The effect of accounting information on share prices of companies listed on ho chi minh stock exchange

INTRODUCTION

The necessity of the topic

Since its establishment on July 11, 1998, the Vietnamese stock market has significantly attracted both domestic and foreign capital, contributing to positive economic transformations As of December 31, 2022, the Ho Chi Minh Stock Exchange (HOSE) reported a remarkable increase in listed companies, rising to 388 from just 5 in 2000 Over the past five years, the VN-Index has fluctuated, dipping below 900 points at times, reflecting the dynamic nature of the market favored by investors.

In 2018, stock market indices were around 1,500 points, but this figure dropped to below 1,000 points by December 31, 2022 Accounting information plays a crucial role in influencing investors' decisions in the stock market, as it serves as a key basis for evaluating listed companies' financial health This information, which adheres to Vietnamese Accounting Standards and is audited by reputable firms, effectively measures business performance Investors rely heavily on annual and quarterly financial statements to make informed investment choices The connection between accounting data and stock prices has garnered significant interest from scholars, with Ohlson's (1995) model providing a theoretical framework for understanding this relationship Numerous studies, including those by MSA Mondal and MS Imran (2010), have explored how various types of accounting information impact share prices.

Liquidity, financial leverage, profit, growth, size, and dividend rate significantly impact the share prices of companies listed on the Dhaka Stock Exchange In contrast, Nguyen Thi Thuc Doan (2011) found that earnings per share and return on equity are key factors influencing share prices in Vietnam's stock market.

The significance of accounting information is highlighted by regulations such as Circular 155/2015/TT-BTC, which replaced Circular 52/2012/TT-BTC to enhance market transparency This issue has become increasingly critical in Vietnam's stock market, possessing both theoretical and practical relevance today Consequently, the author has chosen to explore the topic: "The Effect of Accounting Information on Share Prices of Companies Listed on the Ho Chi Minh Stock Exchange."

Research objectives

This research aims to analyze the factors influencing share prices of companies listed on the Ho Chi Minh City Stock Exchange (HOSE) and offers recommendations to enhance the quality of accounting information presented in financial statements.

- Assessing factors affecting the stock price volatility of companies listed on HOSE

- Analyze the influence of each factor on stock price fluctuations in the period 2018-2022

- Based on mentioned situation analysis, the thesis proposed some recommendations to increase the stability of stock prices of listed companies, towards the sustainability of the stock market.

Research questions

Question 1: What are the determining factors affecting share prices of listed companies on HOSE?

Question 2: How is the impact of factors on share prices of listed companies on

Question 3: What conclusions can be drawn from the evaluation results?

Object and scope of the study

This study investigates how accounting information influences the share prices of companies listed on the Ho Chi Minh Stock Exchange (HOSE) Key metrics analyzed include Earnings per Share (EPS), Book Value per Share (BVPS), Dividend per Share (DPS), Return on Assets (ROA), Return on Equity (ROE), Financial Leverage (FL), Firm Size (SIZE), and the Price-to-Earnings Ratio (P/E) Understanding these relationships is crucial for investors seeking to make informed decisions in the stock market.

In this research, a select group of firms listed on the HOSE was identified, specifically excluding companies in the finance sector, including securities firms, banks, insurance companies, and investment funds This exclusion was necessary as the characteristics of these financial institutions do not align with the objectives of the study.

The study analyzed data from annual financial statements spanning five years (2018-2022) to investigate the dramatic fluctuations in stock prices on the HOSE, which occurred before, during, and after the Covid-19 pandemic.

Research methodology

Quantitative method is applied in the thesis

This study investigates the correlation between the market price of shares as of December 31 and various independent variables, drawing insights from recent research by Hatta and Dwiyanto (2012), Al-Malkawi et al (2018), and Dang Tran Hung et al (2022) The methodology incorporates scales established in prior studies, notably those by Ohlson (1995) and Aboody et al (2002), to ensure a robust analytical framework.

- Data collection: Collect annual reports of enterprises listed on HOSE and published on the website cafef.vn

The study employs descriptive statistical methods and correlation analysis to examine the relationships and significance of independent variables measured by the scale, utilizing a multiple linear regression model These analyses are conducted using STATA 17.0 software.

Significance of research

This research aims to codify accounting data that affects stock prices and synthesize previous studies to propose an effective model for assessing the impact of accounting information on share prices By providing insights into how accounting data influences market trends, this study will assist investors in predicting stock market movements, ultimately enhancing investment efficiency and increasing returns.

Scientific significance: Providing clear evidences showing the influence of accounting information to share prices of listed enterprises on HOSE.

Structure of the themes

Chapter 2: Literature review and theorical foundations

This chapter emphasizes the urgency, objectives, scope, and importance of the research The subsequent chapter will provide a detailed review of various theoretical foundations and scientific studies.

LITERATURE REVIEW AND THEORICAL FRAMEWORK 6 2.1 Previous studies

Foreign studies

Mondal and Imran (2010): “Determinants of Stock Price: A Case Study On

The study on the Dhaka Stock Exchange employed both qualitative and quantitative methods, utilizing a linear regression model to analyze primary data collected from 55 investors through questionnaires, alongside secondary data from the annual financial reports of three listed companies The research highlighted that share prices are influenced by quantitative factors such as cash flows from operations (CFO), debt-to-equity ratio (FL), return on investment (ROI), company size (SIZE), growth (GROWTH), and dividend rate (DR), as well as qualitative factors like rumors, market sentiment, and goodwill However, due to the short reporting period, the author was unable to determine the long-term effects of accounting data on stock prices.

Hatta and Dwiyanto (2012) conducted a study examining the impact of fundamental company factors and systematic risk on stock prices of listed companies on the Indonesian Stock Exchange (IDX) from 2002 to 2006 Utilizing a quantitative approach with pooled and panel data, the research employed regression analysis alongside the McKinnon, White, and Davidson (MWD) test, specifically using a linear-log model The sample comprised 17 companies, with the research framework largely influenced by the work of Seetharaman and Raj.

In a study by Al-Dini et al (2011), various financial metrics were analyzed to determine their impact on stock prices, identifying earnings per share (EPS), last-year stock prices (HSM), price-to-earnings ratio (PER), return on assets (ROA), and dividend payout ratio (DPR) as independent variables positively influencing stock prices Conversely, other factors, including the debt-to-equity ratio (FL) and net profit margin (NPM), exhibited negative effects However, the research faced limitations due to a small sample size, as it only included companies that paid cash dividends during the observation period, potentially undermining the study's reliability.

Asiri and Hameed (2014) investigated the impact of financial ratios on the market value of 44 firms listed on the Bahrain Stock Exchange from 1995 to 2003 The study focused on the firm's market value as the dependent variable, analyzing various financial ratios as independent variables through four models, including general, size, sector, and lag effects A stepwise regression technique was employed to assess how Return on Assets (ROA), Financial Leverage (FL), firm size, and beta influence stock prices, categorizing companies based on Tobin's Q into highly valued and less valued groups The findings revealed that ROA is the most significant determinant of share prices, followed by FL, firm size, and beta However, the study's clarity was diminished due to the exclusion of several companies resulting from data unavailability.

Al-Malkawi et al (2018) investigated the impact of accounting fundamentals on market prices of shares (MPS) in the MENA region from 2000 to 2015, utilizing a panel data regression model and Feasible Generalized Least Squares (FGLS) with a sample of 217 companies The study, grounded in The Ohlson Model, identified nine independent variables: ROE, BVPS, DPS, EPS, Dividend Yield (DY), PER, Debt to Total Assets (DEBT), SIZE, and Financial Crisis (CRISIS), with MPS as the dependent variable Findings indicated that ROE, BVPS, DPS, EPS, PER, and SIZE had significant positive effects on MPS, although the data sourced from third parties may not be entirely accurate, and the impact of the financial crisis was not examined during the research period.

Studies in Vietnam

Nguyen Thi Thuc Doan (2011) conducted a study titled “The Influence of Accounting Information and Financial Indicators on Stock Prices in the Vietnamese Stock Market,” focusing on the impact of accounting data on the share prices of listed companies in 2009 The research analyzed audited financial statements from 474 companies, utilizing a quantitative method with a regression model Key independent variables included Earnings Per Share (EPS), Book Value Per Share (BVPS), Return on Equity (ROE), and Financial Leverage (FL), while the dependent variable was the market share price The findings indicated that both EPS and ROE positively influenced share prices However, the study's limitations included the use of data from only one year, which restricted the analysis of variable fluctuations over time, as well as a limited number of independent variables.

Dang Ngoc Hung et al (2018) investigated the impact of accounting information on the stock prices of energy companies listed on Vietnam's stock market from 2006 to 2016, analyzing data from 44 annual financial statements Utilizing a quantile regression model developed by Koenker and Bassett in 1985, the study measured the effects of Return on Assets (ROA), capital structure (LV), company size (SIZE), current ratio (CR), and accounts receivables turnover (TURNOVER) The findings revealed that ROA, SIZE, CR, and TURNOVER positively influenced stock prices, while LV served as an independent variable However, the research's focus on energy companies limits its applicability, as it did not consider firms from other sectors in Vietnam.

Do Thi My and Nguyen Thu Hien (2021) conducted a study titled “Influence of Accounting Information on Share Price of Listed Companies on the Vietnam Stock Market,” analyzing a sample of 239 listed companies from 2015 to 2019 Utilizing a quantitative research approach, the authors employed methods such as Pooled OLS, FEM, REM, and FGLS The research model was based on the Ohlson Model, with additional modifications to enhance its applicability.

This research analyzed six financial indicators—EPS, BVPS, DPS, SIZE, PER, ROE, SALEGROWTH, and the debt to assets ratio (DAR)—to determine their impact on stock prices The findings revealed that while DAR negatively affected share prices, EPS, BVPS, SIZE, and SALEGROWTH positively influenced them, with a significance level of 1% It is important to note that the study exclusively examined companies listed on HOSE and did not disclose the specific companies involved in the analysis.

In the study "Relationships between Accounting Information on the Business Financial Statements and the Stock Price: A Study with LASSO Method" by Dang Ngoc Hung et al (2022), the authors investigated the impact of accounting information on the stock prices of Vietnamese listed companies from 2008 to 2019 Utilizing a quantitative research approach and the LASSO method, they analyzed 52 financial indicators derived from company financial statements The research model was grounded in the Ohlson Model and Aboody et al (2002), with stock prices as the dependent variable and accounting information as the independent variable Key findings revealed that book value per share (BVPS), company size (SIZE), return on assets (ROA), earnings per share (EPS), gross profit margin, and current ratio (CR) positively influenced share prices, although the overall correlation was weak, explaining only 25% to 30% of the variance.

