Studying the relationship between bank capacity variables and the price of bank shares on the Vietnamese stock market will give investors and other stakeholders a better understanding of
Objectives, research tasks and research Questions - - 5 22+ SS*nsrrererrrrrrree 11 1 Objectives of the StUdy .- Án HT HH Hà TT HT HT nh HT TT HH TH 11
Questions Of the Study 00 cece ố
How does the bank's capacity affect the bank's share price?
Which of the factors representing the bank's capacity according to the CAMEL framework affects the bank's share price?
What are the recommendations for investors, issuers, regulators, the Ministry of Finance and the State Securities Commission?
The analysis covered 27 commercial banks that were listed on three Vietnamese stock markets between 2013 and 2023: HOSE, HNX, and UPCOM.
The study combines two qualitative research techniques with one quantitative technique:
The qualitative method involves gathering credible materials and reviewing relevant prior research to gain in-depth knowledge about the research subject, thereby establishing a solid theoretical foundation and logical reasoning for the investigation.
The team will employ a quantitative approach using the CAMEL framework to analyze capacity variables impacting stock prices By applying a multivariate regression model, they aim to identify which bank characteristics most significantly influence stock price fluctuations over a defined timeframe, contingent upon having a robust dataset and sufficient foundational data.
5 Expected contribution of the study
In reality, there are numerous variables that influence stock prices, making it challenging for investors, particularly novice ones, to choose the most crucial information.
The author proposes the CAMEL model as a valuable tool for investors to simplify decision-making by evaluating five key characteristics that reflect a bank's capabilities This study analyzes historical data from 27 commercial banks listed on the Vietnamese stock market, revealing average quarterly price fluctuations in relation to varying historical market contexts and establishing guidelines for share price behavior.
The study examines 12 mobilized factors, including capital adequacy, asset quality, governance capability, cost of income, and bank liquidity This research provides a foundational understanding for future investigations into the fluctuations of bank stock prices and serves as a valuable reference for issuers, regulators, and investors.
CHAPTER 1: LITERATURE REVIEW AND THEORETICAL FRAMEWORK
A study by Cooper et al (2003) analyzed data from US bank holding companies between June 1986 and December 1999, revealing that factors such as earnings per share, non-interest income, credit allowance, earnings, equity ratio, and standby letter of credit commitments significantly influence bank shares However, bank size and the book-to-market value ratio did not show a significant impact The findings suggest that investors tend to underreact to changes in bank characteristics, affecting their stock performance.
According to another study by Al-Shubiri (2010), he conducted a simple and multiple regression analysis on data from 14 banks on the Amman Stock Exchange in
A recent study by Jordan revealed a strong positive correlation between the market price of stocks and the net asset value per share Additionally, it found a notable negative relationship between stock market prices and dividend percentages relative to gross domestic product, as well as a significant negative correlation between inflation rates and lending interest rates on the Amman Stock Exchange.
Research by Al-Qenae, Li, Mukherjee, Naka (1995), and Wearing (2002) highlights the negative impact of high loan interest rates on the economy A high lending interest rate restricts investors' access to capital, leading to a decline in stock prices Thus, the lending interest rate serves as a crucial tool for economic influence.
A study by Virza Ilham Zaini, Isfenti Sadalia, and Khaira Amalia Fachrudin (2018) investigates the impact of internal and external factors, such as return on assets, debt to equity ratio, non-performing loans, and net profit margin, on stock returns in banking companies listed on the Indonesia Stock Exchange, with price to book value serving as a moderating variable.
The test results indicated that inflation, interest rates, the rupiah exchange rate, return on assets, the debt to total equity ratio, non-performing loans, and Net Interest Margin (NIM) negatively and significantly impacted stock performance Notably, inflation, interest rates, and NIM were found to have a significant influence on stock returns, while the exchange rate exhibited a reverse effect.
ROA, DER, NPL and the type of firm ownership did not have any significant influence on
Research by Girard et al (2010) indicates that bank stocks in emerging and frontier nations are influenced by factors such as bank size, market book value, and term gap, along with socioeconomic elements, average GDP, and competitive dynamics Almumani (2014) found that for banks on the Amman Stock Exchange, earnings per share (EPS), book value, price-to-earnings (P/E) ratio, and size significantly affect stock prices from 2005 to 2011 Additionally, Uddin et al (2013) examined the determinants of stock prices for financial companies on the Dhaka Stock Exchange, further contributing to the understanding of these market influences.
