The Effect of Capital Structure on the Ho Chi Minh Stock Exchange (HOSE) Performance of Companies Listed in the Plastics Industry

: The relationship between capital structure and company performance was examined in this study. From 2019 to 2023, information was gathered from 29 plastic firms that were listed on the Ho Chi Minh Stock Exchange (HOSE). Each company's performance was gauged using three variables: ROA, ROE, and EPS. The major components of capital structure are the ratios of total debt to total assets (DA), total debt to equity (DE), short-term debt to total assets (SDTA), and long-term debt to total assets (LDTA). In addition, the model incorporates growth rate (GROWTH) and company size (SIZE) as control variables. Consequently, every performance characteristic of the company is negatively impacted by the majority of the capital structure variables. Notably, this study not only demonstrates the weak association between SDTA and SDTA but also the negative correlation between ROE and capital structure, which was considered minor in many earlier studies. Furthermore, prior research had not consistently shown ROE. Additionally, the study's findings indicate that size and company performance are positively correlated and have no effect on growth pace.


INTRODUCTION
In the modern world, capital structure is a crucial consideration.Vietnam is an emerging market overall, and the reason these businesses are unable to establish a suitable financial structure is due to a lack of expertise and knowledge in this area.The Vietnamese market has a lot of potential, but the expense of interest payments has put pressure on the country's lack of cash due to restricted access to capital and careless use of it.Because of these restrictions, domestic businesses are unable to compete with international businesses that have access to large amounts of money and have a track record of successful debt management.
While there have been numerous studies conducted in other nations, such as the Abor (2005) study in Ghana or the Ebaid (2009) study in Egypt, research on the relationship between capital structure and firm performance can be found in many other places.For example, Onaolapo & Kajola (2010) studied Nigerian stock exchange companies, and Umar et al. (2012) studied a sample of the top 100 Pakistani companies.Studies on the Vietnamese market include those conducted by Le Dat Chi (2013) with an observed sample of 178 non-financial companies listed on Vietnam Stock Exchanges (HOSE and HNX) in the period 2007-2010, Tran Hung Son (2008) with a sample of 50 non-financial companies listed on the Ho Chi Minh Stock Exchange (HOSE), and Le Thi My Phuong (2017) on the effect of capital structure on business performance of 207 manufacturing companies listed on both HNX and HOSE between 2010 and 2015.The aforementioned investigations, however, did not update the data.Vietnam's economy has been evolving quickly, which could have an impact on the findings of earlier studies.Furthermore, numerous studies and pieces of evidence have shown that different outcomes occur in various industries and professions, indicating that context and industry have a substantial impact on this link.In order to gain a better understanding of the connection between capital structure and financial performance in emerging and promising industries, such as Vietnam's food and beverage sector, the author has undertaken a research study.Research through the topic "The effect of capital structure on the Ho Chi Minh Stock Exchange (HOSE) performance of companies listed in the plastics industry."

RESEARCH MODEL AND HYPOTHESES
As the author noted above, there have been several studies conducted worldwide that examine the impact of capital structure on a company's performance.These studies represented capital structure using a variety of factors.The capital structure was represented by four variables in the study by Ebrati et al. (2013): the ratio of total debt to total assets (DA), the ratio of total debt to equity (DE), the ratio of short-term debt to total assets (SDTA), and the ratio of long-term debt to total assets (LDTA).It is evident that the aforementioned four indices are common variables that are employed in numerous studies-Saeedi and Mahmoodi (2011), Amara & Dr. Bilal Aziz (2014), Sathyamoorthi (2019), Nguyen Thanh Hieu, and Nguyen Huu Anh (2020)as a stand-in for capital structure.Thus, in the study that follows, the author measures capital structure using the four variables mentioned above.