Author Period Objective Research model

2010 The determinan ts of stock price of some listed companies on DSE

DR = α1+ β1CFO + β2DER + β3ROI + β4 G+ β5S+ β6DR + ui

3 Question naire and multiple linear regressio n model

Stock price can be correlated by many factors such as cash flows, leverage, ROI, SIZE, growth, and dividend rate

Factors and systematic risk affecting stock price of companies on ISE

17 Single- dex model, regressio n analysis, MWD test and log linear model

Stock price and EPS have a strong positive relation, following by PER and HSM

NPM and DER affect negatively

Financial ratios and firm‘s value in the Bahrain Bourse

Mvit = β0 + β1 D/Tait + β2 TA T/oit + β3 ROAit + β4 ROEit + β5 Flit + β6 Crit+ β7 TIEit + β8 Betait + β9 IT/oit + β10Tait

44 Cross- section- time- series analysis, stepwise multiple regressio n

ROA, FL, beta have positive impacts on stock prices

The effect of company fundament als on stock prices:

MPS = ϕ + Φ1ROE + Φ2BVPS + Φ3DPS + Φ4EPS + Φ5DYYE ILD + Φ6PER + Φ7DEBT + Φ8SIZE + Φ9CRISI

MPS is positively affected by ROE, BVPS, DPS, EPS, PER, SIZE while DYYEILD affects negatively

2009 The effect of accounting informatio n and financial ratios on stock prices in Vietnam

Pit+60 α + β1Bvit + β2EPSit + εit; Pit

EPS and ROE have positive relationshi ps with stock price

The influence of accounting informatio n on stock prices of companies listed on Vietnam‘s stock market

Pit = β0 + β1Roait + β2Lvit + β3Sizeit + β4Crit + β5Returni t + uit

44 OLS and quantile regressio n models

ER have positive relationshi ps with stock price

The impact of accounting informatio n on share prices of listed companies in Vietnam

P = α0 + α1EPS + α2BVPS + α3DPS + α4 SIZE + α5P/E + α6 ROE + α7SALE GROWT

SALEGRO WTH, EPS, DAR, BVPS, SIZE have positive correlation with share prices

Relationshi ps between accounting informatio n and stock prices with LASSO method

Priceit β0 + β1kAcco unting Informati onit + uit

Compan ies listed on HOSE

BVPS, SIZE, ROA, EPS, gross profit margin,

CR is favorably correlate with share prices

Table 2.1 Summary of previous studies

Determination of research gap

By reviewing the previous studies, there are certain ―gaps‖ are presented as follows:

Research on the connection between accounting information and share prices of listed companies has predominantly been conducted in countries like Dhaka, Indonesia, and Bahrain In contrast, studies focusing on this topic in Vietnam have only emerged in recent years, resulting in a limited number of investigations.

Research on the accounting factors influencing share prices remains inconsistent due to variations in stock markets, time periods, measurement methods, and sample sizes chosen by different authors.

Research on how accounting information influences the share prices of listed companies has been conducted for many years However, in today's increasingly volatile world, stock markets experience significant fluctuations, which can lead to varying research outcomes over time This highlights the need for updated studies to provide the most current insights on this topic.

General problems of annual financial statements

According to VAS 01, as stated in Decision No 165/2002/QD-BTC, financial statements provide insights into a company's financial health by categorizing business and financial activities based on their economic characteristics Key components in assessing financial status include assets, liabilities, and owners' equity, which are essential for evaluating an enterprise's situation Additionally, income statements focus on revenues, other incomes, expenses, and earnings, all of which contribute to a comprehensive performance assessment.

Pursuant Article 100 of Circular No 200/2014/TT-BTC dated December 22,

2014 of Ministry of Finance, ―a complete financial statement comprises: the balance sheet; the income statement, the cash flow statement, notes to the financial statements‖

A balance sheet is a comprehensive report that presents the total value of a company's assets and their sources at a specific point in time It details the value of the enterprise's assets, highlighting both the asset structure and the capital sources that contribute to those assets, as outlined in Article 112 of Circular No 200/2014/TT-BTC.

The income statement provides a comprehensive overview of a company's financial performance, detailing outcomes from its core business operations as well as from financial and other related activities, as outlined in Article 113 of Circular No 200/2014/TT-BTC.

The cash flow statement offers crucial insights for users to assess changes in net assets, financial structure, and the convertibility of assets into cash It highlights the entity's solvency and operational cash flow generation capabilities Furthermore, it enhances the objective evaluation of business performance and facilitates comparability across enterprises by mitigating the impact of varying accounting methods.

Notes to financial statements are essential for interpreting and analyzing the information found in the balance sheet, income statement, and cash flow statement, as well as other relevant details mandated by specific accounting standards, such as Article 115 of Circular No 200/2014/TT-BTC.

The annual financial statement serves to inform business owners, regulatory agencies, and users about the financial position, trading performance, and cash flows necessary for economic decision-making It must detail essential components such as assets, liabilities, equity, revenue, other income, production and business costs, expenses, profit, loss, income distribution, and cash flows, as outlined in Article 97 of Circular No 200/2014/TT-BTC.

2.2.3 Time for submitting and publishing

Pursuant Article 109 of Circular No 200/2014/TT-BTC dated December 22,

State-owned companies are required to submit their annual statements within 30 days following the end of the fiscal year Parent companies and state-owned corporations must ensure their submissions are completed no later than 90 days after the fiscal year concludes.

Sole proprietorships and partnerships are required to submit their annual statements within 30 days after the end of the fiscal year, while other accounting entities must do so within 90 days.

According to Article 8 of Circular 155/2015/TT-BTC issued by the Ministry of Finance on October 6, 2015, publicly traded companies are required to publish their audited annual financial statements within 10 days of the audit report's signing, and no later than 90 days after the fiscal year ends This information must be disclosed through various channels, including the company's publications, electronic information pages, and the State Securities Commission and Stock Exchange's information platforms Additionally, companies must archive this data, both in written and electronic formats, for a minimum of ten years at their headquarters for investor access.

2.2.4 The role of accounting information on financial statements

According to the Law on Accounting No 88/2015/QH13, the primary goal of financial reports is to deliver reliable accounting information processed by the accounting system This information must be factual, legally compliant, and trustworthy Essential to valuable accounting information are clear, complete, timely, and accurate accounting vouchers.

In accordance with paragraphs 9 – 11 of AASB Framework, accounting information plays different roles depending on the groups of users:

Investors/ Shareholders: Helps them determine whether they should buy, hold or sell the stocks, and assess the ability of the entity to pay dividends

Lenders: Enables them to determine whether their loans and interest will be paid when due

Employees: Enables them to assess the ability of providing salary, job opportunities or retirement benefits

Customers: Helps them choose to involve or be dependent on

Suppliers and other trade creditors: Helps them determine whether amounts owing to them will be paid when due

The Government: Allows them to regulate the activities of the enterprises, implementing tax policies, determine national income and other statistics

The Public: Assists the public by providing the trends and developments in the prosperity of the entity and the range of its activities.

Stock market and stock

Pursuant Clause 27 Article 4 of Law on Securities No 54/2019/QH14,

The securities market is a platform for trading securities, encompassing various methods of information exchange According to Dao Le Minh (2009), it includes both centralized and decentralized markets In contrast, a stock exchange is a specific, organized venue where individuals and organizations execute buy and sell orders for securities.

Dao Le Minh (2002) and Bui Kim Yen (2013) claim that securities market usually has 5 main functions:

The primary function of the stock market is to mobilize investment capital for the economy, allowing both governments and businesses to raise funds by issuing stocks and bonds Enterprises utilize this capital to finance production and business projects, whereas governments attract private sector investment to support public initiatives.

The stock market creates a favorable investment environment for both institutional and individual investors, offering a wide array of financial opportunities With numerous stocks listed, investors can choose from a variety of options, each featuring distinct characteristics, risks, and potential returns.

Creating liquidity for securities is a key advantage of the stock market, allowing investors to easily convert their stock investments into cash with minimal costs This high liquidity is appealing to investors, as it enables flexible capital flow between financial assets and cash, enhancing the overall investment experience.

Evaluating company activities is crucial in the stock market, which mandates transparency in financial and operational practices Stock Exchange regulations require enterprises to publicly disclose information that accurately reflects their operational status, facilitating easy review and assessment for investors.

Creating a conducive environment enables governments to effectively implement macroeconomic policies The stock market acts as an expectation market, where stock price fluctuations and overall market indices swiftly respond to changes in the macroeconomic landscape Through transactions involving the buying and selling of government bonds and the execution of monetary policy, governments can regulate the economy with flexibility and efficiency.

Securities are financial assets in the stock market that generate income and can be sold for cash when needed According to Clause 01, Article 04 of the Law on Securities No 54/2019/QH14, securities include shares, bonds, fund certificates, warranties, covered warrants, rights to buy shares, depository certificates, derivatives, and other types defined by the Government.

Persuant Clause 02 Article 04 of Law on Securities No 54/2019/QH14,

“Shares are securities that certify their holders’ lawful rights and interests to a portion of share capital of the issuer”

When investors purchase shares, they become partial owners of the company, with their level of ownership determined by the percentage of shares they hold As co-owners, shareholders share in the company's profits and losses In the event of bankruptcy or liquidation, they are entitled to any remaining assets after the company settles its obligations, including taxes, debts, and payments to bondholders (Mishkin, F S 1992).

The face value of a publicly offered share or fund certificate is set at 10,000 VND, serving as a crucial figure in accounting and determining an enterprise's value during initial capital mobilization For newly established businesses, this nominal value represents the minimum amount received for each issued share, as outlined in Clause 2 of Article 13 of the Law on Securities No 54/2019/QH14.

The book value represents the share price documented in a company's accounting records, indicating its share capital status at a specific moment Essentially, the book value of a stock is synonymous with the net asset value per share.

Intrinsic value is determined by analyzing a company's dividends, prevailing market interest rates, and its growth potential, which together help establish the stock's true current worth.

Market value refers to the current worth of common stock, based on the most recent transaction This value is not set by the company but is influenced by the price sellers are willing to accept and the amount buyers are prepared to pay Essentially, market value is shaped by the dynamics of supply and demand, leading to frequent fluctuations in stock prices.

Related theories

Agency theory posits that a representative relationship exists when one or more parties, known as agents, perform tasks on behalf of another party, typically the shareholders (Jensen & Meckling, 1976) This relationship often leads to conflicts of interest, as managers, who operate the firm, may prioritize maximizing their own compensation over the shareholders' goal of increasing company value Such discrepancies create risks that can result in suboptimal business performance, ultimately harming investors Since shareholders do not actively manage the companies, they face challenges in accessing critical information, making them reliant on managers, who may provide misleading disclosures or fail to report costs accurately As a result, the financial accounting information may become untrustworthy, undermining the interests of shareholders.

The efficient market theory, proposed by Eugene Fama in 1970, posits that financial markets function efficiently and transparently, where security price fluctuations reflect all available public information simultaneously As a result, investors are unable to achieve profits based solely on publicly available information, indicating that it is not possible to outperform or "beat" the market.

The three primary hypotheses in finance are the weak form, semi-strong form, and strong form The weak form hypothesis asserts that stock prices at any given moment incorporate all publicly available information, meaning that investors cannot leverage this information to achieve profits in the stock market.

