This study incorporates five fundamental factors from various areas, including company Size Total assets, Book-to-Market ratio, Earning-to-Price ratio, Profitablity return on equity and
GENERAL INTRODUCTION
Induction
Stocks, also known as equity securities, signify ownership claims on a company’s net assets As a crucial asset class, stocks play a fundamental role in investment analysis and portfolio management They constitute a substantial portion of both individual and institutional investment portfolios Investors widely embrace stocks due to their potential for higher profits and their comparatively lower capital requirements when compared to bonds (CFA Institute, 2023) Understanding stock returns is important for at least two reasons First, understanding stock returns would help portfolio managers in effectively choosing stocks for their clients in order to meet clients’ risk and return objectives Second, different companies have different strategies, risk profiles which affect their share prices and eventually affect the portfolio managers in choosing stocks (CFA Institute, 2023)
Fundamental analysis on stock returns has a long history in developed market, namely
US market Numerous studies have shown that fundamental factors of a company, such as its size, earning-to-price ratio, book-to-market ratios, dividend yields, have impact on stock returns Such analyses allow investors to gain surplus returns (Fama
& French (1992), Mahmoud & Sakr (2012)) Fundamental analysis has gained huge popularity among capital markets researchers Besisde, Suresh (2013) found that fundamental analysis offers several benefits, including the ability to predict long-term trends, identify undervalued stocks, and enhance business acumen However, most of these studies were conducted for developed stock market, notably the study of Fama
& French (1992) which was conducted for US stock market There are limited evidences that these findings are comparable to emerging market like Vietnam market
In Vietnam, there are some studies on fundamental factors and company stock returns Studies of Lộc (2014) investigates the relationship between stock returns and fundamental factors for big-size firm listed on HOSE While, study of Linh Nhat
Minh & Manh Tien (2022) investigates the relationship for companies listed on Ha Noi stock exchange (HNX) Or, study of Duy & Phuoc (2016) investigate the relationship between size and profitability of companies to their stock returns using service-sector companies listed on HOSE
This study would like to study the relationships between stock returns and companies’ fundamental factors in another sector, specifically, manufacturing sector to contribute knowledge on manufacturer stocks Vietnam market is considered as emerging market, so stock behavior is particularly different from developed stock market Moreover, a study on the manufacturing sector would minimize the sector-specific differences in their fundamental factors between companies, allowing a more accurate analysis In addition, the choice of manufacturing sector is because of its importance in economy of Vietnam with manufacturing sector contributed largest share of Vietnam Gross Domestic Product The sector contributed 23.88% to 2023 GDP of Viet Nam (Statista, Gross domestic product (GDP) distribution in Vietnam in 2023, by sector, 2024) Also, Viet Nam is emerged as a new manufacturing hub in the world, which emphasizes the importance of this sector (Statista, 2024)
This study will investigate the relationship between stock returns and company fundamental factors, which are size, growth, capital structure and profitability
Study objectives
This study aims to identify relationships between stock returns and companies’ fundamental factors Some specific objectvives are following:
- To discover the relationship between company stock returns and each of the fundamental factors of the company These fundamental factors are firm size (Total assets), earning-to-price ratio (E/P), book-to-market ratio (B/M), profitability (Return on equity) and capital structure (Debt-to-equity ratio)
Scope of the study
The study is conducted on five fundamental factors which are extracted from public companies’ financial reports The study sample includes 113 companies who are in manufacturing sectors listed on Ho Chi Minh Stock Exchange (HOSE) The study analyzes companies’ fundametal factors for 3 years, 2020, 2021 and 2023 The study excludes analysis for 2022 because stock market was severly impacted by COVID Timeline: the study lasts 3 months from 2/2024 to 5/2024
Significance of the study
This study mainly aims to Facilitate fund managers in screening stocks, making capital allocation decsion in equity asset class, especially working with manufacturing sector By examining relationship between fundamental factors and with stock returns, it provides an empirical understanding about stock returns Fund managers and financial analysts can use companies’ fundmental factors to screen for prospective stocks, assess stock expected returns
In addition, this study provides high-level managers in manufacturing companies in making decision and dealing with banks when raising capital,an empirical understanding about the impacts of companies’ earnings, capital structure and capital management on their companies’ stocks Understanding these relationships may faciliate company managers in negotiating with banks and investors for funding capital.
Structure of the study
The study includes 5 parts Part 1 is introduction to the study Part 2 discusses literature reviews related to the study Part 3 presents research method Part 4 discusses results of the study From results in part 4, part 5 provides conclusions about the study and implications for managers
Figure 1.1 Workflow of the study
The study implemetation process is shown in Figure 1.1 The details of each step as follow:
The first part of the study is introduction part, which includes the study topic, study objectives and study questions:
- Study topic: The study investigates the relationships between stock returns and fundamental factors of manufacturing companies that are listed on Ho Chi Minh Stock Exchange
- Study objectives: the study aims to understand relationships between stock returns and companies’ fundamental factors, which are firm size (Total assets), earning-to-price ratio (E/P), book-to-market ratio (B/M), profitability (Return on equity) and capital structure (Debt-to-equity ratio)
The second part of the study is literature review, in which concepts, formulas of these fundamental factors are reviewed Fundamental factors of a company are its earnings, capital structure, profit, assets, liabilities, and many other information that are reported on the company’s financial reports Firm size (Total assets), earning-to-price ratio (E/P), book-to-market ratio (B/M), profitability (Return on equity) and capital structure (Debt-to-equity ratio) are frequently used in studies about stock returns and fundamental factors
The third part is research method, which shows required data for the study, sources of these data and analyzing methods Required data are acquired in financial statements of manufacturing companies listed on Ho Chi Minh Stock Exchange (HOSE) These financial statements are publicly available on Vietstock official website Multiple regression analysis is used to investigate the impact of five fundamental factors on stock returns simultaneously The data is annual data that is collected for the years 2019, 2020, 2021, 2022, 2023 All data for the study are shown in Appendix
The fourth part shows the results of the study after analyzing, including descriptive statistics of data, correlations between variables and results of study regression model
Finally, the fifth part summarizes the findings of the study and implications of the study.
