-level i,t represents for macroeconomic variables is GDPg (GDP

growth annual %) in Vietnam in year t;

- ε it is the error term and α it is a constant term

2.2.2 Dataset

The research focuses on a cohort of 18 Vietnamese commercial banks listed on the Ho Chi Minh Stock Exchange (HOSE) as of December 2023 Annual data spanning from 2013 to 2023 was utilized, sourced directly from the HOSE

tion

2 Joint Stock Commercial Bank for Investment and

4 Vietnam Commercial Joint Stock Export Import Bank EIB

5 Ho Chi Minh City Development Joint Stock Commercial

Bank

HDB

13 Sai Gon Thuong Tin Commercial Joint Stock Bank STB

14 Vietnam Technological and Commercial Joint Stock Bank TCB

17 Vietnam International Commercial Joint Stock Bank VIB

18 Vietnam Prosperity Joint Stock Commercial Bank VPB

Table 1 List of commercial banks in sample

Specifically, banks were selected based on the availability of their annual reports and accounts within the HOSE archives for the aforementioned period, ensuring adherence to Vietnamese accounting standards This timeframe was chosen due to significant sector-wide reforms, including recapitalization, consolidation, implementation of cashless policies, and enhancements in corporate governance practices

The selection criterion specifically targeted commercial banks due to their predominant role as key stakeholders within the Vietnamese banking landscape, as opposed to foreign bank affiliates and joint-venture banks which operate with certain limitations in the local market The utilization of data encompassed an unbalanced panel structure, primarily attributable to incomplete data disclosure by banks Macroeconomic indicators, such as GDP, were sourced from the World Bank database, aligning with the temporal scope of bank-level data, which was obtained from external databases The dataset frequency employed in this study was annual, encompassing both macroeconomic and micro-level variables

2.2.3 Hypothesis development

Hypothesized relationship with profitability

Source

Dependent variables: Bank profitability

ROA Return on assets (%)

Najimi et al (2022), Gessesow & Venkateswarlu (2023), Onaolapo & Adegoke (2020), Shrestha (2016),

Dao & Nguyen (2020), Ngoc Nguyen (2019)

Bank-specific variables

L

The two-year average of Loans

advances and finance leases to

customers to Total Assets (%) +

Najimi et al (2022), Gessesow & Venkateswarlu (2023), Tee (2017),

Belete (2013)

IS

The two-year average of

Investment securities to Total

Assets (%) +

DC

The two-year average of Deposits

and borrowings from other credit

institutions to Total Assets (%) -

D The two-year average of Deposits

from customers to Total Assets (%) -

TAg The year-on-year growth rate of

Total Assets (%) +

Najimi et al (2022), Shrestha (2016), Dao & Nguyen (2020), Ngoc Nguyen (2019)

Table 2 Variables description

The literature review has unveiled a plausible association between bank profitability and a spectrum of factors, encompassing both asset-liability management, bank-specific characteristics, and macroeconomic indicators This section endeavors to examine potential determinants influencing banks' earnings, as identified and explored

in prior scholarly works These factors are poised to be incorporated into the model

framework of this paper, thereby enriching its analytical depth and explanatory capacity

a) Statistical Cost Accounting (SCA) model

In pursuit of the objectives outlined in this study, the initial focus is directed towards the SCA model This model serves as a foundational element in examining the dynamics of bank profitability in relation to ALM strategies The hypothesis concerning the SCA model stems from the notion that effective financial management practices play a pivotal role in shaping the profitability of banking institutions It is posited that proficient management of assets and liabilities equips banks with the resilience needed

to navigate through unforeseen challenges and capitalize on profitable opportunities

Thus, it is hypothesized that there exists a positive and significant relationship between bank profitability and asset management, while a negative and significant relationship

is anticipated between bank profitability and liability management

This hypothesis is underpinned by a wealth of scholarly literature Nasif & Shubiri (2010) laid the groundwork by highlighting the importance of robust financial capabilities in mitigating risks and enhancing profitability within the banking sector Furthermore, Belete (2013) provided insights into the intricate relationship between revenue generation from assets and liabilities and the resultant influence on overall bank profitability Support for the proposed hypotheses can be found in a multitude of studies Researchers such as Gessesow & Venkateswarlu (2023) corroborated the idea that effective asset management strategies contribute positively to bank profitability, while Tee (2017) emphasized the negative influence of inefficient liability management on profitability However, dissenting views also exist within the academic discourse

Loans and advances (L) and investments in securities (IS) are two crucial variables representing the asset side of a bank's balance sheet These variables play significant roles in influencing the profitability and overall financial performance of banks Loans and advances (L) refer to the amount of money lent out by the bank to customers, including finance leases, relative to the total assets of the bank, expressed as

a percentage This variable reflects the extent to which the bank is involved in lending activities Investments in securities (IS) represent the amount of funds invested by the bank in various financial instruments, such as bonds, equities, and other marketable securities, relative to total assets, expressed as a percentage This variable reflects the bank's investment strategy and its allocation of resources into different financial markets As emphasized by Najimi et al (2022), loans and advances are essential components of a bank's asset portfolio, representing economic resources utilized by the