Exchange (Bangladesh) and come to the conclusion that there is a positive correlation between stock price and net asset value per share, earnings per share, and P/E ratios.
The study by Moeljadi et al (2020) on the Indonesian stock market also examines the elements influencing the firm value (as determined by stock price and stock return) of
Between 2015 and 2018, an analysis of 30 listed banks revealed that the Net Interest Margin (NIM) and the equity to total assets ratio significantly influence stock prices, while showing no effect on stock returns.
Research has explored various factors influencing stock prices, including banking regulations (Pasiouras, Tanna, & Zopounidis, 2008), alterations in dividend policies (Camilleri, Grima, & Grima, 2018), and the business models, funding sources, and health indicators of banks (Yin & ).
1.1.2 Overview of research in Vietnam
Studies on the variables influencing the stock prices of banks listed on the Vietnamese stock market have been conducted quite a bit in Vietnam up until this point.
In their research article, Nguyen Thi Thieu Quang and Ha Xuan Thuy analyze how bank characteristics influence stock profitability in Vietnam's banking sector during the COVID-19 pandemic, utilizing a Fixed Effects Model to derive their findings.
(FEM) regression results demonstrate a negative association between liquidity, credit quality, and loan balance and stock price volatility.
In his 2022 study, author Nguyen Phu Ha utilized both qualitative and quantitative methods, employing panel data and a robust standard error regression model to analyze the stock price volatility of 13 listed banks from Q1 2009 to Q4 2020 The research revealed that GDP growth, the consumer price index (CPI), asset efficiency (ROA), and stock beta positively influence stock price volatility, while factors such as the VnIbor interest rate, exchange rate, and non-performing loans (NPL) negatively affect it Additionally, the study identified varying impacts from other elements, including the M2 money supply, gold prices, the industrial production index (IIP), stock volatility, equity capital, liabilities, return on equity (ROE), and earnings per share (EPS) on the banking sector.
Nguyen Thi Van Hanh and Vo Van Dut (2021) investigated the impact of bank liquidity on stock price volatility using the SPV method, focusing on 17 commercial banks listed on the Vietnam stock market Their study analyzed various factors, including credit risk provisions, P/E ratios, exchange rates, and GDP The findings from the REM regression model revealed that the financial gap (FGAP) positively influences bank stock price volatility Conversely, total asset quantity and exchange rate fluctuations have opposing effects, indicating that significant financial gaps and low bank liquidity contribute to increased stock price volatility for listed commercial banks in Vietnam.
Methodology of the StUdy - Án TH TH TH HH HH TT Thọ TH TH HH Hà Tưng hệt 12 5 Expected contribution of the study - Á- SG 1212 S* SH TT TH TH TH H rkey 12
The study combines two qualitative research techniques with one quantitative technique:
To gain a comprehensive understanding of the research topic, the author will begin by collecting credible materials and reviewing relevant prior studies, establishing a solid theoretical framework and rationale for the subject matter.
The team will utilize the CAMEL framework to analyze and model the capacity variables impacting stock prices through a multivariate regression model This approach aims to identify which bank characteristics most significantly influence stock price fluctuations over a defined time period, contingent upon the availability of adequate foundational data and a sufficiently large dataset.
5 Expected contribution of the study
In reality, there are numerous variables that influence stock prices, making it challenging for investors, particularly novice ones, to choose the most crucial information.
The author proposes the CAMEL model as a valuable tool for investors, highlighting five key characteristics that reflect a bank's capabilities This study analyzes historical data from 27 publicly traded commercial banks in Vietnam, uncovering average quarterly price fluctuations influenced by varying historical market conditions and establishing guidelines for share price behavior.
The study analyzes key factors influencing bank performance, including capital adequacy, asset quality, governance, cost of income, and liquidity This research provides a foundational understanding for future investigations into bank stock price fluctuations and serves as a valuable reference for issuers, regulators, and investors.
