doi: 10.56294/sctconf2024.1194

ORIGINAL

Factors affecting financial capacity

Factores que afectan la capacidad financiera

Dong Thi Van Hong¹ *

¹Phenikaa University, Hanoi 12116, Vietnam.

Cite as: Van Hong DT. Factors affecting financial capacity. Salud, Ciencia y Tecnología - Serie de Conferencias. 2024; 3:.1194. https://doi.org/10.56294/sctconf2024.1194

Submitted: 11-03-2024                   Revised: 04-06-2024                   Accepted: 18-09-2024                 Published: 19-09-2024

Editor: Dr. William Castillo-González

Corresponding author: Dong Thi Van Hong *

ABSTRACT

Introduction: securities companies are a component that makes up the stock market. The birth and development of securities companies is associated with the formation and development of the stock market.

Method: the research data set includes audited financial reports (and financial safety) of Vietnamese securities companies (operating on the HNX, HoSE and Upcom exchanges) in the period from 2014 to 2021. The article uses the PROBIT binary model to analyze regression factors affecting the financial capacity of Vietnamese securities companies in the system, because the dependent variable is a binary variable, the independent variables will be quantitative. Measure the probability of impact of independent variables that change financial capacity from weak to strong.

Results: the article has determined that the financial capacity of Vietnamese securities companies is governed by 6 factors belonging to the securities companies themselves (and 2 control variables and macro variables). All of the above factors have a positive or negative impact on the financial capacity of Vietnamese securities companies.

Conclusions: based on the research results, the author of the article offers some discussions and assessments on improving the financial capacity of Vietnamese securities companies in the coming time, in addition to recommending financial solutions aimed at improving financial capacity of Vietnamese securities companies in the coming time. high financial capacity for securities companies.

Keywords: Securities Company; Operational Efficiency; Financial Capacity.

RESUMEN

Introducción: las sociedades de valores son un componente que conforma el mercado de valores. El nacimiento y desarrollo de las sociedades de valores está asociado a la formación y desarrollo del mercado de valores.

Método: el conjunto de datos de la investigación incluye informes financieros auditados (y seguridad financiera) de compañías de valores vietnamitas (que operan en las bolsas HNX, HoSE y Upcom) en el período de 2014 a 2021. El artículo utiliza el modelo binario PROBIT para analizar los factores de regresión que afectan la situación financiera. capacidad de las compañías de valores vietnamitas en el sistema, debido a que la variable dependiente es una variable binaria, las variables independientes serán cuantitativas. Mida la probabilidad de impacto de variables independientes que cambian la capacidad financiera de débil a fuerte.

Resultados: el artículo ha determinado que la capacidad financiera de las sociedades de valores vietnamitas se rige por 6 factores pertenecientes a las propias sociedades de valores (y 2 variables de control y variables macro). Todos los factores anteriores tienen un impacto positivo o negativo en la capacidad financiera de las sociedades de valores vietnamitas.

Conclusiones: con base en los resultados de la investigación, el autor del artículo ofrece algunas discusiones y evaluaciones sobre cómo mejorar la capacidad financiera de las compañías de valores vietnamitas en el futuro, además de recomendar soluciones financieras destinadas a mejorar la capacidad financiera de las compañías de valores vietnamitas en el futuro. Alta capacidad financiera para las sociedades de valores.

Palabras clave: Sociedad de Valores; Eficiencia Operativa; Capacidad Financiera.

INTRODUCTION

The stock market is a basic element of a modern market economy. Most countries in the world have stock markets. The stock market has become an important medium and long-term capital mobilization channel for the economy.⁽²³⁾ For the stock market to operate effectively, it is impossible not to mention the role of market intermediaries, including securities companies.

Experience in some countries with developed securities markets such as Japan, China and Korea. All show that Company size is the most important factor affecting the financial capacity of a securities company.⁽¹⁸⁾ The advantage of these companies is to take advantage of economies of scale, have high stability of cash flow, make information transparent, and reduce the problem of asymmetric information to mobilize capital in the market finance.