LITERATURE REVIEW
Theoretical framework
Fundamental factors of a company are the earnings, profit, capital structure, assets, liabilities, and many other information that are reported on the company’s financial reports The existence of studies offer compelling evidence of connections between stock prices and microeconomic fundamentals, primarily observed in general stock market indices This relationship is often interpreted through two fundamental theoretical perspectives The efficient market hypothesis (EMH) posits that stock prices reflect all pertinent information already (Fama E F., 1970), while the arbitration theory provides a framework that validates the impact of macroeconomic and microeconomic variables on stock prices (Chen et al., 1986) Such theories suggest that stock prices change in respones to all relevant important information of companies namely, its earning, capital structure, size, profitability, risk, capital investment decision (Fama & French, 1992); (Miller & Modigliani, 1958)
The capital asset pricing model (CAPM) remains one of the most widely accepted asset pricing theories today It suggests that the average returns on stocks are determined by beta and anticipated market returns Nevertheless, numerous research studies challenge this model, pointing to additional factors like company size, leverage, book-to-market ratio, and earnings yield that could potentially exert a greater influence on average stock returns Several studies, most notably is the study of Fama & French (1992), have shown that company size and book-to-market ratio have impact on stock returns, which has become the foundation theory for future analysis of company fundamental factors and stock returns In addition to book-to- market ratio, earning-to-price ratio is also used as a fundamental factor to predict stock returns, as suggested by Graham (1934) in his famous book about fundamental analysis Lewellen (2004) used earning-to-price ratio together with book-to-market ratio and other ratios in analysis of stock returns Theories and many reseaches suggest that profitability of a company affect stock returns, stating that company with higher profitability should have higher prices Capital structure of a company is proved to be particular crucial, which a firm's overall performance is heavily impacted by leverage, as the choice of capital structure can either impede or facilitate the achievement of its objectives (Miller & Modigliani, 1958) Moreover, the Miller
& Modigliani proposition (1958) stated that company value is affected by capital structure in a world with tax The trade-off theory of capital structure says that a company should have an optimal capital structure that maximize company value, indicating that capital structure does affect stock price, and eventually stock returns.
Fundmental factors and hypothesis developement
The following sections discuss in detail the five fundamental factors, which are firm size, Earning-to-Price ratio (E/P), Book-to-Market ratio (B/M), profitability (Return on equity) and capital structure (Debt-to-equity ratio)
Size of a company has long been considered as a factor that affect the risk of company Bigger company are considered safer for investment and eventually required less risk premium than small company (Mossin, 1966) Fama & French (1992) conducted a famous cross-sectional study about effect of company size and book-to-market ratio on stock returns and found that both size and book-to-market ratio have effect on stock return Specifically, company size has an inverse relationship with stock returns, which means small-size stocks have higher returns than large-size stocks However, there are some researches which found that size has a positive impact on stock returns (Wong, 1989); (Yuliza, 2018)
There are various indicators for representing company size, including sales, total assets, market capitalization, market value of invested capital, book value of equity (Grabowski et al., 2016) Moore (2000), however, suggested that total assets is referrable to avoid inflation and deflation of stock prices This is suitable for the Vietnamese market as it is inefficient, leading to stock prices that do not fully incorporate all relevant information Consequently, stock prices might experience volatility as a result of informal reasons Therefore, this study uses Total Assets as indicator for size To avoid the big number of Total Assets, size of a company is the natural logarithm of total assets, as similar to many other researches
This study follows Fama & French (1992) ‘s findings that company size has negative effect on stock returns In common sense, small companies should find difficult in funding capital, governance and holding human capital, thus, they are riskier than large companies and investors require more risk premium
H1: There is statistically significant negative relationship between SIZE and stock returns
Practioners in finance and economics are constantly seeking factors that can account for changes in stock prices and forecast stock returns The market-to-book ratio emerged as a promising candidate following findings of Fama and French (1992), which demonstrated that the book-to-market ratio of specific stocks is able to explain differences in stock returns across various companies Their studies found that book- to-market ratio havs positive impact on stock returns, which mean that stock with higher book-to-market ratio would earn higher return compared to lower book-to- market ratio Book-to-Market ratio is used by both practioners and academic researchers to identify the undervalued or overvalued stocks Numerous researches have found that Book-to-Market ratio does have a positive significant impact on stock returns such as research of Muhammad (2014) In gerneral, the formula for calculating Book-to-Market ratio is:
This study follows the findings Fama & French (1992) that company Book-to-Market ratio has positive impact on stock returns The higher the ratio, the higher stock returns
H2: There is statistically significant positive relationship between Book-to-Market ratio and stock returns
Earning-to-Price ratio is the inverse of Price-Earning ratio (P/E), which is arguably the most popular ratio in finance industry Practioners use Earning-to-Price ratio similarly to Book-to-Market ratio, which aim to identify undervalued and overvalued stocks Stock with high Earning-to-Price ratio is believed to outperform low Earning- to-Price stock Graham (1934) suggested that stock with higher Earning-to-Price ratio is a worthwhile investment, indicating that E/P has positive impact on stock returns Research of Chan and colleagues (1993) found that E/P has negative impact on stock returns In gerneral, the formula for calculating Earning-to-Price ratio is:
This study expects that E/P will have a positive impact on stock returns because high E/P ratio reflect the higher earning yield
H3: There is statistically significant positive relationship between Earning-to-Price ratio and stock returns
Profitability - Return on Equity (ROE)
Return on equity (ROE) reflects the return earned by a company on its equity capital ROE is also a measure of efficiency of a company in using its equity capital (Higgins, 2016) ROE is measured as ( Robinson et al., 2020)
Asikin B and colleagues (2020) concluded from their research that ROE is significantly affect stock prices Investors will have a keen interest in understanding the equity's return that the company yields Investors closely monitor ROE as a metric that influences their investment choices (Asikin et al., 2020) In addition, Allozi &