LITERATURE REVIEW AND THEORETICAL FRAMEWORK - 555cc scssexss 14 1.1 Literature review cece e
Overview of foreign studleS - 6 cà HH HH HT nh Tho TT HH Hàng rệt 14 1.1.2 Overview of research in Vieft'a1m - - - - c1 nh HH 15 1.1.3 Research ỉaD - - 5 HH TH HH TH TT TH TH HH HH TT TT HH HH tư Tư hệt 17 1.2 Theoretical Dasis naa
A study by Cooper et al (2003) analyzed data from US bank holding companies between June 1986 and December 1999, revealing that earnings per share, non-interest income, credit allowance, earnings, equity ratio, and standby letter of credit commitments significantly influence bank shares In contrast, bank size and the book-to-market value ratio showed no significant impact The findings indicate that investors tend to underreact to changes in bank characteristics, contributing to these effects.
According to another study by Al-Shubiri (2010), he conducted a simple and multiple regression analysis on data from 14 banks on the Amman Stock Exchange in
A recent study by Jordan revealed a strong positive correlation between the market price of stocks and the net asset value per share Additionally, it found a notable negative correlation between stock market prices and dividend percentages relative to gross domestic product Furthermore, the research indicated a significant negative relationship between inflation rates and lending interest rates on the Amman Stock Exchange.
Research by Al-Qenae, Li, Mukherjee, Naka (1995), and Wearing (2002) highlights the significant impact of lending interest rates on the economy, particularly through their negative correlation with stock prices High interest rates limit investors' access to capital, ultimately leading to a decline in stock market performance.
A study by Virza Ilham Zaini, Isfenti Sadalia, and Khaira Amalia Fachrudin (2018) investigates the impact of both internal and external factors—such as return on assets, debt to total equity ratio, non-performing loans, and net profit margin—on stock returns in banking companies listed on the Indonesia Stock Exchange, with price to book value serving as a moderating variable.
The study found that inflation, interest rates, the rupiah exchange rate, return on assets, the debt to total equity ratio, non-performing loans, and Net Interest Margin (NIM) significantly and negatively affected stock performance Additionally, inflation, interest rates, and NIM were identified as having a substantial impact on stock returns, while the exchange rate showed an inverse relationship.
ROA, DER, NPL and the type of firm ownership did not have any significant influence on
Research by Girard et al (2010) indicates that bank stocks in 33 emerging and 9 frontier nations are influenced by factors such as size, market value book ratio, and term gap, alongside socioeconomic elements, average GDP, and competitive dynamics Almumani (2014) found that for banks on the Amman Stock Exchange, earnings per share (EPS), book value, price-to-earnings (P/E) ratio, and size significantly affect stock prices Additionally, Uddin et al (2013) analyzed data from 2005 to 2010 to explore factors impacting stock prices of financial companies listed on the Dhaka Stock Exchange.
Exchange (Bangladesh) and come to the conclusion that there is a positive correlation between stock price and net asset value per share, earnings per share, and P/E ratios.
The study by Moeljadi et al (2020) on the Indonesian stock market also examines the elements influencing the firm value (as determined by stock price and stock return) of
Between 2015 and 2018, an analysis of 30 listed banks revealed that the net interest margin (NIM) and the equity to total assets ratio significantly influence stock prices, while showing no effect on stock returns.
Various factors influencing stock prices have been studied, including banking regulations (Pasiouras, Tanna, & Zopounidis, 2008), modifications in dividend policies (Camilleri, Grima, & Grima, 2018), and the business models, funding sources, and financial health indicators of banks (Yin & others).
1.1.2 Overview of research in Vietnam
Studies on the variables influencing the stock prices of banks listed on the Vietnamese stock market have been conducted quite a bit in Vietnam up until this point.
The research conducted by Nguyen Thi Thieu Quang and Ha Xuan Thuy explores the impact of bank characteristics on stock profitability within the context of Vietnam's banking sector during the COVID-19 pandemic, utilizing a Fixed Effects Model for analysis.
(FEM) regression results demonstrate a negative association between liquidity, credit quality, and loan balance and stock price volatility.