Securities companies are a component that makes up the stock market. The birth and development of securities companies is associated with the formation and development of the stock market.⁽¹⁶⁾ In Vietnam, when the stock market came into operation,⁽¹³⁾ the number of new securities companies was only a few companies, however as of October 2021 the market has up to 78 securities companies operating in the market. Previously, the highest number of securities companies was up to 105 securities companies,⁽²⁰⁾ due to the fierce competition of the market economy, leading to the process of mergers and acquisitions, ceasing operations, leading to The number of securities companies has been reduced to the current level. There are many different reasons leading to the above situation, but most experts and managers agree that the root cause is weak financial capacity of securities companies.⁽¹³⁾

Vietnam is increasingly integrating deeply into the global economy. Vietnamese securities companies are facing intertwined opportunities and challenges. If they want to survive and develop, they first need to improve their financial capacity, this is a urgent request.⁽²¹⁾ Improving financial capacity will help securities companies apply modern technology, improve service quality, stock brokerage staff quality, deploy new products, open more branches, invest in technology and expand expand the market, from which securities companies will achieve their goals of sustainable growth and minimize business risks. Recognizing that importance, in recent years, many securities companies have made many efforts to improve financial capacity to meet the requirements of business practices to help securities companies stand firm in a competitive environment to survive and develop. develop. However, faced with new requirements of the development process, many securities companies began to reveal limitations in weak financial resources, leading to loss of business results for many years.⁽¹⁷⁾

Literature review

Theory of diseconomies of scale (Transaction cost economics or theory): The concept of transaction costs was first introduced by Ronald Cose in 1937, published in The study titled “The Nature of the Firm” laid the foundation for the transaction cost theory, later completed and developed by Williamson (1987), and the theory also clarified forms of transaction management. Transactions and different forms of transaction organization affect company size.

According to Cose (1937), the size of a company is limited by the number of transactions that can be carried out efficiently. “the firm becoming larger means that additional transactions are undertaken by the firm’s owners and becoming smaller means that some transactions will be abandoned”,⁽²⁶⁾ and those is most optimally implemented by the market mechanism.⁽²⁶⁾ gives an explanation: (1) When the size of the company is larger, the profits of the company owner may decrease and additional transaction costs within the company may increase. And of course, at some point the additional transaction costs within the company will be equal to the costs of carrying out this transaction on the market or organized by another company owner. (2) Maybe when transactions increase, company owners do not know how to use operations effectively. (3) The price of supplying one or another input factor may increase because other benefits of a small company are greater than those of a large company.

Pecking Order Theory: Also known as capital increase order theory, the theory was initially researched by Myers & Majluf (1984). The theory begins with asymmetric information indicating that company directors know more about their company’s potential and risks than outside investors.⁽¹⁹⁾ Asymmetric information affects the choice between internal and external financing, and between new issuance of debt securities and equity securities. This results in a pecking order whereby a company’s investment projects will be funded first with internal capital, mainly retained profits for reinvestment, and then by issuing new debt. and finally by issuing new share capital. Issuing new shares is often the last resort when the company has used up all its debt capacity, meaning there is a threat to the company’s financial resources, forcing existing creditors as well as the company’s financial director to worry.

Basel Agreement. Before 1987, capital standards that banks had to comply with varied from country to country, which gave some banks a global competitive advantage over others.⁽²⁷⁾ For example, suppose a bank in the US must comply with a 6 % capital requirement, which is twice as high as a foreign bank. The reason is because the country’s government can support their banks every day, so a low capital ratio does not necessarily mean much risk, with US banks not having this advantage. In December 1987, 12 developed countries attempted to resolve this difference by introducing uniform standards for banks. In July 1988, the central bank governors of 12 countries accepted the standards in the Basel agreement. For the capital adequacy ratio, according to the recommendations of the Basel Committee of the Bank for International Settlements (BIS), it has issued a set of standards, including Basel I (1988), which provides credit risk measurement with capital standards. at least equal to 8 % of total risk-weighted assets. Basel II (2004) requires banks to maintain a minimum capital ratio of 4 % for tier 1 capital and 8 % for tier 2 capital, and monitors the operations of financial institutions based on three pillars. , pillar 1 is CAR (quotient of equity capital and total risk-weighted assets), pillar 2 is Strengthening assessment of the quality of risk management of banks, pillar 3 is Supervising disciplinary compliance market. Basel III (2010) sets higher minimum standards than Basel I and Basel II, the CAR coefficient remains unchanged but requires banks’ equity capital to be raised from 4 % to 6 %, of which 4,5 % must be the capital of common shareholders. Especially in Basel III standards (2010), securities companies are added as subjects.