Obeidat (2016), Bambang et al., (2020) also found that ROE positively affect stock returns On the other hand, Abdulmannan & Faturohman (2015) found that ROE did not significantly affect stock returns The insignificant effect of ROE on stock returns was also founded by Afriyani and colleagues (2020)
The inconsistency of conclusions about effect of ROE on stock returns has raised a question about this relationship for this study This study expects that ROE will have a significantly positive effect on stock returns because higher earnings indicates that companies are better and thus, its stock returns should be higher (Higgins, 2016) So, the hypothesis is:
H4: There is statistically significant positive relationship between ROE and stock returns
Leverage ratio (LEV) is a ratio between book value of debt to book value of equity in a company which represent the capital structure of a company The choice of capital structure stands out as a critical decision that managers encounter, where alterations in the leverage ratio can impact a company's financing capabilities, risk profile, cost of capital, investment choices, strategic decisions, and ultimately influence shareholder wealth (Adami et al., 2010) The firm's overall performance is heavily impacted by leverage, as the choice of capital structure can either impede or facilitate the achievement of its objectives (Miller & Modigliani, 1958) A company with higher LEV indicates that the company is riskier and has weaker solvency LEV is calculated as ( Robinson et al., 2020)
In which, total debt is the sum of interest-bearing short-term and long-term debt
Many researches investigated and shown that leverage ratio has no effect on stock returns, including studies of Pasaribu and Nugroho (2023), Thamrin & Sembel (2020), Allozi and Obeidat (2016), Gebhardt et al (2001), Shakeel and Gohar (2018) Thamrin & Sembel (2020) conducted a study using a sample of consumer-goods companies and found that LEV and stock return have no relationship According to the static trade-off theory, while leverage increases the financial risk of a company, it may not necessarily have a negative impact on stock prices up to a certain limit Investors may not feel the financial distress caused by leverage as long as companies keep their leverage below this threshold (Shakeel & Gohar, 2018) On the other side, Bambang et al., (2020) found negative relationship between LEV and stock returns Also, Roberta Adami and colleagues (2010) investigated relationship between leverage and stock returns and found that LEV exhibits a significant negative relationship with stock returns In addition, Dita & Murtaqi (2014) also found that LEV has a significantly negative impact on stock returns
LEV are also found to have inconsistent impact on stock returns Therefore, this study would like to study the relationship between LEV and stock returns The study expects that LEV would have a singificant negative impact on stock returns because higher LEV indicates that the company is risker and thus reduce its stock price So, the hypothesis is:
H5: There is statistically significant negative relationship between LEV and stock returns
Summary study hypotheses
This study examines the relationship between stock returns and 5 fundamental factors which are firm size (Total assets), earning-to-price ratio (E/P), book-to-market ratio (B/M), profitability (Return on equity) and capital structure (Debt-to-equity ratio) This study expects that Book-to-Market ratio, Earning-to-Price ratio and profitablity of a company will postively affect stock returns while capital structure (Debt-to- equity ratio) and firm size will negatively affect stock returns
H1 There is statistically significant negative relationship between SIZE and stock returns
H2 There is statistically significant positive relationship between Book-to-
Market ratio and stock returns
H3 There is statistically significant postive relationship between Earning-to- Price ratio and stock returns
H4 There is statistically significant postive relationship between profitability (Return on equity) and stock returns
H5 There is statistically significant negative relationship between capital structure (Debt-to-equity ratio) and stock returns
RESEARCH METHOD
Data analysis workflow
Figure 3.1 General analysis workflow of this study
Figure 3.1 shows the general process of analyzing data in this study The following sections provide details of each step of data analysis workflow
Study data requirement
The data for the study is fundamental factors of manufacturing listed on Ho Chi Minh Stock Exchange (HOSE) These fundamental factors include Size factor, Growth factor, Profitability factor, Solvency factor Size factor requires collection of company total assets Growth-Value factor requires gathering information about Book-to-Market ratio and Earning-to-Price ratio Profitability factor requires collection of Return on Equity (ROE) Finally, solvency factor requires Leverage ratio, which is Debt-to-Equity ratio.
Data collection
There are 137 manufacturing companies listed on HOSE All data required are obtained from Viet Stock website Collected data for this study is shown in Appendix
Dependent variable in this study is the stock returns, which requires stock prices for calculation Stock prices are collected from April 1 st 2020 to April 1 st 2024 Annual stock returns are measured based on 12-month basis, lag 3 months (90 days) after the year end The reason for this 3-month lag is to minimize the look-ahead bias Look- ahead bias refers to using information that is not actually available at the time in the past (CFA Institute, 2023) A similar study of Allozi & Obeidat (2016) also chose a lag of 3 months for their calculation of stock returns
Size factor is the natual logarithm of company Total Assets Year-end Total Assets of 137 manufacturing companies are collected for the year 2019, 2020, 2021, 2022 and 2023 The number is available on company financial statements
Growth-value factor is Market-to-Book ratio and Earning-to-Price ratio of a company The two ratios for the years 2019, 2020, 2021, 2022 and 2023 are available on VietStock website
Profitability factor is company Return on Equity (ROE) Year-end ROEs of 137 manufacturing companies are collected for the year 2019, 2020, 2021, 2022 and 2023 The ratio is readily availabe on Viet Stock website for all 137 companies
Solvency factor is the company leverage ratio (LEV) Year-end LEV for the year 2019,2020 2021, 2022 and 2023 are collected for all 137 manufacturing companies listed on HOSE The ratio is readily available on Viet Stock website for all 137 companies under the name D/E
Table 3.1 summerizes all variables in the study
Table 3.1 Descriptions of the variables in the study
Symbol Variables Variable type Calculation formula
Data cleansing
This study excludes any company that does not have enough required information for the study Specifically:
- Any company that does not have stock prices from April 1 st 2020 to April 1 st
2024 is excluded from the sample
- Any company that has not yet to public their financial results in any of the 5 years 2019, 2020, 2021, 2022, 2023, is excluded from the sample
After cleansing the data, there is a total of 90 companies in the study sample.
Exploratory data analysis
In this step, descriptive statitistics and correlations between variables are shown In addition, scatter plots between dependent variable and each of independent variables are also displayed for visualization purpose Inspecting distributions of variables as well as correlations between them allows the study to have a preliminary view on the variables.