There are numerous metrics that may be used to assess a company's performance and determine its current state of development.The authors of various studies have represented corporate performance using a range of ratios.Three financial ratios-MBR, ROE and ROA, and Tobin's Q-are used in Zeitun and Tian's (2007) study to gauge the performance of the business.Additionally, profits per share (EPS) was used in conjunction with other factors to quantify performance in the following studies: Sathyamoorthi ( 2019 For the business performance of businesses listed on the stock exchanges in Ho Chi Minh City, two regression models are utilized: the fixed effects model (FEM) and the random effect model (REM) (2019 to 2023).The capital structure as determined by total assets (LDTA), short-term debt to total assets (SDTA), long-term debt to total assets (SDTA), and debt-to-equity (DE) is the independent variable.Financial measures, such as the profits per share (EPS) and return on equity (ROE) and assets (ROA) of food and beverage businesses on both HOSE in the period 2019-2023, are dependent variables.Growth rate (GROWTH) and firm size (SIZE) are the control variables.H1: Return on assets (ROA) is negatively related to total debt to total assets (DA).H2: Return on assets (ROA) is negatively related to total debt to total equity (DE).H3: Return on assets (ROA) is negatively related to short-term debt to total assets (SDTA).H4: Return on assets (ROA) is negatively related to long-term debt to total assets (LDTA).H5: Return on equity (ROE) is negatively related to total debt to total assets (DA).H6: Return on equity (ROE) is negatively related to total debt to equity (DE).H7: Return on equity (ROE) is negatively related to short-term debt to total assets (SDTA).H8: Return on equity (ROE) is negatively related to long-term debt to total assets (LDTA).H9: Earnings per share (EPS) is negatively related to total debt to total assets (DA).H10: Earnings per share (EPS) is negatively related to total debt to equity (DE).H11: Earnings per share (EPS) is negatively correlated with short-term debt to total assets (SDTA).H12: Earnings per share (EPS) is negatively correlated with long-term debt to total assets (LDTA).Two regression models-the random effects model (REM) and the fixed effects model (FEM)-are used to panel data in order to assess the relationship between the variables.Hausman tests are used to evaluate research findings and select appropriate models.The Wald, Wooldridge, and Breauch-Pagan Lagrangian tests are used to verify defects.In the end, visitors with disabilities will, provided that the GLS generalized least squares method has been applied.The debt-to-assets (DA) ratio and the debt-to-equity (DE) ratio have 5-year means that are both more than 0.89 and 0.39, respectively.Furthermore, the minimum index of the ratio of 0.085 with a standard deviation of 0.82 is significantly lower than the maximum index of DE of 5. Calculations reveal that there are 41 values of DE larger than one and 104 values of DE less than one in the data.The DE index of the majority of businesses is less than 3, however some, including Dong A Plastic JSC and Rang Đong Holding JSC, have high DE indices.

RESULTS
When the index's standard deviation is only 0.18 and the mean value is less than 0.5, the DA ratio of the firms demonstrates a more even condition.This indicates that the capital of the plastics industry's companies that are financed by investment capital is more than that of companies that are financed by external capital.Nonetheless, this value, which is near 0.5, shows that businesses in the plastics sector have a relative balance between the various funding levels they receive from internal and external sources.However, it should be noted that the SDTA average short-term debt-to-total assets ratio of 0.32 is comparable to the industry average debt-to-assets (DA) ratio of 0.39.Plastic companies will choose to employ short-term debt if they have to use debt to fund their operations.Following computation, it is discovered that over 87% of the debt held by the subject is short-term obligations.Given that the maximum index of DA is virtually similar to the maximum index of SDTA (variance of 0.17 and maximum index of more than 0.7, respectively), it is evident that certain businesses rely primarily on short-term debt to finance their operations.