In his 2022 study, author Nguyen Phu Ha employed both qualitative and quantitative methods, utilizing panel data and a robust standard error regression model to analyze stock price volatility among 13 listed banks from Q1 2009 to Q4 2020 The research revealed that GDP growth, the consumer price index (CPI), asset efficiency (ROA), and stock beta positively influence stock price volatility, while factors such as the VnIbor interest rate, exchange rate, and non-performing loans (NPL) negatively affect it Additionally, the study identified that the M2 money supply, gold prices, the industrial production index (IIP), stock volatility, equity capital (EquityC), liabilities, return on equity (ROE), and earnings per share (EPS) have varying impacts on the banking sector.
Nguyen Thi Van Hanh and Vo Van Dut (2021) investigated the impact of bank liquidity on stock price volatility using SPV for 17 commercial banks listed on the Vietnam stock market Their study considered factors such as credit risk provisions, P/E ratios, exchange rates, and GDP The findings from the REM regression model revealed that the financial gap (FGAP) positively influences bank stock price volatility Additionally, while total asset volume and exchange rate fluctuations exert opposing effects on bank share prices, significant financial gaps, low liquidity, and high exchange rate volatility contribute to increased stock price fluctuations for these banks.
Research highlights the impact of various factors on financial markets, including the earnings-to-price ratio (EPS), interest rates, exchange rates, gold prices, inflation, investor sentiment, and the effects of COVID-19 These elements complement traditional variables such as company size, value, profitability, stock price trends, and investment strategies.
In their 2022 study, authors Tran Minh Hieu and Nguyen Phuong Linh analyze the banking capacity in Vietnam using the CAMEL model, focusing on Vietcombank's operational soundness and efficiency The research employs the CAMEL analytical framework alongside Basel II standards and regulations set by the State Bank of Vietnam, ultimately providing insightful recommendations for enhancing banking performance.
16 suggestions for enhancing the viability and performance of the Vietcombank company, with the urgent need for pilot projects to increase capital and raise NIM A study from Uyen
Dang (2011) explores whether the CAMEL framework is important for banking oversight.
The CAMEL rating system serves as a valuable supervisory tool in the US; however, it has limitations, particularly in its oversight of Vietnamese banks It fails to adequately consider the interactions with bank management, as well as key factors such as general provisions and loan loss allowance ratios.
Numerous studies have examined the variables affecting bank stock price changes, highlighting the importance of financial indicators; however, these indicators alone fail to provide clear guidance for investors There is a lack of clarity regarding the criteria investors should consider when investing in bank stocks, as existing research does not adequately address the operational characteristics of banks or the impact of state and foreign ownership The differences in ownership types are significant and can influence stock price movements, yet many studies overlook these crucial factors.
Theory of factors affecting Stock Prices 0.0 - (ng TH HH rệt 17
Most investors employ a combination of three key approaches—market sentiment, technical analysis, and fundamental analysis—when making stock selection decisions Rather than relying on just one method, they integrate these techniques to enhance their investment strategies.
17 behavior (Hayat et al., 2011) The three criteria for making specific investment decisions are:
Investors utilizing technical analysis primarily focus on stock valuations, which are derived from essential components of company and value analysis This typical valuation process is crucial for informed investment decisions.
In the initial stage of fundamental analysis, investors assess the economy's growth potential by examining historical data and macroeconomic forecasts for key indicators such as economic growth, inflation, and interest rates This analysis helps them identify industries and businesses with high demand, rapid market expansion opportunities, minimal competition, and stable input costs Subsequently, investors tend to favor established companies known for delivering high-quality products at competitive prices while offering excellent customer service, as noted by Shefrin and Statman (1995) The crucial valuation stage follows, enabling investors to determine whether a stock is overvalued or undervalued, guiding their purchasing decisions effectively.
Investors frequently use the capital asset pricing model (CAPM) to determine the value of a publicly traded company William Sharpe (1964), John Lintner (1965a,b), Jack
Treynor (1962), and Jan Mossin (1966) separately introduced the CAPM, which was based on Harry Markowitz's idea of portfolio diversification The formula of CAPM is:
E(Ri) = Rf + Bi [E(Rm) - Rf]
Where Rf is the risk-free rate of return, Ke is the risk-adjusted fair discount, Rm is the market return, and § is the stock's systematic risk coefficient.