The semi-strong hypothesis asserts that stock prices are influenced not only by existing published information but also by newly released data, reacting instantaneously to such information Consequently, this theory suggests that investors are unable to leverage available information to gain an advantage in the market, as they cannot buy stocks at lower prices or sell them at higher prices based on publicly accessible information.

The strong form hypothesis emphasizes the efficiency of financial markets by asserting that, at any given moment, stock prices incorporate all relevant information, including past, present, and internal data of the company.

Signaling theory explains the interaction between two parties where one possesses information and communicates it to the market, while the other party utilizes that information This theory posits that the intentional disclosure of information influences stock prices, as managers typically have more insights than investors Ultimately, signaling theory seeks to mitigate the information asymmetry between those who have knowledge and those who require it (Bhattacharya, 1979; Aharony & Swaly, 1980; Asquith & Mullins, 1983).

This theory posits that financial statements serve as reliable and transparent signals for the stock market, enhancing investor confidence through robust internal control activities and the expertise of qualified accountants, alongside adherence to tax and legal regulations Such measures aim to improve the reliability and accuracy of information, ultimately elevating the quality of financial statements.

The Bird-in-Hand Theory, developed by John Litner in 1962 and Myron Gordon in 1963, posits that investment returns are never entirely certain in financial markets due to inherent information asymmetries, particularly in how dividends and retained earnings are valued The theory emphasizes the idea that "one bird in the hand (dividend) is worth more than two in the bush (capital gain)," illustrating that investors tend to favor the safety and certainty of dividends over the uncertain potential of capital gains, even when companies promise higher future returns.

The Random Walk Hypothesis, introduced by Maurice Kendall in 1953, posits that stock price movements are inherently unpredictable, with fluctuations occurring independently of one another This theory suggests that historical stock price trends cannot effectively forecast future movements, challenging previous market forecasting models Consequently, it implies that investors seeking to outperform the market must be prepared to accept higher risks, as stock prices behave in a random manner.

In Chapter 2, the author provides a comprehensive overview of financial statements, the stock market, and the significance of accounting information, highlighting the connection between financial statement data and stock prices through the Ohlson model, which has been widely tested in global studies The chapter also introduces key theoretical frameworks, including Agency Theory, Efficient Market Hypothesis, Signaling Theory, Bird-in-Hand Theory, and Random Walk Hypothesis Building on the concepts presented in Chapter 1, the author develops an empirical research model along with a system of variables and research methodologies to facilitate the analysis in Chapters 3 and 4.

RESEARCH METHODOLOGY

Research process

According to the picture above, there will be 7 steps in the thesis:

Step 1: Finding out the problem, objectives, and scope of the research, then consider the research related to the topic in Vietnam and other countries, thereby finding research gaps

Step 2: Reviewing relevant background theories and empirical research models Then, a suitable research model and research hypothesis are proposed

Step 3: Building research model and hypotheses, determining measurement methods and how to calculate variables in the model

Step 4: Taking samples, collect data, put data into STATA software for processing Step 5: Using descriptive statistics, correlation analysis, multivariable regression, and testing model defects

Identify and clarify the research problems Research related theories and introduce previous research models

Step 6: Present research results and discussions

Step 7: Concluding and giving policy implications.

Research method

This article identifies key accounting data that significantly influence the share prices of listed companies, based on a synthesis of relevant documents and previous research The selected factors include Earnings Per Share (EPS), Book Value Per Share (BVPS), Return on Assets (ROA), Return on Equity (ROE), Dividends Per Share (DPS), company size (SIZE), and Price-to-Earnings ratio (P/E) These financial ratios can be accurately derived from annual audited financial statements, making them essential for understanding share price dynamics.

In the second step, we analyze the chosen independent variables against the 52 financial indicators identified by Dang Tran Hung et al (2022) in Appendix 1.1 to determine the most precise calculation formula for these independent variables.

The author will conduct a comprehensive analysis of the data utilizing descriptive statistics, correlation coefficient analysis, and regression analysis This includes employing methods such as Pooled OLS, Random Effect Model (REM), Fixed Effect Model (FEM), and Feasible Generalized Least Squares (FGLS), facilitated by STATA 17 and Excel 2016 Previous studies, including those by Al-Malkawi et al (2018) and Dang Ngoc Hung et al (2018), have successfully implemented these analytical techniques.

Do Thi My and Nguyen Thu Hien (2021).

Research model

3.3.1 Regression model of factors affecting share prices

According to Abhimada Gatuth Satryo, Nur Aini Rokhmania, Pepie Diptyana

In 2016, accounting information influencing share prices is categorized into three main groups: profitability ratios, market ratios, and solvency ratios Profitability ratios encompass metrics such as Return on Assets (ROA), Return on Equity (ROE), and gross profit margin Market ratios include Earnings Per Share (EPS), Book Value Per Share (BVPS), and Price-to-Earnings (P/E) ratio Lastly, solvency ratios are represented by the Debt-to-Equity ratio and the Debt-to-Assets ratio.

Numerous researchers globally have explored the factors influencing the share prices of listed companies Drawing on foundational theories and previous studies, such as those by Hatta and Dwiyanto (2012) in Indonesia, Al-Malkawi et al (2018) in the MENA region, and Dang Ngoc Hung et al (2018) in Vietnam, the author presents a comprehensive list of factors affecting the share prices of companies listed on the HOSE, as detailed in Table 3.1 below.

No Elements Encode Factors Note

1 Market ratio EPS Earnings per share

Names of factors are inherited from Hatta and Dwiyanto (2012), Al-Malkawi et al

(2018), Dang Ngoc Hung et al (2018)

2 BVPS Book value per share

4 Profitability ratio ROA Return on assets

7 Solvency ratio FL Financial leverage

Table 3.1 2 Variables used in the model

The Ohlson model (1995) utilizes earnings per share and book value per share as key accounting metrics influencing stock prices Building on prior research by Hatta and Dwiyanto (2012), Al-Malkawi et al (2018), and Dang Ngoc Hung et al (2018), a new model was established, comprising 8 independent variables and 1 dependent variable.

This research model has the following form:

P = α0 + α1EPS + α2BVPS + α3ROA+ α4ROE + α5DPS + α6FL + α7SIZE + α8P/E + Uit

On the basis of determining the factors included in the research model (Diagram 3.2), the author develops research hypotheses corresponding to each factor in the research model as follows:

Earnings Per Share (EPS) serves as a crucial indicator of a company's profitability, reflecting the portion of net income allocated to each shareholder's share Publicly traded companies are required to disclose their EPS in income statements, as highlighted by Valix & Peralta (2009) This metric is calculated by dividing the profit generated by the number of shares outstanding during a specific accounting period (Besley, 2006, p 20) The positive correlation between EPS and stock prices underscores its significance for investors.

Market price of the share on

P/E been mentioned in studies of Ohlson (1995), Hatta and Dwiyanto (2012), Nguyen Thi Thuc Doan (2011), Do Thi My and Nguyen Thu Hien (2021), Dang Ngoc Hung et al (2022)

Hypothesis 1 (H1): EPS has a positive effect on stock prices of listed companies on HOSE

 Book value per share (BVPS)

BVPS, or Book Value Per Share, indicates the percentage of a company's book value relative to its outstanding shares This metric reflects the firm's asset value, typically calculated using historical figures from the Balance Sheet (Otuya et al., 2019) Consequently, a higher BVPS suggests a greater share price, while a lower BVPS indicates the opposite.

My and Nguyen Thu Hien (2021), Dang Ngoc Hung et al (2022) also reached the same conclusion

Hypothesis 2 (H2): BVPS has a positive effect on stock prices of listed companies on HOSE

Return on Assets (ROA) measures a company's ability to generate earnings after tax from its operational assets, reflecting how effectively it utilizes these assets A higher ROA indicates greater efficiency in profit generation, making it an attractive metric for stock investors who view increased ROA as a positive signal for investment decisions Research by Asiri and Hameed (2014), Dang Ngoc Hung et al (2018), and Dang Ngoc Hung et al (2022) confirms that ROA positively influences share prices.

Hypothesis 3 (H3): ROA has a positive effect on stock prices of listed companies on HOSE

Return on Equity (ROE) is a key metric used to assess a company's profitability from the perspective of common equity investors, as it reflects the profit available to shareholders after tax (Tezel & McManus, 2003) An increase in ROE is perceived positively by the market, signaling to investors that it may be a good time to buy shares (Husnan & Pudjiastuti, 2015) This heightened demand for stocks often leads to an increase in share prices (Al-Malkawi et al., 2018; Nguyen Thi Thuc Doan, 2011).

Hypothesis (H4): ROE has a positive effect on stock prices of listed companies on HOSE

Dividend Per Share (DPS) represents the amount of dividend a shareholder receives for each share owned, and it can be derived from the income statement (Otuya et al., 2019) A higher DPS typically correlates with an increased share price, while a lower DPS may indicate the opposite Research conducted by Mondal and Imran (2010) and Al-Malkawi et al (2018) demonstrates that DPS is significantly relevant to share prices and has a substantial positive impact on them.

Hypothesis 5 (H5): DPS has a positive effect on stock prices of listed companies on HOSE

The financial leverage (FL) of a company is typically assessed through its Debt-to-Equity ratio This ratio evaluates a company's financial structure by comparing its total debt, encompassing both current and long-term obligations, to its total equity, offering insights into the balance between debt and equity financing (Kasmir, 2012).

The financial leverage (FL) ratio measures the relationship between a company's total debt and its equity, indicating that a higher FL signifies increased risk for the company, which can lead to a decline in share prices Research by Mondal and Imran (2010), Hatta and Dwiyanto (2012), and Do Thi My and Nguyen Thu Hien (2021) supports the negative correlation between financial leverage and share prices.

Hypothesis 6 (H6): FL has a negative effect on stock prices of listed companies on HOSE

The size of a company was evaluated using the natural logarithm of its total assets for each year analyzed (Badru and Idowu, 2020) Research by Mondal and Imran (2010), Dang Ngoc Hung et al (2018), Do Thi My and Nguyen Thu Hien (2021), and Dang Ngoc Hung et al (2022) indicates that company size positively influences stock prices.

Hypothesis 7 (H7): SIZE has a positive effect on stock prices of listed companies on HOSE

The P/E ratio, or price-to-earnings ratio, is calculated by dividing the current market price of a stock by its earnings per share (EPS) This price is typically based on the most recent market data, such as the daily closing prices averaged over a week or month (Shen, 2000).

Hypothesis 8 (H8): P/E has a positive effect on stock prices of listed companies on HOSE

The market price of a share is determined by the transaction price on the stock market, reflecting the values set by buyers and sellers during trading This price serves as a key indicator of investors' expectations regarding a company's future performance, making it closely monitored by investors, analysts, and companies alike For this thesis, the required price data must be sourced from cafef.vn and published annually at the end of December.