Conversely, the metrics indicating the performance of the company are ROE and ROA, which have respective averages of 0.1 and 0.03.In terms of ROA, the minimum is 0.031, the maximum is near 0.06, and the standard deviation is 0.03.The maximum ROE is 0.64, while the smallest is -0.46, with a standard deviation of roughly 0.12.In addition, South Basic Chemicals JSC has the highest EPS value of 21171 and the lowest average of 2567; the company's EPS value fell precipitously in 2019 and 2020.Furthermore, Growth's average index is only 0.013, with about 39% of the index falling below zero over time, with the majority of these periods falling between 2020 and 2021.This demonstrates that Several businesses have failed recently, perhaps partly as a result of the pandemic that has impacted the world economy.Because An Tien Industries JSC's abrupt sales increase in 2021 affected the accuracy of industry data, the growth's greatest figure was 0.5.The Pearson correlation coefficient between the variables used in this work is shown in Table 2. Variables that were used to gauge the financial performance and capital structure of listed businesses in the plastics sector between 2019 and 2023.Three categories are included in the regression approach above: Earnings per share (EPS), return on equity (ROE), and return on assets (ROA) are examples of the dependent variables.The independent variable is the second.comprises the following ratios: short-term debt to total assets (SDTA), long-term debt to total assets (LDTA), total debt to equity (DE), and, lastly, the control variables Growth Rate GROWTH and Company Size SIZE.This table's first noteworthy finding is the nearly positive correlation between leverage ratios.Based on common guidelines for describing the relationship, there is a high correlation between total debt-to-total assets (DA) and short-term debt-to-total assets (SDTA), near 0.9 and above 0.7.Hinkle et al. introduced correlation in 1998.The Pearson association Coefficient test indicates a strong association between total short-term debt to total DA and short-term debt to total assets of SDTA; nonetheless, the two variables are kept apart and utilized in regression models.are distinct, hence it has no bearing on the validity of the current investigation.In a similar vein, the correlation between DA and DE shows that both DE and SDTA have indexes above 0.7; however, as these independent variables are distinct and utilized in different regression models, the reliability is unaffected.
Second, there is a negative correlation between business performance and all independent variables.A company's performance always tends to decline when it decides to take on additional debt.This issue is connected to the theoretical hierarchy discussed in Chapter 2, which argues that because profitable businesses put their internal capital before earnings, they typically employ less debt.The results of model regression using FGLS are displayed in the above table following the use of the FGLS model to address the issues of variable variance and autocorrelation in models 1, 2, 3, and 4.
Following analysis, the relationship between ROA and the capital structure representative indexes, such as DA, DE, SDTA, and LDTA, is inversely related, with β equal to -0.00174, -0.000306, -0.00154, and -0.000924, and a standard deviation at the 1% significance level.This is shown in the figure in Table 3.This outcome is consistent with research on the negative correlation between DE and ROA that was conducted by Ebrati 2020) on the Vietnamese market are comparable to the negative link between LDTA and ROA.Furthermore, the company's GROWTH growth index, which is the fixed variable, exhibits a negligible relationship with ROA; in contrast, the SIZE size ratio, for which β is zero, significantly positively affects ROA in each of the three models (0.00024, 0.000646, 0.000119, and 0.000646), with a statistically significant level ranging from 1% to 10%.After using FGLS to address the model's autocorrelation and variable variance issues, Table 4 displays the outcomes of Models 5, 6, 7, and 8.According to the computed data, there is an inverse association (β = -0.53,-0.1, and -0.09) between ROE and the major capital structure indexes, such as DA, DE, and LDTA, with a 1%-5% level of statistical significance.This outcome differs from that of Saedi and Mahmoodi (2011) and Umar et al. (2012), who found no discernible relationship between capital structure and ROE.In contrast to earlier studies, such as those conducted by Nguyen Thanh Hieu and Nguyen Huu Anh (2020), which found an inverse link, the SDTA index displays a minor negative relationship with ROE.This indicates a major dimension between the two indices mentioned above.Furthermore, the fixed variable SIZE shows a substantial positive association in all four models, with β equal to 0.136, 0.098, 0.131, and 0.0718 and a statistical significance of 1% to 5%.In contrast, the fixed variable Firm Growth Index shows a positive but insignificant link with ROE.The FGLS findings for models 9, 10, 11, and 12 are displayed in Table 5.As the table's results demonstrate, there is a negative correlation (β = -5856.2,-621.2, 10027.9, and -1148.5) between EPS and the capital structure proxy indices, which include DA, DE, SDTA, and LDTA.The statistical significance level is set at 1%.The results of this study, except for Nguyen Thanh Hieu and Nguyen Huu Anh's research, are consistent with the negative association between EPS and variable capital structure found in the works of Ebrati et al. (2013), Umar et al. (2012), and the paper.SIZE Scale has a positive effect on EPS in all four models (β = 769.9,47.53, 530.1, and 673.4; 1% statistical significance).In the meantime, a model with β equal to 4571.8 and a 1% threshold of statistical significance demonstrates a positive link between growth rate GROWTH.