The risk level of the company, financial policies (such as those for paying dividends, borrowing loans, issuing shares, and repurchasing shares), and investment policies (such
18 as spending on investments in buying new assets or investing in projects) are all significant factors that affect discount rates in asset pricing (Fisher, 1930).
In contrast to the Discounted Cash Flow Technique, which attempts to predict the intrinsic value of a stock based on cash flow estimates, discount rates, and growth rates,
Comparative Valuation Techniques enable the assessment of a financial asset's value—such as bonds, stocks, or securities—by analyzing similar assets through relative ratios that influence their value, including income, cash flow, book value, and sales Key variables impacting stock prices include Price/Earnings (P/E), Price/Cash Flow, Price/Book Value, and Price/Sales, with P/E ratios being the most commonly utilized For this method to yield accurate valuation results, the careful selection of comparable organizations is crucial (Vu Phuc Thinh & Nguyen Thu Hien, 2010).
The Liquidation Valuation Method, also known as the asset-based valuation method, evaluates a company by considering it as a collection of assets This approach determines that a company's worth, upon liquidation, equates to the total value of its assets Consequently, the formula used to calculate the company's share price reflects this asset-based valuation.
Share price = (Net Asset Value + Advantage Value) / Total outstanding shares
The net asset value of a business reflects its worth during liquidation; however, investors are primarily interested in the company's future potential rather than its current valuation (Le Minh Loc, Nguyen Thu Hien, 2011).
Fundamental analysis is a widely used method for assessing the intrinsic value of stocks by utilizing corporate data, annual financial statements, and financial indicators to forecast prices and future rates of return Additionally, fundamental analysts must consider both macroeconomic and microeconomic factors that impact stock prices This approach encompasses both quantitative and qualitative market methodologies in stock investment.
Investors should evaluate qualitative factors, as these cannot be precisely quantified, to make informed decisions Key elements to consider include the potential for future industry growth, the type of business, competitive advantages, associated risks, and the vision for management and governance.
It is the examination and assessment of the financial indicators displayed in the company's financial statements.
The key objectives for evaluating a company's financial health include growth in sales and profits, return on assets (ROA), return on equity (ROE), return on invested capital (ROIC), net profit margin, earnings per share (EPS), and extraordinary earnings These metrics reflect the company's profitability in its operations, enabling investors to identify strong fundamental stocks that offer potential for long-term gains when assessed with the appropriate percentages.
Understanding a company's assets and capital sources, such as capital structure, asset structure, working capital, and debt ratio, is crucial for investors assessing its financial strength Firms with substantial capital can lead their industries by investing significantly in advertising, product development, and innovation As investor confidence grows, the stock prices of these well-capitalized companies tend to increase steadily.
Understanding the cost of capital, dividend policy, and free cash flow is crucial for evaluating a company's investment strategies By analyzing cash flow, investors gain insights into the company's operational activities and future investment potential This analysis enables investors to select shares from companies that align with their preferred business plans.
The Market Price Index P/E and P/B are essential tools for investors seeking undervalued stocks, enabling them to identify potential businesses that are priced below their true worth Utilizing these indices can lead to informed trading decisions and significant profits.
A long-term stockholder who wishes to invest should use fundamental analysis.
When using fundamental analysis in investment, there are numerous prosperous stock billionaires like Warren Buffett, Peter Lynch, and others The benefit of fundamental
Analyzing financial statements is crucial for investors as it helps them understand various business aspects, especially the company's intrinsic value, while also shielding them from the effects of short-term market fluctuations.
Investor mindset greatly influences behavior, with venture capitalists often opting for high-risk, high-return stocks In contrast, prudent investors typically prefer medium-sized, stable, and low-risk securities, showing little interest in expensive stocks.
The behavioral finance hypothesis by economist Eugene Fama explores investor psychology, highlighting factors such as exaggeration, regret, fear of failure, cognitive inconsistencies, and crowd psychology These elements can drive even skilled investors to behave irrationally, often resulting in unrealistic market growth expectations or prolonged retention of losing stocks Furthermore, psychological factors like awareness, age, and gender significantly influence investment decisions.
Theoretical foundations of commercial banks and shares of commercial banks
A commercial bank is a specialized financial institution that engages with various businesses, organizations, and individuals by collecting deposits to mobilize capital This capital is then utilized to provide loans, facilitate discount transactions, offer payment solutions, and deliver a range of banking services to clients within the economy.