Research model
The study will perform multiple regression analyses following Lewellen L (2004) study with modification of adding lagged profitability suggested by Fama & French (2006) Also, analysis of each year data is recommended by Duy & Phuoc (2016) in their previous research for Vietnam stock market In essence, the study model is:
RETURN t = stock return of company for the end of year t a = intercept of regression b 1 , b 2 , b 3 , b 4 , b 5 = regression coeffients of independent variables ε is the error term
The study model will regress five lagged fundamental factors on company stock returns The regression model will be performed 3 times for three different yearly returns, which are 2020 stock returns, 2021 stock returns and 2023 stock returns The study excludes analysis of 2022 stock returns because COVID negatively impacted Vietnam stock market over 2022 Study still uses the fundametal factors of companies in 2022 because companies started recovering after the first half of 2022
In summary, stock returns in 2020 will analysed with fundamental factors in 2019 Stock returns in 2021 will be analysed with fundamental factors in 2020 Stock returns in 2023 will be analysed with fundamental factors 2022 All of the regression analyses will be performed using Eviews 13.
Verifying regression assumptions and making statistical inferences
In order to make statistical inferences from regression analysis, three main regression assumptions must be satisfied If all of these assumptions are verified, regression coefficients and test statistics are usable for making statistical inferences Otherwise, inferences from regression analysis are prone to error Specifically, these assumptions and testing method for them are:
- Normality of residual: residuals of the regression model are assumed to follow a normal distribution To test for this assumption, Jarque-Bera test will be used (Fa´vero & Belfiore, 2019) A p-value of Jarque-Bera which is greater than 0.05 indicates that the residuals of regression model follow a normal distribution
- Homoscedasticity of residuals: the residuals of the regression model must have mean of 0 and variance term to be finite and stable across the observations To test for this assumption, regression residuals is plotted against the predicted values with residuals as Y-axis The residuals must scatter randomly around the zero line, without any specific pattern, to confirm that the residual is homoscedastic, no violation of homoscedasticity assumption (Fa´vero & Belfiore, 2019) In addition, Breusch-Pagan (BP) test is used to test for homoskedasticity, with BP p-value greater than 0.05 indicates that the model residual is homoscedastic (Fa´vero & Belfiore, 2019)
- Independence of residuals (no autocorrelation): the residual of the regression model must be independent of one another, implying that residuals are uncorrelated across the obseravations To test for this assumption, Breusch- Godfrey (BG) test will be used The BG p-value should be greater than 0.05 in order to satisfy the assumption of no autocorrelation
- Multicollinearity: the independent variables in multiple regression model should not correlated to one another This assumption is verified using Variance Inflation Factors (VIF) A VIF less than 5 indicates that there is no significant impact of multicollinearity brought to the model (Fa´vero & Belfiore, 2019)
In the case where any of these assumptions are violated, Heteroskedasticity- autocorrelation corrected (HAC) standard errors will be used to make any statisical inferences (Fa´vero & Belfiore, 2019) To be specific, Heteroskedasticity-Autocorrelation Corrected standard errors of regression coefficients (HAC) will be used to derive test statistic instead of original standard errors of regression coefficients All of these tests as well as modification of standard errors are performed using Eviews 13 using significant level of 0.05.
RESULTS OF THE STUDY
Results of 2020 data
Table 4.1 Descriptive statistics for 2020 data
Table 4.1 shows the descriptive statistics of the 2020 data There are 90 companies was observed Stock returns for the year 2020 show a mean value of 0.4287, minimum value of -0.2380 and maximum value of 1.0143 As for sizes of companies that were reported on their 2019 financial statements, the mean is 28.1428, maximum value is 32.2538 and minimum value of 25.6846 Book-to-Market ratios show a mean of 1.6573, maximum value of 4.7662 and minimum value of 0.2467 Earning-to-Price ratios of companies at the end of 2019 have mean of 0.1258, maximum value of 0.3226 and minimum value of 0.0028 Profitability of the companies, ROE, shows a mean value of 0.1572, maximum of 0.4787 and minimum if 0.0021 Finally, capital structure of companies, LEV, shows a mean value of 0.5726, maximum value of 2.1356 and minimum value of 0.0000
Figure 4.1 Scatterplot between Returns and Size (2020 data)
Figure 4.1 shows the scatterplot between stock returns for the year 2020 and company sizes that companies reported in their 2019 year-end financial statements There is a slightly linear positive relationship between returns and size The correlation between the two variables is 0.126 A preliminary idea from the scatter plot is that the bigger the firm size, the greater stock returns
Figure 4.2 Scatterplot between Returns and Book-to-Market ratio (2020 data)
Figure 4.2 shows the scatterplot between stock returns for the year 2020 and company Book-to-Market ratios that are collected from companies’ 2019 year-end financial
Book-to-Market_2019Correlation = 0.361 statements There seems to be an apparent positive relation between stock returns and Book-to-Market ratio The correlation between the two variables is 0.361, which is a moderate number The scatterplot forms a first look on the relation of the two variables, that is the higher Book-to-Market value, the higher the stock returns
Figure 4.3 Scatterplot between Returns and Earning-to-Price ratio (2020 data)
Figure 4.3Figure 4.2 shows the scatterplot between stock returns for the year 2020 and company Earning-to-Price ratios that are collected from companies’ 2019 year- end financial statements Data shows that there seems to be a positive relationship between the two variables, indicated by the upward trend line The correlation between the two variables is only 0.168, supports an initial idea about this positive relationship Somehow, stocks with higher Earning-to-Price ratio have their stock returns to be greater
Figure 4.4 Scatterplot between Returns and ROE (2020 data)
Figure 4.4Figure 4.1 shows the scatterplot between stock returns for the year 2020 and company profitability, return on equity (ROE), that companies reported in their
2019 year-end financial statements There is a slightly negative relationship between returns and returns on equity of companies The correlation between the two variables is -0.094
Figure 4.5 Scatterplot between Returns and LEV (2020 data)
Figure 4.5 shows the scatterplot between stock returns for the year 2020 and company capital structure, leverage ratio (LEV), that companies reported in their 2019 year- end financial statements There seems to be a slightly positive relationship between returns and returns on equity of companies The scatterplot shows a prelinimary look at the relation between the two variables, that is company with higher leverage ratio would have its stock returns greater, which is quite intuitive
Table 4.2 Summary of regression resutls (2020 data)