P = Annual closing price on December 31 st

Based on foundational theories and previous research, including studies by Hatta and Dwiyanto (2012), Al-Malkawi et al (2018), and Dang Ngoc Hung et al (2018), the author presents a comprehensive list of factors influencing the share prices of companies listed on the HOSE, as detailed in Table 3.2 below.

No Code Description Equation Expected signs

EAT/ Weighted average shares outstanding

2 BVPS Book value per share

+ Balance sheet, Notes to the financial statements

Total dividend paid/ Weighted average shares outstanding

+ Cash flow statement, Notes to the financial statements

7 SIZE Size of the firm

Log (total assets) + Balance sheet

Dang Ngoc Hung et al (2018)

Price/EPS + Cafef.vn, income statement

Table 3.2 3 Measurement of independent variables

Data collection

According to Nguyen Dinh Tho (2013) in quantitative research, the number of samples for multivariate regression should be: n ≥ 50 + 8m

- m: Number of independent variables in the model

The study analyzed eight independent variables, determining a minimum sample size of 114 observations Data was sourced from the annual audited financial statements of companies listed on the HOSE from 2018 to 2022.

Up to December 31, 2022, there were 388 enterprises on HOSE and were divided into 11 groups of industries which are detailed in Table 3.3

No Subdivision Number of firms

Table 3.3 4 Business groups listed on HOSE on December 31, 2022

(Souce: https://www.hsx.vn)

The research sample excludes 39 financial businesses, including banks, insurance companies, securities firms, and investment funds Additionally, 45 companies were not continuously listed on HOSE from 2018 to 2022 Among the remaining enterprises, 10 did not publish fully audited annual reports during the research period, while 17 companies had annual audited financial statements but lacked sufficient data to measure the independent variables.

The study analyzes 277 annual audited financial statements to explore the relationship between accounting information and the share prices of companies listed on the HOSE The research sample is detailed in the accompanying table.

1 Number of securities trading enterprises on HOSE is on

2 Number of enterprises in the fields of finance 39

3 Number of enterprises not published enough annual report 10

4 Number of enterprises does not have enough necessary data 17

5 Number of enterprises remaining in the research sample 277

Table 3.4 5 Summary of research sample

The final number of companies that are chosen are 277 companies The author finally collects a table of data for 5 years from 2018 – 2022 with 1385 observations

The data gathered from enterprises includes key financial metrics such as the market price of shares as of December 31, the weighted average number of shares outstanding, earnings after tax (EAT), total assets, total liabilities, shareholders' equity, and dividends paid Once collected, this data will be imported and processed using Excel 2016, followed by quantitative analysis in STATA.

This study employs a quantitative approach, beginning with descriptive statistics to summarize key variables, including names, observations, means, standard errors, minimum, and maximum values The author then utilizes a linear regression model for panel data analysis, incorporating four methods: Ordinary Least Squares (OLS), Random Effects Model (REM), Fixed Effects Model (FEM), and Feasible Generalized Least Squares (FGLS) To enhance the reliability of the findings, regression analyses are performed on three distinct panel data models—FEM, REM, and FGLS—alongside the traditional OLS model Finally, the study conducts tests to identify the most appropriate model for empirical research within the Vietnamese stock market.

 Ordinary Least Squares (OLS) Υ it = β1+ β2X2 it + β3X3 it + … + βkX kit + u it (1)

Yit: the dependent variable of the company i in the year t

Xkit: The independent variable k of the company i in year t β1: Coefficient of intercept of the model βk: Slope coefficient of the kth independent variable uit: Error of the company i in year t

The coefficient β has only one or no difference between individuals And the fixed effect model and the random effect model will fix the errors of this model

 Fixed effect model (FEM) Υit = β1i+ β2X2it + β3X3it + … + βkXkit + uit (2) β1i: The slope coefficient of the company i

In this approach, we consider β1i as a random variable rather than a fixed value, similar to the Fixed Effects Model (FEM) We define its mean as β1, without the index i, allowing us to express the individual company effect as β1i = β1 + εi for i = 1, 2, …, N.

In this model, the random error term (εi) has a mean of zero and a variance of σ ε 2, indicating that while firms share a common mean for the slope (β1), individual differences in each firm's slope are captured within the error term The equation Υit = β1 + β2X2it + β3X3it + … + βkXkit + εi + uit illustrates how various factors (X2it, X3it, , Xkit) contribute to the dependent variable (Υit), alongside the unique error components of each firm.

 Feasible Generalized Least Squares (FGLS)

FGLS, or Feasible Generalized Least Squares, is a regression technique employed to estimate the coefficients and covariance matrix of a multiple linear regression model when facing non-spherical innovations with an unknown covariance matrix Its primary benefit lies in addressing issues of heteroskedasticity and autocorrelation within the regression model When panel data exhibits autocorrelation, cross-sectional correlation, and heteroskedasticity, researchers utilize FGLS to accurately estimate the model's coefficients.

Data analysis

 Check for the existence of a fixed effect

The test aims to select the suitable OLS or FEM model for the sample's data set

The test aims to select the appropriate OLS or REM model for the sample data regression

If the p-value from the Breusch-Pagan LM test is statistically significant, it indicates that the null hypothesis (H0) can be rejected, suggesting that the Random Effects Model (REM) is more appropriate Conversely, if the null hypothesis is accepted, the Ordinary Least Squares (OLS) method is deemed suitable for the model.

The objective of the test is to identify the appropriate Fixed Effects Model (FEM) or Random Effects Model (REM) for regression analysis of sample data This selection is based on the assumption that there is no correlation between the explanatory variable and the random factor, as such correlation is the primary reason for the differences observed between FEM and REM.

If the p-value from Hausman's test is statistically significant, it indicates that we reject the null hypothesis (H0), suggesting that Fixed Effects Model (FEM) is the more appropriate choice Conversely, if H0 is accepted, the Random Effects Model (REM) is deemed suitable for the analysis.

In the context of regression analysis, Rj2 represents the coefficient of determination for the independent variable Xj when considering other independent variables A VIFj value exceeding 10 and an Rj2 greater than 0.9 indicate a significant multicollinearity issue between Xj and the other independent variables.

Autocorrelation is the phenomenon of correlation between observations in the same data table:

This phenomenon usually occurs for time series data Since autocorrelation often occurs with data over time, the regression equation is:

If the error Ut is only correlated with Ut-1 (error one period before), then we have the phenomenon of first-order autocorrelation, denoted AR (1)

The first order correlation equation is as follows:

: Autocorrelation coefficient εt: Random error no longer autocorrelated if Ut is correlated with m previous periods, then we have m order autocorrelation, denoted AR(m):

Ut  1Ut 1  2Ut 2   mUt m  t Methods to check for autocorrelation:

Autocorrelation test with panel data: Using Wooldridge's test (2002) and Drukker (2003) hypothesized the following:

Hypothesis H 0 : The model does not have first-order autocorrelation

Hypothesis H 1 : The model has first-order autocorrelation

With the value Prob>F > 5% of the Wooldridge test as above, we conclude to accept the hypothesis H0, which means that there is no autocorrelation and vice versa

Variance means that the variances of the residuals are not constant, that is, they differ in different observations

The causes of variance in economic data can be attributed to several factors, including enhanced data collection and processing methods, which lead to a gradual reduction in errors Additionally, the accumulation of past experience plays a significant role, while inaccuracies in data collection can also contribute to discrepancies.

When variance variation occurs, Ordinary Least Squares (OLS) estimates lose their efficiency, leading to biased variance estimates Consequently, significance tests and confidence intervals derived from t and F distributions become unreliable and lack meaningful interpretation.

Detect variable variance by means of Goldfeld-Quandt, Breusch-Pagan, White, Park test on OLS and Greene method (2000) on panel data

Chapter 3 explores the market price per share (P) through eight independent variables, including EPS, BVPS, ROA, ROE, DPS, FL, SIZE, and P/E The author addresses the research problem, develops models, formulates research hypotheses, and outlines data collection methods, as well as data analysis and model testing techniques Utilizing a quantitative approach, the study analyzes a sample of 277 enterprises, encompassing 1,385 observations over a five-year period from 2018.

2022 The data processing support tool is STATA 17 and excel 2016 software Research results will be presented in the next chapter.

RESULTS AND DISCUSSION

Introducing the history of establishment and development of the securities

4.1.1 History of establishment and development of Vietnam stock market

The Vietnam stock market experienced a slower development compared to other countries, with its initial framework established through Securities Trading Centers under the State Securities Commission before its official inception The formal operation began with the opening of the Ho Chi Minh City Stock Exchange on July 20, 2000, followed by the Hanoi Stock Exchange on March 8, 2005 Over the past two decades, Vietnam's stock market has made remarkable strides towards global integration, evolving into an attractive investment option for both domestic and international investors.

4.1.2 HOSE's history of establishment and development

The State Securities Commission of Vietnam was established on November 28, 1996, under Decree No 75/CP The official launch of the Vietnam stock market occurred on July 11, 1998, with Decree No 48/1998/ND-CP, which also led to the establishment of the Ho Chi Minh Stock Exchange and the Hanoi Securities Trading Center The Ho Chi Minh Stock Exchange commenced operations on July 28, 2000, featuring its first two trading stocks, REE and SAM.

Over its first 20 years, HOSE experienced low liquidity, peaking at VND 5,380 billion per session in 2018 However, liquidity surged in 2021 due to the Covid-19 pandemic, which disrupted various production chains, leading to a dramatic increase in cash flow into the stock exchange and a transaction value of VND 21,590 billion per session In the first half of 2022, HOSE reported a total trading value of 2,563.5 trillion dong, with an average session trading value of 21.36 trillion dong, surpassing previous years.

The Ho Chi Minh City Stock Exchange is a state-owned corporation operating under the Securities Law, the Enterprise Law, and the Charter of the Department of Securities Trading, along with other relevant regulations It is organized as a one-member limited liability company.

- Full name: Ho Chi Minh City Stock Exchange

- International transaction name: Hochiminh Stock Exchange

At the end of August in 2018, 364 enterprises and 55 securities companies,

18 fund management companies, 61 depository organizations were listed on HOSE

In 2018, the Ho Chi Minh City Stock Exchange (HOSE) welcomed 31 new shares, 15 corporate bonds, and 2 investment fund certificates, including major players like Vietnam Thinh Vuong Joint Stock Commercial Bank and Vincom Retail This influx contributed to a remarkable increase in market liquidity, which soared to nearly 5 trillion VND per session, marking a 63% rise from the previous year Additionally, foreign investor capital flow experienced a net inflow of 26.4 trillion VND, propelling the market value to over 2.6 million VND, equivalent to 57% of Vietnam's GDP, positioning the country among the fastest-growing stock markets globally The VNIndex reached a decade-high close of 984.24 points, reflecting an impressive 48% increase Furthermore, the government actively promoted equitization and divestment from state-owned enterprises, with 23 divestitures executed during the year.