In contrast to non-bank credit organizations, which are limited to a legal capital of 500 billion VND and an operational period of 50 years as per Decree 10/2011, banks enjoy a much wider operational scope, conducting all banking activities within the framework established by the Credit Law.
A commercial bank, as defined in Clause 3 of Article 4 of the Law on Credit Institutions of 2010, is a financial institution authorized to engage in a wide range of banking and business activities aimed at generating profit According to Clause 12 of the same article, banking activities encompass the regular business and provision of various financial operations.
A commercial bank serves as a financial intermediary that facilitates economic growth by receiving deposits, granting credit, and providing payment services through accounts Its primary role is to trade in money for profit, mobilizing capital and ensuring prudent allocation through lending and investment activities Furthermore, commercial banks are utilized by the State Bank to implement and manage macroeconomic regulation programs effectively.
Bank stock refers to equity investments issued by banks, where shareholders are individuals who buy shares in the bank When banks are listed on the stock market, they exhibit distinct characteristics that set them apart from other industries.
- Money and services related to money are business banking goods;
- Banks exert significant influence over other economic sectors;
- They are strictly governed by the government, which makes their equitization extremely reputable and transparent;
- And their capitalization rate has accounted for the capitalization of the entire stock market.
The bank, known for its strong reputation and transparency, is rigorously managed by the State, making its stocks an appealing investment option for both domestic and foreign investors.
Overview of Banking Capacity . - - Gà HH HH HT HT TH TT Hà Hàn HH giết 24
According to Budisantoso and Triandaru (2005), the definition of a bank's capacity is very broad because it encompasses a bank's ability to be healthy enough to conduct all of
To ensure compliance with applicable regulations, banks must effectively manage their operations and fulfill their obligations, including the ability to raise funds from the public and other organizations The bank's capacity is determined through a comprehensive qualitative and quantitative analysis of factors influencing its performance, such as risk profile characteristics, corporate governance, earnings, capital, and assets This evaluation includes a quantitative assessment of the bank's financial ratios, alongside a qualitative review of the elements that impact these results, including risk management practices and compliance measures Ultimately, financial indicators serve as key indicators of an organization's operational capacity.
1.2.3.1 Models for assessing organizational capacity
Various models are utilized to assess organizational effectiveness and capability, including Moody's scale, which evaluates companies based on their risk and ability to meet interest payments, making its ratings crucial for global investors Additionally, Japan's FIRST bank rating model incorporates ten criteria such as business management and comprehensive risk management, placing greater emphasis on non-financial management issues In contrast, the CAMEL model focuses on financial statements, highlighting capital analysis, asset quality, management, profitability, and liquidity.
Since 2006, the CAMEL framework has been utilized in the Vietnamese financial sector, offering a highly objective and straightforward method for assessing banking performance over time This model is particularly beneficial for investors, providing reliable indicators that can serve as a foundation for making informed stock purchase decisions By adopting CAMEL, the Vietnamese banking system can effectively monitor and address risks in its activities.
1.2.3.2 Banking capacity according to CAMEL model
The CAMEL analysis model, developed and researched by the IMF, has been widely adopted by nations worldwide to assess the banking system's performance and capability (Tran Minh Hieu, Nguyen Phuong Linh, 2022) This framework utilizes criteria derived from the income statement, making it an effective tool for evaluating banks' financial health Scholars such as B Nimalathasan (2008) and Tesfasion Sahlu Desta have contributed to the understanding and application of this model in banking analysis.
(2016), Nguyen Dang Don (2010), and Phan Thi Cuc (2009) in Vietnam, employ a wide range of measures to gauge the performance of the bank.
CAMEL stands for 5 factors: C (Capital Adequacy) - A (Asset quality) - M (Management ability) - E (Earning) - L (Liquidity).
Capital adequacy refers to a bank's capacity to generate sufficient capital to sustain its operations Ensuring that financial institutions have adequate and readily available capital is essential for assessing their resilience against potential shocks or pressures on their balance sheets.