According to Stowell et al. (2017). Investment Banking in 2008 (B): A Brave New World. Research the factors leading to the collapse of the largest investment banks (stock companies) in the United States in 2008, typically Lehman Brothers Securities Company.⁽⁴⁾ The company’s collapse stemmed from a lack of capital, which was the main engine for strong profit growth. To have enough capital, the company significantly increased its leverage, from a debt-to-equity ratio of 23,7 times in in 2003 to 35,2 times in 2007. As leverage increased, and stock prices began to decline sharply. The partners refused to arrange capital for the company due to the company’s reliance on short-term repo loans.⁽⁴⁾ Research results show that capital is the most important factor affecting the financial capacity of securities companies, and inappropriate use of leverage weakens the financial capacity of securities companies and can lead to bankruptcy.

According to Tran and et al. (2020), with the topic “The productivity and efficiency of Vietnamese securities firms, 2009 to 2017”, the research team examined the impact of factors: scale, regulations and ownership structure affecting the productivity and efficiency of 53 Vietnamese securities companies in the years from 2009 to 2017. The results show that the size of securities companies and government regulations have an impact on the operations of securities companies. Foreign ownership ratio also has a significant negative correlation with performance, while the majority ownership ratio of domestic shareholders and individual shareholders has a positive impact, with no significant correlation. There is no difference between the ownership of banks and securities companies.⁽¹⁾ Thus, the scale, government regulations, leverage ratio, available capital ratio, and margin balance have an impact on the financial capacity of securities companies.

According to Tran Van Hai (2023), the connotation of financial capacity is expressed in the capital capacity, payment capacity and profitability capacity of a securities company.⁽¹³⁾ The financial capacity of a securities company demonstrates not only its actual capabilities, potential and future prospects. Factors affecting the financial capacity of CTC can be internal or external factors.⁽¹⁵⁾

METHOD

The research data set is the actual financial statements (and financial safety ratio reports) of Vietnamese securities companies as of December 31 of each year, which have been audited for the entire period 2014 - 2021 with 649 officials. closely, so as of December 31, 2021, there are 78 securities companies. The number of observations meets the sample size requirements of ⁽¹¹⁾(11) or ⁽³⁾.

Data cleaning: Adjusting variable parameters is carried out as follows:

Step 1: Enter data into excel, check for any abnormalities in the data.

For the independent variables, calculate the values of the indicators according to table 1. The dependent variable (Ability) will receive 2 values (y=1: strong financial capacity; y=0: weak financial capacity).

Based on table 1, evaluate securities companies comprehensively and rank A, B, C, D, E. In case a securities company is ranked A or B, it is a securities company with strong financial capacity, and at the same time ranked C or D or E is a securities company with weak financial capacity. A securities company is rated A if it has a total score from 80 points to less than 100 points and no factor score is less than 65 points. A securities company is rated B if it has a total score from 65 points to less than 80 points and no factor score is below 50 points or a securities company is initially rated A but has one factor score below 65 points. A securities company is ranked C in one of the following cases: A securities company has a score from 50 to less than 65 points and no factor score is less than 35; or the securities company has an initial A rating but has one factor score below 65 points; or the securities company is initially rated B but has a factor score of less than 50 points. A securities company is ranked D in one of the following cases: A securities company has a score from 35 points to less than 50 points; or the securities company is initially rated as B but has more than one factor score below 50 points; or the securities company is initially rated C but has a factor score below 35. A securities company is ranked C in one of the following cases: A securities company has a score from 0 to less than 35 points; or the securities company cannot score because the securities company does not comply with the reporting obligation as required by the management agency.