Table 4.2 shows the summary of regression model between stock returns and five fundamental factors The model regresses the five fundamental factors of companies collected at the end of 2019 on the 2020 stock returns
Before making any statistical inferences, regression assumptions must be verified The Jarque-Bera p-value of 0.2043, which is greater than 0.05, indicates the assumption about normality of residual is verified Next, Breusch-Godfrey p-value of 0.9394, which is much greater than 0.05 This value verifies that the regression model does not violate the autocorrelation assumption The homoscedasticity assumption is also verified by the Breusch-Pagan p-value of 0.4480, which is greater than 0.05 Finally, the multicollinearity assumption is also verified based on the results that VIF values of all independent variables are less than 5
Independent variables Coefficient Std Error t-Statistic Prob VIF
The F-statistic shows a p-value that is less than 0.05, indicating that the model would well fit to the set of fundamental factors The adjusted coefficient of determination (adjusted R-squared) has a value of 0.1309, reflecting that the five fundamental factors would be able to explain the variance of stock returns The explanation power of the five fundamental factors on stock returns is relatively small
Among the five fundamental factors serving as independent variables in the model, there are two factors, SIZE and BOOK-TO-MARKET, that show significant relationship with stock returns and three other factors, EARNING-TO-PRICE, ROE and LEV, exhibit insignificant relationship with stock returns SIZE factor shows a positive impact on stock returns with p-value of 0.0291, which mean that positive impact is statistically significant BOOK-TO_MARKET ratio appears to have a positive signifcant relation with stock returns, evidenced by its positive coefficient of 0.1081 and p-value of 0.0017 EARNING-TO-PRICE ratio shows a postive relationship with stock return with its regression coefficient of 0.1069, but its p-value of 0.8261 indicates that the relationship is insignificant Profitability of companies, proxied by ROE, exhibits a positive impact on stock returns but insignificant as evidenced by its p-value of 0.9838 Finally, company capital structure, as indicated by leverage ratio LEV, have negative effect on stock return, but the effect is statistically insignificant.
Results of 2021 data
Table 4.3 Descriptive statistics for 2021 data
Table 4.3 outlines the descriptive statistics of the data for the year 2021, encompassing information from 90 observed companies The stock returns for 2021 exhibit a mean value of 0.3288, with a minimum of -0.2472 and a maximum of 1.0358 The sizes of the companies, based on their 2020 financial statements, have a mean of 28.2161, a maximum of 32.5101, and a minimum of 25.8497 The Book-to- Market ratios showcase a mean of 1.0411, with a maximum of 2.9878 and a minimum of 0.1830 Furthermore, the Earning-to-Price ratios, calculated using company financial statements at the end of 2020, exhibit a mean of 0.1016 and a maximum of 0.3802, minimum of 0.0011 The profitability of the companies, as reflected by the Return on Equity (ROE), shows a mean value of 0.1448, with a maximum of 0.4922 and a minimum of 0.0003 Lastly, the capital structure of the companies, measured by the Leverage (LEV) ratio, demonstrates a mean value of 0.5451, a maximum of 2.4774, and a minimum of 0.0000
Figure 4.6 Scatterplot between Returns and SIZE (2021 data)
Figure 4.6 depicts a scatterplot illustrating the relationship between stock returns for the year 2021 and the sizes of companies as reported in their 2020 year-end financial statements A slightly positive linear relationship is observed between returns and
Size_2020Correlation =0.083 company size, with a correlation coefficient of 0.083 The scatterplot suggests that larger firm sizes correspond to greater stock returns
Figure 4.7 Scatterplot between Returns and Book-to-Market ratio (2021 data)
In Figure 4.7, the scatterplot demonstrates the association between stock returns for the year 2021 and the Book-to-Market ratios obtained from companies' 2020 year- end financial statements An evident positive relationship between stock returns and the Book-to-Market ratio is observed, supported by a moderate correlation coefficient of 0.473 The visualization implies that stock with higher Book-to-Market values would earn higher returns, which aligns with intuitive expectations
Figure 4.8 Scatterplot between Returns and Earning-to-Price ratio (2021 data)
Figure 4.8 highlights the scatterplot between stock returns for 2021 and the Earning- to-Price ratios derived from companies' 2020 year-end financial statements The data indicates a no relation between the two variables, as depicted by just a slightly upward trend line The correlation coefficient of 0.067, very close to zero, further reinforces the lack of relationship between stock returns and Earning-to-Price ratios Somehow, stocks with higher Earning-to-Price ratio earn a greater return compared to stock with lower Earning-to-Price ratio
Figure 4.9 Scatterplot between Returns and ROE (2021 data)
Moving on to Figure 4.9, the scatterplot illustrates the connection between stock returns for 2021 and the profitability metric of companies, Return on Equity (ROE), reported in their 2020 year-end financial statements A clearly negative relationship is observed between returns and ROE, with a correlation coefficient of -0.320 This result does not seem to be intuitive since it suggests that companies with higher stock returns as they reported on their year-end financial statement would have their stock returns to be lower
Figure 4.10 Scatterplot between Returns and LEV (2021 data)
Lastly, Figure 4.10 displays the scatterplot indicating the relationship between stock returns for 2021 and the capital structure metric of companies, the Leverage ratio (LEV), reported in their 2020 year-end financial statements A slightly positive relationship is depicted between returns and the leverage ratio with the correlation between the two variables is 0.163 The scatterplot provides an initial insight into the connection between the two variables, suggesting that companies with higher leverage ratios may experience greater stock returns, aligning with intuitive expectations
Table 4.4 Summary of regression resutls (2021 data)
Table 4.4 presents an overview of the regression analysis conducted to examine the relationship between stock returns and five fundamental factors The regression model utilized the data of the five fundamental factors of companies gathered from their financial statemtents of 2020 to predict their stock returns in 2021
Prior to drawing any statistical conclusions, it is imperative to confirm the adherence to regression assumptions The Jarque-Bera p-value of 0.1453, which exceeds the significance level of 0.05, verifies the normality assumption of the residuals Furthermore, the Breusch-Godfrey p-value of 0.9775, well above 0.05, indicates no violation of the autocorrelation assumption within the regression model The homoscedasticity assumption is upheld as well, as confirmed by the Breusch-Pagan p-value of 0.7516, which surpasses the significance level of 0.05 Finally, the multicollinearity assumption is validated through the VIF values of all independent variables being under 5