CONCLUSION
The purpose of this study was to look into the relationship between capital structure and corporate performance in the context of 29 businesses that were listed between 2019 and 2023 on the HOSE Ho Chi Minh Stock Exchange.The criteria listed in the first chapter were used to choose these businesses.The study reached the following conclusions after using regression methods, putting defect-elimination strategies into practice, and assessing the reliability of the outcomes to ensure that they were reliable and accurate: Within the food and beverage industry, there is a negative correlation between capital structure and firm performance.The findings of numerous earlier research, such as those of Umar et al. (2012), Ebrati et al. (2013), Nguyen Thi Minh Hue and Dang Tung Lam (2017), Sathyamoorthi (2019), Nguyen Thanh Hieu, and Nguyen Huu Anh (2020), are in line with this one.However, this paper illustrates the negative and significant effects of three on the four representative factors of capital structure, including DA, DE, and LDTA to ROE, but also demonstrates that the relationship between SDTA and ROE is much inverse but not significant, in contrast to the findings of Abor (2005) and Saedi and Mahmoodi (2011) that the relationship between capital structure and ROE is insignificant.
It is noteworthy that the opinions of Le Dat Chi (2013), Nguyen Thi Minh Hue and Dang Tung Lam (2017), Nguyen Thanh Hieu and Nguyen Huu Anh (2020) on the Vietnamese market have a strong correlation with pecking order theory, and this negative relationship between capital structure and firm performance is consistent with their findings.In addition to borrowing in the environment of a volatile economy and opaque information like Vietnam's, profitable enterprises typically prioritize internal financing to retain profits over debt.This sends the wrong signals to the market and negatively affects company activity Concerns in the Vietnamese market these days stem from people's lack of expertise and knowledge when it comes to investing, the effects of COVID-19 on the nation's economy, and unfavorable news about the stock market.sensitive investor.Investors may get uneasy due to the rise in corporate borrowing, which may influence their choice of investments.The lack of awareness among investors is one of the main causes of this sensitivity.For the last five years, there has been a noticeable growth in the number of individuals participating in the securities market.While many people have invested in stocks, they have not fully understood the facts and expertise involved.The stock market is more sensitive than ever because all of their decisions are based on herd mentality and oneway information.Furthermore, it would be impossible to overlook the stock market scams that have destroyed the confidence of the majority of investors.Due to the COVID issue, workers' supplemental costs, medical costs, and the deployment of isolation and distancing measures, together with the fact that business had not yet recovered, domestic enterprises were seriously short of funds.The burden of paying interest is rising daily as a result of the debt required to keep businesses operating.Furthermore, the corporation is confronted with bad debt while domestic sales revenue continues to face several challenges and competition, as many businesses utilize short-term debt to cover long-term interest.After investigation, the data reveals that over 80% of the company's debt is shortterm, but it also demonstrates that the corporation is striking a balance between debt and equity.Furthermore, this analysis indicates that, in contrast to Zeitun and Tian's (2007) study, the growth rate has a favorable but negligible impact on company performance; on the other hand, the size ratio positively influences all variables that gauge a firm's performance.This study bears similarities to that of Nguyen Thanh Hieu, Le Thi My Phuong (2017), and Nguyen Huu Anh (2020).In actuality, investors and consumers will place more trust in giant corporations than in tiny ones.Additionally, larger businesses will benefit from more incentives and easier access to finance than smaller ones, which will reduce interest costs for businesses.
et al. (2013), Amara & Dr. Bilal Aziz (2014), and Sathyamoorthi (2019).Further evidence supporting the negative link between ROA and SDTA or DA comes from studies conducted in 2007 by Zeitun, in 2011 by Saedi and Mahmoodi, and in 2009 by Ebaid.The research findings of Nguyen Thi Minh Hue and Dang Tung Lam (2017) and Nguyen Thanh Hieu and Nguyen Huu Anh (