Adequate capital adequacy ratios are crucial for financial institutions, as they help mitigate significant challenges faced in the industry (Nguyen Thi Canh, 2009) During tough economic times, fluctuations in share prices become more pronounced when capital adequacy ratios are closely monitored (Nguyen Phu Ha, 2023) Currently, the minimum capital adequacy ratio stands at 8%, in line with Basel requirements.
Capital adequacy ratio (CAR), Owner's equity/total assets, and Payables/ Owner’s equity are indicators of capital adequacy.
Asset quality is an expenditure that summarizes the financial sustainability, profitability and management capacity of the bank (Tran Minh Hieu, Nguyen Phuong Linh,
The trajectory of asset quality serves as a critical indicator for share prices, with investors confident that banks will achieve sustainable profit growth over the long term if there is a genuine enhancement in asset quality (VnDirect Research, 2023).
Indicators representing asset quality: NPL ratio; Allowance for credit losses; Credit risk weight.
The effectiveness and safety of banking operations, along with the bank's reputation, rely heavily on the managerial skills of its leaders Strong governance enhances a bank's performance, boosts shareholder value, and protects the rights of small shareholders and stakeholders Consequently, this leads to an increase in the company's share value, attracting both major and minor external capital sources.
Measures of managerial effectiveness include the Cost-to-income ratio and the Profit- after-tax ratio for each employee.
The survival of a business hinges on its profitability, as investors expect substantial returns based on a company's financial performance Profit maximization is essential for commercial banks, significantly influencing their performance, market position, and share According to Balasundaram N (2009), profit analysis is fundamental for guiding investors' decisions.
The ratios show the index of income and profit: Interest Margin Ratio (NIM), Return on Equity (ROE), and Return on Total Assets (ROA).
Liquidity in commercial banks refers to their capacity to fulfill immediate cash requirements, including deposit withdrawals, disbursing committed credits, and covering operating expenses or other financial obligations It serves as a crucial criterion for assessing the quality and stability of a bank's operations, ensuring that customer withdrawal demands are met efficiently.
27 met by banks that lose liquidity, which will undermine their faith At the same time that requests for credits cannot be granted.
Representative costs include the Cash Reserve Ratio and the Loans to Deposits (LDR) ratio.
RESEARCH METHODOLOGY 5 + 21 19121 911511 1103 T1 TH TH TH nghệ 29 2.1, Research Gesign oo ố 29 2.2 Research sample and data collection method - - 5 55 55 2+ *E*EEseEeereeeeereereexee 30 2.3 Research me ÌS - 6 1 St 219119119020 HH HH HT TT TH HH HH HH hờ 30 2.4 Description of the research variaÌ;; - - - SH TH TH TH TH ng Hưng rry 32
The research process consists of three key steps: First, the author identifies the problem through market research, reviewing various articles and news sources Next, the author selects the research variables and appropriate model based on the gathered overview Finally, secondary data is collected and analyzed, leading to synthesized results and tailored recommendations for the Vietnam market.
2.2 Research sample and data collection method
The study draws on secondary data sources, specifically historical information on the financial metrics of 27 commercial banks listed over a ten-year period from 2013 to
In 2023, the Vietnamese stock markets, including HOSE, HNX, and UPCOM, have shown significant trends based on quarterly data sourced from the FinnPro database The financial statement parameters of various banks are presented in an aggregate structure, although the data is imbalanced due to discrepancies in short-term financial reports from certain commercial banks during the data collection process This imbalance reflects varying quantities of crossover units across multiple time periods, highlighting the challenges in data accuracy and consistency within the banking sector.
The author analyzes historical data for banks listed on the exchange for less than 10 years, focusing on a 10-year period from their listing date This study encompasses a dataset of 27 bank stocks, yielding a total of 502 observations.
The author conducts quantitative research utilizing descriptive statistical methods and regression analysis to investigate the factors affecting stock price volatility in Vietnam's joint stock commercial banks The derived equation effectively captures the relationship between the dependent and independent variables, allowing for realistic and accurate estimations By leveraging known values of independent variables, this model enables predictions of the dependent variable, enhancing the understanding of stock price dynamics in the banking sector.
Random sampling, also known as probability sampling, is an efficient technique that ensures all units have an equal chance of being selected This method requires less effort compared to other sampling approaches and is designed to produce a sample that accurately represents the study population.