The F-statistic displays a p-value lower than 0.05, suggesting a good fit of the model to the fundamental factors considered The adjusted R-squared value of 0.2705 indicates that the five fundamental factors can partly explain the variation in stock returns, though the explanatory power is relatively modest
Variable Coefficient Std Error t-Statistic Prob VIF
Among the five fundamental factors analyzed as independent variables, SIZE and BOOK-TO-MARKET exhibit significant relationships with stock returns, whereas EARNING-TO-PRICE, ROE, and LEV show insignificant relationships The SIZE factor demonstrates a statistically significant positive impact on stock returns, with a coefficient of 0.0642 and a p-value of 0.0075 Similarly, the BOOK-TO-MARKET ratio reveals a statistically significant positive relationship with stock returns, supported by a coefficient of 0.2610 and a p-value of less than 0.0002 Next, the EARNING-TO-PRICE ratio displays a positive association with stock returns with its coefficient of 0.4157, yet the relationship is deemed insignificant given its p-value of 0.5091 The profitability of companies, represented by ROE, has a negative albeit insignificant impact on stock returns, evident from its coefficient of -0.5543 and p- value of 0.1546 Lastly, the company's capital structure, indicated by the leverage ratio LEV, demonstrates a negative impact on stock returns without statistical significance, evidenced by its p-value of 0.9768 which is much greater than 0.05
Results of 2023 data
Table 4.5 Descriptive statistics for 2023 data
Table 4.6 provides an overview of the descriptive statistics for the year 2023, analyzing data from 90 observed companies In 2023, the stock returns exhibit a mean value of 0.2135, with a minimum of -0.6483 and a maximum of 0.9031 The sizes of the companies, derived from their 2022 financial statements, have a mean of 28.3692, a maximum of 32.7688, and a minimum of 25.4557 The Book-to-Market ratios demonstrate a mean of 1.2192, with a maximum of 3.9600 and a minimum of 0.2197 Additionally, the Earning-to-Price ratios, calculated using company financial statements at the end of 2022, feature a mean of 0.1163 and a maximum of 0.3509 The profitability of the companies, as indicated by the Return on Equity (ROE), shows a mean value of 0.1448, with a maximum of 0.4922 and a minimum of 0.0003 The capital structure of the companies, measured by the Leverage (LEV) ratio, displays a mean value of 0.5219, a maximum of 2.7855, and a minimum of 0.0000
Figure 4.11 Scatterplot between Returns and SIZE (2023 data)
The scatterplot in Figure 4.11 illustrates the relationship between stock returns for the year 2023 and the sizes of companies, based on their 2022 year-end financial statements A slightly positive linear relationship is observed between returns and company size, supported by a correlation coefficient of 0.133 The visualization suggests that larger firm sizes correspond to greater stock returns
Figure 4.12 Scatterplot between Returns and Book-to-Market ratio (2023 data)
In Figure 4.12, the scatterplot visualizes the association between stock returns for the year 2023 and the Book-to-Market ratios obtained from companies' 2022 year-end financial statements An evident positive relationship between stock returns and the Book-to-Market ratio is observed, backed by a moderate correlation coefficient of 0.112 This suggests that stocks with higher Book-to-Market values tend to yield higher returns, aligning with common expectations
Figure 4.13 Scatterplot between Returns and Earning-to-Price (2023 data)
The scatterplot in Figure 4.13 showcases the relationship between stock returns for
2023 and the Earning-to-Price ratios derived from companies' 2022 year-end financial statements The data indicates a clearly positive relationship between the two variables, as depicted by an upward trend line The correlation of 0.262, further indicates the positive relationship between stock returns and Earning-to-Price ratios
An initial view can be drawn that stocks with higher Earning-to-Price ratio earn a greater return compared to stock with lower Earning-to-Price ratio
Figure 4.14 Scatterplot between Returns and ROE (2023 data)
Figure 4.14 illustrates the relationship between stock returns for 2023 and the profitability metric of companies, Return on Equity (ROE), reported in their 2022 year-end financial statements A clear positive relationship is observed between returns and ROE, with a correlation coefficient of 0.194 This result may be seen as intuitive, suggesting that companies with higher stock returns as reported in their year-end financial statements have higher actual stock returns
Figure 4.15 Scatterplot between Returns and LEV (2023 data)
The scatterplot in Figure 4.15 displays the relationship between stock returns for 2023 and the capital structure metric of companies, the leverage ratio (LEV), reported in their 2022 year-end financial statements A slightly negative relationship is depicted between returns and the leverage ratio, with a correlation coefficient of -0.145 The visualization hints that companies with lower leverage ratios might experience greater stock returns
Table 4.6 Summary of regression resutls (2023 data)
Variable Coefficient Std Error t-Statistic Prob VIF
Table 4.6 provides a summary of the regression analysis conducted to explore the relationship between stock returns and five fundamental factors The regression model utilized the data of these fundamental factors extracted from companies' 2022 financial statements to predict their stock returns in 2023
Before making any statistical inferences, it is crucial to verify adherence to regression assumptions The normality assumption of the residuals is validated by the Jarque- Bera p-value of 0.7962, surpassing the significance level of 0.05 Additionally, the Breusch-Godfrey p-value of 0.7058 indicates no violation of the autocorrelation assumption The homoscedasticity assumption is verified by the Breusch-Pagan p- value of 0.2690 The multicollinearity assumption is verified by VIF values of all independent variables being below 5
The F-statistic, with a p-value less than 0.05, suggests a good fit of the model to the fundamental factors The adjusted R-squared value of 0.1523 indicates that these factors can partially explain the variability in stock returns, though the explanatory power is moderate
Among the five fundamental factors considered as independent variables, SIZE and BOOK-TO-MARKET exhibit significant relationships with stock returns, similar to results of 2020 and 2021 SIZE shows a statistically significant positive impact on stock returns, with a coefficient of 0.0473 and a p-value of 0.0339, which is significant at significant level of 5% Similarly, BOOK-TO-MARKET ratio demonstrates a statistically significant positive relationship with stock returns, supported by a coefficient of 0.0714 and a p-value of 0.0999, which is significant at significant level of 10% In addition, 2023 data shows that EARNING-TO-PRICE exhibits a significant and positive relation with stock returns at significant level of 10%, evidenced by positive coefficient of 0.9907 and a p-value of 0.1006 Conversely, ROE and LEV do not show significant relationships with stock returns ROE displays a positive association with stock returns with an insignificant p-value of 0.7511 LEV shows a negative impact without statistical significance, with a p- value of 0.1426, greater than the 0.10 threshold.