Table 1. Criteria for ranking and evaluating the financial capacity of Vietnamese securities companies in the period 2014 - 2021
No.	Indicator name	Value	Value	Point	Weight
I. Capital capacity
1	Size of equity		Under 500 billion VND or more	20	10 %
		From 500 billion VND	Under 1,000 billion VND	80
		From 1,000 billion VND or more		100
2	Available capital ratio		Below 120 %	0	10 %
		From 120 %	To less than 150 %	20
		From 150 %	To less than 180 %	40
		From 180 %	To less than 300 %	80
		From 300 % or more		100
3	Ratio of total asset value after risk adjustment***/Total assets (excluding fixed assets)		Below 50 %	0	3 %
		From 50 %	Below 65 %	20
		From 60 %	Below 80 %	50
		From 80 %	Arrive 90 %	80
		From 90 % or more		100
4	Provision ratio/(short-term investment + long-term investment + receivables)	From 10 % or more		0	10 %
		From 8 %	To less than 10 %	20
		From 5 %	To less than 8 %	50
		Above 0 %	To less than 5 %	80
		From 0 % or less		100
5	Accounts receivable/ Total assets ratio	From 90 % or more		0	10 %
		From 75 %	Up to 90 %	20
		From 50 %	Up to 75 %	50
		From 25 %	Up to 50 %	80
			Below 25 %	100
6	Operating expenses/net revenue	From 100 % or more		0	0,5 %
			To less than 100 %	100
7	Loan balance (margin)/ Total assets	From 200 % or more		0	0,5 %
			To less than 200 %	100
8	Equity/Legal capital		Below 60 %	0	10 %
		From 60 %	To less than 100 %	30
		From 100 %	To less than 150 %	60
		From 150 %	To less than 200 %	80
		From 200 % or more		100
9	Liabilities/Equity ratio	From 500 % or more		0	0,5 %
			To less than 500 %	100
10	Ratio of equity/Total capital	From 0 %	To less than 51 %	20	0,5 %
		From 51 %	To less than 75 %	80
		From 75 % or more		100
II. Payment capacity
11	Short-term assets/short-term debt ratio		To less than 100 %	0	15 %
		From 100 %	To less than 120 %	40
		From 120 %	To less than 150 %	80
		From 150 % or more		100
12	Ratio of cash and cash equivalents/Short-term debt		To less than 10 %	0	1 %
		From 10 %	To less than 15 %	20
		From 15 %	To less than 20 %	60
		From 20 %	To less than 30 %	80
		From 30 % or more		100
13	Total Assets/Liabilities Ratio		To less than 100 %	0	8 %
		From 100 % or more		100
14	Ratio of Profit before interest and taxes/ Amount of interest paid		To less than 10 %	0	1 %
		From 10 %	To less than 15 %	20
		From 15 %	To less than 20 %	60
		From 20 %	To less than 30 %	80
		From 30 % or more		100
III. Profitability
15	Profit after tax/Net revenue		Less than -10 %	0	10 %
		From -10 %	To less than 0 %	20
		From 0 %	To less than 5 %	50
		From 5 %	To less than 20 %	70
		From 20 % or more		100
16	Profit after tax/average equity		Less than -5 %	0	8 %
		From -5 %	To less than 0 %	20
		From 0 %	To less than 5 %	50
		From 5 %	To less than 25 %	70
		From 25 % or more		100
17	Profit before interest and taxes/Average business capital		Less than 0 %	0	1 %
		From 0 %	To less than 5 %	50
		From 5 % or more		100
18	Profit after tax/Average business capital		Less than 0 %	0	0,5 %
		From 0 %	To less than 5 %	50
		From 5 % or more		100
19	Profit before tax/Average business capital		Less than 0 %	0	0,5 %
		From 0 %	To less than 5 %	50
		From 5 % or more		100
Source: ^(15)

Step 2: Correct the missing value by leaving the data intact. When analyzing, the software automatically assigns the default missing value.