9 equitization auctions, raising almost 123 trillion VND for the State budget

As of the end of 2022, HOSE listed 515 securities codes, with a total volume of 143.75 billion securities valued at approximately 1.43 million billion dong, reflecting increases of 17.28% in volume and 17.30% in value compared to 2021 The total stock market capitalization reached about VND 4.02 million billion, representing over 94% of total market capitalization and 42.22% of GDP for the year Notably, 2022 marked a significant year for foreign capital inflows, with foreign investors net purchasing more than 26,674 billion dong The total trading volume exceeded 22.74 billion securities, with a trading value of 724,016 billion dong, accounting for 8.46% of the overall market's trading value.

The situation of voluntary information disclosure on financial statements

4.2.1 Evaluation of voluntary information disclosure on enterprises' annual financial statements

The publication of annual reports by firms on HOSE has reached a moderate level, according to data collection findings that evaluate both dependent and independent variables Nonetheless, many companies create and release these reports in a disorganized manner, neglecting the necessary structure for disclosing mandatory information.

Research by the Vietnam Association of Financial Executives (VAFE) and Vietstock revealed a concerning trend in regulatory compliance among listed companies on the Ho Chi Minh Stock Exchange (HOSE) In 2018, approximately 60% of listed enterprises, or 420 companies, were warned for violations related to information disclosure This issue worsened in 2019, with 454 firms—64% of the total listed—failing to meet the requirements outlined in Circular No 96/2020/TT-BTC Although there was a slight improvement in 2020, 400 firms still did not fully comply with information disclosure regulations, representing 55% of all listed companies on HOSE.

In 2021 and 2022, 335 and 351 companies, respectively, failed to fully comply with information disclosure regulations, representing 46% and 44% of all listed companies during those years This trend highlights ongoing challenges in regulatory adherence among listed firms.

2022, it can be concluded that the percentage of listed companies on HOSE that strictly comply with regulations on information disclosure is low.

The descriptive statistics for the variables from 2018 to 2022 are summarized based on key criteria, including the number of observations, average, standard deviation, minimum, and maximum values across eight objects This analysis utilizes a strongly balanced panel, with detailed statistical values for the variables incorporated in the regression model provided in Table 4.1.

Variable Obs Mean Std Dev Min Max price 1,385 30.33818 29.4189 1.29 267.5 eps 1,385 2.571978 3.094318 -8.76 33.369 bvps 1,385 21.00238 12.32646 0.0131543 137.95 roa 1,385 0.0702345 0.077311 -0.4834078 0.6537167 roe 1,385 0.1234805 0.1240026 -1.434495 0.9539626 fl 1,385 1.251761 1.596772 0.0026807 27.60514 dps 1,385 1.385995 2.580124 0 65.93884 size 1,385 9.357714 0.6396078 7.009786 11.76148 p/e 1,385 30.85406 162.7613 -1058.929 3,250

Table 4.1 presents a data set comprising 1,385 observations from 277 companies listed on HOSE during the reporting period This study investigates the relationship between the share prices of these companies as of December 31 (P) and various accounting metrics, including EPS, BVPS, ROA, ROE, FL, DPS, SIZE, and P/E, spanning from 2018 to 2022.

In term of price, this variable has average value of 30.33818 (unit: 10,000 VND), and its standard deviation is 29.4189 Min value is 1.29 belonging to TSC in

2018 and max value is 267.5 belonging to SAB in the same year

Graph 4.1 Average volatility of price (P)

From 2018 to 2022, share prices on HOSE exhibited notable fluctuations, particularly increasing in volatility from 2020 onward The average share price in 2018 was 32.2781, which rose to a peak of 44.256 in 2021, before declining to 30.506 in 2022.

The average Earnings Per Share (EPS) for listed companies on the HOSE from 2018 to 2023 is 2.57 (in 10,000 VND), with a standard deviation of 3.09 The EPS values range from a minimum to a maximum, reflecting the performance variability among these companies.

Graph 4.2 Average volatility of earnings per share (EPS)

Despite significant fluctuations in the share prices of listed companies on HOSE during the reporting period, the earnings per share (EPS) demonstrated a steady increase In 2008, the average EPS was 1.87, rising consistently to reach 4.14 by 2022.

The average Book Value Per Share (BVPS) for listed companies on the HOSE from 2018 to 2022 is 21.00 (in 10,000 VND), with a standard deviation of 12.33 The BVPS values range from a minimum of 0.01 to a maximum of 137.95 during this period.

Graph 4.3 Average volatility of book value per share (BVPS)

The graph 4.3 shows that although the average values of share prices among listed companies on HOSE in the period of 2018 to 2022 varied significantly, the

The average values of BVPS Linear (BVPS) showed a consistent upward trend, increasing from 19.21 in 2008 to 25.28 by the end of the research period among 277 listed companies.

Next, in terms of ROA, this variable has mean value of 0.0702345, whereas the standard deviation value is captured at 0.077311 The minimum and maximum values of ROA were -0.4834078 and 0.6537167 respectively

Graph 4.4 Average volatility of return on assets (ROA)

The graph 4.4 illustrates that like share prices, the average values of ROA of

Between 2018 and 2022, the 277 listed companies on HOSE experienced fluctuations in their return on assets (ROA) Initially, the average ROA was 0.0555, which significantly increased to 0.0950 after two years However, this ratio then declined to 0.0754 before surging again to 0.0988 in 2022.

Next, in terms of ROE, this variable has mean value of 0.1234805, whereas the standard deviation value is captured at 0.1240026 The minimum and maximum values of ROE were -1.434495 and 0.9539626 respectively

Graph 4.5 Average volatility of return on equity (ROE)

The graph 4.5 depicts that like share prices, the average values of ROE of

277 listed companies on HOSE between 2018 and 2022 also fluctuated In 2018, the average value of ROE was 0.0977, and this ratio rose dramatically to 0.15255 after

2 years, before declining to 0.1376 and jumped again to 0.17006 at the end of the reporting period The interesting point is that when ROE increases, share prices tend to decrease slightly

Next, in terms of FL, this variable has mean value of 1.251761, whereas the standard deviation value is captured at 1.596772 The minimum and maximum values of FL were 0.0026807 and 27.60514 respectively

Graph 4.6 Average volatility of financial leverage (FL)

Between 2018 and 2022, the average financial leverage (FL) of 277 listed companies on HOSE exhibited fluctuations, starting at 1.2739 in 2018 Over the next three years, this ratio gradually declined to 0.9887 before experiencing a significant increase to 1.5896 by the end of the reporting period.

The average DPS (Dividends Per Share) among 200 listed companies on HOSE from 2018 to 2022 is 1.386, with a standard deviation of 2.580 The fluctuation in DPS values ranges from a minimum of 0 to a maximum of 65.939.

Graph 4.7 Average volatility of dividend per share (DPS)

The line chart 4.7 illustrates the fluctuations in the average Dividend Per Share (DPS) of 277 companies listed on HOSE from 2018 to 2022 In 2018, the average DPS was 0.9667, which gradually fell to 1.8992 over two years, before dropping further to 1.6031 and then surging to 2.2639 in 2022 Notably, there is a correlation between average DPS and average share prices, where a decrease in DPS corresponds with a decline in share prices, and vice versa.

The SIZE variable for 277 listed companies on HOSE from 2018 to 2022 has a mean value of 9.36 and a standard deviation of 0.64 The minimum SIZE recorded is 7.01, while the maximum SIZE reaches 11.76.

Graph 4.8 Average volatility of firm size (SIZE)

Testing the research model

The author will analyze the correlation between the dependent variables and the independent variables in the model and the correlation between the independent variables

P eps bvps roa roe fl dps size pe

Table 4.2 reveals that the independent variable P exhibits the strongest correlation with EPS at 0.6356, while showing the weakest correlation with FL at -0.0697 Additionally, P demonstrates a positive correlation with EPS, BVPS, ROA, ROE, DPS, and SIZE, and a negative correlation with FL and P/E The correlation coefficients between the dependent variable and independent variables range from -0.2810 to 0.8665 Furthermore, the analysis of the autocorrelation matrix indicates that no pair autocorrelation coefficients exceed 0.8, suggesting the absence of significant multicollinearity based on the collected data.

Variable VIF 1/VIF eps 4.74 0.210886 bvps 2.14 0.468017 roa 5.37 0.186145 roe 5.82 0.171721 fl 1.25 0.801961 dps 1.57 0.638860 size 1.14 0.880409 p/e 1.01 0.986149

Table 4.3 8 Variance inflation factor (Appendix 1.4)

Table 4.3 presents the multicollinearity test results, revealing a mean Variance Inflation Factor (VIF) of 2.88, which is below the threshold of 10 (Gujarati, 2004) All variables also exhibit VIF values under 10, indicating the absence of strong multicollinearity within the model This lack of serious multicollinearity suggests that the factors are independent and distinct, making them appropriate for quantitative research The author will proceed with estimation tests on these variables.

4.2.3 Comparison Pooled OLS and FEM

The test assumes that there are no significant differences in observations between companies over the years, making the Pooled model appropriate for the data However, if the sample data reveals variations among companies over time, the Fixed Effects Model (FEM) is more suitable Subsequently, an F-test is performed to determine whether to use the Pooled Ordinary Least Squares (OLS) or the FEM for analysis.

H 0 : Pooled OLS model is more appropriate

H 1 : FEM model is more appropriate

Conclusion FEM is more appropriate

Table 4.4 9 Compare Pooled OLS and FEM (Appendix 1.5)

Table 4.4 shows that P-value of this test is 0.0000 which is less than 0.05 Therefore, hypothesis H 0 is not accepted or FEM is more appropriate than Pooled OLS

4.2.4 Comparison Pooled OLS and REM

The author continues to test Breusch, T S and A R Pagan (1980) chose Pooled and REM models with the following hypothesis:

H 0 : Pooled OLS model is more appropriate

H 1 : REM model is more appropriate

Conclusion REM is more appropriate

Table 4.5 10 Compare Pooled OLS and REM (Appendix 1.5)

Table 4.5 shows that P-value of this test is 0.0000 which is less than 0.05 Therefore, hypothesis H 0 is not accepted or REM is more appropriate than Pooled OLS.

The author continues to perform Hausman test to choose between two REM and FEM models with the following data hypothesis:

H 0 : REM model is more appropriate

H 1 : FEM model is more appropriate

Conclusion FEM is more appropriate

Table 4.6 11 Compare FEM and REM (Appendix 1.5)

Table 4.6 shows that P-value of this test is 0.0000 which is less than 0.05 Therefore, hypothesis H 0 is not accepted or FEM is more appropriate than REM.

The author used Wald test to check heteroskedasticity

H 0 : the error variances are all equal

H 1 : the error variances are not equal

Table above shows that p-value = 0.0000< α = 0.05 Therefore, hypothesis

H 0 is not accepted and heteroskedasticity issue is witnessed in FEM

The Wooldridge test for autocorrelation in panel data is employed to identify autocorrelation by examining the null hypothesis that there is no first-order autocorrelation The results obtained from this test are presented below.