In order to get the sample size n for a regression model, Tabachnick & Fidell (2007) state that the formula n 50 + 8p (p: number of independent variables) should be used Thus,
Research indicates that a sample size of at least 90 is necessary for effective studies, while a sample of 502 observations significantly enhances the accuracy of forecasts Larger sample sizes yield more reliable results, underscoring the importance of robust data in research.
The author utilizes SPSS to conduct descriptive statistics, effectively summarizing a dataset through numerical and visual representations Key statistical measures, including the mean and standard deviation, along with histograms, are employed to provide a comprehensive overview of the research sample.
Multivariate regression is essential for addressing various economic challenges, as economic indicators are influenced simultaneously by multiple positive and negative factors Additionally, these factors exhibit intrinsic linear correlations with one another Regression analysis enables the re-evaluation of hypotheses regarding these influencing factors and quantifies their relationships, laying the groundwork for predictive analysis and informed decision-making that fosters economic growth.
Multiple Linear Regression (MLR) offers the advantage of utilizing historical research data to delineate the study's scope, ensuring a robust foundation for analysis This method is particularly effective for analyzing multi-sample data files, providing high accuracy in its predictions The multivariable regression equation can be represented in linear form as: y = 80 + B1X1 + B2X2 + B3X3 + + BiXi + E.
- Bi are the slopes of the equation according to the variables Xi
- Xiare the variables (influential factors)
The author tested the model for 5 flaws before creating the multivariable regression model, including:
The F ratio, or F statistic, is a key component in analysis of variance (ANOVA) used to evaluate the differences between the mean values of multiple data groups It measures the model's fit by calculating the variance between groups and subtracting the within-group variance A high F value, coupled with a p-value of less than 0.05, indicates that the mean values are significantly different.
The significance of the independent variable is evaluated using the coefficient R², with values closer to 1 indicating a more robust model, while those near 0 suggest lower significance Additionally, the Durbin-Watson index is employed to test first-order series autocorrelation, ranging from 0 to 4; values approaching 0 indicate positive residual correlation, whereas those nearing 4 suggest negative residual correlation.
The variance magnification factor VIF calculates the multicollinearity test.
Multicollinearity occurs when independent variables in a dataset exhibit a strong correlation, causing distortion in various quantitative indicators To assess multicollinearity, the Variance Inflation Factor (VIF) can be calculated using the formula VIF = 1 / (1 - Ri)² A VIF value greater than 2 indicates the presence of multicollinearity.
To evaluate the partial correlation of regression coefficients, it's essential to consider the significance level (Sig.) A significance level exceeding 5% indicates that there is no statistically significant relationship between the independent variables and the dependent variable, suggesting a lack of correlation among the variables.
Finally, the histogram of the normalized residual frequency is used by the author to verify the residuals’ normal distribution.
2.4 Description of the research variable;
Stock Price Volatility (SPV) is the variation, rise or fall in price by measuring the distance between a security's highest and lowest price around the average price for a
The average price coefficient over a 32-period timeframe reflects the extent of stock price variations, with greater fluctuations leading to a higher coefficient and subtle changes resulting in a lower one This study utilizes the marginal value approach introduced by Parkinson in 1980 to assess stock price changes Subsequent research, including works by Baskin (1989), Allen & Rachim (1996), Rashid & Rahman (2009), Nazir et al (2010), Khan (2012), and Vinh (2014), has adopted this methodology for analyzing stock price movements.
Accordingly, the formula for calculating stock price fluctuations is:
In which: Hi and Li are the highest and lowest prices of the year.
The capital adequacy ratio is a crucial metric for central banks to assess the financial stability of banks If a bank is deemed insecure and unable to operate normally, the central bank is obligated to mandate its closure.
Banks are required to consistently maintain a CAR of at least 8% in accordance with
Circular 41/2016/TT-NHNN, which is calculated using the following formula: c CAR = x 100%
- RWA: Total assets based on credit risk;
- KOR: Capital required for operational risk;
- KMR: Capital required for market risk.
Capital adequacy ratio is directly proportional to the bank's resilience to crisis situations, so investors prefer banks with good capital adequacy ratio (Sangmi &
Hypothesis 1 (H1): CAR has a positive relationship with bank stock price volatility.
Owner's Equity/Total Assets (OE/TA)