Step 3: In case data errors are detected that lead to unexplained analysis results, remove the erroneous data.

* Selection of variables in the model. Financial capacity (Y_i=Ability_i) = β₁ + β₂*Size_i + β₃*Lev_i + β₄*Ine_i + β₅* Cap_i +β₆*Rec_i + β₇*CR_i + β₈*Roe_i + β₉*Age_i + β₁₀*GDP_i + β₁₁*CPI_i (**)

Trong đó:

β₁, β₂, β_3, β_4, β_5, β_6, β_7, β_8, β_9, β_10, β₁₁: are the regression coefficients (β_i > 0: same direction impact, (β_i <0: opposite impact of the independent variable on the dependent variable).

Table 2. Statistics of variables in the regression model of factors affecting the financial capacity of securities companies
No.	Variable names and symbols	Calculation formula	Citation basis
Dependent variable: Financial capacity (Ability)
Independent variables:
01	Size of equity of securities company (Size)	Ln (Equity)	(26); (8); (6); (24); (22); (4); (1)
02	Financial leverage ratio (Lev)	Total Debt/Equity	(4); (12); (1)
03	Operational efficiency (Ine)	Operating expenses/net revenue	(26); (9); (25); (10); (7)
04	Available capital ratio (Cap)	Available capital/Total value at risk	(25); (2); (10); (12); (1)
05	Accounts receivable ratio (Rec)	Accounts receivable/Total assets	(25); (10)
06	Solvency (CR)	Short-term assets/Short-term liabilities	(24); (25); (10)
07	Return on equity (Roe)	Profit after tax/Average equity	(24); (25); (10); (14)
Control variables and macro variables
08	Age of securities company (Age)	Ln (Year of data collection – Year of establishment)	(8); (5)
09	Real GDP (Gdp)	Annual growth of real GDP
10	Annual Inflation (Cpi)	Annual inflation growth rate

Research hypotheses:

- Hypothesis H1: The variable (Size) has the same influence as the variable (Ability), the larger the equity size of a securities company, the stronger the probability of financial capacity of the securities company.

- Hypothesis H2: The variable (Lev) has the same influence as the variable (Ability), the higher the financial leverage a securities company uses, the stronger the probability of its financial performance.

- Hypothesis H3: The variable (Ine) has a negative influence on the variable (Ability), the lower the operating costs a securities company has, the stronger the probability of its financial capacity.

- Hypothesis H4: The variable (Cap) has the same influence as the variable (Ability), the higher the ratio of available capital a securities company maintains, the stronger the probability of its financial capacity is.

- Hypothesis H5: The variable (Rec) has a negative influence on the variable (Ability), the lower the ratio of receivables, the stronger the probability of financial capacity of a securities company.

- Hypothesis H6: Variable (Cr) has the same influence as variable (Ability), the greater the solvency, the stronger the probability of financial capacity of a securities company.

- Hypothesis H7: The variable (Roe) has the same influence as the variable (Ability), the higher the profitability on equity, the stronger the probability of financial performance of a securities company.

- Hypothesis H8: The variable (Age) has the same influence as the variable (Ability). If a securities company has been in operation for a long time, the probability of its financial performance is stronger.

- Hypothesis H9: The variable (Gdp) has the same influence as the variable (Ability), the annual growth of real GDP, the probability of financial capacity of securities companies is stronger.

- Hypothesis H10: The variable (Cpi) has a negative influence on the variable (Ability). If the annual inflation growth rate decreases, the probability of financial capacity of securities companies is stronger.