Result summary and discussion
Table 4.7 Summary relationship between fundamental factors and stock returns for different year data
Table 4.7 summerizes the impact of the five fundamental factors on stock returns In general, both Size and Book-to-Market ratio show positive and significant impact on stock returns in 3 different data set Earnig-to-Price ratio consistently exerts a negative impact on stock returns, but its impact is statistically insignificant Company profitablility, as indicated by return on equity (ROE), and company capital structure, as proxied by leverage ratio (LEV), have show inconsistent relations with stock returns
As for company size effect, the finding of this study suggested that company size does affect manufacturer stock returns The study finding strongly follow the findings of Fama & French (1992), Grabowski et al., (2016), Duy & Phuoc (2016) that company size does have a significant impact on stock return However, the direction of the impact of size from their findings is different from this study findings, as they found that small-size stocks outperform large-size stock In contrast, this study found that the bigger the manufacturer size, the better their stock returns This is not a supprise result as small-size stocks do not always outperform large-size stocks Many international and Vietnamese researchers have found that company size has positive impact on stock returns (Nguyen & Pham, 2022); (Wong, 1989); (Yuliza, 2018) There seems to have some possible explanations for this positive relation First, Larger companies are often perceived as more stable, established, and investors may have more confidence in the long-term prospects of larger companies, leading to higher demand for their stocks and subsequently higher stock returns Second, larger
Fundamental factors Impact Significant Impact Significant Impact Significant
SIZE Positive Yes Positive Yes Positive Yes
BOOK-TO-MARKET Positive Yes Positive Yes Positive Yes
EARNING-TO-PRICE Positive No Positive No Positive Yes
PROFITABILITY (ROE) Negative No Negative No Positive No CAPITAL STRUCTURE (LEV) Negative No Negative No Negative No
2020 2021 2023 company tend to have easier access to capital, which allow them to fund for their growth opportunities and expansions Eventually, investors perceive them as having higher long-term prospects Last but not least, established larger companies usually have strong brand recognition and reputation, which can translate into customer loyalty, pricing power, and a competitive advantage in the market and may ultimately lead to higher profitability and ultimately higher stock returns
Regarding the Book-to-Market ratio, it is strongly supported by the findings of Fama
& French (1992) Market participants and academic researchers consider stocks with high Book-to-Market ratio as value stocks These value stocks are undervalued and their prices are believed to rise in future, leading to higher stock returns Another explanation is the mean-reversion theory, which states that stock prices tend to revert to its long-term average level This reversion can drive higher returns for investors who buy undervalued stocks with high B/M ratios Beside study of Fama & French (1992), many researchers around the world have test the relationship between Book- to-Market ratio and stock returns and confirm the existence of this relationship (Muhammad & Scrimgeour, 2014); (Lewellen, 2004)
About the Earning-to-Price ratio impact on stock returns, the use of earning-related ratios has long been a strategy in investment industry In this study, it seems that there is a positive relationship between stock returns of manufacturing companies and this ratio From the preliminary views based on the scatterplots between this ratio and stock returns, it can be clearly seen that it positively affects stock returns However, this positive relation is not consistent since it is only significant in 2023 data, while the other two years shows that this relation is insignificant This result further supports the suggestion of Vermeulen (2016) and Aras & Yilmaz (2008) that Book- to-Market ratio should be preferred rather than using Earning-to-Price ratio because the former ratio is more stable than the latter ratio To explain for the instability of Earning-to-Price ratio, both earnings of company and company stock price are unstable and fluctuate significantly over time Hence, the Earning-to-Price ratio may somehow fluctuate very much over time
As for profitability of company, indicated by the return on equity (ROE), the study finds that company profitability seems to have no significant relationship with stock returns From the study, scatterplots show that ROE effect on stock return is not consistent as well, evidenced by the negative and positive relationship with stock returns in different years None of years shows ROE has significant impact on stock returns Many researches also show that ROE has insignifcant relation with stock returns (Muhammad & Scrimgeour, 2014); (Vermeulen, 2016) This result seems to be counterintuitive because it is a common sense that company with high ROE would have its stock return to be greater Maybe, the most possible explaination for this phenomenon is that investors and market participants are very sensitive to and fear of earning manipulation Perhaps, earning of a company is the number that is most vulnerable to manipulation (CFA Institute, 2023) As a result, market participants do not want to rely much on these earning-related number, such as ROE and Earning-to- Price ratio, to form their expectations about companies
Looking at the capital structure of companies, proxied by leverage ratio (LEV), the study finds that capital structure of companies seems to have no relation with stock returns, suggesting that capital structure may not be an important factor in analysing manufacturing company stocks From the scatterplots, a preliminary view on capital structure is that it has a negative impact on stock returns Regression results confirm that the capital structure of company has negative impact on stock return, but the relationship is not significant Negative impact means that companies with higher Debt-to-Equity ratio are perceived by investors and market participants as riskier and thus, they are more cautious to the companies One possible reason why capital structure of companies does not significantly affect stock returns is that market participants may not view leverage as a critical factor in the valuation of a company Instead, they focus on growth prospects and other financial indicators such as size to form their expectations on companies.