H 0 : there is no first-order autocorrelation

H 1 : there is first-order autocorrelation

Table 4.8 13 Testing first-order autocorrelation (Appendix 1.7)

The Wooldridge test results indicate a value of 0.016 with a p-value of 0.9000, which exceeds the 0.05 threshold Therefore, we do not reject the null hypothesis, confirming that there is no evidence of autocorrelation present in the dataset.

The author analyzes experimental regression results after assessing correlation, multicollinearity, heteroskedasticity, and autocorrelation The analysis utilizes various regression methods, beginning with the Pooled regression model, followed by the Fixed Effect Model (FEM) and the Random Effect Model (REM) To address heteroskedasticity, the author subsequently employs cross-sectional time-series Feasible Generalized Least Squares (FGLS) regression.

Regression analysis

The author progresses from a simple model to a more advanced one to address the limitations of the original regression model Initially, panel data regression models such as Pooled OLS, FEM, and REM are utilized Pooled OLS examines the relationship between intrinsic factors influencing stock prices under the assumption that companies are homogeneous, while FEM focuses on company-specific differences However, FEM is hindered by heteroskedasticity, compromising its reliability and potentially leading to inflated statistical outcomes To rectify this issue, the author employs FGLS regression, yielding improved results.

Variable Coefficient Z-test P-value eps 3.584563 10.59 0.000 bvps 0.3146175 7.24 0.000 roa 90.02081 10.58 0.000 roe -30.84852 -4.87 0.022 fl -0.0124804 -0.10 0.922 dps 1.84855 7.72 0.000 size 8.729099 16.92 0.000 p/e 0.0063159 2.91 0.004

Table 4.9 14 FGLS regression model (Appendix 1.8)

Next, the author will compare the research model from FGLS with Pooled OLS, FEM, REM to select the best model:

Pooled OLS FEM REM FGLS

(1) (2) (3) (4) price price price price eps 3.579** 3.214*** 3.252*** 3.585***

Table 4.10 15 Compare four regression models (Appendix 1.9)

(Note: ***, **, * are equivalent to significance level of 1%, 5% and 10%)

Based on the results of Table 4.10, the regression equation according to the Pooled OLS model is rewritten as follows:

P = -14.08 + 9.23EPS + 4.69BVPS + 7.66ROA – 3.83ROE + 5.35DPS + 14.64SIZE + 2.88P/E+ Uit

The analysis reveals that among eight dependent variables, free cash flow (FL) does not influence stock price, while earnings per share (EPS), book value per share (BVPS), return on assets (ROA), return on equity (ROE), dividends per share (DPS), and company size (SIZE) show significant correlations with stock price Specifically, EPS, BVPS, ROA, DPS, SIZE, and price-to-earnings ratio (P/E) exhibit a positive relationship with stock price, indicating that higher values in these variables correspond to higher stock prices Conversely, return on equity (ROE) demonstrates a negative relationship with stock price.

Based on the results of Table 4.10, the regression equation according to FEM is rewritten as follows:

P = -5.43 + 8.91EPS – 6.23BVPS – 2.00FL - 5.33DPS + 6.14SIZE + 1.10P/E + Uit

The analysis reveals that while Return on Assets (ROA) and Return on Equity (ROE) do not influence stock prices, other variables such as Earnings Per Share (EPS), Book Value Per Share (BVPS), Financial Leverage (FL), Dividend Per Share (DPS), company size (SIZE), and Price-to-Earnings (P/E) ratio show significant correlations Specifically, EPS, SIZE, and P/E exhibit a positive relationship with stock prices, indicating that increases in these metrics lead to higher stock prices Conversely, BVPS, FL, and DPS demonstrate a negative relationship with stock prices.

Based on the results of Table 4.10, the regression equation according to REM is rewritten as follows:

P = -7.76+ 9.11EPS + 3.95ROA – 3.27ROE + 8.68SIZE + Uit

The analysis reveals that among the eight dependent variables studied, BVPS, FL, DPS, and P/E do not influence stock prices In contrast, EPS, ROA, and SIZE demonstrate a statistically significant positive correlation with stock prices, indicating that higher values in these variables lead to increased stock prices Conversely, ROE exhibits a negative relationship with stock prices.

Based on the results of Table 4.10, the regression equation according to FGLS is rewritten as follows:

P = -16.49 + 10.59EPS + 7.24BVPS + 10.58ROA – 4.87ROE + 7.72DPS + 16.92SIZE + 2.91P/E + Uit

The study indicates that while financial leverage (FL) does not influence stock price, several other variables—earnings per share (EPS), book value per share (BVPS), return on assets (ROA), dividends per share (DPS), company size (SIZE), and price-to-earnings ratio (P/E)—demonstrate a statistically significant correlation with stock price Specifically, an increase in EPS, BVPS, ROA, DPS, SIZE, and P/E is associated with a rise in stock price, whereas return on equity (ROE) exhibits a negative relationship with stock price.

The regression analysis results presented in Table 4.10 illustrate the relationship between independent variables and the dependent variable of stock price Among the four models analyzed—OLS, FEM, REM, and FGLS—the author selected the FGLS model due to its superior reliability Consequently, the findings from the FGLS model support the accepted assumptions.

Hypothesis 1 (H1): EPS has a positive effect on stock prices of listed companies on HOSE

Hypothesis 2 (H2): BVPS has a positive effect on stock prices of listed companies on HOSE

Hypothesis 3 (H3): ROA has a positive effect on stock prices of listed companies on HOSE

Hypothesis 5 (H5): DPS has a positive effect on stock prices of listed companies on HOSE

Hypothesis 7 (H7): SIZE has a positive effect on stock prices of listed companies on HOSE

Hypothesis 8 (H8): P/E has a positive effect on stock prices of listed companies on HOSE.

Discussion

After choosing the FGLS model and addressing its limitations, the author summarizes the influence of eight accounting information variables presented in Table 4.11 and examines the research hypotheses outlined in Chapter 3.

Accounting information Symbol Direction of influence Statistical significance

2 Book value per share BVPS + 1%

7 Size of the firm SIZE + 1%

Table 4.11 16 Summarize the effect of the factors Factor 01: EPS

According to the regression results, in the period of 5 years from 2018 to

In 2022, the analysis indicates that Earnings Per Share (EPS) positively influences stock prices across four distinct models, achieving a significance level of 1% This supports Hypothesis 1 (H1), confirming that EPS has a beneficial effect on the stock prices of companies listed on the HOSE These findings align with earlier research conducted by Ohlson (1995) and Hatta and Dwiyanto (2012), reinforcing the established relationship between EPS and stock performance.

Thuc Doan (2011), Do Thi My and Nguyen Thu Hien (2021), Dang Ngoc Hung et al (2022)

According to the regression results, in the period of 5 years from 2018 to

In 2022, the analysis reveals that Book Value Per Share (BVPS) positively influences stock prices in Pooled OLS, FEM, and FGLS models, achieving a significance level of 1% This supports Hypothesis 2 (H2), confirming that BVPS positively affects the stock prices of companies listed on the HOSE These findings align with previous research conducted by Al-Malkawi et al (2018), Nguyen Thi Thuc Doan (2011), Do Thi My and Nguyen Thu Hien (2021), and Dang Ngoc Hung et al (2022).

According to the regression results, in the period of 5 years from 2018 to

In 2022, the analysis revealed that Return on Assets (ROA) positively influences stock prices across Pooled OLS, REM, and FGLS models, achieving a significance level of 1% This supports Hypothesis 3 (H3), which posits that ROA positively affects the stock prices of companies listed on the HOSE These findings align with earlier research conducted by Asiri and Hameed (2014), as well as studies by Dang Ngoc Hung et al (2018) and Dang Ngoc Hung et al (2022).

The regression analysis reveals that Return on Equity (ROE) negatively impacts stock prices across Pooled OLS, REM, and FGLS models at a 1% significance level, leading to the rejection of hypothesis 4 (H4) that posits ROE positively affects stock prices of listed companies on HOSE This finding contradicts previous studies by Al-Malkawi et al (2018) and Nguyen Thi Thuc Doan (2011), likely due to differences in selected companies, market share prices, and time periods analyzed in this research.

According to the regression results, in the period of 5 years from 2018 to

In 2022, the findings indicate that financial leverage (FL) shows no correlation with the share prices of listed companies across all four models analyzed The experiments conducted at the Ho Chi Minh Stock Exchange (HOSE) during the research period did not provide sufficient evidence to either accept or reject the hypothesis that FL negatively impacts the stock prices of these companies.

According to the regression results, in the period of 5 years from 2018 to

In 2022, the analysis reveals that Dividend Per Share (DPS) positively influences share prices in both Pooled OLS and FGLS models, achieving significance at 1% Conversely, a negative impact on share prices is observed in the Fixed Effects Model (FEM), also with 1% significance These findings align with the studies conducted by Mondal and Imran (2010) and Al-Malkawi et al (2018) Consequently, Hypothesis 06, which posits that DPS positively affects the stock prices of listed companies on the HOSE, is accepted.

According to the regression results, in the period of 5 years from 2018 to

In 2022, the analysis reveals that SIZE positively influences stock prices across various models, including Pooled OLS, FEM, REM, and FGLS, with a significance level of 1% This supports Hypothesis 7 (H7), confirming that SIZE positively affects the stock prices of companies listed on HOSE These findings align with previous research conducted by Mondal and Imran (2010), Dang Ngoc Hung et al (2018), Do Thi My and Nguyen Thu Hien (2021), and Dang Ngoc Hung et al (2022).

According to the regression results, in the period of 5 years from 2018 to

In 2022, analysis using Pooled OLS and FGLS models reveals that SIZE significantly influences stock prices at a 1% significance level, supporting hypothesis 8 (H8), which posits that P/E positively affects the stock prices of companies listed on HOSE These findings align with prior research conducted by Hatta and Dwiyanto (2012) and Al-Malkawi et al.

Empirical research on the HCMC stock market from 2018 to 2022 using the FGLS model indicates that stock prices are significantly influenced by accounting metrics such as EPS, BVPS, ROA, ROE, DPS, and SIZE Specifically, increases in EPS, BVPS, ROA, DPS, SIZE, and P/E are associated with rising share prices, highlighting the positive relationship between these financial indicators and stock valuation.

The study indicates that a higher Return on Equity (ROE) correlates with lower share prices, suggesting a negative relationship Furthermore, no significant connection was found between financial leverage (FL) and the share prices of listed companies on HOSE during the research period These findings provide valuable insights for management agencies, businesses, investors, and researchers to understand the factors influencing stock prices of listed companies.

In Chapter 4, the author examines how accounting information influences the financial statements and stock prices of companies listed on HOSE Utilizing descriptive statistics and various regression methods on panel data, including Pooled OLS, FEM, REM, and FGLS analyzed through STATA 17, the study identifies a suitable model The findings indicate that stock prices (P) are significantly impacted by factors such as EPS, BVPS, ROA, ROE, DPS, SIZE, and P/E.

The study reveals that EPS, BVPS, ROA, DPS, SIZE, and P/E positively influence share prices, whereas ROE has a negative impact Additionally, FL shows no correlation with share prices These findings contrast with Nguyen Thi Thuc Doan's (2011) research, which examined different companies, time periods, and market share prices.