RESULTS

Research sample information

The article uses Stata 14 software to statistically calculate the data variables in the model, and the results are shown in Table 3 there are a total of 649 observations in the 8 years from 2014 to 2021, the dependent variable is financial capacity (Ability). The independent variables include: variable (Size) representing the equity size of the securities company (Logarithm of equity) with the smallest value 21,304, the largest value 30,285, the average value 26,524. Variable (Lev) Financial leverage ratio (Total debt/Equity) has the smallest value of -0,001, the largest value of 133,749, the average value of 0,908. The variable (Ine) operating efficiency has the smallest value of -3,422, the largest value of 19,33, the average value of 0,620. The variable (Cap) available capital ratio (Available capital/Total risk value) has the smallest value of -76, the largest value of 4279,153, the average value of 460,336. The variable (Rec) ratio of receivables (Receivables/Total assets) has the smallest value of 0, the largest value of 0,871, and the average value of 0,094. The variable (CR) of solvency (Current assets/Current liabilities) has the smallest value -741,149, the largest value 106460,6, the average value is 213,884. Variable (ROE) Profitability on equity (Profit after tax/Average equity) has the smallest value of -1,578, the largest value of 0,621, the average value of 0,037. The control variables Age, GDP, and CPI have the smallest and largest values of 0,602 - 1,342, respectively; 2,56 – 7,47; 0,63 – 3,54.

Table 3. Statistical results of variables in the regression model
Variable	Obs	Mean	Std. Dev.	Min	Max
Ability	649	0,865	0,340	0	1
Size	649	26,524	1,529	21,304	30,285
Lev	649	0,908	6,082	-0,001	133,749
Cap	649	460,336	378,734	-76	4 279,153
Ine	649	0,620	1,0340	-3,422	19,331
Rec	649	0,094	0,173	0	0,871
CR	649	213,884	4.187,726	-741,149	106460,6
Roe	649	0,037	0,174	-1,578	0,621
Age	649	1,145	0,120	0,602	1,342
GDP	649	5,938	1,850	2,56	7,47
CPI	649	2,482	0,954	0,63	3,54
Source: Statistical research on Stata 14 software

Standard deviation is used to measure the degree of dispersion of the data set around the mean value (Mean), it is easy to see that the STD Deviation/Mean value of most variables has a value greater than 1, the deviation The standard is smaller than the average, the data fluctuates strongly, and the observed statistical data of the sample vary widely.

Regression model validation

Check for multicollinearity. The study used the variance inflation factor (VIF) to check for multicollinearity. If the VIF coefficient exceeds 10, there are signs of multicollinearity in the research model.

Table 4. Results of checking multicollinearity in the model
Variable	VIF	1/VIF
Size	1,61	0,622627
Rec	1,47	0,681438
Roe	1,46	0,684027
CPI	1,42	0,706710
Cap	1,27	0,786972
Lev	1,20	0,830587
Age	1,17	0,852585
Ine	1,12	0,890182
GDP	1,12	0,891486
CR	1,05	0,953785
Mean VIF	1,29
Source: Statistical research on Stata 14 software

To see if the independent variables have multicollinearity with each other, the author conducted a multicollinearity test with the independent variables when included in the model at the same time. The results show that the variables with correlation coefficients all reach statistical significance (less than 0,5). Thus, it can be concluded that the model does not have multicollinearity, the variables in the model are correlated with each other. Thus, the Probit model has overcome the defects. In addition, to compare models with each other: Probit model, strong standard Probit, Logit, strong standard Logit, use the command: esttab LogitRobust Probit ProbitRobust, r2 star(* 0,1 ** 0,05 *** 0,01) brackets nogap compress, results table 5, the results show that the strong standard Probit model and the strong standard Logit model do not have much difference:

Table 5. Comparison of regression results of Logit and Probit models
Variable	(1)	(2)	(3)	(4)
Ability	Probit	Probit robust	Logit	Logit robust
Size	0,216***	0,316***	0,589***	0,589***
	[2,90]	[2,92]	[2,98]	[2,86]
Lev	-0,333***	-0,333***	-0,602***	-0,602***
	[-5,80]	[-6,27]	[-5,56]	[-6,24]
Cap	0,00984***	0,00984***	0,0178***	0,0178***
	[5,93]	[5,81]	[5,77]	[5,71]
Ine	-0,0182	-0,0182	-0,0358	-0,0358
	[-0,27]	[-0,26]	[-0,31]	[-0,31]
Rec	-2,858***	-2,858***	-5,253***	-5,253***
	[-4,54]	[-4,65]	[-4,47]	[-4,32]
CR	0,10101**	0,00101**	0,00164**	0,00164**
	[2,30]	[2,11]	[2,03]	[2,10]
Roe	11,95***	11,95***	21,74***	21,74***
	[6,32]	[5,69]	[5,86]	[4,99]
Age	-0,317	-0,317	-0,917	-0,917
	[-0,30]	[-0,39]	[-0,50]	[-0,66]
GDP	0,158	0,158*	0,320*	0,320**
	[1,63]	[1,84]	[1,83]	[1,98]
CPI	0,578***	0,578***	1,060***	1,060***
	[4,04]	[4,28]	[4,04]	[4,35]
_cons	-10,85***	-10,85***	-19,92***	-19,92***
	[-3,79]	[-3,85]	[-3,87]	[-3,75]
N	649	649	649	649
t statistics in brackets
* p<0,1, ** p<0,05, *** p<0,01
Source: Statistical research on STATA 14 software

DISCUSSION

Model regression results (table 5):

Ability = 0,316*Size - 0,333*Lev + 0,00984*Cap – 2,858*Rec + 0,00101*CR+ 11,95*Roe + 0,158*GDP + 0,578*CPI

Thus, there are 6 independent variables and 2 control variables that affect the financial capacity of securities companies. Specifically, the variables Size, Cap, Cr, Roe, GDP, and CPI have a positive influence on the financial capacity of securities companies with high significance levels of 10 %, 5 %, and 1 %, respectively. Meanwhile, the variables Lev and Rec have a negative effect on financial capacity.

The results of research on the current situation show that the size of equity capital of listed securities companies is still limited and unreasonable, significantly affecting the financial capacity of the company. This is relatively consistent with the research by ⁽¹⁵⁾. To improve the financial capacity of listed securities companies, it is necessary to follow the following directions:

First, increase retained profits for reinvestment. In recent years, the retained profits of listed securities companies have been low. To increase this source, securities companies need to consider and decide on a reasonable dividend policy between distributing profits to shareholders in cash or Retain profits to reinvest.

Second, increase equity capital by issuing new shares. With this option, securities companies need to consider the benefits between improving business results and increasing profits when expanding scale from increased equity with sharing voting rights and public control rights. company as well as the right to distribute high income to new shareholders.

Third, merge and consolidate securities companies. The current market situation shows that the number of securities companies is greater than the demand and size of the market, while the majority of securities companies have limited financial potential.

CONCLUSIONS

Through the regression results of the model of factors affecting the financial capacity of Vietnamese securities companies, the article found 6 independent variables and 2 control variables (68,14 %) affecting the financial capacity. of Vietnamese securities companies, which are: Scale of equity capital of securities companies; Financial leverage ratio; Available capital ratio; Accounts receivable ratio; Solvency; Profitability on equity; (and real GDP; Annual Inflation), with high levels of statistical significance at 10 %, 1 % and 5 % respectively. Through regression results, we demonstrate the role of factors, as well as the level of influence of factors in contributing to improving financial capacity, this is an important basis for the article to propose constructive solutions to improve financial performance. The financial capacity of Vietnamese securities companies in the coming time is consistent with the theoretical basis and empirical results of the regression model.

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FINANCING

The authors did not receive financing for the development of this research.

CONFLICT OF INTEREST

The authors declare that there is no conflict of interest.

AUTHORSHIP CONTRIBUTION

Conceptualization: Dong Thi Van Hong.

Data curation: Dong Thi Van Hong.

Formal analysis: Dong Thi Van Hong.

Research: Dong Thi Van Hong.

Methodology: Dong Thi Van Hong.

Project management: Dong Thi Van Hong.

Resources: Dong Thi Van Hong.

Software: Dong Thi Van Hong.

Supervision: Dong Thi Van Hong.

Validation: Dong Thi Van Hong.

Display: Dong Thi Van Hong.

Drafting - original draft: Dong Thi Van Hong.

Writing - proofreading and editing: Dong Thi Van Hong.