CONCLUSION
This study aimed to create a screening tool for fund managers and finacial analysts to evaluate firms before making investment decision To achieve this purpose, the fundamental factors that influence stock performance were examined using a sample of 90 companies from manufacturing industry listed on HOSE The multiple regression model was used to analyze the annual return of these stocks based on financial factors including Size, Book-to-Market ratio, Earning-to-Price ratio, Profitablity (ROE) and Capital structure (LEV) The sample included annual financial data from 2019-2023, allowing for the estimation and comparison of three regressions per year
In conclusion, the data analysis results highlight that size effect does exist in company stocks returns In manufacturing sectors, company size positively impacts stock returns In other words, companies with larger size would have their stock returns higher In addition to size, the value aspect of stock is also a determinant of stock returns Study found that companies with higher Book-to-Market ratio tend to have their stock returns higher than those with lower Book-to-Market ratio Earning-to- Price ratio is also found to have positive impact on stock returns, but the relation is insignificant as the ratio is highly vary The relationship between company profitability and their stock returns seems to be vague The study found that the relationship is insignifcant and the direction of profitability effect on stock returns also varies Finally, company capital structure seems to not be an important factor to be considered by market participants in manufacturing sector
Implications for fund managers and investors
On the perspective of fund managers and investors, the findings from this research offer valuable insights for fund managers and individual investors seeking to optimize their investment portfolios The demonstrated positive relationship between stock returns and firm size suggests that larger manufacturing companies listed on the Ho
Chi Minh Stock Exchange tend to yield higher stock returns This insight could guide fund managers and investors in making more informed decisions regarding asset allocation By prioritizing investments in larger firms, they can potentially achieve better returns on their investments
Moreover, the significant positive relationship between the Book to Market ratio (B/M) and stock returns reinforces the usefulness of value investing strategies Stocks with higher B/M ratios tend to be undervalued relative to their book value and could offer greater potential for appreciation For investors who are apt in fundamental analysis, prioritizing companies with high B/M ratios could be a robust strategy for capital appreciation
Although the Earning to Price ratio (E/P) has shown a positive impact on stock returns, it was not statistically significant Nonetheless, this factor should not be entirely dismissed E/P could still provide a quatitative measure supporting investment decisions when combined with other indicators
Despite profitability (Return on Equity - ROE) and capital structure (Debt to Equity
- D/E ratio) being less impactful and statistically insignificant in this study, they remain integral to thorough company analysis ROE is a measure of a company's efficiency in generating profits from shareholders' equity, and remains a vital indicator of managerial effectiveness Similarly, the D/E ratio, although less impactful in this context, provides insight into a company's leverage and financial risk By maintaining a balanced approach that includes these supplementary metrics, investors can formulate a robust investment thesis and enhance their predictive models
Lastly, the unique dynamic of the Vietnamese market, characterized by its emerging status and fluctuating economic cycles, underscores the necessity for dynamic and localized investment strategies Investors and fund managers can learn to navigate the specific regulatory, economic, and market conditions prevalent in Vietnam by understanding how fundamental factors interact in such an environment Adapting global investment models to better suit local conditions can optimize returns and mitigate risks associated with geopolitical and economic volatility
Implications for manufacturing company managers
The findings from this study offer actionable insights for company managers in the manufacturing sector, particularly those listed on the HOSE On the perspective of manufacturing managers, understanding the fundamental factors that affect their company values can facilitate decision making of managers One significant implication is the relationship between firm size and stock performance As larger firms tend to yield higher stock returns, managers should focus on strategic growth initiatives to expand operations, optimize asset utilization, and potentially pursue mergers and acquisitions By scaling the business effectively, managers can not only enhance company size but also favorably influence investor perceptions, thereby boosting stock performance Therefore, the decisions about capital investment, expensing or capitalizing costs, are very important This study could be a good reference to examine the current business conditions for business plan of growing
Maintaining a healthy Book to Market (B/M) ratio should also be a concern for company managers A high B/M ratio signifies that a firm's stock is perceived as undervalued, thus attracting more investors Eventually company manager would find it easier and less costly when funding for their company growth Managers should ensure transparency in financial reporting and make capital allocation decisions that reinforce the intrinsic value of the company Enhancing book value through prudent capital expenditure, efficient equity management, and sustainable earnings retention or distribution policies can significantly impact stock performance
Although the Earning to Price (E/P) ratio was not a significant factor, maintaining consistent earning remains crucial Managers should prioritize operational efficiency, cost management, and revenue-enhancement strategies to sustain earnings growth, thereby having a sustainable earning and favorable E/P ratios Consistent profitability can foster positive market perception, reinforcing investor confidence even if immediate statistical significance is not evident in stock performance
Regarding capital structure, the study highlighted the negative but insignificant relationship between the Debt to Equity (D/E) ratio and stock returns Managers should carefully consider their leverage strategies, balancing debt to fund growth without overburdening the company Prudent financial management practices that optimize the use of debt and equity can enhance the firm's stability and attract a wider range of investors, including those particularly cautious of excessive leverage
In summary, the study underscores the importance of integrating growth, value, profitability, and prudent financial management By aligning these objectives with investor expectations and market dynamics, manufacturing companies in Vietnam can achieve sustainable growth and robust stock performance Managers are encouraged to leverage these insights to drive strategic decisions that position their companies favorably on the stock exchange while fostering long-term value creation for stakeholders
First, the study is not meant to delve into the reasons behind the size factor or other factors Hence it seems crucial to thoroughly explore the factors influencing firm size, Market-to-Book ratio, capital structure, profitablity that may differ across various industries and markets
Second, the study only focused on manufacturing company that listed on HOSE In fact, there are many manufacturers that are private and are not listed on HOSE Moreover, private companies might have different characteristics than listed companies, such as their optimal capital structure or their expenses