CONCLUSION AND IMPLICATIONS

Conclusion

The thesis titled "The Effect of Accounting Information on Share Prices of Companies Listed on Ho Chi Minh Stock Exchange" explores the practical needs of stock investors who rely on accounting information from financial statements for securities investment The research aims to clearly define the relationship between accounting information and stock prices of companies listed on HOSE during the period from 2018 to 2022.

The research conducted on listed companies on HOSE from 2018 to 2022 provides empirical evidence of the impact of accounting information on financial statements on share prices Utilizing previous studies, the author developed research models and analyzed panel data through descriptive statistics and various linear regression methods, including OLS, FEM, REM, and FGLS, focusing on eight independent variables: EPS, BVPS, ROA, ROE, DER, DPS, SIZE, and P/E, with P as the dependent variable The analysis, performed using STATA 17 software, revealed that stock prices are significantly influenced by accounting information, specifically EPS and BVPS.

The analysis reveals that key financial metrics—ROA, ROE, DPS, SIZE, P/E, EPS, and BVPS—significantly influence stock prices (P) at the 1% significance level, with ROA, DPS, SIZE, P/E, EPS, and BVPS exhibiting a positive correlation, while ROE shows a negative correlation Notably, FL does not correlate with P These findings underscore the critical role of financial statement information in stock investment decisions, highlighting the impact of these seven independent variables on stock price dynamics.

Earnings Per Share (EPS) is a key indicator of a company's financial health, with higher EPS suggesting stronger business performance and an increased ability to pay dividends, which often correlates with rising stock prices Book Value Per Share (BVPS) serves as a benchmark for comparing market stock prices to a company's true value Return on Assets (ROA) reveals how effectively a company generates profits from its investments, with a higher ROA indicating greater efficiency in profit generation Annual increases in Dividends Per Share (DPS) demonstrate a company's profitability and commitment to rewarding shareholders Financial leverage (FL) is a preferred strategy among managers, reflecting the impact of debt on earnings per share A high DPS typically fosters positive sentiment among shareholders, contributing to stock price appreciation The Price-to-Earnings (P/E) ratio is vital for investors, indicating how much they are willing to pay for each dollar of profit, with higher P/E ratios often signaling potential for future growth This analysis aligns with findings from previous studies by notable authors in the field.

The research findings provide valuable insights for business managers, investors, and researchers to better understand the factors influencing stock prices of listed companies on HOSE These insights can inform policy recommendations aimed at enhancing the quality of financial statement information in relation to stock prices.

Policy implications

Corporations need to clearly and accurately present the accounting information on financial statements, specifically:

To achieve medium- and long-term stock price stability and growth, companies must implement a sustainable development strategy They should adhere to commitments made at shareholder meetings and strive to exceed previously established goals This approach should include policies that enhance shareholder value, such as regular cash dividends and a robust business plan aimed at expanding the company and increasing the number of outstanding shares By fostering a stable environment, businesses can cultivate investor confidence, encouraging long-term investment rather than short-term trading, ultimately leading to steady stock growth.

Timely and accurate disclosure of crucial information, including financial status, business performance, ownership structure, and management quality, is essential in the complex landscape of financial markets Investors rely on this transparency to ensure the accuracy of the information they receive Proper information disclosure not only helps raise capital but also fosters investor confidence Conversely, inadequate and unclear disclosure can harm the company, its shareholders, and the broader economy.

To ensure effective corporate governance, it is crucial for the board of directors to provide strategic direction and oversee their responsibilities to the company and its shareholders This principle highlights the board's primary role in implementing quality management, prioritizing the interests of shareholders, and safeguarding their rights Additionally, it underscores the importance of transparent information disclosure to maintain trust and accountability.

Supplementing the regulation that listed companies must have a transparent, clear and accessible policy on the roles and interests of customers, suppliers/business partners

Establishing comprehensive quality management rules involves creating evaluation and classification criteria, alongside a code of business ethics for the Board of Directors, leaders, and all employees Additionally, these regulations should include specific procedures for addressing violations, tailored to both the collective group and individual members.

Enhancing regulations on Internal Control operations is essential for early detection and prevention of quality management defects, enabling timely and cost-effective remediation Additionally, promoting the separation of roles between the Chairman of the Board and the Company's Director can strengthen the supervisory and executive functions within each department.

The auditor evaluates the financial statements to assess their accuracy, fairness, and adherence to relevant legal standards They will highlight any discrepancies or approve the data, indicating areas of non-compliance.

Auditors and accountants must consistently maintain their professional and ethical standards By recognizing situations that threaten their ethical conduct, they can take proactive measures to mitigate, eliminate, or manage these risks effectively.

When investing in securities, it is essential to closely analyze accounting information, as it can significantly influence stock prices Key metrics such as Earnings Per Share (EPS), Book Value Per Share (BVPS), Return on Assets (ROA), Return on Equity (ROE), Dividends Per Share (DPS), and Price-to-Earnings (P/E) ratios should be considered alongside the company's financial statements This research underscores the importance of these indicators for investors looking to invest in companies listed on the HOSE It is advisable for investors to target firms with strong EPS, BVPS, ROA, DPS, SIZE, and P/E ratios, as these metrics are indicative of potential share price growth To make informed investment decisions, investors must gather comprehensive information from various sources.

In addition to the 2006 Law on Securities, the Ministry of Finance regularly issues circulars that update information disclosure practices for listed companies The most recent document, Circular 96/2020/TT-BTC, dated November 16, 2020, provides guidance on mandatory stock market information disclosure However, there is currently no governing document for voluntary information disclosure in the stock market To improve voluntary information disclosure, several solutions are proposed.

To enhance transparency, it is essential to recognize the legal significance of voluntary information disclosure and adjust current practices accordingly The Ministry of Finance, along with law enforcement agencies, should provide official guidelines on voluntary disclosures in annual reports, enabling businesses to better understand and improve their information-sharing practices.

Supporting businesses in simplifying and accelerating voluntary information disclosure promotes transparency and enhances corporate governance Legal modifications to voluntary disclosure activities will encourage listed companies to diversify the types of information shared Additionally, companies should be permitted to publish information beyond the required categories, including periodic and extraordinary disclosures, fostering a more open business environment.

To enhance information disclosure, it is essential to diversify both required and optional methods Currently, electronic channels dominate stock market news, overshadowing traditional methods Daily stock market newsletters issued by the Stock Exchange or the Association of Securities Investors can play a crucial role in this diversification By creating and distributing securities newsletters, we can expand the channels and methods available for accessing vital securities-related information.

To enhance stock market transparency and ensure fair treatment for all investors, it is essential to implement laws mandating the disclosure of information in both Vietnamese and English by all stock market participants The Securities Depository Center and Stock Exchange should adhere to the requirements of Circular 96/2020/TT-BTC, which stipulates that information be published in both languages This bilingual disclosure will facilitate access to vital information for both domestic and foreign investors, fostering a more equitable investment environment.

Limitations

This thesis has explored a wide range of topics and data to the best of its ability However, due to both objective and subjective factors, several limitations were encountered in the study.

The study's findings are based on a limited sample of companies, which restricts the ability to generalize the results to the entire Vietnamese stock market.

Second, the thesis examines the influence of accounting information on financial statements on share prices of listed companies that have not been classified by groups and industries

The thesis focuses solely on eight accounting information metrics from financial statements that influence stock prices, leaving many other relevant factors, such as current ratio (CR), cash flow from operations (CFO), net profit margin (NPM), and beta, unexamined.

Fourth, the analysis was selected based on a random sample of the list of listed companies, but the results were taken as a whole This should be carefully considered and evaluated.

Future studies

In order to strengthen and contribute to answering the research question from the limitations of the topic, the author would like to suggest possible research solutions in the future:

To enhance research quality, it is essential to increase the number of listed companies on the Vietnamese stock market, which will broaden the observed sample size and allow for an expansion of the analysis over additional years.

Second, the study focuses on analyzing the influence of information on financial statements on stock prices of listed companies by industry, such as real estate, construction, food, and beverages

Third, the study expands the information on financial statements such as current ratio (CR), cash flow from operation (CFO), ROI (Return on investment), etc affect stock prices

Future research will build upon the previously mentioned directions to provide managers and investors with precise and valuable insights This will enable the development of customized investment and business strategies aimed at fostering sustainable and profitable growth.

Vào năm 2012, Bộ Tài chính đã ban hành Quyết định số 165/2002/QĐ-BTC ngày 31 tháng 12 năm 2002, công bố sáu chuẩn mực kế toán Việt Nam (Đợt 2) Quyết định này có thể được truy cập tại , với thông tin được cập nhật đến ngày 10/08/2023.

Bộ Tài chính đã ban hành Thông tư số 52/2012/TT-BTC vào ngày 5 tháng 4 năm 2012, hướng dẫn về việc công bố thông tin trên thị trường chứng khoán Thông tư này cung cấp các quy định chi tiết nhằm đảm bảo tính minh bạch và công khai thông tin cho các nhà đầu tư Để tìm hiểu thêm, bạn có thể truy cập vào tài liệu tại thuvienphapluat.vn, thông tin được cập nhật đến ngày 10/08/2023.

Bộ Tài chính 2014, Thông tư của Bộ Tài chính số 200/2014/TT-BTC ngày 22 tháng

12 năm 2014 hướng dẫn chế độ kế toán doanh nghiệp, truy cập tại , [truy cập ngày 10/08/2023]

Bộ Tài chính 2015, Thông tư của Bộ Tài chính số 155/2015/TT-BTC ngày 6 tháng

Vào năm 2015, Thông tư 155/2015/TT-BTC đã được ban hành nhằm hướng dẫn việc công bố thông tin trên thị trường chứng khoán Thông tư này quy định các yêu cầu và quy trình cần thiết để đảm bảo tính minh bạch và công bằng trong hoạt động giao dịch chứng khoán Các tổ chức niêm yết và nhà đầu tư cần nắm rõ nội dung của Thông tư để tuân thủ đúng quy định và bảo vệ quyền lợi của mình trên thị trường.

2015 (thuvienphapluat.vn)>, [truy cập ngày 11/08/2023]

Bùi Kim Yến và Nguyễn Minh Kiều (2013) đã trình bày trong cuốn sách "Thị trường tài chính và các định chế tài chính" những lý thuyết và thực hành ứng dụng cho thị trường Việt Nam, xuất bản bởi NXB Tài chính tại Hà Nội.

CafeF 2023, Dữ liệu lịch sử, truy cập tại , [29 August 2023]

Vào ngày 28 tháng 11 năm 1996, Chính phủ Việt Nam đã ban hành Nghị định số 75-CP về việc thành lập Ủy ban Chứng khoán Nhà nước Nghị định này đánh dấu bước tiến quan trọng trong việc quản lý và phát triển thị trường chứng khoán tại Việt Nam Để biết thêm thông tin chi tiết, vui lòng truy cập tại , [truy cập ngày 12/08/2023].

Chính Phủ 1998, Nghị định của Chính Phủ số 48/1998/NĐ-CP ngày 11 tháng 7 năm 1998 về chứng khoán và thị trường chứng khoán, truy cập tại , [truy cập ngày 12/08/2023]

Nghị định số 48/2017/NĐ-CP ngày 24 tháng 4 năm 2017 của Chính phủ quy định các cơ chế và chính sách tài chính – ngân sách đặc thù cho Thành phố Hồ Chí Minh, có thể tham khảo tại , [truy cập ngày 12/08/2023] Đào Lê Minh (2002) trong cuốn "Những vấn đề cơ bản về chứng khoán và thị trường chứng khoán" đã cung cấp kiến thức nền tảng về lĩnh vực này Ngoài ra, nghiên cứu của Đỗ Thị Mỹ và Nguyễn Thị Thu Hiền (2021) trong Tạp chí Khoa học và Công nghệ đã chỉ ra rằng thông tin kế toán trên báo cáo tài chính có ảnh hưởng đáng kể đến giá cổ phiếu của các doanh nghiệp niêm yết trên thị trường chứng khoán Việt Nam.

Trong tháng 5 năm 2023, thanh khoản trên sàn HOSE đã có sự tăng trưởng đáng kể, cho thấy sự phục hồi của thị trường chứng khoán Theo báo cáo từ Thời báo Tài chính Việt Nam, sự gia tăng này phản ánh niềm tin của nhà đầu tư vào triển vọng kinh tế Để biết thêm chi tiết, vui lòng truy cập bài viết gốc.

Nguyễn Đình Thọ 2013, Phương pháp nghiên cứu khoa học trong kinh doanh,

NXB Lao động Xã hội, Hà Nội

Năm 2022, Nguyễn Dũng đã chỉ ra rằng số lượng doanh nghiệp niêm yết vi phạm công bố thông tin tăng đột biến, điều này có thể ảnh hưởng tiêu cực đến thị trường chứng khoán Bài viết của Nguyễn Khánh Hà năm 2023 phân tích sự biến động của thị trường chứng khoán từ đỉnh cao xuống vực sâu, đồng thời nhấn mạnh "ánh sáng cuối đường hầm" cho những nhà đầu tư Ngoài ra, nghiên cứu của Nguyễn Thị Thục Đoan (2011) đã chỉ rõ ảnh hưởng của thông tin kế toán và các chỉ số tài chính đến giá cổ phiếu trên thị trường chứng khoán Việt Nam, cho thấy tầm quan trọng của việc công bố thông tin chính xác và kịp thời.

Quốc Hội 2015, Luật Kế toán của Quốc Hội số 88/2015/QH13, truy cập tại , [truy cập ngày 11/08/2023]

Quốc Hội 2019, Luật Chứng khoán của Quốc Hội số 54/2019/QH14, truy cập tại

, [truy cập ngày 12/08/2023]

Sở Giao Dịch Chứng Khoán Thành phố Hồ Chí Minh 2022, Báo cáo thường niên

2022, truy cập tại , [15

Vào ngày 11 tháng 7 năm 1998, Thủ tướng Chính phủ đã ban hành Quyết định số 127/1998/QĐ-TTg về việc thành lập Trung tâm Giao dịch Chứng khoán, đánh dấu một bước quan trọng trong việc phát triển thị trường tài chính Việt Nam Quyết định này có thể được truy cập tại , [truy cập ngày 12/08/2023].

Trung tâm Lưu ký Chứng khoán Việt Nam đóng vai trò quan trọng trong sự phát triển của ngành chứng khoán tại Việt Nam Để tìm hiểu thêm về các hoạt động và thông tin liên quan, bạn có thể truy cập vào trang web của Tổng công ty Lưu ký và Bù trừ chứng khoán Việt Nam tại , [truy cập ngày 20/08/2023].

Aboody, D., Hughes, J and Liu, J 2002, ‗Measuring value relevance in a (possibly) inefficient market‘, Journal of accounting research, vol 40, no 4, pp 965-986

Al-Malkawi, H A N., AlShiab, M S and Pillai, R 2018, ‗The impact of company fundamentals on common stock prices: evidence from MENA region‘, The Business

& Management Review, vol 9, no 4, pp 162-172

Asiri, B K and Hameed, S A 2014, ‗Financial ratios and firm's value in the Bahrain Bourse‘, Research journal of finance and accounting, vol 5, no 7, pp 1-9

Asquith, P., Bruner, R F and Mullins Jr, D W 1983, ‗The gains to bidding firms from merger‘, Journal of financial economics, vol 11, no 4, pp 121-139

Badru, B., Nordiana Osagie Davies, N O D and Idowu, A 2020, ‗Board size determinants: Evidence from Nigeria‘, The International Journal of Banking and

Besley, S and Brigham, F 2006, Essential of Managerial Finance,

THOSON:South-Western, United States

Bhattacharya, S 1979, ‗Imperfect information, dividend policy, and "the bird in the hand" fallacy‘, The bell journal of economics, vol 10, no 1, pp 259-270

Gordon, M J 1963, ‗Optimal investment and financing policy‘, The Journal of finance, vol 18, no 2, pp 264-272

Gower Fama and E F 1970, ‗Session topic: stock market price behavior‘, The

Journal of Finance, vol 25, no 2, pp 383-417

Ha, H T V., Hung, D N and Xuan, N T 2022, ‗Relationships between Accounting Information on the Business Financial Statements and the Stock Price:

A Study with LASSO Method‘, Calitatea, vol 23, no 186, pp 237-245

Hatta, A J and Dwiyanto, B S (2012), ‗The company fundamental factors and systematic risk in increasing stock price‘, Journal of Economics, Business, &

Accountancy Ventura, vol 15, no 2, pp 245-256

The study by Hung, D N., Ha, H T V., and Binh, D T (2018) examines how accounting information influences financial statements and subsequently affects the stock prices of energy enterprises listed on Vietnam's stock market The research highlights the critical role of accurate accounting data in shaping investor perceptions and market valuations within the energy sector.

Jensen, M C and Meckling, W H (2019), ‗Theory of the firm: Managerial behavior, agency costs and ownership structure‘, Journal of Financial Economics, vol 3, no 15, pp 77-132

Kendall, M G and Hill, A B 1953, ‗The analysis of economic time-series-part i: Prices‘, Journal of the Royal Statistical Society Series A (General), vol 116, no 1, pp 11-34

Lintner, J 1962, ‗Dividends, earnings, leverage, stock prices and the supply of capital to corporations‘, The review of Economics and Statistics, vol 44, no 3, pp 243-269

Mondal, S A and Imran, M S 2010, ‗Determinants of stock price: a case study on Dhaka stock exchange‘, International Journal of Finance, vol 2, no 3, pp 1-16

Ohlson, J A 1995, ‗Earnings, book values, and dividends in equity valuation‘, Contemporary accounting research, vol 11, no 2, pp 661-687

Otuya, S 2019, ‗Auditors‘ independence and quality of financial reporting in listed Nigerian manufacturing companies‘, International Journal of Accounting and

Finance (IJAF), vol 8, no 1, pp 111-128

Raharjo, D and Muid, D 2013, ‗Analisis Pengaruh Faktor-Faktor Fundamental Rasio Keuangan Terhadap Perubahan Harga Saham‘, Diponegoro Journal of

In their 2017 study published in The Indonesian Accounting Review, Satryo, Rokhmania, and Diptyana investigate the impact of profitability, market, and solvency ratios on the share prices of companies listed on the LQ 45 Index The research, spanning volume 6, issue 1, pages 55-66, highlights the significant relationships between these financial ratios and stock performance, providing valuable insights for investors and analysts in understanding market dynamics.

Shen, P 2000, ‗The P/E ratio and stock market performance‘, Economic review-

Federal reserve bank of Kansascity, vol 85, no 4, pp 23-36

The Australian Accounting Standards Board 2019, Conceptual Framework for Financial Reporting, Available from , [15 July

Valix, C and Peralta, J 2009, Financial accounting Volume 2, Manila: GIC

Wooldridge, J M (2002), Econometric Analysis of Cross Section and Panel Data, The MIT Press Cambridge, London

Appendix 1.1: Variables used by Dang Ngoc Hung et al (2022)

X1 Company size (Total assets) Log (Total assets)

X2 Company size (Total revenue) Log (Total revenue)

X3 Assets growth (Total assetst - Total assetst-1) / Total assetst X4 Revenue growth (Revenuet - Revenuet-1) / Revenuet X5 Assets to debts ratio Total assets / Total debts

X6 Coefficient of short-term debt solvency

Total current assets / Total short-term liabilities

X7 Current ratio (Current assets - Inventory) / Total short-term liabilities X8 Quick solvency ratio Cash and cash equivalents / Total short- term liabilities

X9 Net trade cycle (squared) Squared ((Average receivables +

Average inventory - Average payables) x 365 / Total revenue) X10 Cash conversion cycle (squared) Squared (Average receivables x 365 /

To assess financial performance, key ratios are calculated, including the average payables period, which is derived from the formula (365 / Cost of Goods Sold) x Average Payables Financial leverage is represented as the square of the total debt divided by total assets, while the long-term debt ratio is calculated as the square of long-term debt over total assets Similarly, the short-term debt ratio is determined by squaring the short-term debt in relation to total assets Lastly, the cash ratio is evaluated by squaring the cash amount relative to total assets These metrics provide valuable insights into a company's financial health and leverage.

X15 Financial leverage Total debt / Total assets

X16 Long-term debt ratio Long-term debt / Total assets

X17 Short-term debt ratio Short-term debt / Total assets

X18 Cash flows / Total short-term liabilities ratio

Net cash flow from operating activities / Average short-term liabilities

X19 Cash flow / Debt-to-maturity ratio

Net cash flow from operating activities / Debt-to-maturity

X20 Debt ratio Total debt / Total liabilities

X21 Financing factor Total equity / Total liabilities

X22 Liabilities / Equity ratio Total liabilities / Total equity

X23 Book value per share (BV) Book value of equity / Number of common shares in circulation X24 Change in earnings per share

(Earnings per share (EPS)t - Earnings per share (EPS)t-1) / Earnings per share (EPS)t-1

X25 Earnings per share (EPS) (Profit after tax - Dividends of preferred shares) / Average number of common shares outstanding X26 Profit after tax to Net revenue

Profit after tax / Net revenue

X27 Coefficient of long-term debt solvency

Long-term assets / Long-term debt

X28 Coefficient of loan interest solvency

Profit before corporate income tax and interest expenses / Interest expenses X29 Coefficient of periodic interest payment

Average cash / Average interest payable

X30 Current assets turnover Net revenue / Current assets

X31 Assets turnover Net revenue / Total assets

X32 Inventory turnover (days) Average inventory value x 365 / Cost of goods sold X33 Account receivables turnover Net revenue / Account receivables X34 Retained earnings on equity Retained earnings / Total equity